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Clinical Trials and Clinical Research: A Comprehensive Review

Venkataramana kandi.

1 Clinical Microbiology, Prathima Institute of Medical Sciences, Karimnagar, IND

Sabitha Vadakedath

2 Biochemistry, Prathima Institute of Medical Sciences, Karimnagar, IND

Clinical research is an alternative terminology used to describe medical research. Clinical research involves people, and it is generally carried out to evaluate the efficacy of a therapeutic drug, a medical/surgical procedure, or a device as a part of treatment and patient management. Moreover, any research that evaluates the aspects of a disease like the symptoms, risk factors, and pathophysiology, among others may be termed clinical research. However, clinical trials are those studies that assess the potential of a therapeutic drug/device in the management, control, and prevention of disease. In view of the increasing incidences of both communicable and non-communicable diseases, and especially after the effects that Coronavirus Disease-19 (COVID-19) had on public health worldwide, the emphasis on clinical research assumes extremely essential. The knowledge of clinical research will facilitate the discovery of drugs, devices, and vaccines, thereby improving preparedness during public health emergencies. Therefore, in this review, we comprehensively describe the critical elements of clinical research that include clinical trial phases, types, and designs of clinical trials, operations of trial, audit, and management, and ethical concerns.

Introduction and background

A clinical trial is a systematic process that is intended to find out the safety and efficacy of a drug/device in treating/preventing/diagnosing a disease or a medical condition [ 1 , 2 ]. Clinical trial includes various phases that include phase 0 (micro-dosing studies), phase 1, phase 2, phase 3, and phase 4 [ 3 ]. Phase 0 and phase 2 are called exploratory trial phases, phase 1 is termed the non-therapeutic phase, phase 3 is known as the therapeutic confirmatory phase, and phase 4 is called the post-approval or the post-marketing surveillance phase. Phase 0, also called the micro-dosing phase, was previously done in animals but now it is carried out in human volunteers to understand the dose tolerability (pharmacokinetics) before being administered as a part of the phase 1 trial among healthy individuals. The details of the clinical trial phases are shown in Table ​ Table1 1 .

This table has been created by the authors.

MTD: maximum tolerated dose; SAD: single ascending dose; MAD: multiple ascending doses; NDA: new drug application; FDA: food and drug administration

Clinical research design has two major types that include non-interventional/observational and interventional/experimental studies. The non-interventional studies may have a comparator group (analytical studies like case-control and cohort studies), or without it (descriptive study). The experimental studies may be either randomized or non-randomized. Clinical trial designs are of several types that include parallel design, crossover design, factorial design, randomized withdrawal approach, adaptive design, superiority design, and non-inferiority design. The advantages and disadvantages of clinical trial designs are depicted in Table ​ Table2 2 .

There are different types of clinical trials that include those which are conducted for treatment, prevention, early detection/screening, and diagnosis. These studies address the activities of an investigational drug on a disease and its outcomes [ 4 ]. They assess whether the drug is able to prevent the disease/condition, the ability of a device to detect/screen the disease, and the efficacy of a medical test to diagnose the disease/condition. The pictorial representation of a disease diagnosis, treatment, and prevention is depicted in Figure ​ Figure1 1 .

This figure has been created by the authors.

The clinical trial designs could be improvised to make sure that the study's validity is maintained/retained. The adaptive designs facilitate researchers to improvise during the clinical trial without interfering with the integrity and validity of the results. Moreover, it allows flexibility during the conduction of trials and the collection of data. Despite these advantages, adaptive designs have not been universally accepted among clinical researchers. This could be attributed to the low familiarity of such designs in the research community. The adaptive designs have been applied during various phases of clinical trials and for different clinical conditions [ 5 , 6 ]. The adaptive designs applied during different phases are depicted in Figure ​ Figure2 2 .

The Bayesian adaptive trial design has gained popularity, especially during the Coronavirus Disease-19 (COVID-19) pandemic. Such designs could operate under a single master protocol. It operates as a platform trial wherein multiple treatments can be tested on different patient groups suffering from disease [ 7 ].

In this review, we comprehensively discuss the essential elements of clinical research that include the principles of clinical research, planning clinical trials, practical aspects of clinical trial operations, essentials of clinical trial applications, monitoring, and audit, clinical trial data analysis, regulatory audits, and project management, clinical trial operations at the investigation site, the essentials of clinical trial experiments involving epidemiological, and genetic studies, and ethical considerations in clinical research/trials.

A clinical trial involves the study of the effect of an investigational drug/any other intervention in a defined population/participant. The clinical research includes a treatment group and a placebo wherein each group is evaluated for the efficacy of the intervention (improved/not improved) [ 8 ].

Clinical trials are broadly classified into controlled and uncontrolled trials. The uncontrolled trials are potentially biased, and the results of such research are not considered as equally as the controlled studies. Randomized controlled trials (RCTs) are considered the most effective clinical trials wherein the bias is minimized, and the results are considered reliable. There are different types of randomizations and each one has clearly defined functions as elaborated in Table ​ Table3 3 .

Principles of clinical trial/research

Clinical trials or clinical research are conducted to improve the understanding of the unknown, test a hypothesis, and perform public health-related research [ 2 , 3 ]. This is majorly carried out by collecting the data and analyzing it to derive conclusions. There are various types of clinical trials that are majorly grouped as analytical, observational, and experimental research. Clinical research can also be classified into non-directed data capture, directed data capture, and drug trials. Clinical research could be prospective or retrospective. It may also be a case-control study or a cohort study. Clinical trials may be initiated to find treatment, prevent, observe, and diagnose a disease or a medical condition.

Among the various types of clinical research, observational research using a cross-sectional study design is the most frequently performed clinical research. This type of research is undertaken to analyze the presence or absence of a disease/condition, potential risk factors, and prevalence and incidence rates in a defined population. Clinical trials may be therapeutic or non-therapeutic type depending on the type of intervention. The therapeutic type of clinical trial uses a drug that may be beneficial to the patient. Whereas in a non-therapeutic clinical trial, the participant does not benefit from the drug. The non-therapeutic trials provide additional knowledge of the drug for future improvements. Different terminologies of clinical trials are delineated in Table ​ Table4 4 .

In view of the increased cost of the drug discovery process, developing, and low-income countries depend on the production of generic drugs. The generic drugs are similar in composition to the patented/branded drug. Once the patent period is expired generic drugs can be manufactured which have a similar quality, strength, and safety as the patented drug [ 9 ]. The regulatory requirements and the drug production process are almost the same for the branded and the generic drug according to the Food and Drug Administration (FDA), United States of America (USA).

The bioequivalence (BE) studies review the absorption, distribution, metabolism, and excretion (ADME) of the generic drug. These studies compare the concentration of the drug at the desired location in the human body, called the peak concentration of the drug (Cmax). The extent of absorption of the drug is measured using the area under the receiver operating characteristic curve (AUC), wherein the generic drug is supposed to demonstrate similar ADME activities as the branded drug. The BE studies may be undertaken in vitro (fasting, non-fasting, sprinkled fasting) or in vivo studies (clinical, bioanalytical, and statistical) [ 9 ].

Planning clinical trial/research

The clinical trial process involves protocol development, designing a case record/report form (CRF), and functioning of institutional review boards (IRBs). It also includes data management and the monitoring of clinical trial site activities. The CRF is the most significant document in a clinical study. It contains the information collected by the investigator about each subject participating in a clinical study/trial. According to the International Council for Harmonisation (ICH), the CRF can be printed, optical, or an electronic document that is used to record the safety and efficacy of the pharmaceutical drug/product in the test subjects. This information is intended for the sponsor who initiates the clinical study [ 10 ].

The CRF is designed as per the protocol and later it is thoroughly reviewed for its correctness (appropriate and structured questions) and finalized. The CRF then proceeds toward the print taking the language of the participating subjects into consideration. Once the CRF is printed, it is distributed to the investigation sites where it is filled with the details of the participating subjects by the investigator/nurse/subject/guardian of the subject/technician/consultant/monitors/pharmacist/pharmacokinetics/contract house staff. The filled CRFs are checked for their completeness and transported to the sponsor [ 11 ].

Effective planning and implementation of a clinical study/trial will influence its success. The clinical study majorly includes the collection and distribution of the trial data, which is done by the clinical data management section. The project manager is crucial to effectively plan, organize, and use the best processes to control and monitor the clinical study [ 10 , 11 ].

The clinical study is conducted by a sponsor or a clinical research organization (CRO). A perfect protocol, time limits, and regulatory requirements assume significance while planning a clinical trial. What, when, how, and who are clearly planned before the initiation of a study trial. Regular review of the project using the bar and Gantt charts, and maintaining the timelines assume increased significance for success with the product (study report, statistical report, database) [ 10 , 11 ].

The steps critical to planning a clinical trial include the idea, review of the available literature, identifying a problem, formulating the hypothesis, writing a synopsis, identifying the investigators, writing a protocol, finding a source of funding, designing a patient consent form, forming ethics boards, identifying an organization, preparing manuals for procedures, quality assurance, investigator training and initiation of the trial by recruiting the participants [ 10 ].

The two most important points to consider before the initiation of the clinical trial include whether there is a need for a clinical trial, if there is a need, then one must make sure that the study design and methodology are strong for the results to be reliable to the people [ 11 ].

For clinical research to envisage high-quality results, the study design, implementation of the study, quality assurance in data collection, and alleviation of bias and confounding factors must be robust [ 12 ]. Another important aspect of conducting a clinical trial is improved management of various elements of clinical research that include human and financial resources. The role of a trial manager to make a successful clinical trial was previously reported. The trial manager could play a key role in planning, coordinating, and successfully executing the trial. Some qualities of a trial manager include better communication and motivation, leadership, and strategic, tactical, and operational skills [ 13 ].

Practical aspects of a clinical trial operations

There are different types of clinical research. Research in the development of a novel drug could be initiated by nationally funded research, industry-sponsored research, and clinical research initiated by individuals/investigators. According to the documents 21 code of federal regulations (CFR) 312.3 and ICH E-6 Good Clinical Practice (GCP) 1.54, an investigator is an individual who initiates and conducts clinical research [ 14 ]. The investigator plan, design, conduct, monitor, manage data, compile reports, and supervise research-related regulatory and ethical issues. To manage a successful clinical trial project, it is essential for an investigator to give the letter of intent, write a proposal, set a timeline, develop a protocol and related documents like the case record forms, define the budget, and identify the funding sources.

Other major steps of clinical research include the approval of IRBs, conduction and supervision of the research, data review, and analysis. Successful clinical research includes various essential elements like a letter of intent which is the evidence that supports the interest of the researcher to conduct drug research, timeline, funding source, supplier, and participant characters.

Quality assurance, according to the ICH and GCP guidelines, is necessary to be implemented during clinical research to generate quality and accurate data. Each element of the clinical research must have been carried out according to the standard operating procedure (SOP), which is written/determined before the initiation of the study and during the preparation of the protocol [ 15 ].

The audit team (quality assurance group) is instrumental in determining the authenticity of the clinical research. The audit, according to the ICH and GCP, is an independent and external team that examines the process (recording the CRF, analysis of data, and interpretation of data) of clinical research. The quality assurance personnel are adequately trained, become trainers if needed, should be good communicators, and must handle any kind of situation. The audits can be at the investigator sites evaluating the CRF data, the protocol, and the personnel involved in clinical research (source data verification, monitors) [ 16 ].

Clinical trial operations are governed by legal and regulatory requirements, based on GCPs, and the application of science, technology, and interpersonal skills [ 17 ]. Clinical trial operations are complex, time and resource-specific that requires extensive planning and coordination, especially for the research which is conducted at multiple trial centers [ 18 ].

Recruiting the clinical trial participants/subjects is the most significant aspect of clinical trial operations. Previous research had noted that most clinical trials do not meet the participant numbers as decided in the protocol. Therefore, it is important to identify the potential barriers to patient recruitment [ 19 ].

Most clinical trials demand huge costs, increased timelines, and resources. Randomized clinical trial studies from Switzerland were analyzed for their costs which revealed approximately 72000 USD for a clinical trial to be completed. This study emphasized the need for increased transparency with respect to the costs associated with the clinical trial and improved collaboration between collaborators and stakeholders [ 20 ].

Clinical trial applications, monitoring, and audit

Among the most significant aspects of a clinical trial is the audit. An audit is a systematic process of evaluating the clinical trial operations at the site. The audit ensures that the clinical trial process is conducted according to the protocol, and predefined quality system procedures, following GCP guidelines, and according to the requirements of regulatory authorities [ 21 ].

The auditors are supposed to be independent and work without the involvement of the sponsors, CROs, or personnel at the trial site. The auditors ensure that the trial is conducted by designated professionally qualified, adequately trained personnel, with predefined responsibilities. The auditors also ensure the validity of the investigational drug, and the composition, and functioning of institutional review/ethics committees. The availability and correctness of the documents like the investigational broacher, informed consent forms, CRFs, approval letters of the regulatory authorities, and accreditation of the trial labs/sites [ 21 ].

The data management systems, the data collection software, data backup, recovery, and contingency plans, alternative data recording methods, security of the data, personnel training in data entry, and the statistical methods used to analyze the results of the trial are other important responsibilities of the auditor [ 21 , 22 ].

According to the ICH-GCP Sec 1.29 guidelines the inspection may be described as an act by the regulatory authorities to conduct an official review of the clinical trial-related documents, personnel (sponsor, investigator), and the trial site [ 21 , 22 ]. The summary report of the observations of the inspectors is performed using various forms as listed in Table ​ Table5 5 .

FDA: Food and Drug Administration; IND: investigational new drug; NDA: new drug application; IRB: institutional review board; CFR: code of federal regulations

Because protecting data integrity, the rights, safety, and well-being of the study participants are more significant while conducting a clinical trial, regular monitoring and audit of the process appear crucial. Also, the quality of the clinical trial greatly depends on the approach of the trial personnel which includes the sponsors and investigators [ 21 ].

The responsibility of monitoring lies in different hands, and it depends on the clinical trial site. When the trial is initiated by a pharmaceutical industry, the responsibility of trial monitoring depends on the company or the sponsor, and when the trial is conducted by an academic organization, the responsibility lies with the principal investigator [ 21 ].

An audit is a process conducted by an independent body to ensure the quality of the study. Basically, an audit is a quality assurance process that determines if a study is carried out by following the SPOs, in compliance with the GCPs recommended by regulatory bodies like the ICH, FDA, and other local bodies [ 21 ].

An audit is performed to review all the available documents related to the IRB approval, investigational drug, and the documents related to the patient care/case record forms. Other documents that are audited include the protocol (date, sign, treatment, compliance), informed consent form, treatment response/outcome, toxic response/adverse event recording, and the accuracy of data entry [ 22 ].

Clinical trial data analysis, regulatory audits, and project management

The essential elements of clinical trial management systems (CDMS) include the management of the study, the site, staff, subject, contracts, data, and document management, patient diary integration, medical coding, monitoring, adverse event reporting, supplier management, lab data, external interfaces, and randomization. The CDMS involves setting a defined start and finishing time, defining study objectives, setting enrolment and termination criteria, commenting, and managing the study design [ 23 ].

Among the various key application areas of clinical trial systems, the data analysis assumes increased significance. The clinical trial data collected at the site in the form of case record form is stored in the CDMS ensuring the errors with respect to the double data entry are minimized.

Clinical trial data management uses medical coding, which uses terminologies with respect to the medications and adverse events/serious adverse events that need to be entered into the CDMS. The project undertaken to conduct the clinical trial must be predetermined with timelines and milestones. Timelines are usually set for the preparation of protocol, designing the CRF, planning the project, identifying the first subject, and timelines for recording the patient’s data for the first visit.

The timelines also are set for the last subject to be recruited in the study, the CRF of the last subject, and the locked period after the last subject entry. The planning of the project also includes the modes of collection of the data, the methods of the transport of the CRFs, patient diaries, and records of severe adverse events, to the central data management sites (fax, scan, courier, etc.) [ 24 ].

The preparation of SOPs and the type and timing of the quality control (QC) procedures are also included in the project planning before the start of a clinical study. Review (budget, resources, quality of process, assessment), measure (turnaround times, training issues), and control (CRF collection and delivery, incentives, revising the process) are the three important aspects of the implementation of a clinical research project.

In view of the increasing complexity related to the conduct of clinical trials, it is important to perform a clinical quality assurance (CQA) audit. The CQA audit process consists of a detailed plan for conducting audits, points of improvement, generating meaningful audit results, verifying SOP, and regulatory compliance, and promoting improvement in clinical trial research [ 25 ]. All the components of a CQA audit are delineated in Table ​ Table6 6 .

CRF: case report form; CSR: clinical study report; IC: informed consent; PV: pharmacovigilance; SAE: serious adverse event

Clinical trial operations at the investigator's site

The selection of an investigation site is important before starting a clinical trial. It is essential that the individuals recruited for the study meet the inclusion criteria of the trial, and the investigator's and patient's willingness to accept the protocol design and the timelines set by the regulatory authorities including the IRBs.

Before conducting clinical research, it is important for an investigator to agree to the terms and conditions of the agreement and maintain the confidentiality of the protocol. Evaluation of the protocol for the feasibility of its practices with respect to the resources, infrastructure, qualified and trained personnel available, availability of the study subjects, and benefit to the institution and the investigator is done by the sponsor during the site selection visit.

The standards of a clinical research trial are ensured by the Council for International Organizations of Medical Sciences (CIOMS), National Bioethics Advisory Commission (NBAC), United Nations Programme on Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (HIV/AIDS) (UNAIDS), and World Medical Association (WMA) [ 26 ].

Recommendations for conducting clinical research based on the WMA support the slogan that says, “The health of my patient will be my first consideration.” According to the International Code of Medical Ethics (ICME), no human should be physically or mentally harmed during the clinical trial, and the study should be conducted in the best interest of the person [ 26 ].

Basic principles recommended by the Helsinki declaration include the conduction of clinical research only after the prior proof of the safety of the drug in animal and lab experiments. The clinical trials must be performed by scientifically, and medically qualified and well-trained personnel. Also, it is important to analyze the benefit of research over harm to the participants before initiating the drug trials.

The doctors may prescribe a drug to alleviate the suffering of the patient, save the patient from death, and gain additional knowledge of the drug only after obtaining informed consent. Under the equipoise principle, the investigators must be able to justify the treatment provided as a part of the clinical trial, wherein the patient in the placebo arm may be harmed due to the unavailability of the therapeutic/trial drug.

Clinical trial operations greatly depend on the environmental conditions and geographical attributes of the trial site. It may influence the costs and targets defined by the project before the initiation. It was noted that one-fourth of the clinical trial project proposals/applications submit critical data on the investigational drug from outside the country. Also, it was noted that almost 35% of delays in clinical trials owing to patient recruitment with one-third of studies enrolling only 5% of the participants [ 27 ].

It was suggested that clinical trial feasibility assessment in a defined geographical region may be undertaken for improved chances of success. Points to be considered under the feasibility assessment program include if the disease under the study is related to the population of the geographical region, appropriateness of the study design, patient, and comparator group, visit intervals, potential regulatory and ethical challenges, and commitments of the study partners, CROs in respective countries (multi-centric studies) [ 27 ].

Feasibility assessments may be undertaken at the program level (ethics, regulatory, and medical preparedness), study level (clinical, regulatory, technical, and operational aspects), and at the investigation site (investigational drug, competency of personnel, participant recruitment, and retention, quality systems, and infrastructural aspects) [ 27 ].

Clinical trials: true experiments

In accordance with the revised schedule "Y" of the Drugs and Cosmetics Act (DCA) (2005), a drug trial may be defined as a systematic study of a novel drug component. The clinical trials aim to evaluate the pharmacodynamic, and pharmacokinetic properties including ADME, efficacy, and safety of new drugs.

According to the drug and cosmetic rules (DCR), 1945, a new chemical entity (NCE) may be defined as a novel drug approved for a disease/condition, in a specified route, and at a particular dosage. It also may be a new drug combination, of previously approved drugs.

A clinical trial may be performed in three types; one that is done to find the efficacy of an NCE, a comparison study of two drugs against a medical condition, and the clinical research of approved drugs on a disease/condition. Also, studies of the bioavailability and BE studies of the generic drugs, and the drugs already approved in other countries are done to establish the efficacy of new drugs [ 28 ].

Apart from the discovery of a novel drug, clinical trials are also conducted to approve novel medical devices for public use. A medical device is defined as any instrument, apparatus, appliance, software, and any other material used for diagnostic/therapeutic purposes. The medical devices may be divided into three classes wherein class I uses general controls; class II uses general and special controls, and class III uses general, special controls, and premarket approvals [ 28 ].

The premarket approval applications ensure the safety and effectiveness, and confirmation of the activities from bench to animal to human clinical studies. The FDA approval for investigational device exemption (IDE) for a device not approved for a new indication/disease/condition. There are two types of IDE studies that include the feasibility study (basic safety and potential effectiveness) and the pivotal study (trial endpoints, randomization, monitoring, and statistical analysis plan) [ 28 ].

As evidenced by the available literature, there are two types of research that include observational and experimental research. Experimental research is alternatively known as the true type of research wherein the research is conducted by the intervention of a new drug/device/method (educational research). Most true experiments use randomized control trials that remove bias and neutralize the confounding variables that may interfere with the results of research [ 28 ].

The variables that may interfere with the study results are independent variables also called prediction variables (the intervention), dependent variables (the outcome), and extraneous variables (other confounding factors that could influence the outside). True experiments have three basic elements that include manipulation (that influence independent variables), control (over extraneous influencers), and randomization (unbiased grouping) [ 29 ].

Experiments can also be grouped as true, quasi-experimental, and non-experimental studies depending on the presence of specific characteristic features. True experiments have all three elements of study design (manipulation, control, randomization), and prospective, and have great scientific validity. Quasi-experiments generally have two elements of design (manipulation and control), are prospective, and have moderate scientific validity. The non-experimental studies lack manipulation, control, and randomization, are generally retrospective, and have low scientific validity [ 29 ].

Clinical trials: epidemiological and human genetics study

Epidemiological studies are intended to control health issues by understanding the distribution, determinants, incidence, prevalence, and impact on health among a defined population. Such studies are attempted to perceive the status of infectious diseases as well as non-communicable diseases [ 30 ].

Experimental studies are of two types that include observational (cross-sectional studies (surveys), case-control studies, and cohort studies) and experimental studies (randomized control studies) [ 3 , 31 ]. Such research may pose challenges related to ethics in relation to the social and cultural milieu.

Biomedical research related to human genetics and transplantation research poses an increased threat to ethical concerns, especially after the success of the human genome project (HGP) in the year 2000. The benefits of human genetic studies are innumerable that include the identification of genetic diseases, in vitro fertilization, and regeneration therapy. Research related to human genetics poses ethical, legal, and social issues (ELSI) that need to be appropriately addressed. Most importantly, these genetic research studies use advanced technologies which should be equally available to both economically well-placed and financially deprived people [ 32 ].

Gene therapy and genetic manipulations may potentially precipitate conflict of interest among the family members. The research on genetics may be of various types that include pedigree studies (identifying abnormal gene carriers), genetic screening (for diseases that may be heritable by the children), gene therapeutics (gene replacement therapy, gene construct administration), HGP (sequencing the whole human genome/deoxyribonucleic acid (DNA) fingerprinting), and DNA, cell-line banking/repository [ 33 ]. The biobanks are established to collect and store human tissue samples like umbilical tissue, cord blood, and others [ 34 ].

Epidemiological studies on genetics are attempts to understand the prevalence of diseases that may be transmitted among families. The classical epidemiological studies may include single case observations (one individual), case series (< 10 individuals), ecological studies (population/large group of people), cross-sectional studies (defined number of individuals), case-control studies (defined number of individuals), cohort (defined number of individuals), and interventional studies (defined number of individuals) [ 35 ].

Genetic studies are of different types that include familial aggregation (case-parent, case-parent-grandparent), heritability (study of twins), segregation (pedigree study), linkage study (case-control), association, linkage, disequilibrium, cohort case-only studies (related case-control, unrelated case-control, exposure, non-exposure group, case group), cross-sectional studies, association cohort (related case-control, familial cohort), and experimental retrospective cohort (clinical trial, exposure, and non-exposure group) [ 35 ].

Ethics and concerns in clinical trial/research

Because clinical research involves animals and human participants, adhering to ethics and ethical practices assumes increased significance [ 36 ]. In view of the unethical research conducted on war soldiers after the Second World War, the Nuremberg code was introduced in 1947, which promulgated rules for permissible medical experiments on humans. The Nuremberg code suggests that informed consent is mandatory for all the participants in a clinical trial, and the study subjects must be made aware of the nature, duration, and purpose of the study, and potential health hazards (foreseen and unforeseen). The study subjects should have the liberty to withdraw at any time during the trial and to choose a physician upon medical emergency. The other essential principles of clinical research involving human subjects as suggested by the Nuremberg code included benefit to the society, justification of study as noted by the results of the drug experiments on animals, avoiding even minimal suffering to the study participants, and making sure that the participants don’t have life risk, humanity first, improved medical facilities for participants, and suitably qualified investigators [ 37 ].

During the 18th world medical assembly meeting in the year 1964, in Helsinki, Finland, ethical principles for doctors practicing research were proposed. Declaration of Helsinki, as it is known made sure that the interests and concerns of the human participants will always prevail over the interests of the society. Later in 1974, the National Research Act was proposed which made sure that the research proposals are thoroughly screened by the Institutional ethics/Review Board. In 1979, the April 18th Belmont report was proposed by the national commission for the protection of human rights during biomedical and behavioral research. The Belmont report proposed three core principles during research involving human participants that include respect for persons, beneficence, and justice. The ICH laid down GCP guidelines [ 38 ]. These guidelines are universally followed throughout the world during the conduction of clinical research involving human participants.

ICH was first founded in 1991, in Brussels, under the umbrella of the USA, Japan, and European countries. The ICH conference is conducted once every two years with the participation from the member countries, observers from the regulatory agencies, like the World Health Organization (WHO), European Free Trade Association (EFTA), and the Canadian Health Protection Branch, and other interested stakeholders from the academia and the industry. The expert working groups of the ICH ensure the quality, efficacy, and safety of the medicinal product (drug/device). Despite the availability of the Nuremberg code, the Belmont Report, and the ICH-GCP guidelines, in the year 1982, International Ethical Guidelines for Biomedical Research Involving Human Subjects was proposed by the CIOMS in association with WHO [ 39 ]. The CIOMS protects the rights of the vulnerable population, and ensures ethical practices during clinical research, especially in underdeveloped countries [ 40 ]. In India, the ethical principles for biomedical research involving human subjects were introduced by the Indian Council of Medical Research (ICMR) in the year 2000 and were later amended in the year 2006 [ 41 ]. Clinical trial approvals can only be done by the IRB approved by the Drug Controller General of India (DGCI) as proposed in the year 2013 [ 42 ].

Current perspectives and future implications

A recent study attempted to evaluate the efficacy of adaptive clinical trials in predicting the success of a clinical trial drug that entered phase 3 and minimizing the time and cost of drug development. This study highlighted the drawbacks of such clinical trial designs that include the possibility of type 1 (false positive) and type 2 (false negative) errors [ 43 ].

The usefulness of animal studies during the preclinical phases of a clinical trial was evaluated in a previous study which concluded that animal studies may not completely guarantee the safety of the investigational drug. This is noted by the fact that many drugs which passed toxicity tests in animals produced adverse reactions in humans [ 44 ].

The significance of BE studies to compare branded and generic drugs was reported previously. The pharmacokinetic BE studies of Amoxycillin comparing branded and generic drugs were carried out among a group of healthy participants. The study results have demonstrated that the generic drug had lower Cmax as compared to the branded drug [ 45 ].

To establish the BE of the generic drugs, randomized crossover trials are carried out to assess the Cmax and the AUC. The ratio of each pharmacokinetic characteristic must match the ratio of AUC and/or Cmax, 1:1=1 for a generic drug to be considered as a bioequivalent to a branded drug [ 46 ].

Although the generic drug development is comparatively more beneficial than the branded drugs, synthesis of extended-release formulations of the generic drug appears to be complex. Since the extended-release formulations remain for longer periods in the stomach, they may be influenced by gastric acidity and interact with the food. A recent study suggested the use of bio-relevant dissolution tests to increase the successful production of generic extended-release drug formulations [ 47 ].

Although RCTs are considered the best designs, which rule out bias and the data/results obtained from such clinical research are the most reliable, RCTs may be plagued by miscalculation of the treatment outcomes/bias, problems of cointerventions, and contaminations [ 48 ].

The perception of healthcare providers regarding branded drugs and their view about the generic equivalents was recently analyzed and reported. It was noted that such a perception may be attributed to the flexible regulatory requirements for the approval of a generic drug as compared to a branded drug. Also, could be because a switch from a branded drug to a generic drug in patients may precipitate adverse events as evidenced by previous reports [ 49 ].

Because the vulnerable population like drug/alcohol addicts, mentally challenged people, children, geriatric age people, military persons, ethnic minorities, people suffering from incurable diseases, students, employees, and pregnant women cannot make decisions with respect to participating in a clinical trial, ethical concerns, and legal issues may prop up, that may be appropriately addressed before drug trials which include such groups [ 50 ].

Conclusions

Clinical research and clinical trials are important from the public health perspective. Clinical research facilitates scientists, public health administrations, and people to increase their understanding and improve preparedness with reference to the diseases prevalent in different geographical regions of the world. Moreover, clinical research helps in mitigating health-related problems as evidenced by the current Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic and other emerging and re-emerging microbial infections. Clinical trials are crucial to the development of drugs, devices, and vaccines. Therefore, scientists are required to be up to date with the process and procedures of clinical research and trials as discussed comprehensively in this review.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.

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Integrating Clinical Trials and Practice : A New JAMA Series and Call for Papers

• 1 Executive Editor, JAMA
• Special Communication The Integration of Clinical Trials With the Practice of Medicine Derek C. Angus, MD, MPH; Alison J. Huang, MD, MAS; Roger J. Lewis, MD, PhD; Amy P. Abernethy, MD, PhD; Robert M. Califf, MD; Martin Landray, PhD; Nancy Kass, ScD; Kirsten Bibbins-Domingo, PhD, MD, MAS; JAMA Summit on Clinical Trials Participants; Ali B Abbasi; Kaleab Z Abebe; Amy P Abernethy; Stacey J. Adam; Derek C Angus; Jamy Ard; Rachel A Bender Ignacio ; Scott M Berry; Deepak L. Bhatt; Kirsten Bibbins-Domingo; Robert O. Bonow; Marc Bonten; Sharon A. Brangman; John Brownstein; Melinda J. B. Buntin; Atul J Butte; Robert M. Califf; Marion K Campbell; Anne R. Cappola; Anne C Chiang; Deborah Cook; Steven R Cummings; Gregory Curfman; Laura J Esserman; Lee A Fleisher; Joseph B Franklin; Ralph Gonzalez; Cynthia I Grossman; Tufia C. Haddad; Roy S. Herbst; Adrian F. Hernandez; Diane P Holder; Leora Horn; Grant D. Huang; Alison Huang; Nancy Kass; Rohan Khera; Walter J. Koroshetz; Harlan M. Krumholz; Martin Landray; Roger J. Lewis; Tracy A Lieu; Preeti N. Malani; Christa Lese Martin; Mark McClellan; Mary M. McDermott; Stephanie R. Morain; Susan A Murphy; Stuart G Nicholls; Stephen J Nicholls; Peter J. O'Dwyer; Bhakti K Patel; Eric Peterson; Sheila A. Prindiville; Joseph S. Ross; Kathryn M Rowan; Gordon Rubenfeld; Christopher W. Seymour; Rod S Taylor; Joanne Waldstreicher; Tracy Y. Wang JAMA
• Viewpoint Why Should the FDA Focus on Pragmatic Clinical Research? Ali B. Abbasi, MD; Lesley H. Curtis, PhD; Robert M. Califf, MD JAMA

Randomized clinical trials remain the cornerstone of evidence-based medicine. As a leading medical journal publishing the science that advances the clinical care of patients and the health of the public, JAMA is committed to the publication of clinical trials, as well as promoting the discourse on how clinical trial evidence can best serve the needs of patients and clinicians.

In autumn of 2023, JAMA hosted its inaugural in-person JAMA Summit 1 on the topic of randomized clinical trials and the challenges and opportunities to improve their design and conduct to be most responsive to the needs of clinical practice. The Special Communication published in JAMA, 2 “The Integration of Clinical Trials With the Practice of Medicine: Repairing a House Divided,” was written on behalf of the participants in the JAMA Summit and outlines many of the themes discussed during this provocative 2-day meeting.

A central theme of the JAMA Summit, which is elaborated on in the Special Communication in this issue, is how best to integrate clinical trials with clinical practice. Traditionally, clinical trialists and clinicians have worked independently, and, as the authors of the Special Communication underscore, their separate missions, incentives, and infrastructures have been siloed. The result is inefficiency in the performance of trials and limitations in their scope and impact. The authors offer solutions, including advances in implementation science, novel approaches to statistical analysis of trial data, and integration of trials with the electronic health record as a very rich source of clinical data. The clinical trial and health care delivery disciplines have functioned as a house divided. The authors proffer an approach to bridging the gap.

The future of clinical medicine will be greatly influenced by the data derived from randomized clinical trials, and trials will need to be accomplished more quickly, efficiently, and cheaply than they are today. A recent example is the platform trials 3 that were conducted during the COVID-19 pandemic. 4 - 6 These trials were embedded within clinical care and permitted the study of multiple therapeutic interventions simultaneously, with the results applicable to patient care in short order. The platform trials are exemplary of the types of novel approaches to clinical trials that are needed to realign the house divided.

With this Special Communication and an accompanying Viewpoint, 7 we launch a new series in JAMA— Integrating Clinical Trials and Practice. JAMA invites submissions that explore innovations in clinical trial design, implementation, funding, regulation, education, and application that may bring randomized trial evidence to more effectively address the needs in clinical practice. Our goal is to engage the research community in a significant publishing project to advance clinical trials and better align them with clinical practice. We welcome articles of any type, and we are happy to hear from you with presubmission inquiries. We are eager to chart a new path for randomized clinical trials and the delivery of health care, and we hope you will participate in navigating the road ahead.

Published Online: June 3, 2024. doi:10.1001/jama.2024.10266

Corresponding Author: Greg Curfman, MD, JAMA, Editorial Office, 330 N Wabash Ave, Chicago, IL 60611 ( [email protected] ).

Conflict of Interest Disclosures: None reported.

See More About

Curfman G. Integrating Clinical Trials and Practice : A New JAMA Series and Call for Papers . JAMA. Published online June 03, 2024. doi:10.1001/jama.2024.10266

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A novel, non-invasive treatment using electrical currents exploits physiological properties of dividing cancer cells to prolong survival and augment current therapies.

clinical trials

Methodological Issues and Strategies in Clinical Research

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• Book details

Now in its fifth edition, this classic text helps readers learn how to design, conduct, analyze, and report high-quality clinical studies.

Alan E. Kazdin brings together a wide array of authoritative articles with his own expert insights to illustrate fundamental issues research in an accessible manner, including generating ideas, selecting participants, randomization, selecting assessment measures, analyzing data, and evaluating the implications of and publishing the results.

New to this edition are articles emphasizing the importance of diversity in research, not only cultural diversity among study participants but also in methodology (including quantitative, qualitative, and mixed methods); the role of big data; using technology such as artificial intelligence and apps; and strategies to improve transparency and accessibility, including open science practices, replication, and preregistration.

From generating hypotheses for study and selecting appropriate assessments to interpreting data and presenting findings, readers will come to better understand the whole research process as well as the importance of ethics and scientific integrity.

Part I. Introduction: Overview and Background

• Chapter 1. Methodology: What It Is and Why It Is So Important Alan E. Kazdin

Part II. Beginning the Research Process

• Chapter 2. Beginning the Process: Key Concepts and Questions to Guide Research Alan E. Kazdin
• Chapter 3. Getting Out of Our Conceptual Ruts: Strategies for Expanding Conceptual Frameworks Allan W. Wicker
• Chapter 4. In Defense of External Invalidity Douglas G. Mook
• Chapter 5. When Small Effects Are Impressive Deborah A. Prentice and Dale T. Miller

Part III. Participants in Research

• Chapter 6. A WEIRD View of Human Nature Skews Psychologists' Studies Dan Jones
• Chapter 7. Toward a Psychology of Homo Sapiens : Making Psychological Science More Representative of the Human Population Mostafa Salari Rad, Alison Jane Martingano, and Jeremy Ginges

Diversity of Participants

• Chapter 8. On Becoming Multicultural in a Monocultural Research World: A Conceptual Approach to Studying Ethnocultural Diversity Gordon C. Nagayama Hall, Tiffany Yip, and Michael A. Zárate
• Chapter 9. Designing Studies for Sex and Gender Analyses: How Research Can Derive Clinically Useful Knowledge for Women's Health Ruth Klap and Keith Humphreys

Part IV. Design Options With and Without Randomization

Research Designs Options

• Chapter 10. Experimental and Observational Designs: An Overview Alan E. Kazdin
• Chapter 11. Observational Studies and Their Utility for Practice Julia F. M. Gilmartin-Thomas, Danny Liew, and Ingrid Hopper

Randomization and Randomized Controlled Trials

• Chapter 12. Random Sampling, Randomization, and Equivalence of Contrasted Groups in Psychotherapy Outcome Research Louis M. Hsu
• Chapter 13. Randomized Controlled Trials: Characteristics, Options, and Challenges Alan E. Kazdin

Part V. Assessment

Core Concepts and Considerations in Developing and Selecting Measures

• Chapter 14. Constructing Validity: New Developments in Creating Objective Measuring Instruments Lee Anna Clark and David Watson
• Chapter 15. Selecting Measures for Research Investigations Alan E. Kazdin

Novel Measurement Options

• Chapter 16. Computer-Enhanced Practice: The Benefits of Computer-Assisted Assessment in Applied Clinical Practice Stephanie Ruth Young, Danika L. S. Maddocks, and Jacqueline M. Caemmerer
• Chapter 17. Ecological Momentary Assessment (EMA) in Studies of Substance Use Saul Shiffman
• Chapter 18. AI in Mental Health Simon D’Alfonso

Part VI. Data Analysis, Evaluation, and Presentation

Background and Underpinnings of Data Analyses

• Chapter 19. A Power Primer Jacob Cohen
• Chapter 20. Abandon Statistical Significance Blakeley B. McShane, David Gal, Andrew Gelman, Christian Robert, and Jennifer L. Tackett
• Chapter 21. Ethical Concerns in Statistical Analyses: Implications for Clinical Research and Practice Owen J. Gaasedelen

Data Exploration and Multiple Methods of Data Analyses

• Chapter 22. Exploratory Data Analysis as a Foundation of Inductive Research Andrew T. Jebb, Scott Parrigon, and Sang Eun Woo
• Chapter 23. When Should We Use One-Tailed Hypothesis Testing? Graeme D. Ruxton and Markus Neuhäuser
• Chapter 24. The Proof of the Pudding: An Illustration of the Relative Strengths of Null Hypothesis, Meta-Analysis, and Bayesian Analysis George S. Howard, Scott E. Maxwell, and Kevin J. Fleming

Data Presentation

• Chapter 25. Designing Better Graphs by Including Distributional Information and Integrating Words, Numbers, and Images David M. Lane and Anikó Sándor

Part VII. Special Topics: Evaluation in Clinical Practice and Research

Evaluating Clinical Effects of Treatment

• Chapter 26. Routine Outcome Monitoring (ROM) and Feedback: Research Review and Recommendations Michael Barkham, Kim De Jong, Jaime Delgadillo, and Wolfgang Lutz
• Chapter 27. Revisiting and Reenvisioning the Outcome Problem in Psychotherapy: An Argument to Include Individualized and Qualitative Measurement Clara E. Hill, Harold Chui, and Ellen Baumann

Extending Treatments

• Chapter 28. Beyond Efficacy and Effectiveness: A Multifaceted Approach to Treatment Evaluation Timothy D. Nelson and Ric G. Steele
• Chapter 29. Testing Psychosocial Interventions in the Contexts They Are Meant to be Delivered Rinad S. Beidas, Lisa Saldana, and Rachel C. Shelton

Part VIII. Multiple Methodologies and Levels of Data Analysis

Beyond Quantitative Methods

• Chapter 30. What Can Qualitative Psychology Contribute to Psychological Knowledge? Carla Willig
• Chapter 31. Mixed Methods Research in Psychology Timothy C. Guetterman and Analay Perez
• Chapter 32. Single-Case Experimental Research Designs Alan E. Kazdin

Big Data, Secondary Data Sets, and Collaborative Science

• Chapter 33. Big Data in Psychology: A Framework for Research Advancement Idris Adjerid and Ken Kelley
• Chapter 34. Getting Started: Working With Secondary Data Amy M. Pienta, JoAnne McFarland O'Rourke, and Melissa M. Franks
• Chapter 35. How to Build Up Big Team Science: A Practical Guide for Large-Scale Collaborations Heidi A. Baumgartner, Nicolás Alessandroni, Krista Byers-Heinlein, Michael C. Frank, J. Kiley Hamlin, Melanie Soderstrom, Jan G. Voelkel, Robb Willer, Francis Yuen, and Nicholas A. Coles

Part IX. Ethics and Scientific Integrity

Guidelines and Codes

• Chapter 36. Ethical Principles of Psychologists and Code of Conduct American Psychological Association
• Chapter 37. Research Ethics: How to Treat People Who Participate in Research Ezekiel Emanuel, Emily Abdoler, and Leanne Stunkel

Professional Responsibilities for the Conduct of Research

• Chapter 38. International Recommendations to Guide Multiple Facets of the Research and Publication Process Alan E. Kazdin
• Chapter 39. False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant Joseph P. Simmons, Leif D. Nelson, and Uri Simonsohn
• Chapter 40. Best Practices for Allocating Appropriate Credit and Responsibility to Authors of Multi-Authored Articles Lucas D. Eggert

Part X. Open Science, Replication, and Research Practices

Open Science

• Chapter 41. A Manifesto for Reproducible Science Marcus R. Munafò, Brian A. Nosek, Dorothy V. M. Bishop, Katherine S. Button, Christopher D. Chambers, Nathalie Percie du Sert, Uri Simonsohn, Eric-Jan Wagenmakers, Jennifer J. Ware, and John P. A. Ioannidis
• Chapter 42. Replicate Others as You Would Like to Be Replicated Yourself Nicole Janz and Jeremy Freese

Practices to Improve Research

• Chapter 43. A Template for Preregistration of Quantitative Research in Psychology: Report of the Joint Psychological Societies Preregistration Task Force Michael Bosnjak, Christian J. Fiebach, David Mellor, Stefanie Mueller, Daryl B. O’Connor, Frederick L. Oswald, and Rosemarie I. Sokol
• Chapter 44. Responsible Practices for Data Sharing George Alter and Richard Gonzalez

Part XI. Publication and Communication of Research

Reporting Standards: What to Cover and Include in an Article

• Chapter 45. Journal Article Reporting Standards for Quantitative Research in Psychology: The APA Publications and Communications Board Task Force Report Mark Appelbaum, Harris Cooper, Rex B. Kline, Evan Mayo-Wilson, Arthur M. Nezu, and Stephen M. Rao

Communicating Research Findings

• Chapter 46. Publication and Communication of Research Findings Alan E. Kazdin

Part XII. Perspectives on Methodology

• Chapter 47. Methodology: Perspectives and General Lessons to Guide Research Alan E. Kazdin

About the Editor

Alan E. Kazdin, PhD, is a research scientist and sterling professor of psychology and child psychiatry at Yale University where he also served as chairman of the psychology department, director of the Child Study Center, director of child psychiatric services, and chair of the publications committee.

He has published 50 books on methodology, parenting and child-rearing, psychosocial interventions, interpersonal violence, and novel treatment delivery models.

His awards include the Research Scientist and MERIT Awards from the National Institute of Mental Health and the Gold Medal Award for Life Achievement in the Science of Psychology from the American Psychological Foundation.

This book is a must-read for all students and trainees in clinical and counseling psychology and the go-to resource for everyone interested in clinical science. It is an updated classic from the foremost leader in clinical psychological science. Kazdin assembled the best works in psychological methods to walk us through all stages of the research process emphasizing the importance of using science to understand and treat clinical disorders while at the same time addressing the challenges and pitfalls head-on. This updated masterpiece will be required reading in the training of the next generation of clinical scientists. —Jutta Joormann, PhD, Richard Ely Professor and Chair of Psychology, Yale University, New Haven, CT

Once again, Alan E. Kazdin has interwoven his own research design and methodological contributions with those of leading scholars across a variety of relevant areas to describe and clarify research and methodological issues in scientific inquiry. The result—an expanded and updated contemporary fifth edition of a book that will continue to serve as the model for informing and addressing methodological issues. It simply sets the standard in this arena for both academic and clinical readers. —W. Edward Craighead, PhD, ABPP, J. Rex Fuqua Professor and Vice Chair, Department of Psychiatry and Behavioral Sciences and Department of Psychology, Emory University, Atlanta, GA

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Qualitative Research in Psychology, Second Edition

Masks Strongly Recommended but Not Required in Maryland, Starting Immediately

Due to the downward trend in respiratory viruses in Maryland, masking is no longer required but remains strongly recommended in Johns Hopkins Medicine clinical locations in Maryland. Read more .

• Vaccines  
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Understanding Clinical Trials

Clinical research: what is it.

Your doctor may have said that you are eligible for a clinical trial, or you may have seen an ad for a clinical research study. What is clinical research, and is it right for you?

Clinical research is the comprehensive study of the safety and effectiveness of the most promising advances in patient care. Clinical research is different than laboratory research. It involves people who volunteer to help us better understand medicine and health. Lab research generally does not involve people — although it helps us learn which new ideas may help people.

Every drug, device, tool, diagnostic test, technique and technology used in medicine today was once tested in volunteers who took part in clinical research studies.

At Johns Hopkins Medicine, we believe that clinical research is key to improve care for people in our community and around the world. Once you understand more about clinical research, you may appreciate why it’s important to participate — for yourself and the community.

What Are the Types of Clinical Research?

There are two main kinds of clinical research:

Observational Studies

Observational studies are studies that aim to identify and analyze patterns in medical data or in biological samples, such as tissue or blood provided by study participants.

Clinical Trials

Clinical trials, which are also called interventional studies, test the safety and effectiveness of medical interventions — such as medications, procedures and tools — in living people.

Clinical research studies need people of every age, health status, race, gender, ethnicity and cultural background to participate. This will increase the chances that scientists and clinicians will develop treatments and procedures that are likely to be safe and work well in all people. Potential volunteers are carefully screened to ensure that they meet all of the requirements for any study before they begin. Most of the reasons people are not included in studies is because of concerns about safety.

Both healthy people and those with diagnosed medical conditions can take part in clinical research. Participation is always completely voluntary, and participants can leave a study at any time for any reason.

“The only way medical advancements can be made is if people volunteer to participate in clinical research. The research participant is just as necessary as the researcher in this partnership to advance health care.” Liz Martinez, Johns Hopkins Medicine Research Participant Advocate

Types of Research Studies

Within the two main kinds of clinical research, there are many types of studies. They vary based on the study goals, participants and other factors.

Biospecimen studies

Healthy volunteer studies.

Clinical trials study the safety and effectiveness of interventions and procedures on people’s health. Interventions may include medications, radiation, foods or behaviors, such as exercise. Usually, the treatments in clinical trials are studied in a laboratory and sometimes in animals before they are studied in humans. The goal of clinical trials is to find new and better ways of preventing, diagnosing and treating disease. They are used to test:

Drugs or medicines

New types of surgery

Medical devices

New ways of using current treatments

New ways of changing health behaviors

New ways to improve quality of life for sick patients

 Goals of Clinical Trials

Because every clinical trial is designed to answer one or more medical questions, different trials have different goals. Those goals include:

Treatment trials

Prevention trials, screening trials, phases of a clinical trial.

In general, a new drug needs to go through a series of four types of clinical trials. This helps researchers show that the medication is safe and effective. As a study moves through each phase, researchers learn more about a medication, including its risks and benefits.

Is the medication safe and what is the right dose?   Phase one trials involve small numbers of participants, often normal volunteers.

Does the new medication work and what are the side effects?   Phase two trials test the treatment or procedure on a larger number of participants. These participants usually have the condition or disease that the treatment is intended to remedy.

Is the new medication more effective than existing treatments?  Phase three trials have even more people enrolled. Some may get a placebo (a substance that has no medical effect) or an already approved treatment, so that the new medication can be compared to that treatment.

Is the new medication effective and safe over the long term?   Phase four happens after the treatment or procedure has been approved. Information about patients who are receiving the treatment is gathered and studied to see if any new information is seen when given to a large number of patients.

“Johns Hopkins has a comprehensive system overseeing research that is audited by the FDA and the Association for Accreditation of Human Research Protection Programs to make certain all research participants voluntarily agreed to join a study and their safety was maximized.” Gail Daumit, M.D., M.H.S., Vice Dean for Clinical Investigation, Johns Hopkins University School of Medicine

Is It Safe to Participate in Clinical Research?

There are several steps in place to protect volunteers who take part in clinical research studies. Clinical Research is regulated by the federal government. In addition, the institutional review board (IRB) and Human Subjects Research Protection Program at each study location have many safeguards built in to each study to protect the safety and privacy of participants.

Clinical researchers are required by law to follow the safety rules outlined by each study's protocol. A protocol is a detailed plan of what researchers will do in during the study.

In the U.S., every study site's IRB — which is made up of both medical experts and members of the general public — must approve all clinical research. IRB members also review plans for all clinical studies. And, they make sure that research participants are protected from as much risk as possible.

Earning Your Trust

This was not always the case. Many people of color are wary of joining clinical research because of previous poor treatment of underrepresented minorities throughout the U.S. This includes medical research performed on enslaved people without their consent, or not giving treatment to Black men who participated in the Tuskegee Study of Untreated Syphilis in the Negro Male. Since the 1970s, numerous regulations have been in place to protect the rights of study participants.

Many clinical research studies are also supervised by a data and safety monitoring committee. This is a group made up of experts in the area being studied. These biomedical professionals regularly monitor clinical studies as they progress. If they discover or suspect any problems with a study, they immediately stop the trial. In addition, Johns Hopkins Medicine’s Research Participant Advocacy Group focuses on improving the experience of people who participate in clinical research.

Clinical research participants with concerns about anything related to the study they are taking part in should contact Johns Hopkins Medicine’s IRB or our Research Participant Advocacy Group .

Learn More About Clinical Research at Johns Hopkins Medicine

For information about clinical trial opportunities at Johns Hopkins Medicine, visit our trials site.

Video Clinical Research for a Healthier Tomorrow: A Family Shares Their Story

Clinical Research for a Healthier Tomorrow: A Family Shares Their Story

• Open access
• Published: 07 June 2024

Effects of intensive lifestyle changes on the progression of mild cognitive impairment or early dementia due to Alzheimer’s disease: a randomized, controlled clinical trial

• Dean Ornish 1 , 2 ,
• Catherine Madison 1 , 3 ,
• Miia Kivipelto 4 , 5 , 6 , 7 ,
• Colleen Kemp 8 ,
• Charles E. McCulloch 9 ,
• Douglas Galasko 10 ,
• Jon Artz 11 , 12 ,
• Dorene Rentz 13 , 14 , 15 ,
• Jue Lin 16 ,
• Kim Norman 17 ,
• Anne Ornish 1 ,
• Sarah Tranter 8 ,
• Nancy DeLamarter 1 ,
• Noel Wingers 1 ,
• Carra Richling 1 ,
• Rima Kaddurah-Daouk 18 ,
• Rob Knight 19 ,
• Daniel McDonald 20 ,
• Lucas Patel 21 ,
• Eric Verdin 22 , 23 ,
• Rudolph E. Tanzi 13 , 24 , 25 , 26 &
• Steven E. Arnold 13 , 27  

Alzheimer's Research & Therapy volume  16 , Article number:  122 ( 2024 ) Cite this article

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Evidence links lifestyle factors with Alzheimer’s disease (AD). We report the first randomized, controlled clinical trial to determine if intensive lifestyle changes may beneficially affect the progression of mild cognitive impairment (MCI) or early dementia due to AD.

A 1:1 multicenter randomized controlled phase 2 trial, ages 45-90 with MCI or early dementia due to AD and a Montreal Cognitive Assessment (MoCA) score of 18 or higher. The primary outcome measures were changes in cognition and function tests: Clinical Global Impression of Change (CGIC), Alzheimer’s Disease Assessment Scale (ADAS-Cog), Clinical Dementia Rating–Sum of Boxes (CDR-SB), and Clinical Dementia Rating Global (CDR-G) after 20 weeks of an intensive multidomain lifestyle intervention compared to a wait-list usual care control group. ADAS-Cog, CDR-SB, and CDR-Global scales were compared using a Mann-Whitney-Wilcoxon rank-sum test, and CGIC was compared using Fisher’s exact test. Secondary outcomes included plasma Aβ42/40 ratio, other biomarkers, and correlating lifestyle with the degree of change in these measures.

Fifty-one AD patients enrolled, mean age 73.5. No significant differences in any measures at baseline. Only two patients withdrew. All patients had plasma Aβ42/40 ratios <0.0672 at baseline, strongly supporting AD diagnosis. After 20 weeks, significant between-group differences in the CGIC ( p = 0.001), CDR-SB ( p = 0.032), and CDR Global ( p = 0.037) tests and borderline significance in the ADAS-Cog test ( p = 0.053). CGIC, CDR Global, and ADAS-Cog showed improvement in cognition and function and CDR-SB showed significantly less progression, compared to the control group which worsened in all four measures. Aβ42/40 ratio increased in the intervention group and decreased in the control group ( p = 0.003). There was a significant correlation between lifestyle and both cognitive function and the plasma Aβ42/40 ratio. The microbiome improved only in the intervention group ( p <0.0001).

Conclusions

Comprehensive lifestyle changes may significantly improve cognition and function after 20 weeks in many patients with MCI or early dementia due to AD.

Trial registration

Approved by Western Institutional Review Board on 12/31/2017 (#20172897) and by Institutional Review Boards of all sites. This study was registered retrospectively with clinicaltrials.gov on October 8, 2020 (NCT04606420, ID: 20172897).

Increasing evidence links lifestyle factors with the onset and progression of dementia, including AD. These include unhealthful diets, being sedentary, emotional stress, and social isolation.

For example, a Lancet commission on dementia prevention, intervention, and care listed 12 potentially modifiable risk factors that together account for an estimated 40% of the global burden of dementia [ 1 ]. Many of these factors (e.g., hypertension, smoking, depression, type 2 diabetes, obesity, physical inactivity, and social isolation) are also risk factors for coronary heart disease and other chronic illnesses because they share many of the same underlying biological mechanisms. These include chronic inflammation, oxidative stress, insulin resistance, telomere shortening, sympathetic nervous system hyperactivity, and others [ 2 ]. A recent study reported that the association of lifestyle with cognition is mostly independent of brain pathology, though a part, estimated to be only 12%, was through β-amyloid [ 3 ].

In one large prospective study of adults 65 or older in Chicago, the risk of developing AD was 38% lower in those eating high vs low amounts of vegetables and 60% lower in those consuming omega-3 fatty acids at least once/week, [ 4 ] whereas consuming saturated fat and trans fats more than doubled the risk of developing AD [ 5 ].A systematic review and meta-analysis of 243 observational prospective studies and 153 randomized controlled trials found a similar relationship between these and similar risk factors and the onset of AD [ 6 ].

The multifactorial etiology and heterogeneity of AD suggest that multidomain lifestyle interventions may be more effective than single-domain ones for reducing the risk of dementia, and that more intensive multimodal lifestyle interventions may be more efficacious than moderate ones at preventing dementia [ 7 ].

For example, in the Finnish Geriatric Intervention Study (FINGER) study, a RCT of men and women 60-77 in age with Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) dementia risk scores of at least 6 points and cognition at mean or slightly lower, a multimodal intervention of diet, exercise, cognitive training, vascular risk monitoring maintained cognitive function after 2 years in older adults at increased risk of dementia [ 8 ]. After 24 months, global cognition in the FINGER intervention group was 25% higher than in the control group which declined. Moreover, the FINGER intervention was equally beneficial regardless of several demographic and socioeconomic risk factors [ 9 ] and apolipoprotein E (APOE) ε4 status [ 10 ].

The FINGER lifestyle intervention also resulted in a 13-20% reduction in rates of cardiovascular disease events (stroke, transient ischemic attack, or coronary), providing more evidence that “what’s good for the heart is good for the brain”(and vice versa) [ 11 ]. Other large-scale multidomain intervention studies to determine if this intervention can help prevent dementia are being conducted or planned in over 60 countries worldwide, as part of the World-Wide FINGERS network, including the POINTER study in the U.S. [ 12 , 13 ].

More recently, a similar dementia prevention-oriented RCT showed that a 2-year personalized multidomain intervention led to modest improvements in cognition and dementia risk factors in those at risk for (but not diagnosed with) dementia and AD [ 14 ].

All these studies showed that lifestyle changes may help prevent dementia. The study we are reporting here is the first randomized, controlled clinical trial to test whether intensive lifestyle changes may beneficially affect those already diagnosed with mild cognitive impairment (MCI) or early dementia due to AD.

In two earlier RCTs, we found that the same multimodal lifestyle intervention described in this article resulted in regression of coronary atherosclerosis as measured by quantitative coronary arteriography [ 15 ] and ventricular function, [ 16 ] improvements in myocardial perfusion as measured by cardiac PET scans, and 2.5 times fewer cardiac events after five years, all of which were statistically significant [ 17 ]. Until then, it was believed that coronary heart disease progression could only be slowed, not stopped or reversed, similar to how MCI or early dementia due to AD are viewed today.

Since AD and coronary heart disease share many of the same risk factors and biological mechanisms, and since moderate multimodal lifestyle changes may help prevent AD, [ 18 ] we hypothesized that a more intensive multimodal intervention proven to often reverse the progression of coronary heart disease and some other chronic diseases may also beneficially affect the progression of MCI or early dementia due to AD.

We report here results of a randomized controlled trial to determine if the progression of MCI or early dementia due to AD may be slowed, stopped, or perhaps even reversed by a comprehensive, multimodal, intensive lifestyle intervention after 20 weeks when compared to a usual-care randomized control group. This lifestyle intervention includes (1) a whole foods, minimally processed plant-based diet low in harmful fats and low in refined carbohydrates and sweeteners with selected supplements; (2) moderate exercise; (3) stress management techniques; and (4) support groups.

This intensive multimodal lifestyle modification RCT sought to address the following questions:

Can the specified multimodal intensive lifestyle changes beneficially affect the progression of MCI or early dementia due to AD as measured by the AD Assessment Scale–Cognitive Subscale (ADAS-Cog), CGIC (Clinical Global Impression of Change), CDR-SB (Clinical Dementia Rating Sum of Boxes), and CDR-G (Clinical Dementia Rating Global) testing?

Is there a significant correlation between the degree of lifestyle change and the degree of change in these measures of cognition and function?

Is there a significant correlation between the degree of lifestyle change and the degree of change in selected biomarkers (e.g., the plasma Aβ42/40 ratio)?

Participants and methods

This study was a 1:1 multi-center RCT during the first 20 weeks of the study, and these findings are reported here. Patients who met the clinical trial inclusion criteria were enrolled between September 2018 and June 2022.

Participants were enrolled who met the following inclusion criteria:

Male or female, ages 45 to 90

Current diagnosis of MCI or early dementia due to AD process, with a MoCA score of 18 or higher (National Institute on Aging–Alzheimer’s Association McKhann and Albert 2011 criteria) [ 19 , 20 ]

Physician shared this diagnosis with the patient and approved their participation in this clinical trial

Willingness and ability to participate in all aspects of the intervention

Availability of spouse or caregiver to provide collateral information and assist with study adherence

Patients were excluded if they had any of the following:

Moderate or severe dementia

Physical disability that precludes regular exercise

Evidence for other primary causes of neurodegeneration or dementia, e.g., significant cerebrovascular disease (whose primary cause of dementia was vascular in origin), Lewy Body disease, Parkinson's disease, FTD

Significant ongoing psychiatric or substance abuse problems

Fifty-one participants with MCI or early-stage dementia due to AD who met these inclusion criteria were enrolled between September 2018 and June 2022 and underwent baseline testing. 26 of the enrolled participants were randomly assigned to an intervention group that received the multimodal lifestyle intervention for 20 weeks and 25 participants were randomly assigned to a usual habits and care control group that was asked not to make any lifestyle changes for 20 weeks, after which they would be offered the intervention. Patients in both groups received standard of care treatment managed by their own neurologist.

The intervention group received the lifestyle program for 20 weeks (initially in person, then via synchronous Zoom after March 2020 due to COVID-19). Two participants who did not want to continue these lifestyle changes withdrew during this time, both in the intervention group (one male, one female). Participants in both groups completed a follow-up visit at 20 weeks, where clinical and cognitive assessments were completed. Data were analyzed comparing the baseline and 20 week assessments between the groups.

In a drug trial, access to an investigational new drug can be restricted from participants in a randomized control group. However, we learned in our prior clinical trials of this lifestyle intervention with other diseases that it is often difficult to persuade participants who are randomly assigned to a usual-care control group to refrain from making these lifestyle changes for more than 20 weeks, which is why this time duration was chosen. If participants in both groups made similar lifestyle changes, then it would not be possible to show differences between the groups. Therefore, to encourage participants randomly assigned to the control group not to make lifestyle changes during the first 20 weeks, we offered to provide them the same lifestyle program at no cost to them for 20 weeks after being in the usual-care control group and tested after 20 weeks.

We initially planned to enroll 100 patients into this study based on power calculations of possible differences between groups in cognition and function after 20 weeks. However, due to challenges in recruiting patients, especially with the COVID-19 emergency and that many pharma trials began recruiting patients with similar criteria, it took longer to enroll patients than initially planned [ 21 ]. Because of this, we terminated recruitment after 51 patients were enrolled. This decision was based only on recruitment issues and limited funding, without reviewing the data at that time.

Patients were recruited from advertisements, presentations at neurology meetings, referrals from diverse groups of neurologists and other physicians, and a search of an online database of patients at UCSF. We put a special emphasis on recruiting diverse patients, although we were less successful in doing so than we hoped (Table 1 ).

This clinical trial was approved by the Western Institutional Review Board on 12/31/2017 (approval number: 20172897) and all participants and their study partners provided written informed consent. The trial protocol was also approved by the appropriate Institutional Review Board of all participating sites, and all subjects provided informed consent. Due to the COVID-19 emergency, planned MRI and amyloid PET scans were no longer feasible, and the number of cognition and function tests was decreased. An initial inclusion criterion of “current diagnosis of mild to moderate dementia due to AD (McKhann et al., 2011)” was further clarified to include a MoCA score of 18 or higher. This study was registered with clinicaltrials.gov on October 8, 2020 (NCT04606420, Unique Protocol ID: 20172897) retrospectively due to an administrative error. None of the sponsors who provided funding for this study participated in its design, conduct, management, or reporting of the results. Those providing the lifestyle intervention were separate from those performing testing and from those collecting and analyzing the data, who were blinded to group assignment. All authors contributed to manuscript draft revisions, provided critical comment, and approved submission for publication.

Any modifications in the protocol were approved in advance and in writing by the senior biostatistician (Charles McCulloch PhD) or the senior expert neuropsychologist (Dorene Rentz PsyD), and subsequently approved by the WIRB.

Patients were initially recruited only from the San Francisco Bay area beginning October 2018 and met in person until February 2020 when the COVID-19 pandemic began. Subsequently, this multimodal lifestyle intervention was offered to patients at home in real time via Zoom.

Offering this intervention virtually provided an opportunity to recruit patients from multiple sites, including the Massachusetts General Hospital/Harvard Medical School, Boston, MA; the University of California, San Diego; and Renown Regional Medical Center, Reno, NV, as well as with neurologists in the San Francisco Bay Area. These participants were recruited and tested locally at each site and the intervention was provided via Zoom and foods were sent directly to their home.

Patient recruitment

This is described in the Supplemental Materials section.

Intensive multimodal lifestyle intervention

Each patient received a copy of a book which describes this lifestyle medicine intervention for other chronic diseases. [ 2 ]

A whole foods minimally-processed plant-based (vegan) diet, high in complex carbohydrates (predominantly fruits, vegetables, whole grains, legumes, soy products, seeds and nuts) and especially low in harmful fats, sweeteners and refined carbohydrates. It was approximately 14-18% of calories as total fat, 16-18% protein, and 63-68% mostly complex carbohydrates. Calories were unrestricted. Those with higher caloric needs were given extra portions.

To assure the high adherence and standardization required to adequately test the hypothesis, 21 meals/week and snacks plus the daily supplements listed below were provided throughout the 40 weeks of this intervention to each study participant and his or her spouse or study partner at no cost to them. Twice/week, we overnight shipped to each patient as well as to their spouse or study partner three meals plus two snacks per day that met the nutritional guidelines as well as the prescribed nutritional supplements.

We asked participants to consume only the food and nutritional supplements we sent to them and no other foods. We reasoned that if adherence to the diet and lifestyle intervention was high, whatever outcomes we measured would be of interest. That is, if patients in the intervention group were adherent but showed no significant benefits, that would be a disappointing but an important finding. If they showed improvement, that would also be an important finding. But if they did not follow the lifestyle intervention sufficiently, then we would not have been able to adequately test the hypotheses.

Aerobic (e.g., walking) at least 30 minutes/day and mild strength training exercises at least three times per week from an exercise physiologist in person or with virtual sessions. Patients were given a personalized exercise prescription based on age and fitness level. All sessions were overseen by a registered nurse.

• Stress management

Meditation, gentle yoga-based poses, stretching, progressive relaxation, breathing exercises, and imagery for a total of one hour per day, supervised by a certified stress management specialist. The purpose of each technique was to increase the patient’s sense of relaxation, concentration, and awareness. They were also given access to online meditations. Patients had the option of using flashing-light glasses at a theta frequency of 7.83 Hz plus soothing music as an aid to meditation and insomnia [ 22 ]. They were also encouraged to get adequate sleep.

Group support

Participants and their spouses/study partners participated in a support group one hour/session, three days/week, supervised by a licensed mental health professional in a supportive, safe environment to increase emotional support and community as well as communication skills and strategies for maintaining adherence to the program. They also received a book with memory exercises used periodically during group sessions [ 23 ].

To reinforce this lifestyle intervention, each patient and their spouse or study partner met three times/week, four hours/session via Zoom: 2

one hour of supervised exercise (aerobic + strength training)

one hour of stress management practices (stretching, breathing, meditation, imagery)

one hour of a support group

one hour lecture on lifestyle

Additional optional exercise and stress management classes were provided.

Supplements

Omega-3 fatty acids with Curcumin (1680 mg omega-3 & 800 mg Curcumin, Nordic Naturals ProOmega CRP, 4 capsules/day). Omega-3 fatty acids: In those age 65 or older, those consuming omega-3 fatty acids once/week or more had a 60% lower risk of developing AD, and total intake of n-3 polyunsaturated fatty acids was associated with reduced risk of Alzheimer disease [ 24 ]. Curcumin targets inflammatory and antioxidant pathways as well as (directly) amyloid aggregation, [ 25 ] although there may be problems with bioavailability and crossing the blood-brain barrier [ 26 ].

Multivitamin and Minerals (Solgar VM-75 without iron, 1 tablet/day). Combinatorial formulations demonstrate improvement in cognitive performance and the behavioral difficulties that accompany AD [ 27 ].

Coenzyme Q10 (200 mg, Nordic Naturals, 2 soft gels/day). CoQ10. May reduce mitochondrial impairment in AD [ 28 ].

Vitamin C (1 gram, Solgar, 1 tablet/day): Maintaining healthy vitamin C levels may have a protective function against age-related cognitive decline and AD [ 29 ].

Vitamin B12 (500 mcg, Solgar, 1 tablet/day): B12 hypovitaminosis is linked to the development of AD pathology [ 30 ].

Magnesium L-Threonate (Mg) (144 mg, Magtein, 2 tablets/day). A meta-analysis found that Mg deficiency may be a risk factor of AD and Mg supplementation may be an adjunctive treatment for AD [ 31 ].

Hericium erinaceus (Lion’s Mane, Stamets Host Defense, 2 grams/day): Lion’s mane may produce significant improvements in cognition and function in healthy people over 50 [ 32 ] and in MCI patients compared to placebo [ 33 ].

Super Bifido Plus Probiotic (Flora, 1 tablet/day). A meta-analysis suggests that probiotics may benefit AD patients [ 34 ].

Primary outcome measures: cognition and function testing

Four tests were used to assess changes in cognition and function in these patients. These are standard measures of cognition and function included in many FDA drug trials: ADAS-Cog; Clinical Global Impression of Change (CGIC); Clinical Dementia Rating Sum of Boxes (CDR-SB); Clinical Dementia Rating Global (CDR Global). All cognition and function raters were trained psychometrists with experience in administering these tests in clinical trials. Efforts were made to have the same person perform cognitive testing at each visit to reduce inter-observer variability. Those doing ADAS-Cog assessments were certified raters and tested patients in person. The CGIC and CDR tests were administered for all patients via Zoom by different raters than the ADAS-cog. Also, raters were blind to treatment arm to the degree possible.

Secondary outcome measures: biomarkers and microbiome

These are described in the Supplemental Materials section. These include blood-based biomarkers (such as the plasma Aβ42/40 ratio) and microbiome taxa (organisms).

Statistical methods

These are described in the Supplemental Materials section.

The recruitment effort for this trial lasted from 01/23/2018 to 6/16/2022. The most effective recruitment method was referral from the subjects’ physician or healthcare provider. Additional recruitment efforts included advertising in print and digital media; speaking to community groups; mentioning the study during podcast and radio interviews; collaborating with research institutions that provide dementia diagnosis and treatment; and contracting a clinical trials recruitment service (Linea). A total of 1585 people contacted us; of these, 1300 did not meet the inclusion criteria, 102 declined participation, and 132 were screening incomplete when enrollment closed, resulting in the enrollment of 51 participants (Fig. 1 ).

CONSORT flowchart: patients, demographics, and enrollment

The remaining 51 patients were randomized to an intervention group (26 patients) that received the lifestyle intervention for 20 weeks or to a usual-care control group (25 patients) that was asked not to make any lifestyle changes. Two patients in the intervention group withdrew during the intervention because they did not want to continue the diet and lifestyle changes. No patients in the control group withdrew prior to 20-week testing. Analyses were performed on the remaining 49 patients. No patients were lost to follow-up.

All of these 49 patients had plasma Aβ42/40 ratios <0.089 (all were <0.0672), strongly supporting the diagnosis of Alzheimer’s disease [ 35 ].

At baseline, there were no statistically significant differences between the intervention group and the randomized control group in any measures, including demographic characteristics, cognitive function measures, or biomarkers (Table 1  and Table 2 ).

Cognition and function testing: primary analysis

Results after 20 weeks of a multimodal intensive lifestyle intervention in all patients showed overall statistically significant differences between the intervention group and the randomized control group in cognition and function in the CGIC ( p = 0.001), CDR-SB ( p = 0.032), and CDR Global ( p = 0.037) tests and of borderline significance in the ADAS-Cog test ( p = 0.053, Table 3 ). Three of these measures (CGIC, CDR Global, ADAS-Cog) showed improvement in cognition and function in the intervention group and worsening in the control group, and one test (CDR-SB) showed significantly less progression when compared to the randomized control group, which worsened in all four of these measures.

PRIMARY ANALYSIS (with outlier included), Table 3 :

CGIC (Clinical Global Impression of Change)

These scores improved in the intervention group and worsened in the control group.

(Fisher’s exact p -value = 0.001). 10 people in the intervention group showed improvement compared to none in the control group. 7 people in the intervention group and 8 people in the control group were unchanged. 7 people in the intervention group showed minimal worsening compared to 14 in the control group. None in the intervention group showed moderate worsening compared to 3 in the control group.

CDR-Global (Clinical Dementia Rating-Global)

These scores improved in the intervention group (from 0.69 to 0.65) and worsened in the randomized control group (from 0.66 to 0.74), mean difference = 0.12, p = 0.037 (Table 3 and Fig. 2 ).

Changes in CDR-Global (lower = improved)

ADAS-Cog (Alzheimer’s Disease Assessment Scale)

These scores improved in the intervention group (from 21.551 to 20.536) and worsened in the randomized control group (from 21.252 to 22.160), mean group difference of change = 1.923 points, p = 0.053 (Table 3 and Fig. 3 ). (ADAS-Cog testing in one intervention group patient was not administered properly so it was excluded.)

Changes in ADAS-Cog (lower = improved)

CDR-SB (Clinical Dementia Rating Sum of Boxes)

These scores worsened significantly more in the control group (from 3.34 to 3.86) than in the intervention group (from 3.27 to 3.35), mean group difference = 0.44, p = 0.032 (Table 3 and Fig. 4 ).

Changes in CDR-SB (lower = improved)

There were no significant differences in depression scores as measured by PHQ-9 between the intervention and control groups.

Secondary sensitivity analyses

One patient in the intervention group was a clear statistical outlier in his cognitive function testing based on standard mathematical definitions (none was an outlier in the control group) [ 36 ]. Therefore, this patient’s data were excluded in a secondary sensitivity analysis. These results showed statistically significant differences in all four of these measures of cognition and function (Table 4 ). Three measures (ADAS-Cog, CGIC, and CDR Global) showed significant improvement in cognition and function and one (CDR-SB) showed significantly less worsening when compared to the randomized control group, which worsened in all four of these measures.

Sensitivity analysis (with outlier excluded)

There were no significant differences in depression scores as measured by PHQ-9 between the intervention and control groups in either analysis.

A reason why this patient might have been a statistical outlier is that he reported intense situational stress before his testing. As a second sensitivity analysis, this same outlier patient was retested when he was calmer, and all four measures (ADAS-Cog, CGIC, CDR Global, and CDR-SB) showed significant improvement in cognition and function, whereas the randomized control group worsened in all four of these measures.

Biomarker results

We selected biomarkers that have a known role in the pathophysiology of AD (Table 5 ). Of note is that the plasma Aβ42/40 ratio increased in the intervention group but decreased in the randomized control group ( p = 0.003, two-tailed).

Correlation of lifestyle index and cognitive function

In the current clinical trial, despite the inherent limitations of self-reported data, we found statistically significant correlations between the degree of lifestyle change (from baseline to 20 weeks) and the degree of change in three of four measures of cognition and function as well as correlations between the adherence to desired lifestyle changes at just the 20-week timepoint and the degree of change in two of the four measures of cognition and function and borderline significance in the fourth measure.

Correlation with lifestyle at 20 weeks: p = 0.052; correlation: 0.241

Correlation with degree of change in lifestyle: p = 0.015; correlation: 0.317

Correlation with lifestyle at 20 weeks: p = 0.043; correlation: 0.251

Correlation with degree of change in lifestyle: p = 0.081; correlation: 0.205

Correlation with lifestyle at 20 weeks: p = 0.065; correlation: 0.221

Correlation with degree of change in lifestyle: p = 0.024; correlation: 0.286

Correlation with lifestyle at 20 weeks: p = 0.002

Correlation with degree of change in lifestyle: p = 0.0005

(CGIC tests are non-parametric analyses, so standard effect size calculations are not included for this measure.)

Also, we also found a significant correlation between dietary total fat intake and changes in the CGIC measure ( p = 0.001), but this was not significant for the other three measures.

Correlation of lifestyle index and biomarker data

In the current clinical trial, despite the inherent limitations of self-reported data, we found statistically significant correlations between the degree of lifestyle change (from baseline to 20 weeks) and the degree of change in many of the key biomarkers, as well as correlations between the degree of lifestyle change at 20 weeks and the degree of change in these biomarkers:

Plasma Aβ42/40 ratio

Correlation with lifestyle at 20 weeks: p = 0.035; correlation: 0.306

Correlation with degree of change in lifestyle: p = 0.068; correlation: 0.266

Correlation with lifestyle at 20 weeks: p = 0.011; correlation: 0.363

Correlation with degree of change in lifestyle: p = 0.007; correlation: 0.383

LDL-cholesterol

Correlation with lifestyle at 20 weeks: p < 0.0001; correlation: 0.678

Correlation with degree of change in lifestyle: p < 0.0001; correlation: 0.628

Beta-Hydroxybutyrate (ketones)

Correlation with lifestyle at 20 weeks: p = 0.013; correlation: 0.372

Correlation with degree of change in lifestyle: p = 0.034; correlation: 0.320

Correlation with lifestyle at 20 weeks: p = 0.228; correlation: 0.177

Correlation with degree of change in lifestyle: p = 0.135; correlation: 0.219

GFAP/glial fibrillary acidic protein

Correlation with lifestyle at 20 weeks: p = 0.096; correlation: 0.243

Correlation with degree of change in lifestyle: p =0.351; correlation: 0.138

What degree of lifestyle change is correlated with improvement in cognitive function tests?

What degree of lifestyle is needed to stop or improve the worsening of MCI or early dementia due to AD? In other words, what % of adherence to the lifestyle intervention was correlated with no change in MCI or dementia across both groups? Higher adherence than this degree of lifestyle change was associated with improvement in MCI or dementia.

Correlation with lifestyle at 20 weeks: 71.4% adherence

Correlation with lifestyle at 20 weeks: 120.6% adherence

CDR-Global:

Correlation with lifestyle at 20 weeks: 95.6%

Microbiome results

There was a significant and beneficial change in the microbiome configuration in the intervention group but not in the control group.

Several taxa (groups of microorganisms) that increased only in the intervention group were consistent with those involved in reduced AD risk in other studies. For example, Blautia, which increased during the intervention in the intervention group, has previously been associated with a lower risk of AD, potentially due to its involvement in increasing γ-aminobutyric acid (GABA) production [ 37 ].  Eubacterium also increased during the intervention in the intervention group, and prior studies have identified Eubacterium genera (namely Eubacterium fissicatena) as a protective factor in AD [ 38 ].

Also, there was a decrease in relative abundance of taxa involved in increased AD risk in the intervention group, e.g., Prevotella and Turicibacter , the latter of which has been associated with relevant biological processes such as 5-HT production. Prevotella and Turicibacter have previously been shown to increase with disease progression, [ 39 ] and these taxa decreased over the course of the intervention.

These results support the hypothesis that the lifestyle intervention may beneficially modify specific microbial groups in the microbiome: increasing those that lower the risk of AD and decreasing those that increase the risk of AD. (Please see Supplement for more detailed information.)

We report the first randomized, controlled trial showing that an intensive multimodal lifestyle intervention may significantly improve cognition and function and may allay biological features in many patients with MCI or early dementia due to AD after 20 weeks.

After 20 weeks of a multimodal intensive lifestyle intervention, results of the primary analysis when all patients were included showed overall statistically significant differences between the intervention group and the randomized control group in cognition and function as measured by the CGIC ( p = 0.001), CDR-SB ( p = 0.032), and CDR Global ( p = 0.037) tests and of borderline significance in the ADAS-Cog test ( p = 0.053).

Three of these measures (CGIC, CDR Global, ADAS-Cog) showed improvement in cognition and function in the intervention group and worsening in the randomized control group, and one test (CDR-SB) showed less progression in the intervention group when compared to the control group which worsened in all four of these measures.

These differences were even clearer in a secondary sensitivity analysis when a mathematical outlier was excluded. These results showed statistically significant differences between groups in all four of these measures of cognition and function. Three of these measures showed improvement in cognition and function and one (CDR-SB) showed less deterioration when compared to the randomized control group, which worsened in all four of these measures.

The validity of these changes in cognition and function and possible biological mechanisms of improvement is supported by the observed changes in several clinically relevant biomarkers that showed statistically significant differences in a beneficial direction after 20 weeks when compared to the randomized control group.

One of the most clinically relevant biomarkers is the plasma Aβ42/40 ratio, which increased by 6.4% in the intervention group and decreased by 8.3% in the randomized control group after 20 weeks, and these differences were statistically significant ( p = 0.003, two-tailed).

In the lecanemab trial, plasma levels of the Aβ42/40 biomarker increased in the intervention group over 18 months with the presumption that this reflected amyloid moving from the brain to the plasma [ 40 ]. We found similar results in the direction of change in the plasma Aβ42/40 ratio from this lifestyle intervention but in only 20 weeks. Conversely, this biomarker decreased in the control group (as in the lecanemab trial), which may indicate increased cerebral uptake of amyloid.

Other clinically relevant biomarkers also showed statistically significant differences (two-tailed) in a beneficial direction after 20 weeks when compared to the randomized control group. These include hemoglobin A1c, insulin, glycoprotein acetyls (GlycA), LDL-cholesterol, and β-Hydroxybutyrate (ketone bodies).

Improvement in these biomarkers provides more biological plausibility for the observed improvements in cognition and function as well as more insight into the possible mechanisms of improvement. This information may also help in predicting which patients are more likely to show improvements in cognition and function by making these intensive lifestyle changes.

Other relevant biomarkers were in a beneficial direction of change in the intervention group compared with the randomized control group after 20 weeks. These include pTau181, GFAP, CRP, SAA, and C-peptide. Telomere length increased in the intervention group and was essentially unchanged in the control group. These differences were not statistically significant even when there was an order of magnitude difference between groups (as with GFAP and pTau181) or an almost four-fold difference (as with CRP), but these changes were in a beneficial direction. At least in part, these findings may be due to a relatively small sample size and/or a short duration of only 20 weeks.

We found a statistically significant dose-response correlation between the degree of lifestyle changes in both groups (“lifestyle index”) and the degree of change in many of these biomarkers. This correlation was found in both the degree of change in lifestyle from baseline to 20 weeks as well as the lifestyle measured at 20 weeks. These correlations also add to the biological plausibility of these findings.

We also found a statistically significant dose-response correlation between the degree of lifestyle changes in both groups (“lifestyle index”) and changes in most measures of cognition and function testing. In short, the more these AD patients changed their lifestyle in the prescribed ways, the greater was the beneficial impact on their cognition and function. These correlations also add to the biological plausibility of these findings. This variation in adherence helps to explain in part why some patients in the intervention group improved and others did not, but there are likely other mechanisms that we do not fully understand that may play a role. These statistically significant correlations are especially meaningful given the greater variability of self-reported data, the relatively small sample size, and the short duration of the intervention.

These findings are consistent with earlier clinical trials in which we used this same lifestyle intervention and the same measure of lifestyle index and found significant dose-response correlations between this lifestyle index (i.e., the degree of lifestyle changes) and changes in the degree of coronary atherosclerosis (percent diameter stenosis) in coronary heart disease; [ 41 , 45 ] changes in PSA levels and LNCaP cell growth in men with prostate cancer; [ 42 ] and changes in telomere length [ 43 ].

We also found significant differences between the intervention and control groups in several taxa (groups of micro-organisms) in the microbiome which may be beneficial.

There were no significant differences in depression scores as measured by PHQ-9 between the intervention and control groups. Therefore, reduction in depression is unlikely to account for the overall improvements in cognition and function seen in the intervention group patients.

We also found that substantial lifestyle changes were required to stop the progression of MCI in these patients. In the primary analysis, this ranged from 71.4% adherence for ADAS-Cog to 95.6% adherence for CDR-Global to 120.6% adherence for CDR-SB. In other words, extensive lifestyle changes were required to stop or improve cognition and function in these patients. This helps to explain why other studies of less-intensive lifestyle interventions may not have been sufficient to stop deterioration or improve cognition and function.

For example, comparing these results to those of the MIND-AD clinical trial provides more biological plausibility for both studies [ 44 ]. That is, more moderate multimodal lifestyle changes may slow the rate of worsening of cognition and function in MCI or early dementia due to early-stage AD, whereas more intensive multimodal lifestyle changes may result in overall average improvements in many measures of cognition and function when compared to a randomized usual-care control group in both clinical trials.

Lifestyle changes may provide additional benefits to patients on drug therapy. Anti-amyloid antibodies have shown modest effects on slowing progression, but they are expensive, have potential for adverse events, are not yet widely available, and do not result in overall cognitive improvement [ 40 ]. Perhaps there may be synergy from doing both.

Limitations

This study has several limitations. Only 51 patients were enrolled and randomized in our study, and two of these patients (both in the intervention group) withdrew during the trial. Showing statistically significant differences across different tests of cognition and function and other measures despite the relatively small sample size suggests that the lifestyle intervention may be especially effective and has strong internal validity.

However, the smaller sample size limits generalizability, especially since there was much less racial and ethnic diversity in this sample than we strived to achieve. Also, we measured these differences despite the relative insensitivity of these measures, which might have increased the likelihood of a type II error.

Raters were blinded to the group assignment of the participants. However, unlike a double-blind placebo-controlled drug trial, it is not possible to blind subjects in a lifestyle intervention about whether or not they are receiving the intervention. This might have affected outcome measures, although to reduce positive expectations and because it was true, patients were told during the study that we did not know whether or not this lifestyle intervention would be beneficial, and we said that whatever we showed would be useful.

Also, 20 weeks is a relatively short time for any intervention with MCI or early dementia due to AD. We did not include direct measures of brain structure in this trial, so we cannot determine whether there were direct impacts on markers of brain pathology relevant to AD. However, surrogate markers such as the plasma Aβ42/40 ratio are becoming more widely accepted.

Not all patients in the intervention group improved. Of the 24 patients in the intervention group, 10 showed improvement as measured by the CGIC test, 7 were unchanged, and 7 worsened. In the control group, none improved, 8 were unchanged, and 17 worsened. In part, this may be explained by variations in adherence to the lifestyle intervention, as there was a significant relationship between the degree of lifestyle change and the degree of change in cognition and function across both groups. We hope that further research may further clarify other factors and mechanisms to help explain why cognition and function improved in some patients but not in others.

The findings on the degree of lifestyle change required to stop the worsening or improve cognition and function need to be interpreted with caution. Since data from both groups were combined, it was no longer a randomized trial for this specific analysis, so there could be unknown confounding influences. Also, it is possible that those with improved changes in cognition were better able to adhere to the intervention and thus have higher lifestyle indices.

In summary, in persons with mild cognitive impairment or early dementia due to Alzheimer’s disease, comprehensive lifestyle changes may improve cognition and function in several standard measures after 20 weeks. In contrast, patients in the randomized control group showed overall worsening in all four measures of cognition and function during this time.

The validity of these findings was supported by the observed changes in plasma biomarkers and microbiome; the dose-response correlation of the degree of lifestyle change with the degree of improvement in all four measures of cognition and function; and the correlation between the degree of lifestyle change and the degree of changes in the Aβ42/40 ratio and the changes in some other relevant biomarkers in a beneficial direction.

Our findings also have implications for helping to prevent AD. Newer technologies, some aided by artificial intelligence, enable the probable diagnosis of AD years before it becomes clinically apparent. However, many people do not want to know if they are likely to get AD if they do not believe they can do anything about it. If intensive lifestyle changes may cause improvement in cognition and function in MCI or early dementia due to AD, then it is reasonable to think that these lifestyle changes may also help to prevent MCI or early dementia due to AD. Also, it may take less-extensive lifestyle changes to help prevent AD than to treat it. Other studies cited earlier on the effects of these lifestyle changes on diseases such as coronary heart disease support this conclusion. Clearly, intensive lifestyle changes rather than moderate ones seem to be required to improve cognition and function in those suffering from early-stage AD.

These findings support longer follow-up and larger clinical trials to determine the longer-term outcomes of this intensive lifestyle medicine intervention in larger groups of more diverse AD populations; why some patients beneficially respond to a lifestyle intervention better than others besides differences in adherence; as well as the potential synergy of these lifestyle changes and some drug therapies.

Availability of data and materials

The datasets used and/or analyzed during the current study may be available from the corresponding author on reasonable request. Requesters will be asked to submit a study protocol, including the research question, planned analysis, and data required. The authors will evaluate this plan (i.e., relevance of the research question, suitability of the data, quality of the proposed analysis, planned or ongoing analysis, and other matters) on a case-by-case basis.

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Acknowledgements

We are grateful to each of the following people who made this study possible. Paramount among these are all of the study participants and their spouse or support person. Their commitment was inspiring, and without them this study would not have been possible. Each of the staff who provided and supported this program is exceptionally caring and competent, and includes: Heather Amador, who coordinated and administered all grants and infrastructure; Tandis Alizadeh, who is chief of staff; as well as Lynn Sievers, Nikki Liversedge, Pamela Kimmel, Stacie Dooreck, Antonella Dewell, Stacey Dunn-Emke, Marie Goodell, Emily Dougherty, Kamala Berrio, Kristin Gottesman, Katie Mayers, Dennis Malone, Sarah & Mary Barber, Steven Singleton, Kevin Lane, Laurie Case, Amber O’Neill, Annie DiRocco, Alison Eastwood, Sara Henley, Sousha Naghshineh, Sarah Reinhard, Laura Kandell, Alison Haag, Sinead Lafferty, Haley Perkins, Chase Delaney, Danielle Marquez, Ava Hoffman, Sienna Lopez, and Sophia Gnuse. Dr. Caitlin Moore conducted much of the cognition and function testing along with Dr. Catherine Madison, Trevor Ragas, Andrea Espinosa, Lorraine Martinez, Davor Zink, Jeff Webb, Griffin Duffy, Lauren Sather, and others. Dr. Cecily Jenkins trained the ADAS-Cog rater. Dr. Jan Krumsiek and Dr. Richa Batra performed important analyses in Dr. Rima Kaddurah-Daouk’s lab. Dr. Pia Kivisåkk oversaw biomarker assays in Dr. Steven Arnold's lab. We are grateful to all of the referring neurologists. Board members of the nonprofit Preventive Medicine Research Institute provided invaluable oversight and support, including Henry Groppe, Jenard & Gail Gross, Ken Hubbard, Brock Leach, and Lee Stein, as well as Joel Goldman.

Author’s information

DO is the corresponding author. RT contributed as the senior author.

We are very grateful to Leonard A. Lauder & Judith Glickman Lauder; Gary & Laura Lauder; Howard Fillit and Mark Roithmayr of The Alzheimer’s Drug Discovery Foundation; Mary & Patrick Scanlan of the Mary Bucksbaum Scanlan Family Foundation; Laurene Powell Jobs/Silicon Valley Community Foundation; Pierre & Pamela Omidyar Fund/Silicon Valley Community Foundation (Pat Christen and Jeff Alvord); George Vradenburg Foundation/Us Against Alzheimer’s; American Endowment Foundation (Anna & James McKelvey); Arthur M. Blank Family Foundation/Around the Table Foundation (Elizabeth Brown, Natalie Gilbert, Christian Amica); John Paul & Eloise DeJoria Peace Love & Happiness Foundation (Constance Dykhuizen); Maria Shriver/Women’s Alzheimer’s Movement (Sandy Gleysteen, Laurel Ann Gonsecki, Erin Stein); Mark Pincus Family Fund/Silicon Valley Community Foundation; Christy Walton/Walton Family Foundation; Milken Family Foundation; The Cleveland Clinic Lou Ruvo Center for Brain Health (Larry Ruvo); Jim Greenbaum Foundation; R. Martin Chavez; Wonderful Company Foundation (Stewart & Lynda Resnick); Daniel Socolow; Anthony J. Robbins/Tony Robbins Foundation; John Mackey; John & Lisa Pritzker and the Lisa Stone Pritzker Family Foundation; Ken Hubbard; Greater Houston Community Foundation (Jenard & Gail Gross); Henry Groppe; Brock & Julie Leach Family Charitable Foundation; Bucksbaum/Baum Foundation (Glenn Bucksbaum & April Minnich); YPO Gold Los Angeles; Lisa Holland/Betty Robertson; the Each Foundation (Lionel Shaw); Moby Charitable Fund; California Relief Program; Gary & Lisa Schildhorn; McNabb Foundation (Ricky Rafner); Renaissance Charitable Foumdation (Stephen & Karen Slinkard); Network for Good; Ken & Kim Raisler Foundation; Miner Foundation; Craiglist Charitable Fund (Jim Buckmaster and Annika Joy Quist); Gaurav Kapadia; Healing Works Foundation/Wayne Jonas; and the Center for Innovative Medicine (CIMED) at the Karolinska Institutet, Hjärnfonden, Stockholms Sjukhem, Research Council for Health Working Life and Welfare (FORTE). In-kind donations were received from Alan & Rob Gore of Body Craft Recreation Supply (exercise equipment), Dr. Andrew Abraham of Orgain, Paul Stamets of Fungi Perfecta ( Host Defense Lion’s Mane), Nordic Naturals, and Flora. Dr. Rima Kaddurah-Daouk at Duke is PI of the Alzheimer Gut Microbiome Project (funded by NIA U19AG063744). She also received additional funding from NIA that has enabled her research (U01AG061359 & R01AG081322).

The funders had no role in the conceptualization; study design; data collection; analysis; and interpretation; writing of the report; or the decision to submit for publication.

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Preventive Medicine Research Institute, 900 Bridgeway, Sausalito, CA, USA

Dean Ornish, Catherine Madison, Anne Ornish, Nancy DeLamarter, Noel Wingers & Carra Richling

University of California, San Francisco and University of California, San Diego, USA

Dean Ornish

Ray Dolby Brain Health Center, California Pacific Medical Center, San Francisco, CA, USA

Catherine Madison

Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Karolinska vägen 37 A, SE-171 64, Solna, Sweden

Miia Kivipelto

Theme Inflammation and Aging, Karolinska University Hospital, Karolinska vägen 37 A, SE-171 64, Stockholm, Solna, Sweden

The Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, St Mary’s Hospital, Norfolk Place, London, W2 1PG, United Kingdom

Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Yliopistonranta 8, 70210, Kuopio, Finland

Clinical Services, Preventive Medicine Research Institute, Bridgeway, Sausalito, CA, 900, USA

Colleen Kemp & Sarah Tranter

Division of Biostatistics, Department of Epidemiology & Biostatistics, UCSF, San Francisco, CA, USA

Charles E. McCulloch

Neurosciences, University of California, San Diego, CA, USA

Douglas Galasko

Clinical Neurology, School of Medicine, University of Nevada, Reno, USA

Renown Health Institute of Neurosciences, Reno, NV, USA

Harvard Medical School, Boston, MA, USA

Dorene Rentz, Rudolph E. Tanzi & Steven E. Arnold

Center for Alzheimer Research and Treatment, Boston, MA, USA

Dorene Rentz

Mass General Brigham Alzheimer Disease Research Center, Boston, MA, USA

Elizabeth Blackburn Lab, UCSF, San Francisco, CA, USA

UCSF, San Francisco, CA, USA

Departments of Medicine and Psychiatry, Duke University Medical Center and Member, Duke Institute of Brain Sciences, Durham, NC, USA

Rima Kaddurah-Daouk

Department of Pediatrics; Department of Computer Science & Engineering; Department of Bioengineering; Center for Microbiome Innovation, Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, CA, USA

Department of Pediatrics and Scientific Director, American Gut Project and The Microsetta Initiative, University of California San Diego, La Jolla, CA, USA

Daniel McDonald

Bioinformatics and Systems Biology Program; Rob Knight Lab; Medical Scientist Training Program, University of California, San Diego, La Jolla, CA, USA

Lucas Patel

Buck Institute for Research on Aging, San Francisco, CA, USA

Eric Verdin

University of California, San Francisco, CA, USA

Genetics and Aging Research Unit, Boston, MA, USA

Rudolph E. Tanzi

McCance Center for Brain Health, Boston, MA, USA

Massachusetts General Hospital, Boston, MA, USA

Interdisciplinary Brain Center, Massachusetts General Hospital, Boston, MA, USA

Steven E. Arnold

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Contributions

DO, CM, MK, CK, DG, JA, DR, CEM, JL, KN, AO, ST, ND, NW, CR, RKD, RK, EV, RT, and SEA were involved in the study design and conduct. DO conceptualized the study hypotheses (building on the work of MK), obtained funding, prepared the first draft of the manuscript, and is the principal investigator. CEM oversaw the statistical analyses and interpretation, and DR oversaw the cognition and function testing and interpretation. CK and ST oversaw all clinical operations and patient recruitment, including the IRB. JL conducted the telomere analyses. CM oversaw patient selection. AO developed the learning management system and community platform for patients and providers. KN managed an IRB. ND co-led most of the support groups, and CR oversaw all aspects involving nutrition. All authors participated in writing the manuscript. NW and ST oversaw data collection and prepared the databases other than the microbiome databases which were overseen by RK and prepared by DM and LP who helped design this part of the study. CM, CK, JL, RKD, RK, DM, and LP were involved in the acquisition of data. SA, RT, and RKD did biomarker analyses. All authors contributed to critical review of the manuscript and approved the final manuscript.

Corresponding author

Correspondence to Dean Ornish .

Ethics declarations

Competing interests.

MK is one of the Editors-in-Chief of this journal and has no relevant competing interests and recused herself from the review process. RKD is an inventor on key patents in the field of metabolomics and holds equity in Metabolon, a biotech company in North Carolina. In addition, she holds patents licensed to Chymia LLC and PsyProtix with royalties and ownership. DO and AO have consulted for Sharecare and have received book royalties and lecture honoraria and, with CK, have received equity in Ornish Lifestyle Medicine. RK is a scientific advisory board member and consultant for BiomeSense, Inc., has equity and receives income. He is a scientific advisory board member and has equity in GenCirq. He is a consultant and scientific advisory board member for DayTwo, and receives income. He has equity in and acts as a consultant for Cybele. He is a co-founder of Biota, Inc., and has equity. He is a cofounder of Micronoma, and has equity and is a scientific advisory board member. The terms of these arrangements have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies. DM is a consultant for BiomeSense. RT is a co-founder and equity holder in Hyperion Rx, which produces the flashing-light glasses at a theta frequency of 7.83 Hz used as an optional aid to meditation. The rest of the authors declare that they have no competing interests.

Ethics approval and consent to participate

This clinical trial was approved by the Western Institutional Review Board on 12/31/2017 (approval number: 20172897) and all participants and their study partners provided written informed consent. The trial protocol was also approved by the appropriate Institutional Review Board of all participating sites; and all subjects provided informed consent.

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Informed consent was received from all patients. All data from research participants described in this paper is de-identified.

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Ornish, D., Madison, C., Kivipelto, M. et al. Effects of intensive lifestyle changes on the progression of mild cognitive impairment or early dementia due to Alzheimer’s disease: a randomized, controlled clinical trial. Alz Res Therapy 16 , 122 (2024). https://doi.org/10.1186/s13195-024-01482-z

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Leading Change in Cancer Clinical Research, Because Our Patients Can’t Wait

May 31, 2024 , by W. Kimryn Rathmell, M.D., Ph.D., and Shaalan Beg, M.D.

Greater use of technologies that can increase participation in cancer clinical trials is just one of the innovations that can help overcome some of the bottlenecks holding up progress in clinical research. 

Thanks to advances in technology, data science, and infrastructure, the pace of discovery and innovation in cancer research has accelerated, producing an impressive range of potential new treatments and other interventions that are being tested in clinical studies . The extent of the innovative ideas that might help people live longer, improve our ability to detect cancer early, or otherwise transform care is staggering. 

Our understanding of tumor biology is also evolving, and those gains in knowledge are being translated into the continued discovery of targets for potential interventions  and the development of novel types of treatments. Some of these therapies are producing unprecedented clinical responses  in studies, including in traditionally difficult-to-treat cancers. 

These advances have contributed to a record number of Food and Drug Administration (FDA) approvals in recent years with, arguably, the most notable approvals being those for drugs that can be used for any cancer, regardless of where it is in the body . 

In some instances, the activity of new agents has been so profound that clinical investigators are having to rethink their criteria for implementation in patient care and their definitions of treatment response. 

For example, although HER2 has been a known therapeutic target in breast cancer for many decades, the new antibody-drug conjugates  (ADCs) that target HER2 have proven to be vastly more effective than the original HER2-targeted therapies. This has forced researchers to rethink fundamental questions about how these ADCs are used in patient care: Can they be effective in people whose tumors have lower expression of HER2 than we previously thought was needed ? And, if so, do we need to redefine how we classify HER2-positive cancer? 

As more innovative therapies like ADCs hit the clinic at a far more rapid cadence than ever before, the research community is being inundated with such fundamentally important questions.

However, the remarkable progress we're experiencing with novel new therapies is tempered by a critical bottleneck: the clinical research infrastructure can’t be expected to keep pace in this new landscape. 

Currently, many studies struggle to enroll enough participants. At the same time, there are patients who don’t have ready access to studies from which they might benefit. Furthermore, ideas researchers have today for studies of innovative new interventions might not come to fruition for 2 or 3 years, or even longer—years that people with cancer don’t have. 

The key to overcoming this bottleneck is to invite innovation to help reshape our clinical trials infrastructure. And here’s how we plan to accomplish that.

Testing Innovation in Cancer Clinical Trials

A transformation in cancer clinical research is already underway. That transformation has been led in part by the success of novel precision oncology approaches, such as those tested in the NCI-MATCH trial .

This innovative study ushered in novel ways of recruiting participants and involving oncologists at centers big and small. And NCI-MATCH has spawned several successor studies that are incorporating and building on its innovations and achievements.

An innovation that emerged from the COVID pandemic was the increase of remote work, even in the clinical trials domain. Indeed, staffing shortages have caused participation in NCI-funded trials to decline. In response, NCI is piloting a Virtual Clinical Trials Office to offer remote support staff to participating study sites. This support staff includes research nurses, clinical research associates, and data specialists, all of whom will help NCI-Designated Cancer Centers and community practices engaged in clinical research activities.

Such technology-enabled services can allow us to reimagine how clinical trials are designed and run. This includes developing technologies and processes for remotely identifying clinical trial participants, shipping medications to participants at home, having imaging performed in the health care settings where our patients live, and empowering local physicians to participate in clinical trials.

We also need mechanisms to test and implement innovations in designing and conducting clinical studies. 

The Pragmatica-Lung Cancer Treatment Trial , an innovative phase 3 study launched by  NCI’s National Clinical Trials Network (NCTN) , was designed to be easy to launch, enroll participants, and interpret its results. 

NCI recently established Clinical Trials Innovation Unit (CTIU) to pressure test a variety of innovations. The CTIU, which includes leadership from FDA and NCTN, is already working on future innovations, including those that will streamline data collection and apply novel approaches to clinical studies, all with the goal of making them less burdensome to run and easier for patients to participate.

Data-Driven Solutions

The era of data-driven health care is here, providing still more opportunities to transform cancer clinical research. 

The emergence of artificial intelligence (AI) solutions, large language models, and informatics brings real potential for wholesale changes in how we match patients to clinical studies, assess side effects, and monitor events like disease progression. 

Recognizing this potential, NCI is offering funding opportunities and other resources that will fuel the development of AI tools for clinical research, allow us to carefully test their usefulness, and ultimately deploy them across the oncology community. 

Creating Partnerships and Expanding Health Equity

To be sure, none of this will be, or can be, done by NCI alone. All these innovations require partnerships. We will increase our engagement with partners in the public- and private-sectors, including other government agencies and nonprofits. 

That includes high-level engagement with the Office of the National Coordinator for Health Information Technology (ONC), with input from FDA, Centers for Medicare & Medicaid Services, and Centers for Disease Control and Prevention.

Dr. W. Kimryn Rathmell, M.D., Ph.D.

NCI Director

One example of such a partnership is the USCDI+ Cancer program . Conducted under the auspices of the ONC, this program will further the aims of the White House's reignited Cancer Moonshot SM by encouraging the adoption and utilization of interoperable cancer health IT standards, providing resources to support cancer-specific use cases, and promoting alignment between federal partners. 

And just as importantly, the new partnerships we create must include those with patients, advocates, and communities in ways we have never considered before.

A central feature of this community engagement must involve intentional efforts to expand health equity, to create study designs that are inclusive and culturally appropriate. Far too many marginalized communities and populations today are further harmed by studies that fail to provide findings that apply to their unique situations and needs.

Very importantly, the future will require educating our next generation of clinical investigators and empowering them with the tools that enable new ways of managing clinical studies. By supporting initiatives spearheaded by FDA and professional groups like the American Society of Clinical Oncology, NCI is making it easier for community oncologists to participate in clinical trials and helping clarify previously misunderstood regulatory requirements. 

These efforts must also ensure that we have a clinical research workforce that is representative of the people it is intended to serve. Far too many structural barriers have prevented this from taking place in the past, and it’s time for that to change. 

Expanding our capacity doesn’t mean doing more of the same, it means challenging ourselves to work differently. This will let us move forward to a new state, one in which clinical research is integrated in everyday practice. It is only with more strategic partnerships and increased inclusivity that we can open the doors to seeing clinical investigation in new ways, with new standards for success.

A Collaborative Effort

Shaalan Beg, M.D.

Senior Advisor for Clinical Research

To make the kind of progress we all desire, we have to recognize that our clinical studies system needs to evolve.

There was a time when taking years to design, launch, and complete a clinical trial was acceptable. It isn’t acceptable anymore. We are in an era where we have the tools and the research talent to make far more rapid progress than we have in the past. 

And we can do that by engaging with many different communities and stakeholders in unique and dynamic ways—making them partners in our effort to end cancer as we know it.

Together, our task is to capitalize on this work so we can move faster and enable cutting-edge research that benefits as many people as possible. 

We also know that there are more good ideas in this space, and part of this transformation includes grass roots efforts to drive systemic change. So, we encourage you to share your ideas on how we can transform clinical research. Because achieving this goal can’t be done by any one group alone. We are all in this together. 

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NIH will bring clinical research into primary care offices with $30 million pilot

By Annalisa Merelli June 7, 2024

F or many Americans, health care means going to a local primary care office. But the vast majority of clinical research is conducted inside the walls of large, specialized academic health centers. Millions of patients are left out of those studies, which often fail to capture the population in all its diversity.

Now, for the first time, the National Institutes of Health is investing in the creation of a national primary care research network to try to address this issue. Its $30 million pilot program, called Communities Advancing Research Equity for Health and announced on Thursday, will fund and support a small number of primary care sites as they participate in a range of clinical trials.

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“This is an incredibly exciting opportunity,” said Diane Harper, a primary care physician and professor in family medicine at the University of Michigan, Ann Arbor. Instead of running individual, siloed research projects out of specialized sites, the program will allow network members to participate in several trials — choosing between 20 to 30 studies — to match their local population’s health needs.

“A person is not a disease, and most of the NIH is organized around diseases,” said Harper. “This is the first time that NIH is recognizing that people are complex, and have many factors that pertain to their health care…that cannot be teased out and separated to be studied in a single, particular line.”

Related: NIH-funded clinical trials often miss racial, gender diversity enrollment goals, report finds

The pilot is an opportunity to better understand how research can serve the needs of patients outside traditional settings, said NIH director Monica Bertagnolli. “We know that every community is different, and we cannot just assume that a rural community in Alabama is going to be the same as a rural community in Montana or that their health issues are the same,” she said. “What we want to do is to be able to offer any community a whole bunch of different research opportunities,” learning through experience what they find most meaningful.

The research projects will go beyond drug trials to emphasize issues that are acutely experienced by communities facing health disparities, including substance abuse, mental health disorders, and obesity.

The timeline is tight: NIH hopes to award funding very soon, and hold its first investigator meeting by the winter. The focus on a speedy start, said Harper, is not giving primary care sites sufficient time to apply for the funding deadline, which is set for next week. As a result, she worries the first round of research will be led by academic networks with links to primary care. “These are not primary care networks,” she said. “These are PhDs with ideas about what it means to be in primary care, it’s not the people who practice.”

The accelerated timeline was put in place to support a launch by the end of fiscal year 2024, said NIH spokesperson Renate Myles, while still allowing the application period to be open for about six weeks. “We expect more opportunities in future years for potential applicants who were unable to participate this year,” she said.

This isn’t the first experiment with primary care research networks. “There’s many folks who’ve worked for a long time to help the NIH get to this point where they’re ready to take their research out of the academic medical center into rural and frontier and underserved community practices,” said Jack Westfall, a rural primary care physician and retired professor at the University of Colorado.

In the late 1990s, Westfall helped establish the High Plains Research Network, a research network of all the primary care practices in eastern, rural, and frontier Colorado towns — most with just a few thousand residents each. He’s found that community-based studies can pay dividends for researchers, too.

“The NIH research needs to move outside of the academic medical centers, out into the community, out into the primary care practices, both for finding study subjects, but also for finding research ideas,” said Westfall. “Many times there are clinical questions that come up out of the community, from the patients, from their interactions with their physicians that could generate ongoing ideas for research.”

Related: Inside a push to create an NIH office for post-infection chronic illness

The NIH also sees the program as an opportunity to gain trust from communities that are skeptical of the medical establishment. “We are here to understand what people need and to earn their trust by delivering for them,” said Bertagnolli. “Trust is not automatic, it has to be earned.”

To build that trust, the network will have to be careful not to treat patients and their local providers like cogs in a machine. “The risk is that this will just be extractive, not collaborative,” said Westfall. “We want to make sure that this is not just an extraction of study subjects out of primary care and NIH, but a bidirectional flow of resources, of ideas, of topics, of power.”

“Making studies available closer to where people are actually getting treated, that’s the first step,” said Andrew Trister, chief medical and scientific officer at Verily, an Alphabet company that builds tools for clinical research. But it raises a number of important questions, he said: “What’s the chain of the trust chain? Who is trusted in the community? Who could be able to help people understand more about what the clinical study is about? Why participate in research?”

Down the line, the network could help primary care sites to mobilize more effectively in case of national health emergencies. “The Covid pandemic did not use primary care at all efficiently,” said Harper. But if the pilot is successful and expands to create a nationwide network, it could eventually enable a faster, more effective public health response — and clinical trials, to boot.

About the Author Reprints

Annalisa merelli.

General Assignment Reporter

Annalisa (Nalis) Merelli is a general assignment reporter at STAT. Her interests are ever-expanding, but she is especially drawn to the coverage of reproductive and maternal health, and their intersection with health equity.

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Common Comorbidities with Substance Use Disorders Research Report Part 1: The Connection Between Substance Use Disorders and Mental Illness

Many individuals who develop substance use disorders (SUD) are also diagnosed with mental disorders, and vice versa. 2,3 Although there are fewer studies on comorbidity among youth, research suggests that adolescents with substance use disorders also have high rates of co-occurring mental illness; over 60 percent of adolescents in community-based substance use disorder treatment programs also meet diagnostic criteria for another mental illness. 4

Data show high rates of comorbid substance use disorders and anxiety disorders—which include generalized anxiety disorder, panic disorder, and post-traumatic stress disorder. 5–9 Substance use disorders also co-occur at high prevalence with mental disorders, such as depression and bipolar disorder, 6,9–11 attention-deficit hyperactivity disorder (ADHD), 12,13 psychotic illness, 14,15 borderline personality disorder, 16 and antisocial personality disorder. 10,15 Patients with schizophrenia have higher rates of alcohol, tobacco, and drug use disorders than the general population. 17 As Figure 1 shows, the overlap is especially pronounced with serious mental illness (SMI). Serious mental illness among people ages 18 and older is defined at the federal level as having, at any time during the past year, a diagnosable mental, behavior, or emotional disorder that causes serious functional impairment that substantially interferes with or limits one or more major life activities. Serious mental illnesses include major depression, schizophrenia, and bipolar disorder, and other mental disorders that cause serious impairment. 18 Around 1 in 4 individuals with SMI also have an SUD.

Data from a large nationally representative sample suggested that people with mental, personality, and substance use disorders were at increased risk for nonmedical use of prescription opioids. 19 Research indicates that 43 percent of people in SUD treatment for nonmedical use of prescription painkillers have a diagnosis or symptoms of mental health disorders, particularly depression and anxiety. 20

Youth—A Vulnerable Time

Although drug use and addiction can happen at any time during a person’s life, drug use typically starts in adolescence, a period when the first signs of mental illness commonly appear. Comorbid disorders can also be seen among youth. 21–23 During the transition to young adulthood (age 18 to 25 years), people with comorbid disorders need coordinated support to help them navigate potentially stressful changes in education, work, and relationships. 21

Drug Use and Mental Health Disorders in Childhood or Adolescence Increases Later Risk

The brain continues to develop through adolescence. Circuits that control executive functions such as decision making and impulse control are among the last to mature, which enhances vulnerability to drug use and the development of a substance use disorder. 3,24 Early drug use is a strong risk factor for later development of substance use disorders, 24 and it may also be a risk factor for the later occurrence of other mental illnesses. 25,26 However, this link is not necessarily causative and may reflect shared risk factors including genetic vulnerability, psychosocial experiences, and/or general environmental influences. For example, frequent marijuana use during adolescence can increase the risk of psychosis in adulthood, specifically in individuals who carry a particular gene variant. 26,27

It is also true that having a mental disorder in childhood or adolescence can increase the risk of later drug use and the development of a substance use disorder. Some research has found that mental illness may precede a substance use disorder, suggesting that better diagnosis of youth mental illness may help reduce comorbidity. One study found that adolescent-onset bipolar disorder confers a greater risk of subsequent substance use disorder compared to adult-onset bipolar disorder. 28 Similarly, other research suggests that youth develop internalizing disorders, including depression and anxiety, prior to developing substance use disorders. 29

Untreated Childhood ADHD Can Increase Later Risk of Drug Problems

Numerous studies have documented an increased risk for substance use disorders in youth with untreated ADHD, 13,30 although some studies suggest that only those with comorbid conduct disorders have greater odds of later developing a substance use disorder. 30,31 Given this linkage, it is important to determine whether effective treatment of ADHD could prevent subsequent drug use and addiction. Treatment of childhood ADHD with stimulant medications such as methylphenidate or amphetamine reduces the impulsive behavior, fidgeting, and  inability to concentrate that characterize ADHD. 32

That risk presents a challenge when treating children with ADHD, since effective treatment often involves prescribing stimulant medications with addictive potential. Although the research is not yet conclusive, many studies suggest that ADHD medications do not increase the risk of substance use disorder among children with this condition. 31,32 It is important to combine stimulant medication for ADHD with appropriate family and child education and behavioral interventions, including counseling on the chronic nature of ADHD and risk for substance use disorder. 13,32

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High Blood Pressure & Kidney Disease

On this page:

What is high blood pressure?

What are the kidneys and what do they do.

• How does high blood pressure affect the kidneys?

How common are high blood pressure and kidney disease?

Who is more likely to have high blood pressure or kidney disease, what are the symptoms of high blood pressure and kidney disease, how do health care professionals diagnose high blood pressure and kidney disease, how can i prevent or slow the progression of kidney disease from high blood pressure, how does eating, diet, and nutrition affect high blood pressure and kidney disease, clinical trials for kidney disease.

Blood pressure is the force of blood pushing against blood vessel walls as your heart pumps out blood. High blood pressure , also called hypertension , is an increase in the amount of force that blood places on blood vessels as it moves through the body.

Healthy kidneys filter about a half cup of blood every minute, removing wastes and extra water to make urine . The urine flows from each kidney to the bladder through a pair of thin tubes called ureters, one on each side of your bladder. Your bladder stores urine. Your kidneys, ureters, and bladder are part of your urinary tract system.

How does high blood pressure affect the kidneys

High blood pressure can constrict and narrow the blood vessels, which eventually damages and weakens them throughout the body, including in the kidneys. The narrowing reduces blood flow.

If your kidneys’ blood vessels are damaged, they may no longer work properly. When this happens, the kidneys are not able to remove all wastes and extra fluid from your body. Extra fluid in the blood vessels can raise your blood pressure even more, creating a dangerous cycle, and cause more damage leading to kidney failure.

Almost 1 in 2 U.S. adults—or about 108 million people—have high blood pressure. 1

More than 1 in 7 U.S. adults—or about 37 million people—may have chronic kidney disease (CKD) . 2

High blood pressure is the second leading cause of kidney failure in the United States after diabetes , as illustrated in Figure 1. 2

Almost 1 in 2 U.S. adults—or about 108 million people—have high blood pressure.

High blood pressure

You are more likely to have high blood pressure if you

• are older. Blood pressures tends to increase with age. Our blood vessels naturally thicken and stiffen over time.
• have family members with high blood pressure. High blood pressure tends to run in families.
• have unhealthy lifestyle habits. Unhealthy habits such as eating too much sodium (salt), drinking too many alcoholic beverages, or not being physically active can increase your risk of high blood pressure.
• are African American. High blood pressure is more common in African American adults than in Caucasian, Hispanic, or Asian adults.
• are male.  Men are more likely to develop high blood pressure before age 55; women are more likely to develop it after age 55.

Kidney disease

In addition to high blood pressure, other factors that increase your risk of kidney disease are

• a family history of kidney failure
• race or ethnicity—African Americans, Hispanics, and American Indians tend to have a greater risk for CKD

High blood pressure can be both a cause and a result of kidney disease.

Most people with high blood pressure do not have symptoms. In rare cases, high blood pressure can cause headaches.

Early CKD also may not have symptoms. As kidney disease gets worse, some people may have swelling, called edema . Edema happens when the kidneys cannot get rid of extra fluid and salt. Edema can occur in the legs, feet, ankles, or—less often—in the hands or face.

Symptoms of advanced kidney disease can include

• loss of appetite, nausea, or vomiting
• drowsiness, feeling tired, or sleep problems
• headaches or trouble concentrating
• increased or decreased urination
• generalized itching or numbness, dry skin, or darkened skin
• weight loss
• muscle cramps
• chest pain or shortness of breath

Blood pressure test results are written with the two numbers separated by a slash. The top number is called the systolic pressure and represents the pressure as the heart beats and pushes blood through the blood vessels. The bottom number is called the diastolic pressure and represents the pressure as blood vessels relax between heartbeats.

Your health care professional will diagnose you with high blood pressure if your blood pressure readings are consistently higher than 130/80 when tested repeatedly in a health care office.

Health care professionals measure blood pressure with a blood pressure cuff. You can also buy a blood pressure cuff to monitor your blood pressure at home.

To check for kidney disease , health care professionals use

• a blood test that checks how well your kidneys are filtering your blood, called GFR, which stands for glomerular filtration rate .
• a urine test to check for albumin . Albumin is a protein that can pass into the urine when the kidneys are damaged.

If you have kidney disease, your health care professional will use the same two tests to monitor your kidney disease.

The best way to slow or prevent kidney disease  from high blood pressure is to take steps to lower your blood pressure. These steps include a combination of medicines and lifestyle changes, such as

• being physically active
• maintaining a healthy weight
• quitting smoking
• managing stress
• following a healthy diet, including less sodium (salt) intake

No matter what the cause of your kidney disease, high blood pressure can make your kidneys worse. If you have kidney disease, you should talk with your health care professional about your individual blood pressure goals and how often you should have your blood pressure checked.

Medicines that lower blood pressure can also significantly slow the progression of kidney disease. Two types of blood pressure-lowering medications, angiotensin-converting enzyme (ACE) inhibitors  and angiotensin receptor blockers (ARBs) , may be effective in slowing the progression of kidney disease.

Many people require two or more medications to control their blood pressure. In addition to an ACE inhibitor or an ARB, a health care professional may prescribe a diuretic —a medication that helps the kidneys remove fluid from the blood—or other blood pressure medications .

Physical activity

Regular physical activity  can lower your blood pressure and reduce your chances of other health problems.

Aim for at least 150 minutes per week of moderate-intensity aerobic activity. These activities make your heart beat faster and may cause you to breathe harder. Start by trying to be active for at least 10 minutes at a time without breaks. You can count each 10-minute segment of activity toward your physical activity goal. Aerobic activities include

• biking (Don’t forget the helmet.)
• brisk walking
• wheeling yourself in a wheelchair or engaging in activities that will support you such as chair aerobics

If you have concerns, a health care professional can provide information about how much and what kinds of activity are safe for you.

Body weight

If you are overweight or have obesity , aim to reduce your weight by 7 to 10 percent during the first year of treatment for high blood pressure. This amount of weight loss can lower your chance of developing health problems related to high blood pressure.

Body Mass Index (BMI) is the tool most commonly used to estimate and screen for overweight and obesity in adults. BMI is a measure based on your weight in relation to your height. Your BMI can tell if you are at a normal or healthy weight, are overweight, or have obesity.

• Normal or healthy weight. A person with a BMI of 18.5 to 24.9 is in the normal or healthy range.
• Overweight. A person with a BMI of 25 to 29.9 is considered overweight.
• Obesity. A person with a BMI of 30 to 39.9 is considered to have obesity.
• Severe obesity. A person with a BMI of 40 or greater is considered to have severe obesity.

Your goal should be a BMI lower than 25 to help keep your blood pressure under control. 3

If you smoke, you should quit. Smoking can damage blood vessels, raise the chance of developing high blood pressure, and worsen health problems related to high blood pressure.

If you have high blood pressure, talk with your health care professional about programs and products to help you quit smoking.

Learning how to manage stress, relax, and cope with problems can improve your emotional and physical health. Some activities that may help you reduce stress include

• practicing yoga or tai chi
• listening to music
• focusing on something calm or peaceful

Following a healthy eating plan  can help lower your blood pressure. Reducing the amount of sodium in your diet is an important part of any healthy eating plan. Your health care professional may recommend the Dietary Approaches to Stop Hypertension (DASH) eating plan . DASH focuses on fruits, vegetables, whole grains, and other foods that are healthy for your heart and lower in sodium, which often comes from salt. The DASH eating plan

• is low in fat and cholesterol
• features fat-free or low-fat milk and dairy products, fish, poultry, and nuts
• suggests less red meat, sweets, added sugars, and sugar-containing beverages
• is rich in nutrients, protein, and fiber

A registered dietitian can help tailor your diet to your kidney disease. If you have congestive heart failure or edema, a diet low in sodium intake can help reduce edema and lower blood pressure. Reducing saturated fat and cholesterol can help control high levels of lipids, or fats, in the blood.

People with advanced kidney disease should speak with their health care professional about their diet.

What should I avoid eating if I have high blood pressure or kidney disease?

If you have kidney disease, avoid foods and beverages that are high in sodium .

Additional steps you can take to meet your blood pressure goals may include eating heart-healthy and low-sodium meals, quitting smoking, being active, getting enough sleep, and taking your medicines as prescribed. You should also limit alcoholic drinks—no more than two per day for men and one per day for women—because consuming too many alcoholic beverages raises blood pressure.

In addition, a health care professional may recommend that you eat moderate or reduced amounts of protein.

Proteins break down into waste products that the kidneys filter from the blood. Eating more protein than your body needs may burden your kidneys and cause kidney function to decline faster. However, eating too little protein may lead to malnutrition, a condition that occurs when the body does not get enough nutrients.

If you have kidney disease and are on a restricted protein diet, a health care professional will use blood tests to monitor your nutrient levels.

The NIDDK conducts and supports clinical trials in many diseases and conditions, including kidney diseases. The trials look to find new ways to prevent, detect, or treat disease and improve quality of life.

What are clinical trials for high blood pressure and kidney disease?

Clinical trials—and other types of clinical studies —are part of medical research and involve people like you. When you volunteer to take part in a clinical study, you help doctors and researchers learn more about disease and improve health care for people in the future.

Researchers are studying many aspects of high blood pressure and kidney disease, such as

• managing high blood pressure through diet, education, and counseling in patients with kidney disease
• testing new medications to treat high blood pressure and kidney disease

Find out if clinical studies are right for you .

What clinical studies for high blood pressure and kidney disease are looking for participants?

You can view a filtered list of clinical studies on high blood pressure and kidney disease that are federally funded, open, and recruiting at www.ClinicalTrials.gov . You can expand or narrow the list to include clinical studies from industry, universities, and individuals; however, the National Institutes of Health does not review these studies and cannot ensure they are safe. Always talk with your health care professional before you participate in a clinical study.

What have we learned about high blood pressure and kidney disease from NIDDK-funded research?

The NIDDK has supported many research projects to learn more about the effects of high blood pressure on kidney disease including identifying genes related to a cholesterol protein that causes African Americans to be at higher risk for kidney disease .

This content is provided as a service of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), part of the National Institutes of Health. NIDDK translates and disseminates research findings to increase knowledge and understanding about health and disease among patients, health professionals, and the public. Content produced by NIDDK is carefully reviewed by NIDDK scientists and other experts.

The NIDDK would like to thank: Raymond R. Townsend, M.D., Perelman School of Medicine, University of Pennsylvania, and Matthew Weir, M.D., University of Maryland School of Medicine