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The Central Council for Research in Homoeopathy is an autonomous organization under Ministry of Ayurveda, Yoga, Unani, Sidha and Homoeopathy (AYUSH), Government of India. The Council aids and/or conducts effective, scientific and ethical research in homoeopathy and disseminate latest research for enhancing its global acceptance. 

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Indian Journal of Research in Homoeopathy (IJRH) [ISSN: 0974-7168] is an internationally acclaimed official publication of Central Council for Research in Homoeopathy, New Delhi published quarterly in print as well as online with free access at www.ijrh.org. Since, first issue in 2007 we have published ten volumes comprising over 36 issues and around 200 research articles on Homoeopathy.  The Journal was made open access online in July 2013 and is following rigorous peer-review process to provide constructive feedback to Authors to improve submission quality. 

The current focus of homoeopathic research is on the evidence-based practices and universally acknowledged parameters, with special emphasis on documentation.

The journal is committed to meet the needs of readers and authors, to constantly improve the quality of content and maintain integrity of the academic records. It is determined to handle complications transparently by publications of acknowledgements consistent with established policies. The Journal ensures that research paper published has ethical clearance, no conflict of interest and discourages plagiarism and copyright violations.

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The Journal publishes evidence and science based articles limited to Homoeopathic research which has positive impact globally. The journal’s regular subscribers include homoeopathic practitioners, health care professionals, authors, other bio-medical researchers, medical students, policy makers and ultimately patients.   We invite scientific submissions in Homoeopathy from the authors in the following categories: Original, substantiated and unpublished research in all aspects of basic and applied research in Homoeopathy, Evidence based/Systematic reviews, Case reports/series, Book Reviews, Debates etc. Some of the areas of focus are Drug Standardisation, Drug Proving, Clinical Verification, Clinical Research, Extramural Research and Collaborative Research in Homoeopathy. 

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Homeopathy research shows the effectiveness of homeopathy in humans, animals and plants.

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Research FAQs

Is there research to support homeopathy and is it evidence-based.

Yes! There are over 600 published homeopathy research studies and more are being conducted every day.

Research shows the effectiveness of homeopathy in a wide range of acute, chronic, and epidemic conditions in both humans and animals. Conditions such as eczema, asthma, upper respiratory illnesses, ear infections, fibromyalgia, menopause, diarrhea, ADHD, irritable bowel and depression show positive responses to homeopathy.

There is even laboratory research showing the action of homeopathic remedies on individual cells, including cancer cells.

What is the history of homeopathy research?

Homeopaths have been conducting homeopathic research since 1792, when Samuel Hahnemann completed the first homeopathic study of Cinchona bark. Every homeopathic remedy is first subjected to a study to elicit symptoms, called a “proving”. Homeopaths were the earliest researchers to introduce the use of placebo into their studies.

For decades, homeopaths have been researching multiple facets of homeopathy including the following:

• Homeopathy’s role in treating infectious epidemics, acute illnesses, and chronic diseases
• The effect of homeopathic dilutions on human and bacterial cells
• The mode of action of ultra-molecular dilutions in the body
• The success of treatment of acute diseases in livestock and farm animals
• The cost effectiveness of homeopathy compared to conventional drug therapy

What is the status of homeopathy research today?

Within today’s clinical research industry, homeopathy studies are considered “emerging” research. Traditional clinical trials are extremely expensive and, in the case of drug research, are often funded by pharmaceutical companies and the US National Institutes of Health. Millions of dollars are awarded to professional medical researchers at universities and medical centers to conduct this type of research. These centers are equipped to organize and implement clinical trials that include large numbers of patients.

Homeopaths do not typically work in or have access to these research environments; therefore, much of their research has been conducted with small groups of patients. In the last decade some professional homeopathic researchers have received funding and their work is showing great promise.

Research knowledge comes from building on previous individual studies and learning from the challenges and strengths of those studies. As more funding and experience is gained, homeopathic research is becoming more and more prominent.

Why do some scientists question homeopathy research?

Some scientists will accept only one method of research, the Randomized Placebo Controlled Trial (RCT). The RCT is the most popular method used by pharmaceutical companies to test a new drug, and the one that the media publicizes the most. However, RCT is not always the best scientific method for researching “whole systems” treatment approaches, such as homeopathy.

A “whole systems approach” recognizes that the human body and mind are dynamic and complex, with each part influencing the other and acting together. Therefore, one part or system of the body cannot be studied in isolation without looking at the effect that it has on the whole person. Scientists find the RCT methodology is too restrictive when studying a “whole system.”

Many scientists and health officials question the usefulness of RCT studies even in standard drug testing. This group prefers “real world” or “clinical outcome” studies that are more applicable to day-to-day practice instead of strictly controlled drug trials. Today health practitioners and the US Department of Health and Human Services are calling for “comparative effectiveness” research.

Comparative effectiveness research compares the usefulness of various treatments and provides more practical information about their use for patients and practitioners. “Clinical outcome,” “comparative effectiveness,” and “systems-based” studies are types of research that are better suited for investigating the healing ability of the body and the effect of homeopathic treatment.

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"Every Secret of a Writer's Soul, Every Experience of his Life, Every Quality of his Mind, Is Writtern Large in his Works

The homoeopathic heritage.

The Homoeopathic Heritage is the ongoing oldest monthly journal in homoeopathy with the largest circulation nationally as well as internationally.for more than 50 years, it has been able to build a robust and continually enlarging network of homoeopathic lovers who have trusted it as the best journal for quality information on homoeopathy.

Homoeopathic Professionals, Lecturers as well as Budding Homoeopaths approach the journal for the knowledge, evidence-based case studies and research papers, updates about Homoeopathy, as well as inspiration that they can't get anywhere else. “The Homoeopathic Heritage” gives in-depth knowledge about the latest researches and the clinical experiences of renowned homoeopathic physicians.

“The Homoeopathic Heritage” is published under the strong leadership of Dr Farokh J. Master, the Editor-in-Chief , a leading international teacher and an author of more than 30 books in homoeopathy. Since January 2013, the journal has been listed as a “Peer-reviewed Journal”. All the manuscripts are being peer-reviewed by the in-house editorial team and selected articles from each issue are sent for peer-review by an external board of reviewers and those articles are distinctly marked with a stamp of ‘Peer Reviewed’ . The Journal strictly follows the International Guidelines of manuscript submission. The prestigious House of B. Jain cordially invites you to team up and connect with us to share your knowledge and clinical experiences in our circle of influence.

Mr. Kuldeep Jain & Mr. Manish Jain, the Directors at B. Jain Publishing House , one of the largest publishers of alternative health in the world, represent the journal, having so many International and National Homoeopaths attached to it.

We believe that information should be made available to everyone and that’s what we are working, to create a world where latest updates and research are made available to all the readers free of cost. Being an authentic Homoeopathic Journal which acknowledges to present quality information to all, our Vision is to connect numerous homoeopaths from all over the world.

We visualize Homoeopathy at great heights through advanced technology, innovative research and quality education. "Homoeopathy is considered the BEST when it comes to safe and sound treatment", hence our vision is to encourage and spread homoeopathy all over the world by sharing knowledge, thus facilitating the development of thoughtful, creative, adaptable and humane citizens worldwide.

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The current scenario of Homoeopathic science is keenly focussed on evidence-based practices according to the universally acknowledged parameters, with a special emphasis on documentation. On the same note, our mission is to provide diverse Homoeopathic content commencing from various research papers and case studies of Homoeopathic Practitioners, Professors, Researchers as well as budding Homoeopaths nationally and internationally.

“The Homoeopathic Heritage” Journal commits to meet the needs of our readers as well as our authors and relentlessly boost the quality of our content. Our main focus is to showcase the different escapades of clinicians at a single platform which will not only nurture Homoeopathy but also safeguard the whole Homoeopathic fraternity.

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Homeopathy effects in patients during oncological treatment: a systematic review

• Original Article – Clinical Oncology
• Open access
• Published: 22 June 2022
• Volume 149 , pages 1785–1810, ( 2023 )

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• Anna Wagenknecht 1 ,
• Jennifer Dörfler 1 ,
• Maren Freuding 1 ,
• Lena Josfeld 1 &
• Jutta Huebner   ORCID: orcid.org/0000-0003-4931-568X 1  

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In this systematic review we included clinical studies from 1800 until 2020 to evaluate evidence of the effectiveness of homeopathy on physical and mental conditions in patients during oncological treatment.

In February 2021 a systematic search was conducted searching five electronic databases (Embase, Cochrane, PsychInfo, CINAHL and Medline) to find studies concerning use, effectiveness and potential harm of homeopathy in cancer patients.

From all 1352 search results, 18 studies with 2016 patients were included in this SR. The patients treated with homeopathy were mainly diagnosed with breast cancer. The therapy concepts include single and combination homeopathic remedies (used systemically or as mouth rinses) of various dilutions. Outcomes assessed were the influence on toxicity of cancer treatment (mostly hot flashes and menopausal symptoms), time to drain removal in breast cancer patients after mastectomy, survival, quality of life, global health and subjective well-being, anxiety and depression as well as safety and tolerance. The included studies reported heterogeneous results: some studies described significant differences in quality of life or toxicity of cancer treatment favouring homeopathy, whereas others did not find an effect or reported significant differences to the disadvantage of homeopathy or side effects caused by homeopathy. The majority of the studies have a low methodological quality.

Conclusions

For homeopathy, there is neither a scientifically based hypothesis of its mode of action nor conclusive evidence from clinical studies in cancer care.

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Introduction

Cancer embodies one of the leading causes of death; morbidity and mortality due to cancer are increasing steadily (Radtke 2022 ). Receiving the diagnosis, many patients are desperate and try additional treatment to their standard cancer therapy. More than 25% of the general population in Europe is using complementary and alternative medicine (CAM) regularly on less severe health conditions such as neck pain or allergies (Laura et al. 2018 ), prescribed by some physicians as a placebo with few side effects. Faced with a cancer diagnosis, many patients revert to the use of CAM. Homeopathy is a CAM system that, globally, became more and more popular over the past decades. Based on the “Law of Similars” by the German physician Samuel Hahnemann, homeopaths assume that a substance, which causes certain effects, can also be used to treat them if prescribed in a very low dosage (Shah 2018 ). Therefore, homeopathic remedies (e.g. plant, animal or mineral) are diluted to so-called potencies. In classical homeopathy, these steps of dilution (1:10; 1:100 or 1:50.000) are repeated so many times that there is not a single molecule of the substance left in the remedy (Tschech 2022 ). Nevertheless, homeopaths are convinced of the effectiveness of homeopathic treatments, while science expresses criticism and doubt. Some explanation attempts for the mode of action of homeopathy are nanoparticles and water memory, but none of these were verified through clinical studies yet (Fritzsche 2011 ; Nuhn 2005 ).

The most common dilution (1:100) is the C- potency, or, using Hahnemann’s dilution method, CH-potency. Repeating this dilution-method for a second time creates a C2-potency (1:10.000). C2 diluted again results in a C3-potency and so forth (Genneper 2017 ). There exist three main approaches to homeopathic prescribing: in the individualised or classical homeopathy single remedies are used depending on the patients individual condition and history, in the clinical homeopathy the same remedy is used for a group of patients with specific conditions and in the complex homeopathy a number of remedies is used in a defined combination for particular symptoms (Pérol et al. 2012 ).

Due to the controversial discussions on homeopathic therapies, a wide variety of publications exists addressing this matter. But for homeopathy being such a popular treatment method, there are surprisingly few clinical studies, systematic reviews (SRs) or meta-analyses, and only of limited quality. Likewise, only a few studies examine the influence of homeopathy on carcinoma, while homeopathy is frequently used against the toxicity of cancer treatments and even for its cure. Therefore, SRs and an extensive evaluation of clinical studies are needed to provide high-level evidence of the effects of homeopathy in cancer patients.

Criteria for including and excluding studies in the review

Inclusion and exclusion criteria are listed in Table 1 based on a PICO- model. Generally, all study types were included if they reported patient-relevant outcomes after guideline-based treatment of adult cancer patients with any intervention containing homeopathy. Because of the wide range of application fields, all cancer entities were included. Since little high-quality evidence was expected, systematic reviews and randomized controlled trials were included as well as controlled trials, one-armed studies and retrospective studies. Criteria for rejecting studies were primary prevention, grey literature, other publication type than primary investigation/report (e.g. comments, letters, abstracts) and study population with children (under the age of 18) or precancerous conditions, if results or numeral details of adult patients with cancer were not reported separately. Additionally, studies were excluded if they reported no patient centred outcomes (laboratory parameters except Prostate Specific Antigen (PSA) which is a valuable parameter for cancer progression of prostate cancer). Language restrictions were made to English and German.

Study selection

A systematic research was conducted using five databases (Medline (Ovid), CINAHL (EBSCO), EMBASE (Ovid), Cochrane CENTRAL and PsycINFO (EBSCO)) in February 2021. For each of these databases a complex search strategy was developed consisting of a combination of MeshTerms, keywords and text words in different spellings connected to cancer and homeopathic therapy (Table 2 ). The search string was highly sensitive, since it was not restricted by filters of study or publication type. After importing the search results into EndNote X9, all duplicates were removed and a title- abstract- screening was carried out by two independent reviewers (AW and JD). In case of disagreement consensus was made by discussion or a third reviewer was consulted (JH). After that, all full texts were retrieved and screened again independently by both reviewers. When title and abstract did not have sufficient information for screening purposes, a full-text copy was retrieved as well. Additionally bibliography lists of all retrieved articles were searched for relevant studies.

Assessment of risk of bias and methodological quality

All characteristics were assessed by two independent reviewers (AW and JD). In case of disagreement a third reviewer was consulted (JH) and consensus was made by discussion.

The risk of bias in the included studies was analysed with the SIGN- Checklist (“ https://www.sign.ac.uk/what-we-do/methodology/checklists/ ”) for controlled trials Version 2.0 and IHE Quality Appraisal Checklist for Case Series Studies (“ http://sandbox.ihe.ca/research-programs/methodology-development/case-series-studies-quality-appraisal/cssqac-about ”). In addition, blinding of researchers, blinding of outcome assessment and comparability of groups before treatment, not only in terms of demographic variables but also concerning the outcomes, was examined.

The included studies were rated with the Oxford criteria. Additional criteria concerning methodology were size of population, application of power analysis, dealing with missing data and drop-out (report of drop-out reasons, application of intention-to-treat-analysis), adequacy of statistical tests (e.g. control of premises or multiple testing) and selective outcome reporting (report of all assessed outcomes with specification of statistical data as the p-value).

Data extraction

Data extraction was performed by one reviewer (AW) and controlled by two independent reviewers (JD, JH). As a template for data extraction, the evidence tables from the National Guideline on Complementary and Alternative Medicine in Oncological Patients of the German Guideline Program in Oncology (“ https://www.leitlinienprogramm-onkologie.de/english-language/ ”) were used. Concerning systematic reviews, only data from primary literature meeting the inclusion criteria of the present work were extracted.

The systematic search revealed 1352 results. No study was added by hand search. At first, duplicates were removed leaving 1007 studies. After screening title and abstract, 110 studies remained to complete review.

Finally, 18 publications were considered relevant due to the inclusion criteria of this present work and were included in this SR. We included 11 studies for endpoints: 0 SRs, 9 randomized controlled trials (RCTs) (Balzarini et al. 2000 ; Frass et al. 2015 ; Frass et al. 2020a , b ; Heudel et al. 2019 ; Jacobs et al. 2005 ; Lotan et al. 2020 ; Luca Sorrentino 2017 ; Pérol et al. 2012 ; Thompson et al. 2005 ) and 2 controlled trials (CTs) (Karp et al. 2016 ; Steinmann et al. 2012 ) which investigated the efficacy of homeopathic treatment in cancer therapy. These studies were heterogeneous in terms of the assessed homeopathic intervention and cancer type. Additional seven studies were included only for safety and side effects due to severe lack of methodical and reporting quality (one uncontrolled three-armed pilot outcome study, five prospective single-armed studies and one single-armed retrospective study). The majority of studies observed breast cancer patients, the most common primary endpoint was influence of homeopathic treatment on toxicity of cancer treatment and one of the most frequent secondary endpoints was QoL. Detailed characterization of the included studies may be seen in Table 3 . The flow of studies through the review can be seen in Fig.  1 .

Flow Diagram

Characteristics of included studies

Concerning all relevant studies, 2016 patients were included, of whom 1594 were analysed, due to 422 drop-outs. The age of the mostly female patients ranged from 20 to 87 years, with a mean age of 54.5 (47.9–64.9) years. Reported was the inclusion of patients with breast cancer ( N =  1448), lung cancer ( N =  213), gastrointestinal cancer ( N =  54), hematological cancer ( N =  45), head and neck tumours ( N =  40), renal cell cancer ( N =  28), sarcoma ( N =  23), pancreas cancer ( N =  9) and other types of cancer ( N =  61).

Risk of bias in included studies

The results are presented in Table 4 . Eleven of the included studies have moderate quality. Seven studies were included only for side effects and AEs due to their severe lack of methodological and reporting quality (poor quality).

Excluded studies

A list of excluded studies after full-text screening and reasons for the exclusion can be seen in Table 5 . The studies that could not be found for full-text screening (eSupplement) are listed in the appendix. One of the studies (Genre et al. 2003 ) was not available and our lending request remained unanswered, so we were not able to analyse the results. But while searching for the study we came across the following two reviews that had excluded the study: Mathie et al. ( 2013 ) rated the trial as a minor journal article with only an abstract available and Kassab et al. ( 2009 ) excluded the study for the following reason: “it was only available in abstract form and the results were not included in the abstract […]: the lead author was contacted but not willing to provide us with the results as the data was not published”.

Efficacy of homeopathic therapy

Influence on toxicity of cancer treatment: skin reaction.

Balzarini et al. ( 2000 ) analysed the effects of Belladonna 7CH globules (two times a day) and X-ray globules (once a day) associated in the treatment of acute radiodermatitis compared to a placebo in 61 randomized breast cancer patients. Over 30 days after radiotherapy the physician assessed skin color, temperature to the touch, edema and hyperpigmentation at eight defined times ( t 1– t 8). There were no differences in skin color (all p ’s > 0.050) and hyperpigmentation (all p ’s ≥ 0.050) but the study found significant differences in temperature for t 3, t 4, t 6 and t 7 ( p =  0.008; p =  0.016; p =  0.023; p =  0.011) in favour of the homeopathy group. They also found a difference for oedema on at t 5 and t 6 in favour of the placebo group ( p =  0.025; p =  0.025).

Influence on toxicity of cancer treatment: nausea and vomiting

Pérol et al. ( 2012 ) included 403 breast cancer patients in a RCT to investigate chemotherapy-induced nausea and vomiting. Patients in the intervention group took the complex homeopathic remedy “Cocculine”, while the control group was given a placebo in addition to the standard antiemetic therapy during six chemotherapy cycles. Instruments to assess nausea and emesis were the Functional Living Index for Emesis questionnaire, patient diaries and the Common Terminology Criteria for Adverse Events Scale. There was no significant difference between the arms during first, second or third chemotherapy cycle (all p ’s > 0.050), except for significantly more vomiting episodes during third cycle (assessed with patient diaries, p =  0.030) in favour of the homeopathy arm.

Influence on toxicity of cancer treatment: joint pain (JP) and joint stiffness (JS)

In an open, not randomized CT by Karp et al. ( 2016 ) 27 breast cancer patients were included, taking only aromatase inhibitors in the control group or additionally Ruta graveolens 5CH and Rhus toxicodendron 9CH (twice a day for 3 months) in the homeopathic group. The overall scores showed a significant advantage in the homeopathic arm for JP ( p =  0.000) but not for JS ( p =  0.057). More results of significance, all in favour of the homeopathy arm, were frequency, intensity and number of sites regarding JP ( p =  0.000; p =  0.000; p =  0.032), morning (not daytime) intensity, worsening of JS and time to disappearance of morning stiffness and ( p =  0.020; p =  0.179; p =  0.014; p =  0.022) as well as frequency and increase of analgesic use concerning JP ( p =  0.003; p =  0.008). At inclusion, 65% and 80% of patients in the homeopathic and control arm complained of JP, whereas 76.9% and 62.5% had taken analgesics in the week before inclusion.

Influence on toxicity of cancer treatment: oral mucositis

Another non-blinded and not randomized CT by Steinmann et al. ( 2012 ) analysed the grade of oral mucositis in 20 patients with head and neck tumours receiving radiotherapy or radio-chemotherapy. Patients in the homeopathic arm carried out mouth rinses with a Traumeel S solution, the control group with sage tea (Salvia officinalis) for 6–7 weeks. The authors found no significant differences in the grade of oral mucositis between both groups (no p values given) and reported a consistent worsening of intraoral pain during the study period, except for one single time in week 5 in the homeopathic arm. At the end of the study, 6 and 3 out of 10 patients took systemic analgesics in the homeopathic and placebo arm, while 5 and 1 out of 10 patients used local analgesics, but no statistical analysis was made. Regarding xerostomia (difficulty in speech and eating), they reported a significant difference in preservation of taste favouring Traumeel in week 4, but presented no p value.

Influence on toxicity of cancer treatment: influence of JP on sleep

Twenty-seven breast cancer patients were assessed regarding the impact of JP on quality and quantity of sleep in an open, not randomized CT by Karp et al. ( 2016 ). While patients in the control group were taking aromatase inhibitors only, patients in the homeopathic group received additionally Ruta graveolens 5CH and Rhus toxicodendron 9CH (twice a day for 3 months).

The impact of JP on sleep after 3 months showed a significant difference in favour of the homeopathy arm ( p =  0.008). No statistical analyses were done for the results of patients who stated that pain never disturbed their sleep.

Time to drain removal after mastectomy

A RCT by Luca Sorrentino et al. ( 2017 ) observed 53 breast cancer patients (intention to treat (ITT)-sample; in the per protocol (PP)-sample 43 patients) who were either taking Arnica montana 1000 K or a placebo (3 times a day) from one day before until 4 days after surgery. The results of reduction in drained blood and serum volumes were analysed with three different models.

Regarding the changes in volume collected from day one, analysed with the analysis of variance (ANOVA), neither the PP- nor the ITT- sample showed significant overall differences ( p =  0.772; p =  0.122). When analysed with the regression model including treatment and collected volume on the day of intervention, the differences between the groups in the PP-sample were significant on days 2 and 3 to the advantage of homeopathy ( p =  0.033; p =  0.022). The estimates of the mean difference in total volume analysed with regression models showed significant differences only in the PP-sample for the model including treatment, collected volume on the day of surgery and patient weight ( p =  0.030). The differences in the ITT- sample were not significant ( p =  0.600).

Regarding self-evaluation of pain , bruises and haematomas or breast swelling after surgery both arms showed no significant differences ( p  > 0.050; p =  0.670; p =  0.570).

Fifty-five patients with breast cancer or risk patients wishing for risk reduction by undergoing mastectomy and immediate breast reconstruction were assessed in a RCT (Lotan et al. 2020 ). Patients were either taking three globes of Arnica montana Bellis C30 & perennis C30 each or a placebo until drain removal. Concerning this matter, a significant difference favouring homeopathy was found (11.1 ± 6.1 days in study group, 13.5 ± 6.4 days in placebo group, p <  0.050), but because the amputated breast weight and implant volume may affect drainage and differed significantly between both groups ( p <  0.001), this result cannot be fully attributed as intervention effect. Concerning postoperative pain, haemoglobin, opioid intake and cortisol levels, no significant differences were found.

Frass et al. ( 2020a , b ) observed 150 randomized patients with advanced non-small cell lung cancer until death or in case of survival for a maximum of 24 months. Fifty-two patients gave no consent to randomization and were, therefore, used as a control group for this endpoint only (arm C), while the other groups received chemotherapy and either individualized homeopathic medicine (daily on a 3-week interval, arm A) or a placebo (arm B). Over the observed 2 years, median- and 2-year mortality differed significantly between arm A and B (435 and 257 days, p =  0.010; 45.1% and 23.4%, p =  0.020), arms A and C (228 days, p <  0.001; 13.5%, p <  0.001) but not between arms B and C ( p =  0.258; p =  0.154). Further significant differences were found for the estimated survival time between arms A and B (477 and 352 days, p =  0.014), arms A and C (477 and 274 days, p <  0.001) but not arm B vs arm C ( p =  0.145), as well as for patients who died within the 2 years (A vs C, p =  0.020; not A vs B p =  0.172 and B vs C p =  0.747).

Hot flashes (HF) and other menopausal symptoms

To explore the effect of homeopathy on HF, Jacobs et al. ( 2005 ) conducted a randomized study with 66 breast cancer patients receiving either a placebo combination medicine and a homeopathic single remedy (arm A), a homeopathic combination medicine (Hyland’s Menopause) and a placebo single remedy (arm B) or 2 placebos (single and combination remedy, arm C). The overall results regarding severity and frequency of HF and typical menopausal symptoms (via Kupperman Menopausal Index) did not differ significantly, except for an increase of headache in arm B at 6 and 12 months ( p =  0.040; p =  0.030). A subgroup analysis including only patients without tamoxifen regimen showed significant differences, arm B, in HF severity score (frequency times severity: B vs C p =  0.010, A vs B p <  0.001) and in the total number of HF (B vs C p =  0.006, A vs B p =  0.002). Furthermore, patients in arm A had a lower severity score and fewer HF in total.

Assessing 53 breast cancer patients, a RCT by Thompson et al. ( 2005 ) did not find any significant differences in activity- and profile-scores (all p ’s > 0.05) between the intervention group receiving individual homeopathic treatment for 16 weeks and the placebo group. No significant differences were found in menopausal symptoms (conducted through a questionnaire) as well, assessing night sweats frequency and influence on sleep ( p =  0.750; p =  0.870) and day sweats frequency and disturbance of everyday functioning ( p =  0.300; 0.220). Only the differences in terms of satisfaction were significant, but in favour of the placebo group ( p =  0.010). On HF -severity and -frequency no data were reported.

In another study, 138 randomised patients took the homeopathic remedy BRN-01 (Actheane ® ) or a placebo twice a day for at least 8 weeks in addition to their adjuvant endocrine therapy (aromatase inhibitor or tamoxifen with/without ovarian suppression). There were no significant differences in the HF-score after 4 or 8 weeks ( p =  0.756; p =  0.775), compliance ( p =  0.606) or satisfaction (Heudel et al. 2019 ).

Quality of life (QoL), quality of recovery (QoR), global health and subjective well-being

The influence of homeopathy on improving the global health status or subjective wellbeing was assessed in an RCT by Frass et al. ( 2015 ). For an unstated duration, 373 unblinded patients with different kinds and stages of carcinoma received either chemotherapy or radiotherapy only or an additional individual homeopathic treatment. After 4 months, the arms showed significant differences in global health (via EORTC QLQ-C30, p =  0.005) and subjective wellbeing (via visual analogue scale (VAS), p <  0.001) favouring homeopathy.

Assessing 150 patients with advanced non-small cell lung cancer (NSCLC) receiving chemotherapy and an individualized homeopathic treatment or a placebo, the authors found comparable results in their RCT in 2020 after 9 and 18 weeks in global health status/QoL ( p <  0.001) and subjective well-being (via SF-36, p <  0.001) (Frass et al. 2020a , b ). In both trials, most of the assessed function- and symptom- scales showed significant differences favouring homeopathy after 4 months (Frass et al. 2015 ): p <  0.001 for physical, cognitive, social and emotional functioning as well as fatigue and pain; role functioning p =  0.040, dyspnoea p =  0.002, insomnia p =  0.029, appetite loss p =  0.007) and after 9 and 18 weeks (Frass et al. 2020a , b : p  ≤ 0.001 for physical, role, emotional and social functioning as well as fatigue, nausea and vomiting, dyspnoea, insomnia, appetite loss as well as constipation ( p =  0.008; p =  0.005). Significant differences only after 18 (and not 9) weeks were found in cognitive function ( p =  0.113; p =  0.001), pain ( p =  0.061; p <  0.001), diarrhoea ( p =  0.590; p =  0.017) and financial difficulties ( p =  0.134; p =  0.021). The results for vomiting and nausea, constipation and diarrhoea in the study by (Frass et al. 2015 ) did not reach significance.

Patients with former homeopathic experience were surveyed regarding their attitude concerning homeopathy by Frass et al. 2020a , b ) in their study on patients with NSCLC. The majority of patients in the study arm receiving homeopathy had been referred to the former homeopathic treatment by doctors (57.1%, arm B 17.6%) and their expectations regarding a homeopathic effect were significantly lower ( p =  0.010) than the expectations of patients in the placebo arm, who had significantly more often used homeopathy without a doctor’s recommendation ( p =  0.039).

In a RCT by Jacobs et al. ( 2005 ) 66 breast cancer patients were analysed and received either a placebo combination medicine plus a homeopathic single remedy (arm A), Hyland’s Menopause (a homeopathic combination medicine) plus a placebo single remedy (arm B) or 2 placebo medications (arm C). After 1 year the study found significant results in QoL not in terms of physical function but in general health (via SF-36) favouring both homeopathic arms A and B over placebo ( p =  0.020; p =  0.030).

Further studies observing QoL did not find significant differences: neither in a controlled trial with 20 non-blinded and non-randomized patients with head and neck tumours (Steinmann et al. 2012 ), no p values reported) receiving Traumeel S or sage tea for mouth rinses against radiotherapy- or radiochemotherapy- induced oral mucositis, nor in a RCT with 138 patients who took, additionally to their adjuvant endocrine therapy, the homeopathic remedy BRN-01 (Actheane ® ) or a placebo (Heudel et al. 2019 ). In the latter study no statistical analysis was made between the groups and the result presentation was incomprehensible.

Two RCTs (Lotan et al. 2020 ; Thompson et al. 2005 ) found no significant differences in general health, QoL or QoR comparing the effects of Arnica montana and an indiviualized homeopathic remedy to a placebo (no p value reported; p =  0.850).

Anxiety and depression

This endpoint was assessed by Thompson et al. ( 2005 ), who found no significant differences for anxiety and depression between the homeopathic and placebo arm in 53 randomized breast-cancer patients.

Safety, tolerance and side effects

Two studies analysed safety and side effects as one of their secondary endpoints.

The reported adverse events (AEs) in the RCT by Luca Sorrentinoet al. ( 2017 ) by five patients taking Arnica montana were not correlated with the homeopathic treatment. None of the AEs stated in another RCT were related to the study treatment with BRN-01 (Actheane ® ) or the placebo, as well (Heudel et al. 2019 ).

Six studies reported no side effects related to the intervention drug (Frass et al. 2015 ; Frass et al. 2020a , b ; Freyer et al. 2014 ; Karp et al. 2016 ; Lotan et al. 2020 ; Pérol et al. 2012 ). Further four studies (Clover and Ratsey 2002 ; Gaertner et al. 2014 ; Schlappack 2004 ; Steinmann et al. 2012 ) gave no information on side effects of the study remedies. Because the studies assessed the homeopathic treatment during cancer care, it was often impossible to define the exact cause of the reported AEs. Balzarini et al. ( 2000 ) reported one drop-out due to homeopathic exacerbation (Belladonna 7cH globules, two times a day and X-ray globules once a day) and four drop-outs due to the AE’s of radiation.

In another study (Jacobs et al. 2005 ) there were no AEs reported by the breast cancer patients receiving a placebo combination medicine and a verum single remedy in arm A, a verum combination medicine (Hyland’s menopause) and a placebo single remedy in arm B or 2 placebo medications in arm C. But statistical analysis showed an increase of HF and headaches in arm B although the overall incidence (any type, any grade) was equally distributed between all groups.

Thompson et al. ( 2005 ) reported that about 25% of patients in both groups (receiving an individualized homeopathic remedy or a placebo) suffered side effects with only minor differences in terms of aggravations, appearance of new symptoms or return of former symptoms. Details about severity, kind of AE and whether they relate to the remedies were not given.

Further seven studies were included for side effects (Clover and Ratsey 2002 ; Forner-Cordero et al. 2009 ; Freyer et al. 2014 ; Gaertner et al. 2014 ; Schlappack 2004 ; Thompson and Reilly 2002 ; 2003 ). Of these, two studies reported no information about AEs and were, therefore, mentioned in the listing above (Gaertner et al. 2014 ; Schlappack 2004 ).

A study by Forner-Cordero et al. ( 2009 ) analysed 17 breast cancer patients after unilateral breast surgery with exhibited arm- lymphedema, who were treated with oral Lymphomyosot (15 drops or 3 tablets) for three times a day over the study period, in combination with compression hosiery, daily kinesiotherapy and skin care. Eight patients experienced treatment-emergent AE ‘s and four patients had to discontinue their treatment due to AEs (one patient each with nycturia, hypertensive crisis, right hypochondrial pain, heartburn, no further information given). Further AEs reported were anxiety, constipation and dry mouth.

Another study by Thompson and Reilly ( 2002 ) reported reactions of homeopathic remedies that were given according to individual assessment in 17 of 57 patients with different cancer types receiving conventional cancer treatments. Reactions included aggravation of symptoms, development of old symptoms from years ago (reported as part of the healing) and transient worsening of symptoms (which settled on stopping the remedy). None of the AEs necessitated withdrawal of homeopathic medicines, but one patient was advised to stop the treatment because of an acute blast phase of chronic myeloid leukaemia.

In 2003 the authors assessed individualised homeopathic medicine in breast cancer patients under conventional cancer therapy and reported new symptoms in 7 of 40 patients, return of old symptoms in 10 patients and 1 patient suffering a difficult aggravation of symptoms which stopped with pausing the homeopathic treatment (no further information given) (Thompson and Reilly 2003 ).

Before summing up the main results it should be noted that due to the variety of remedies, potencies and indications used in the included studies, finding evidence of the effectiveness of homeopathic treatment in cancer patients is problematic. Patients receiving individualized and changing homeopathic treatment even within a single study generate difficulties in deriving results for certain symptoms. As heterogeneous as the homeopathic agents were the types of cancer and, consequently, the conventional anti-cancer therapies, leading to many different observed endpoints.

All of the included studies showed strong methodical deficits in study design and reporting of the data such as incomplete description of sample, patient characteristics, drop-out, dose, duration of intervention or statistical data.

Regarding the influence of homeopathy on toxicity of cancer treatment, one study analysed skin reactions of irradiation (Balzarini et al. 2000 ) and obtained conflicting results both to the advantage and disadvantage of homeopathy which may have been biased by the small sample size. The authors reported a trend of less dermatitis and for one assessment (t5) interpreted a p =  0.05 wrongly as significant in favour of the homeopathy group. It remains unclear why the authors used invalid scores instead of internationally accepted and valid scores (Radiation Therapy Oncology Group -score for example).

One study by Karp et al. ( 2016 ) addressed the homeopathic influence on JP and JS caused by aromatase inhibitors. Patients who received homeopathic treatment were reported to have a significantly greater improvement in all results concerning JP and analgesic use. Contrary to this, only a few measurements were significant (mean time to disappearance of JS, morning intensity and worsening of JS). Strangely, more patients in the control group stated JP at inclusion, but took less analgesics than patients in the homeopathic group. The analgesic consumption, however, was not properly described at materials and methods. Moreover, the study shows severe methodological weaknesses: both arms were unblinded, not randomized and important inclusion criteria, such as cancer stage, are not mentioned. The authors report only few p values that mostly refer to the composite scores for joint pain and joint stiffness, leading to highly significant p values. But these scores are not valid and seem questionable. Moreover, the generated percentages are based on different baseline values. For their calculations, the authors seem to use either two different numbers of patients at inclusion for each study arm or the number of patients after 3 months. It remains incomprehensible and unreported which dataset is used for which endpoint and some calculated results stay questionable. Also, some numbers reported in the text differ from those in the tables. Furthermore, the comparability of both groups is questionable: each group was treated at a different hospital and patients showed severe differences at inclusion already. Besides, the drop-out was high and differed in both arms (homeopathy arm 45%, control arm 20%).

Chemotherapy-induced nausea and vomiting (Pérol et al. 2012 ) as well as oral mucositis during radiotherapy or radio-chemotherapy (Steinmann et al. 2012 ) were studied in one trial only, and both were unable to find a homeopathy effect. Vomiting episodes that Perol et al. reported significantly more often in the placebo group during the 3rd chemotherapy cycle, were not obtained over the 4–6th cycle and had no impact on the Functional Living Index. Although Steinmann et al. reported a significant advantage for the homeopathic group regarding preservation of taste in week 4, the authors provided no data on significance for this statement that was based on diaries of the 20 patients. Furthermore, the use of systemic and local analgesics was higher in the homeopathy group compared to the control group. Whether this is the result of harm caused by the homeopathic remedy or other reasons remains unclear.

Only one study assessed the influence on JP on quality and quantity of sleep (Karp et al. 2016 ). The patients in this controlled trial received either aromatase inhibitors only or additionally Ruta graveolens 5CH and Rhus toxicodendron 9CH. To the benefit of homeopathy, the study showed a significantly worsened impact of pain on sleep concerning JP in the placebo group after 3 months, while the homeopathy group remained unchanged. Regarding the results of patients whose sleep was never disturbed by pain, no statistical analyses were done. However, the authors use different baseline values for their calculations and it remains incomprehensible and unreported which dataset is used for which result. Also, the patients in this study were neither blinded nor randomized and important inclusion criteria, such as cancer stage, was not reported. Furthermore, the patients in the study arms showed strong differences right from the start and were treated at two different hospitals, which limits the comparability. Additionally, the drop-out was high and uneven (homeopathy arm 45%, control arm 20%).

Inconsistent findings were obtained in two blinded and placebo-controlled studies assessing the effects of homeopathic interventions on time to drain removal in breast cancer patients after mastectomy (Lotan et al. 2020 ; Luca Sorrentino et al. 2017 ). Luca Sorrentino et al. ( 2017 ) reported significant differences favouring homeopathy in two different regression models of the per-protocol-analysis only: in total volume (including treatment, collected volume on day of surgery, patient weight) and in changes in volume collected from day 1 to each following day in two time points (including treatment, collected volume on day of surgery). Yet, neither the overall results in the ANOVA—nor the regression- model of the ITT-sample did reach significance. The study lacks reporting quality: only few baseline characteristics are described, details on cancer stage are missing and the reporting of results for the endpoints is incomplete. The comparability of both study arms is questionable due to missing detail about whether mastectomy was performed with or without reconstruction, which most likely affects the amount of volume. Most importantly, the authors do not report whether both arms of the PP-analysis are comparable to the baseline data or not. That is why the results of the PP-dataset are not usable. Furthermore, the high and uneven drop-out (homeopathic arm 12%, placebo arm 26%) and the small sample size (53 patients) may have biased the PP-dataset and limits the generalizability of the results even more.

Lotan et al. ( 2020 ) reported significant advantages for the homeopathic group, but included patients for therapeutic as well as prophylactic mastectomy which may have gone along with different radicality of the operation in both arms. Also, the volume of the operated breast and the implant were different in both arms. This, and a different radicalism of the operation, most likely affected the drained volume and postoperative complications and biased the outcome. Additionally, the durations until drain removal in the results are in contrast with the range of drain times stated in the limitations (3–32 days). Further severe inconsistencies are the changed trial protocols during the study, as well as the uneven compliance and drop-out of patients. They were kept in the statistical analysis as partially treated, but no data were reported. Besides, only few patient characteristics are stated. Last but not least, the authors either report wrong numbers or transposed them. Further limitations of this study were discussed by the authors. Hence, these trials cannot serve as evidence for the effectiveness of homeopathic treatment in breast cancer patients.

Frass et al. ( 2020a , b ) conducted the only study observing the use of a homeopathic treatment on survival among patients with advanced non-small-cell lung cancer. Significant differences in median-, 2-year- mortality and estimated survival time were found favouring a homeopathic over a placebo and a not randomized control group. But as discussed by the authors the comparability between the arms is restricted as there were significantly more patients with N (Nodus) stages 0–1 in the placebo arm, and more patients with N stage 3 in the homeopathic arm ( p =  0.010). Furthermore, there are serious concerns with respect to the reporting of this study: the authors gave contradictory statements in the text and study protocol on whether the control group, that refused randomization, was given verum or not. Additionally, the high and uneven drop-out (homeopathy 9.8%, placebo 29.8%, no data for control group) might be the result of some selection bias. A serious concern also is the unusually high number of deaths in the first weeks in the placebo group, for which there is no explanation. The fact which is most serious concerning the scientific conduct of the study is the fact that the trial protocol has been changed for several times. This is well documented as the study was registered in clinicaltrials.gov (“ https://clinicaltrials.gov/ct2/show/ NCT01509612?term = 33010094 + %5BPUBMED-IDS%5D&draw = 2&rank = 1”). Instead of 3 pre-planned only data on patients with one cancer type was reported, instead of 600 participants as stated in the registration only 150 were included in the final manuscript of the study while the number of exclusion criteria was raised from 1 to 20. The date of a document with modifications (January 2011), is set a year before the study was first registered in January 2012, but already contains changed parameters similar to those in the published paper (but lists 300 patients to include). Moreover, the planned follow-up was reduced from 104 to 18 weeks.

Three studies assessed the influence of homeopathic interventions on HF and menopausal symptoms. Two of the studies, that were placebo-controlled and double-blinded, demonstrated no significant effect on HF or menopausal symptoms (Heudel et al. 2019 ; Thompson et al. 2005 ). On the contrary, according to Thompson et al. ( 2005 ), patients receiving homeopathy were, to a significant degree, even more unsatisfied with the treatment than the placebo group.

Contrary to this, in a subgroup without tamoxifen regimen, a three-armed, placebo-controlled, blinded study (Jacobs et al. 2005 ) showed a significant increase in the total number of HF in arm B (homeopathic combination medicine (Hyland’s Menopause)) compared to arm C (2 placebos) and compared to arm A (placebo plus an individualized homeopathic single remedy). Whether or not that was the result of a harmful impact of the homeopathic combination remedy is not discussed by the authors. The study also showed a lower severity score and fewer HF in total in patients in arm A. The p values for mean difference of HF severity score also showed significance to the disadvantage of arm B, but looking at the confidence intervals the calculated significance is highly uncertain. The comparison of the single homeopathic remedy and a placebo did not reach statistical significance. While the patients in arm B showed a higher number of HF, had a worse HF severity score and an increase of headache, they showed, just as the single homeopathic remedy, a significantly improved general health score (via SF-36) compared to the placebo group after 1 year. Strangely, the non-responding placebo group did not receive significantly more changes of prescription. These inconsistencies might be the result of numerous methodological weaknesses of the study: most importantly, the high and uneven number of patients that had dropped out at 12 months (single remedy 36.7%, combination remedy 23.1%, placebo 40.7%), although all of the randomized patients were analysed. Methodologically questionable is the inclusion of patients with only 3 HF per day, which leaves only a low potential for improvement. It remains unreported whether patients in arm A had taken the remedy before the first telephone interview (after 1 month) because it was mostly given monthly or every 2 months. Furthermore, the patients were analysed in small subgroups with only ten patients in some groups. Baseline data for the endpoints are missing, and many results were (most likely due to missing significance) not reported at all. Therefore, the statements in this study should be viewed with caution.

Six studies investigated the effect of homeopathic interventions on QoL and QoR. Two trials reported a positive influence on global health status and subjective wellbeing (Frass et al. 2015 ; Frass et al. 2020a , b ). Significant differences were found for the majority of the assessed function- and symptom-scales after 4 months or 9 and 18 weeks, which were valued subjectively by the patients themselves. Contrary to this, Jacobs et al. ( 2005 ) reported an effect of homeopathy regarding QoL only in general health, but not in physical function. Four studies (Heudel et al. 2019 ; Lotan et al. 2020 ; Steinmann et al. 2012 ; Thompson et al. 2005 ) did not show a significant effect on QoL or QoR.

Again, the seemingly positive studies have numerous methodological weaknesses. The patients in the trial by Frass et al. ( 2015 ) were unblinded and not compared to a placebo- or active control group. Moreover, the results were reported for patients without chemotherapy and metastases, while the authors state that 24.4% of the patients had metastases and 49.1% received chemotherapy. Furthermore, the VAS used in the study is not a valid score. The authors used multiple imputation models without reporting the quantity of the calculated missings. Taking a closer look, 37 out of 410 randomized patients dropped out, leaving 373 patients to receive study treatment. Only 335 completed the questionnaires at the first and second visit and only 282 patients completed the third visit, while 373 patients were analysed. Thus, about 10% of the data for the second visit was imputed, about 24% for the third. Considering the high dropout (homeopathic arm 34.8%, control arm 27.5%) and the different attention between groups, the multiple imputation techniques that were used might have led to incorrect results: patients in the homeopathic arm (who might expect an improvement in well-being due to the remedy or talks to a homeopath) are more likely to drop out because of disappointment than patients in the control arm (mostly taking part to support science). Perhaps because these results were more pleasant for the authors, they compared only visit one and three and did not report the results of the second visit.

The second study by the author Frass et al. 2020a , b ) has been discussed above— due to the serious concerns on that study, also the data on QoL do not provide sound evidence. The follow-up for QoL changed from 2 years to 18 months. Likewise, as mentioned already, the drop-out in the study by Jacobs et al. ( 2005 ) was high and uneven (single remedy 36.7%, combination remedy 23.1%, placebo 40.7%) and might have, together with the small sample size of the subgroups (ten patients only in some groups) biased the results.

No effect of homeopathy was found regarding anxiety and depression by Thompson et al. ( 2005 ), the sole study in this review assessing that endpoint and lacking report quality.

All in all, our systematic review does not provide any evidence on the effectiveness of homeopathy in cancer care that is higher than a placebo effect.

As in higher dilutions there is no substance left any more, this result is in accordance with scientific knowledge. Accordingly, we doubt that any further well-conducted studies will come to another result. Some physicians may be inclined to use homeopathy as a placebo due to its high acceptance and reputation in the society and for patients. This makes it much easier to use the placebo effect than prescribing an unknown receipt. Moreover, homeopathy seemingly has no strong side-effects. Yet, lower dilutions may contain an amount of the substance that may lead to allergies or other side effects. Mostly, these effects will be small. Yet, this seeming advantage is no argument to justify the use of homeopathy as a placebo. Patients having a positive experience with homeopathy and other CAM tend to use these ineffective methods also in case of serious diseases (Huebner et al. 2014 ). Also, any delay in symptom management during cancer treatments in favour of a homeopathic treatment goes along with a deterioration of the patient’s supportive management.

Important to know, homeopaths have their own interpretation of symptoms going on or even increasing while the patient is taking homeopathy: initial worsening allegedly is a proof of the correct choice of the homeopathic remedy. For cancer patients, this idea is highly dangerous as it may lead to a further delay of treatment. Such worsening has been reported and misinterpreted in several studies in our review (Balzarini et al. 2000 ; Jacobs et al. 2005 ; Thompson et al. 2005 ; Thompson and Reilly 2002 ; 2003 ).

Limitations of this work

This systematic review exhibits some limitations that must be mentioned. As listed in the exclusion criteria in Table 1 , studies concerning children or teenagers were excluded and only trials with adult patients were analysed in this SR. Excluded were also other publication types than primary investigations or reports; preclinical studies, case reports or gray literature such as ongoing studies, unpublished literature, conference articles, abstracts, comments or letters. Besides, we included only studies in English or German language, leaving possible studies in other languages unconsidered. Furthermore, we could not conduct a meta-analysis. The essential reason for this is the large heterogeneity of the included studies, which was already described in the beginning of the discussion. We had to compare trials with differing design, endpoints, homeopathic intervention, type of cancer, cancer stage or cancer care to gain a comprehensive overlook. Besides, most of the subgroups were small and the majority of studies had a high risk of bias. The points mentioned would have limited the quality of a meta-analysis severely so we decided to summarize the included studies as a systematic review.

All in all, the results for the effectiveness of homeopathy in cancer patients are heterogeneous, mostly not significant and fail to show an advantage of homeopathy over other active or passive comparison groups. No evidence can be provided that homeopathy exceeds the placebo effect. Furthermore, the majority of the included studies shows numerous and severe methodological weaknesses leading to a high level of bias and are consequently hardly reliable. Therefore, based on the findings of this SR, no evidence for positive effectiveness of homeopathy can be verified.

Availability of data and material

Not applicable.

Code availability

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Wagenknecht, A., Dörfler, J., Freuding, M. et al. Homeopathy effects in patients during oncological treatment: a systematic review. J Cancer Res Clin Oncol 149 , 1785–1810 (2023). https://doi.org/10.1007/s00432-022-04054-6

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Efficacy of homoeopathic treatment: Systematic review of meta-analyses of randomised placebo-controlled homoeopathy trials for any indication

• H. J. Hamre   ORCID: orcid.org/0000-0003-1098-1079 1 , 2 ,
• A. Glockmann 1 ,
• K. von Ammon 2 ,
• D. S. Riley 3 , 4 &
• H. Kiene 1 , 2  

Systematic Reviews volume  12 , Article number:  191 ( 2023 ) Cite this article

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Background and objective

Since 1997, several meta-analyses (MAs) of placebo-controlled randomised efficacy trials of homoeopathy for any indication (PRETHAIs) have been published with different methods, results and conclusions. To date, a formal assessment of these MAs has not been performed. The main objective of this systematic review of MAs of PRETHAIs was to evaluate the efficacy of homoeopathic treatment.

The inclusion criteria were as follows: MAs of PRETHAIs in humans; all ages, countries, settings, publication languages; and MAs published from 1 Jan. 1990 to 30 Apr. 2023. The exclusion criteria were as follows: systematic reviews without MAs; MAs restricted to age or gender groups, specific indications, or specific homoeopathic treatments; and MAs that did not assess efficacy. We searched 8 electronic databases up to 14 Dec. 2020, with an update search in 6 databases up to 30 April 2023.

The primary outcome was the effect estimate for all included trials in each MA and after restricting the sample to trials with high methodological quality, according to predefined criteria. The risk of bias for each MA was assessed by the ROBIS (Risk Of Bias In Systematic reviews) tool. The quality of evidence was assessed by the GRADE framework. Statistical analyses were performed to determine the proportion of MAs showing a significant positive effect of homoeopathy vs. no significant difference.

Six MAs were included, covering individualised homoeopathy (I-HOM, n  = 2), nonindividualised homoeopathy (NI-HOM, n  = 1) and all homoeopathy types (ALL-HOM = I-HOM + NI-HOM, n  = 3). The MAs comprised between 16 and 110 trials, and the included trials were published from 1943–2014. The median trial sample size ranged from 45 to 97 patients. The risk of bias (low/unclear/high) was rated as low for three MAs and high for three MAs.

Effect estimates for all trials in each MA showed a significant positive effect of homoeopathy compared to placebo (5 of 5 MAs, no data in 1 MA). Sensitivity analyses with sample restriction to high-quality trials were available from 4 MAs; the effect remained significant in 3 of the MAs (2 MAs assessed ALL-HOM, 1 MA assessed I-HOM) and was no longer significant in 1 MA (which assessed NI-HOM).

The quality of evidence for positive effects of homoeopathy beyond placebo (high/moderate/low/very low) was high for I-HOM and moderate for ALL-HOM and NI-HOM. There was no support for the alternative hypothesis of no outcome difference between homoeopathy and placebo.

The available MAs of PRETHAIs reveal significant positive effects of homoeopathy beyond placebo. This is in accordance with laboratory experiments showing partially replicable effects of homoeopathically potentised preparations in physico-chemical, in vitro, plant-based and animal-based test systems.

Systematic review registration

PROSPERO CRD42020209661. The protocol for this SR was finalised and submitted on 25 Nov. 2020 and registered on 26 Dec. 2020.

Peer Review reports

Background and rationale

Homoeopathy is a therapy system widely used in Europe, India and other countries [ 1 ]. Core features of homoeopathy include drug provings (observation of symptoms occurring in healthy persons exposed to substances of mineral, botanical or zoological origin), simile principle (similarity between symptom patterns in drug provings and the symptoms to be treated with the same substance) and potentization (successive dilution of the homoeopathic substance, with each dilution step involving repeated shaking of liquids or grinding of solids into lactose) [ 2 ].

The clinical effects of homoeopathic treatment have been investigated in several hundred randomised controlled trials [ 3 ] and in systematic reviews (SRs). Among the SRs, two contrasting approaches can be discerned.

One approach is to focus on a specific indication (e.g., depression [ 4 ], acute respiratory tract infections in children [ 5 ]) while often including open-label trials and observational studies. In this approach, data synthesis is grouped by design, thus yielding information about homoeopathy in patient care.

The opposite approach is to include all indications while restricting study designs to placebo-controlled trials and aggregating results in an MAs, thus yielding information about the specific effects of homoeopathy beyond those of placebo. A major reason for using this approach has been the claim that ‘homoeopathy violates natural laws and thus any effect must be a placebo effect’ [ 6 ].

Since 1997, at least six MAs of placebo-controlled homoeopathy trials for any condition have been published [ 6 , 7 , 8 , 9 , 10 , 11 ]. These MAs have differed in their methods for trial inclusion, data synthesis and assessment of risk of bias; furthermore, their results and conclusions have been inconsistent. During this period, there have been substantial advancements in methodology and quality standards for MAs and other SRs [ 12 , 13 , 14 , 15 ], including SRs of SRs (also called overviews or umbrella reviews) [ 16 , 17 , 18 ]. To our knowledge, a formal SR of MAs of randomised placebo-controlled homoeopathy trials for any condition has not been performed. Herein, we report such an SR.

Research questions

Does homoeopathic treatment have positive effects beyond placebo in MAs of randomised placebo-controlled trials for any condition?

Do the findings from these MAs support the notion of a common effect—or absence thereof—across different types of homoeopathic treatment (e.g. individualised, clinical or complex homoeopathy) and across different types of indications (e.g. acute, chronic)?

Eligibility criteria for meta-analyses (MAs)

The eligibility criteria are presented in Table 1 .

Information sources and search strategy

We searched eight online databases, including four databases largely or totally restricted to SRs (A–D), two generic databases (E–F) and two databases focused on complementary or alternative therapies (G–H) (Table 2 ). In addition, one private database (author HJH) was searched.

Other sources

A list of included MAs was sent to experts in the field to identify any missing eligible MAs or additional analyses of the included MAs.

Selection process

Two reviewers (HJH, AG) independently searched the online literature databases and screened the titles and abstracts to identify potentially eligible MAs. The reviewers compared their screening results, and discrepancies were resolved by discussion (HJH, AG).

Eligibility

For the potentially eligible MA records, full-text reports were obtained. Two reviewers (HJH, AG) independently read the full texts and assessed their eligibility in accordance with the eligibility criteria (Table 1 ). The reviewers compared their eligibility assessments, and discrepancies were resolved by discussion (HJH, AG).

Data collection process

Two reviewers independently extracted data from the full-text reports into Excel files (HJH + [GSK, HK or AG]) using a piloted data extraction form. Reviewer AG compared the two sets of extracted data. Discrepancies were resolved by discussion (HJH + [GSK, HK or AG]).

We extracted and summarised trial-level data from tables of the MAs but did not inspect original trial publications (with one exception, cf. Additional file 2 , Section 2.3.1). Indications/diagnoses in individual trials were coded according to the International Classification of Diseases, 10th Edition (ICD-10). If more than one diagnosis was listed, the first listed diagnosis was coded. If two trials or trial comparisons were analysed separately in one MA and analysed together in another MA, they were counted as 3 trials or trial comparisons, respectively. If more than one trial report for the same trial was listed, only one trial report was extracted.

All outcomes in the following subsections refer to the combined effect estimate with a measure of precision for the primary clinical outcome reported in each MA (henceforth ‘effect estimate’).

Primary outcome

Effect estimates for.

All included trials in each MA.

One analysis with the trial sample restricted to ‘high-quality trials’ according to the following criteria, all of which must be fulfilled:

trials of higher methodological quality (or lower risk of bias), as stated and defined by the authors of the MA

based on an assessment of at least three specified components of methodological quality (e.g. concealment of allocation sequence, blinding of outcome assessors)

maximum one single high-quality category defined for the respective MA

Sensitivity analyses

Effect estimates in sensitivity analyses, calculated after restricting the sample based on the methodological quality (risk of bias) of individual trials, as assessed by:

individual quality (risk of bias) components such as concealment of allocation sequence, double blinding [blinding of participants, study personnel and outcome assessors], risk of outcome reporting bias, peer-reviewed trial publication

the criterion ‘high-quality trials’ (as in Item 2 above) + one or several additional quality components

other combination of quality components, grouped by total number of components in the respective analysis: 2–4 or ≥ 5

cumulative MAs with stepwise removal of trials by risk-of-bias ratings, conceptualised in a hierarchical order by the authors of the respective MA (e.g. ascending numbers in a numeric scale or ‘poor’, ‘fair’, ‘good’)

Supplementary analyses addressing meta-bias

Effect estimates in supplementary analyses based on assumed risk of bias across trials (meta-bias):

Statistical adjustment for possible publication bias/small study bias

Sensitivity analyses, with restrictions of included trials, based on trial sample size

Analyses addressing possible outcome reporting bias

Combined analyses

Effect estimates in analyses combining features of Sections ' Sensitivity analyses ' and ' Supplementary analyses addressing meta-bias ' above.

Subgroup analyses

With regard to research question 2, five types of trial subgroups in the respective MAs (A.1–5) were examined. The subgroup analyses had four types of results (B.1–4), and they were grouped by the timing of the analysis (C.1–2):

Subgroup types

Homoeopathy type ( descriptions from Linde 1997 [ 6 ]; further descriptions in Suppl. Table 10 )

individualised or classical homoeopathy (I-HOM) ( single homoeopathic remedy selected, based on the total symptom picture of a patient )

clinical homoeopathy ( one or several single remedies administered for standard clinical situations or conventional diagnoses )

complex homoeopathy ( multiple remedies mixed into a standard formula to cover a person’s symptoms and diagnoses )

isopathy ( serial agitated dilutions made from the causative agent in an infectious or toxicological condition )

nonindividualised homoeopathy (NI-HOM) = b + c + d

Homoeopathic potency range: low (< C1 or < D24)/high (≥ C12 or ≥ D24)

Age groups: children, adults, elderly (according to definitions in MA)

Indication: acute or chronic (according to definitions in MA)

Type of outcome extracted from trial

continuous or rank-ordered

Analysis results

Tests for interactions between subgroups

Effect estimates in subgroups

Statistical homogeneity/heterogeneity

Funnel plot symmetry/asymmetry and related statistical tests

Timing of subgroup analysis

Prespecified (specified in prepublished protocol OR explicitly stated to be prespecified)

Post hoc OR no information

Other variables

Other variables collected from the MAs are listed in Suppl. Table 1 .

Assessment of risk of bias in the included MAs

Risk of bias/methodological quality of the MA was assessed using the ROBIS tool (Risk of Bias in Systematic Reviews) [ 13 ], supplemented with items 7, 10 and 16 from the AMSTAR-2 tool (A MeaSurement Tool to Assess systematic Reviews) [ 14 ], which are not addressed in ROBIS. Assessments were performed independently by two reviewers (HJH, GSK); discrepancies were resolved by discussion between the reviewers.

The outcome of these assessments was the composite body of reports, comprising.

protocol for the MA, if available

primary publication of the respective MA

additional analyses of the MA, if the authors include first author or last author or corresponding author for item 2.

Effect measures

Effect estimates of each MA (cf. Section 'Outcomes', above) were reported using the metric reported in the MA (e.g., odds ratio [OR], standardised mean difference [SMD]). Standardised mean differences for homoeopathy vs. placebo were reported with point estimates > 0 indicating a benefit of homoeopathy.

Synthesis methods

Effect estimates were summarised in table format and classified as follows:

‘Significant, positive effect of homoeopathy beyond placebo’: Effect estimate favouring the homoeopathy group with the 95% confidence interval not crossing the boundary between ‘favouring homoeopathy’ and ‘favouring placebo’, as defined in the respective meta-analysis OR (if 95% confidence interval not reported) p value < 0.05

‘No significant difference between homoeopathy and placebo’: The 95% confidence interval for the effect estimate crosses the boundary between ‘favouring homoeopathy’ and ‘favouring placebo’, as defined in the respective meta-analysis OR (if 95% confidence interval not reported) p value ≥ 0.05

‘Significant, negative effect of homoeopathy beyond placebo’: same as 1, except the effect estimate favours the placebo group

If both fixed effects and random effects models had been used for the same analysis, the results from random effects models were used for the data synthesis herein.

Meta-bias assessment

See Sections ' Supplementary analyses addressing meta-bias ' and ' Combined analyses ', above.

Confidence in cumulative evidence/certainty assessment

Confidence in cumulative evidence for the two research questions (Sect.  Research questions ) was assessed.

For question 1, the conceptual framework of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) group [ 20 ] was used, with a focus on six issues: risk of bias of individual trials [ 21 ], inconsistency/heterogeneity [ 22 ], risk of publication bias/small study bias [ 23 ], imprecision [ 24 ], indirectness [ 25 ] and occasions for rating up the quality of evidence [ 26 ].

For question 2, results of subgroup and heterogeneity [ 22 ] analyses were used.

Identification, screening and inclusion of meta-analyses

From the eight online databases, we identified 293 literature records of potentially eligible meta-analyses (search completed on 14 Dec. 2020). After the removal of 82 duplicates, 211 records were screened, of which 191 were excluded and 20 were further assessed for eligibility. In addition, searches in the database of reviewer HH (20 Jan. 2021 + addition of Gartlehner 2022 on 04 July 2022, cf. Section ' Additional data: Gartlehner 2022 ') and letters to experts (sent 10 Feb. 2021) yielded a total of 9 nonduplicate records that were also assessed for eligibility. Thus, 29 full-text reports were assessed for eligibility, of which 13 were excluded. Thus, 16 reports of 6 different MAs were included (PRISMA 2020 [ 27 ] flow diagram, cf. Fig.  1 ).

PRISMA 2020 flow diagram for new systematic review which included searches of databases, registers and other sources

By 30 April 2023, a period of 30 months had passed after the end of the report time frame according to the original eligibility criteria (reports published up to 31 Oct. 2020). We therefore conducted an updated search of reports published in the period from 01 Nov. 2020 to 30 April 2023. We searched databases A–C, E, G–H (Table 2 ; D was no longer available, and F was omitted for budget reasons, having yielded no nonduplicate records in the primary search) and the database of reviewer HJH. The updated search yielded 13 records, of which 11 were excluded and 2 were assessed for eligibility. Of these, 1 report had already been included on 04 July 2022 (Gartlehner 2022 cf. Section ' Additional data: Gartlehner 2022 '), and 1 was excluded (PRISMA 2020 flow diagram for the update in Additional file 4).

A list of the 14 excluded publications (original search: n  = 13, update n  = 1) with reasons for exclusions is presented in Suppl. Table 2 .

The 16 reports consisted of 6 primary publications of one [ 6 , 7 , 8 , 10 , 11 ] or two [ 9 ] MAs, 2 published MA protocols [ 28 , 29 ], 7 publications of additional analyses [ 3 , 30 , 31 , 32 , 33 , 34 ] and 1 error correction [ 35 ] (Table 3 ).

Description of meta-analyses

Chronological overview.

The six MAs were published in the period 1997–2017. The two first (Linde 1997 [ 6 ] and 1998 [ 7 ]) and the two most recent (Mathie 2014 [ 10 ] and 2017 [ 11 ]) MAs were MA ‘pairs’, i.e. they were conducted and published by the same first author with overlapping co-authorships. The other two MAs (Cucherat 2000 [ 8 ], Shang 2005 [ 9 ]) were published by different author groups.

The MA conducted by Linde (1997) [ 6 ] was the first MA of placebo-controlled homoeopathy trials for any condition worldwide. The primary publication was followed by a detailed assessment of the relation between study quality (risk of bias) and effect estimates (Linde 1999) [ 30 ]. The MA conducted by Linde (1998) [ 7 ] was an updated subgroup analysis of Linde (1997) [ 6 ], restricted to I-HOM.

The MA conducted by Cucherat (2000) [ 8 ] originated from a homoeopathy report prepared for the European Parliament by the Homoeopathic Medicine Research Group (Boissel 1996) [ 31 ]. Compared to the Boissel report, the MA conducted by Cucherat [ 8 ] had modifications in some analyses. We considered this MA the definitive work, but we also consulted the Boissel report as an additional source of details on the methods and conduct of the MA.

The MA conducted by Shang  [ 9 ] was designed as a prospective comparison of two MAs of placebo-controlled trials: one MA of any type of homoeopathic treatment for any disorder and one MA with matched trials on conventional treatment. According to the protocol for the present SR [ 37 ], the results of the latter MA were beyond the scope of this SR. However, the authors of the MA conducted by Shang [ 9 ] used the results of the MA on conventional treatment to draw inferences about the homoeopathy MA results. We therefore included comparative data on the two MAs (presented in Additional file 2 ).

The MAs conducted by Mathie (2014, 2017) [ 10 , 11 ] were part of a comprehensive MA program (Mathie 2013) [ 3 ], covering placebo-controlled trials of individualised [ 10 ] and nonindividualised  [ 11 ] homoeopathy, respectively.

Methods of the meta-analyses

Research objective or hypothesis.

The main research objective concerned the efficacy of homoeopathic products vs. placebo in all six MAs: generally stated [ 7 , 8 ] or in terms of outcome difference between homoeopathy and placebo [ 6 , 10 , 11 ] (full text excerpts in Suppl. Table 3 ). In the MA conducted by Shang [ 9 ], the research hypothesis was further specified: ‘We assumed that the effects observed in placebo-controlled trials of homoeopathy could be explained by a combination of methodological deficiencies and biased reporting’ (Discussion, p.730).

Eligibility criteria

Design, publication types.

In all six MAs, parallel group randomised trials were included, while crossover trials were excluded from four MAs [ 6 , 9 , 10 , 11 ], included in the MA conducted by Linde (1998) [ 7 ] and not mentioned in the MA conducted by Cucherat [ 8 ]. Four MAs had no restrictions regarding publication format, while two (Mathie 2014 and 2017) [ 10 , 11 ] were restricted to peer-reviewed journal articles of at least 500 words (Suppl. Table 4 ).

Patients and indications

Restriction to disease groups as such was not applied in any MA (Suppl. Table 5 ). Notably, in the MA conducted by Shang [ 9 ], the homoeopathy trials were compared to placebo-controlled trials of interventions used in conventional medicine, matched for indication. For 94.0% ( n  = 110/117) of otherwise eligible homoeopathy trials, a trial of conventional medicine for the respective indication could be found, while 7 unmatchable homoeopathy trials were excluded.

Interventions, comparators

In the MAs conducted by Mathie (2014 and 2017) [ 10 , 11 ], the homoeopathic intervention types were restricted as follows: radionically prepared medicines, anthroposophic medicine, homotoxicology, and homoeopathy combined with other (complementary or conventional) treatments were excluded (Suppl. Table 6 ).

In the meta-analysis conducted by Cucherat [ 8 ], ‘only trials with a clearly defined primary outcome’ were included (Suppl. Table 7 ).

Literature search and inclusion, data extraction and analysis

For all six MAs, previously published MAs or SRs [ 38 ] were consulted. Between 4 [ 6 ] and 19 [ 9 ] online databases were researched. For all MAs, experts in the field were contacted for information on additional trials; manual searches of reference lists were used in five MAs but not in the MA conducted by Linde (1998) [ 7 ], which was largely an update on their previous MA from 1997 (Suppl. Table 8 ). Screening of titles and abstracts was performed independently by two reviewers in the MA conducted by Linde (1997) [ 6 ] and by one reviewer in the MA conducted by Cucherat [ 8 ]. The screening approach was not reported in the four other MAs. Full-text assessments were performed independently by two persons in the MA conducted by Linde (1997) [ 6 ]; by one person and checked in part by another person in the MA conducted by Cucherat [ 8 ]; and by one person in the MA conducted by Linde (1998) [ 7 ]. The full text assessment approach was not reported in three MAs.

Data extraction was performed independently by two persons in five MAs and by one person in the MA conducted by Linde (1998 [ 7 ]). Risk of bias assessments were performed independently by two persons in three MAs [ 6 , 10 , 11 ] and by one person in the MA conducted by Linde (1998 [ 7 ]). The number of persons performing risk of bias assessment was not reported in two MAs. Lists of excluded trials were available in three MAs [ 9 , 10 , 11 ]. The reasons for exclusion of trials were provided in all MAs except the one conducted by Linde (1998) [ 7 ] (Table 4 ).

All six MAs used one main clinical outcome for each trial or trial comparison. For the MA conducted by Cucherat [ 8 ], this was the primary outcome as reported in the trials (cf. Section ' Eligibility criteria ', above); for the other MAs, a predefined hierarchical list of criteria for extraction of the main outcome was used (Suppl. Table 9 ).

For two MAs (Mathie 2014 and 2017) [ 10 , 11 ], a prepublished protocol was available; for two MAs (Linde 1997. Cucherat [ 6 , 8 ]), a protocol was referred to in the publication; and for two MAs (Linde 1998, Shang 2005 [ 7 , 9 ]), a protocol was not mentioned in the publication, while one single design criterion (outcome extraction in both cases) was explicitly stated as predefined.

Risk of bias assessment, heterogeneity, meta-bias

High-quality trials.

High-quality trials according to our criteria (cf. Section ' Data items ' / ' Primary outcome ', above) were performed in four MAs [ 6 , 9 , 10 , 11 ]. The criteria for high-quality trials were described as predefined (Linde 1997) [ 6 ] or fully (Mathie 2017) [ 11 ] or partially (Mathie 2014) [ 10 ] defined in a prepublished protocol. One MA did not mention this aspect (Shang [ 9 ]). The criteria for high-quality trials were as follows:

The MA conducted by Linde (1997) [ 6 ] used a combination of two score-based instruments:

Jadad score [ 39 ] (range 0–5 points, thereof 0, 1 or 2 points each for items no. 1 and 3 and 0–1 point for item 11 in Table 5 ): ≥ 3 points

Internal validity scale [ 30 ] (range 0–7 points, thereof 0, 0.5 or 1 point each for items 1–2, 4–7 and 11 in Table 5 ): ≥ 5 points

The instruments used in the following MAs consisted of sets of mandatory criteria, all of which were to be fulfilled.

The MAs conducted by Mathie (2014 and 2017) [ 10 , 11 ] used the Cochrane risk-of-bias tool (RoB, version 2011) [ 40 ]: low risk of bias for items 1–2 and 4–5 in Table 5 , low risk for two of the three items 8 and 12–13 and low or uncertain risk for one of the latter four items.

In the MA conducted by Shang [ 9 ], the number of quality components used was variously described as 3 or 4, corresponding to fulfilment of items (1–3) or (1–3 + 10) in Table 5 . Lüdtke [ 32 ] interpreted Shang [ 9 ] as having used 3 components (Suppl. Table 29 ). Details in support of either 3 or 4 components are presented in Suppl. Table 11 .

The high-quality criteria were based on 8 [ 6 ], 7 [ 10 , 11 ] and either 3 or 4 quality components [ 9 ] (Table 5 ).

Risk of bias (methodological quality) otherwise

The total number of methodological quality components assessed in each MA (including components of high-quality criteria as well as other components) ranged from 3 [ 8 ] to 10 [ 6 , 7 ], details in Suppl. Table 12 .

Associations between quality components and outcome were analysed with hypothesis testing in four MAs (not in the MA conducted by Linde (1998) [ 7 ] and Cucherat [ 8 ]).

Cumulative MA with stepwise removal of trials according to increasing quality categories was performed in four MAs using interval-scaled [ 7 , 10 , 11 ] or rank-ordered [ 8 ] categories. Of the two other MAs, one [ 7 ] had outcome analysis in 4 ranked quality subgroups instead of cumulative MA.

Statistical heterogeneity testing was performed in four MAs (not in the MAs conducted by Linde (1998) [ 7 ] and Cucherat [ 8 ]); all but one MA [ 7 ] included an assessment of publication bias/small study bias (Suppl. Table 14 ).

Potential conflicts of interest were stated and explained for at least one author in two MAs (Mathie 2014 and 2017) [ 10 , 11 ]; a statement of no conflicts of interest for any author was included in one MA (Shang) [ 9 ], while this issue was not addressed in the three other MAs.

Trial characteristics

Number of trials, trial comparisons and trial reports.

For each MA, between 150 and 359 full-text records were assessed for eligibility (data available for four MAs) and between 16 and 119 trials were eligible for SR, including 16–110 trials with extractable data for MA. Altogether, 182 different trials (or in some cases, trial comparisons) reported in 165 different publications or other trial reports were included in the 6 MAs. Of these, n  = 88 trials were included in 1 MA, 65 trials in 2 MA, 24 trials in 3 MA and 5 trials in 4 MA, with a total of 310 trials or trial comparisons (Suppl. Table 15 ). All following descriptions refer to these 310 trials.

Availability of descriptive data

Summary descriptive data on 12 different trial properties (excluding design, trial quality and results) were presented, ranging from 3 [ 8 ] to 9 [ 7 ] items per MA (Suppl. Table 16 ).

All six MAs had at least one table with characteristics of individual trials. A total of 38 different items were presented (or summarily stated as present/absent in all trials), ranging from 8 (Shang [ 9 ]) to 33 items (Mathie 2017 [ 11 ]) per MA (Suppl. Table 17 ). The most frequently reported items were as follows:

first author, number of patients, indication (brief), intervention in homoeopathy group, outcome, summarised rating of methodological quality (presented in n  = 6 MA)

indication group, graphical display of effect size with 95% confidence interval ( n  = 5 MA)

Descriptive data

The trials were published in the period 1943–2014 (Table 6 ). The median trial sample size per trial was in the range of 45–97 patients with a minimum sample size of 5–28 and a maximum size of 175–1573 patients. The trials of each MA had been performed in 11–15 countries (data available for four MAs). The countries where each trial was performed was reported in three MAs [ 7 , 10 , 11 ]; the most common countries were the UK ( n  = 18 trials among the three MAs, multiple responses possible), Germany ( n  = 17), USA ( n  = 9) and France and India (both with n  = 6 trials) (Suppl. Table 18 ). The most common languages of trial publications were English (range 39–95% of trials), German (5–29%) and French (0–28%) (Table 6 ).

Data on age groups and gender were available in three MAs [ 7 , 10 , 11 ] with a total of 94 trials (multiple responses possible). A total of 14.9% ( n  = 14/94) of all trials included children only, 55.3% ( n  = 52) included adults only and 29.8% ( n  = 28) included both adults and children or unknown. A total of 14.9% ( n  = 14/94) of trials included only females; 2.1% ( n  = 2) of trials included only males; and 83.0% ( n  = 78) of trials included both genders or did not report these data (data on individual MAs in Suppl. Table 19 ).

Indications for all 310 trials (multiple responses possible) were coded according to ICD-10:

The most frequent ICD-10 Diagnosis chapters were J00-J99 Diseases of the respiratory system (24.5%, n  = 76/310), S00-T98 Injury, poisoning and certain other consequences of external causes (11.9%, n  = 37), K00-K93 Diseases of the digestive system (11.0%, n  = 34) and M00-M99 Diseases of the musculoskeletal system and connective tissue (8.7%, n = 27) (Suppl. Table 20 ).

The most frequent ICD-10 three-digit diagnoses were J30 Vasomotor and allergic rhinitis (7.1%, n  = 22/310), J11 Influenza, virus not identified (4.8%, n  = 15), J06 Acute upper respiratory infections of multiple and unspecified sites (4.2%, n  = 13) and K91 postprocedural disorders of digestive system, not elsewhere classified [postoperative ileus] (4.2%, n  = 13) (Suppl. Table 21 ).

Interventions, results

The intervention was I-HOM in all trials for 2 MAs [ 7 , 10 ] and in 0–18% of trials of the four other MAs. In these four MAs, the NI-HOM intervention was clinical homoeopathy in 44–71% of trials, complex homoeopathy in 6–44% (Mathie 2017 [ 11 ]: including ‘combination products’) and isopathy in 6–13% (Table 7 ). The homoeopathic products used were high potencies only (≥ C12 or ≥ D24) in 29–39% of trials.

The main outcome was binary in 43–89% of trials. The main outcome analysis showed a significant positive effect of homoeopathy compared to placebo in 14–65% (weighted mean 36.5% ( n  = 113 of 310 trials), a nonsignificant superiority of homoeopathy in 18–55% (weighted mean 44.2%), a nonsignificant superiority of placebo in 16–32% (mean 19.0%) and a significant positive effect of placebo compared to homoeopathy in 0–1% (0.3%, n  = 1 trial) (Table 7 ).

Assessments of bias and heterogeneity

Risk of bias (methodological quality) of trials

Overview of methodological quality components

For 10 different methodological quality components, the number of trials fulfilling the respective criterion was assessed in at least two MAs, with a total of 43 analyses (Table 8 , components 1–10). Fulfilment rates ranged from 17% (allocation concealment adequate in the MAs conducted by Mathie (2017) [ 11 ]) to 100% (8 cases); 44% ( n  = 19/43) of analyses showed a fulfilment rate of ≥ 50%. Weighted mean fulfilment rates for each of the 10 components (multiple responses possible, as trials could be included in more than one MA) ranged from 20% (no funding-related vested interests in the MAs conducted by Mathie (2014) [ 10 ] and (2017) [ 11 ]) to 89% (publication format = journal article in all six MAs). Three components (journal article, double blinding adequate, no selective outcome reporting) had weighted average fulfilment rates above 75%.

Outcome reporting bias

In the MA conducted by Linde (1997) [ 6 ], 23.6% ( n  = 21/89) of trials had a predefined primary outcome (effect estimate after sample restriction to these trials reported in Suppl. Table 28 ). In the MA conducted by Cucherat [ 8 ], only trials with one single ‘clearly defined’ primary outcome were eligible.

In the MAs conducted by Mathie (2014 and 2017) [ 10 , 11 ], the risk of outcome reporting bias was assessed in Domain V of the Cochrane RoB tool by comparison of the results section with the protocol or, if no protocol was available, with the methods section of publications. In the MA conducted by Mathie (2014) [ 10 ], freedom from risk of outcome reporting bias was rated as ‘yes’ in 86.4% ( n  = 19/22) of trials in the MA, ‘uncertain’ in 4.5% ( n  = 1) and ‘no’ in 9.1% ( n  = 2). In the MA conducted by Mathie (2017) [ 11 ], the corresponding ratings were ‘yes’ in 74.1% ( n  = 40/54) of the trials in the MA, ‘uncertain’ in 9.3% ( n  = 5) and ‘no’ in 16.7% (n = 9) (Table 8 , component no. 5). Effect estimates for the 19 and 40 ‘yes’-rated trials, respectively, were not published.

The proportion of high-quality trials ranged from 6% ( n  = 3/54) of trials analysed by Mathie (2017) [ 11 ] to 29% ( n  = 26/89) of trials analysed by Linde (1997) [ 6 ] (Table 8 ). Notably, the criteria for ‘high quality’ differed widely among the MAs:

High quality (named ‘reliable evidence’) in the MAs conducted by Mathie (2014 and 2017) [ 10 , 11 ] approximately corresponds to an internal validity scale of 6.5 points or higher in the MA conducted by Linde (1997) [ 6 ], which was fulfilled by 8% ( n  = 7/89) trials in the MA conducted by Linde (1997) [ 6 ], while 29% fulfilled the high-quality criteria of the authors for Linde (1997) [ 6 ].

If the high-quality criteria in the MAs conducted by Mathie (2014 and 2017) [ 10 , 11 ] had been restricted to the quality components 1–3 in Table 8 (corresponding to the 3-component model in Shang), the proportion of high-quality trials had been 23% instead of 14% of trials in the MA conducted by Mathie (2014) [ 10 ] and 11% instead of 6% in the MA conducted by Mathie (2017) [ 11 ]. When applying the same criteria to the MA conducted by Cucherat [ 8 ] (which did not have a ‘high-quality trial’ assessment as defined in this SR), they would be fulfilled for 94% of trials.

For the three MAs using a set of mandatory criteria for ‘high-quality’ (Shang with 3 or 4 criteria; Mathie (2014) [ 10 ] and (2017) [ 11 ] with 7 criteria each), methodological quality was compared with the quality of other trials, assessed according to identical criteria:

Shang [ 9 ] included such a comparison: Among 110 HOM and 110 CON trials, matched for diagnosis and outcome type, the proportion of high-quality trials was significantly higher among HOM trials (19.1%, n  = 21/110) than for CON trials (8.2%, n  = 9/110), ( p  = 0.0294) (Additional file 2 ).

Mathie [ 10 , 11 ] used the Cochrane RoB tool (2011 version) with 6 standardised criteria and 1 nonstandardised item ‘other sources of bias’, which was omitted from the subsequent RoB version 2 [ 41 ]. In an evaluation of this instrument, the methodological quality of randomised trials in 100 Cochrane SRs and 18 non-Cochrane SRs published at the end of 2014 was summarised using the 6 standardised criteria. The two SRs conducted by Mathie ([ 10 , 11 ], including trials eligible for SR but not for MA) and the Cochrane SRs had similar proportions of randomised trials rated as having low (A: 3–6%), uncertain (B: 33–38%) and high (C: 59–61%) risk of bias, respectively, while the non-Cochrane SRs had comparatively more trials with uncertain risk (53%) and fewer trials with high risk (41%) [ 42 ] (Table 9 ).

Heterogeneity

Heterogeneity in the full sample.

Significant statistical heterogeneity across trials was found in 3 MAs [ 6 , 9 , 11 , 30 ] and was not found in 1 MA (Mathie 2014) [ 10 ], while heterogeneity was not assessed in 2 MAs [ 7 , 8 ] (Suppl. Table 23 ). Notably, in the MA conducted by Cucherat [ 8 ], the likelihood of statistical heterogeneity because of clinical heterogeneity was stated as a major reason for choosing p value combination instead of meta-analytic effect estimation.

Heterogeneity after sample restriction or ‘trim-and-fill’

In the MA conducted by Linde (1997/1999) [ 6 , 30 ], heterogeneity was τ -squared 0.43 in the full sample ( n  = 89 trials). After sample restriction to trials with higher methodological quality, heterogeneity was reduced in 6 of 7 univariate analyses, with τ -squared ranging from 0.31 for double-blind trials ( n  = 81) to 0.41 for explicitly randomised trials ( n  = 64). In one multivariate analysis, heterogeneity was reduced to τ -squared = 0.28 for explicitly randomised trials (Suppl. Table 23 ).

In the MA conducted by Mathie (2017) [ 11 ], heterogeneity (I-squared 65%) was not reduced after the ‘trim-and-fill’ procedure for funnel plot asymmetry (FPA, I-squared 79%).

Nonreporting bias, small study bias

Unavailable trials.

Extensive searches for potentially eligible trials were performed for five MAs (not Linde 1998) [ 7 ], and unpublished trials were eligible for three MAs [ 6 , 8 , 9 ] but not for the two MAs conducted by Mathie [ 10 , 11 ].

Data on unavailable trials were reported for three MAs:

Linde (1997) [ 6 ]: The authors assumed that 15–30 unpublished trials that they could not obtain might exist, but did not present any quantitative findings supporting this assumption.

Cucherat [ 8 ]: The authors identified 1 unpublished trial, for which data were protected by industrial property protection laws and hence unavailable.

Shang [ 9 ]: The authors reported 9 unavailable trial reports, thereof 5 journal articles in English ( n  = 2) and Spanish ( n  = 3) language, respectively, and 4 conference proceedings in English language. Of these nine reports, one journal article had been misclassified, as it was actually a case of multiple publication (Straumsheim 1997, included in the MA conducted by Shang [ 9 ] as homoeopathy trial No. 87), three journal articles were listed in Mathie (2013) [ 3 ] as placebo-controlled trials but not eligible for the MAs conducted by Mathie (2014) [ 10 ] ( n  = 2) and Mathie (2017) [ 11 ] ( n  = 1), respectively, because they had not been published in a peer-review journal. One conference proceeding (Lara-Marquez 1997) was included in the SR performed by Linde (1998) [ 7 ] but not in the respective MA, as it was only available as an abstract (Suppl. Table 24 ).

Unidentified trials

Mathie (2013) [ 3 ] identified the following:

25 trial reports (2 peer-reviewed, 23 not peer-reviewed) potentially eligible for inclusion in the MA conducted by Linde (1997) [ 6 ] but not listed therein,

41 trial reports (14 peer-reviewed, 27 not peer-reviewed) potentially eligible for the MA conducted by Shang [ 9 ] but not listed therein.

Funnel plot, full sample

Funnel plot inspection was performed in four MAs. Funnel plots were constructed by plotting the effect estimate for each trial—expressed as the log odds ratio [ 6 , 9 , 10 ] or standardised mean difference (Mathie 2017 [ 11 ])—against the standard error. In three MAs [ 6 , 9 , 11 ], FPA was found, with trials with higher standard error having larger effects. In one MA (Mathie 2014 [ 10 ]), the funnel plot was symmetric. Egger’s test was significant in the first three MAs but not in the MA conducted by Mathie (2014) [ 10 ] (Suppl. Table 25 ).

Trim-and-fill tests were performed in three MAs [ 6 , 8 , 11 ]. Random effects and nonparametric selection models to assess possible missing trials were used in the MA conducted by Linde (1997) [ 6 ]. Under different conditions, the number of fictive additional trials with zero effect required to change results from a significant to a nonsignificant superiority of homoeopathy ranged from 11 (Mathie (2017) [ 11 ]) to 4511 (Linde (1997) [ 6 ], fixed effects model) (Suppl. Table 26 ).

Funnel plot, trials with higher quality

Sterne (2001) [ 36 ] constructed a funnel plot of n  = 34 trials with ‘adequate concealment’ + ‘double-blinding’ from the MA conducted by Linde (1997) [ 6 ] (not the n  = 26 high-quality trials according to Linde (1997) [ 6 ]). On inspection, FPA was found, and the corresponding tests were significant (rank correlation: p  = 0.014; regression: p  < 0.001).

Lüdtke (2008) [ 32 ] constructed a funnel plot of the 21 high-quality trials analysed by Shang [ 9 ] by plotting the log odds ratio against the standard error. The plot showed a cluster of 18 largely symmetric trials and 3 extreme outliers, with 2 strongly favouring homoeopathy and 1 strongly favouring placebo. Egger’s test showed a large but not significant FPA (asymmetry coefficient 0.40, p  = 0.17); this was also the case for the 8 largest high-quality trials (1.15, p  = 0.94, funnel plot not shown) [ 32 ] (Suppl. Table 25 ).

Associations between methodological quality and effect estimates

Associations between methodological quality or other subgroups and effect estimates were analysed in 4 MAs (Linde 1997 [ 6 ], Shang [ 9 ], Mathie 2014 [ 10 ] and 2017 [ 11 ], Suppl. Table 27 ).

Linde (1997 [ 6 ] and 1999 [ 30 ]): The authors analysed uni- and multivariate associations between four single quality components and the effect estimate and found significant associations for ‘double blinding’ (uni- and multivariate) and ‘explicitly randomised’ (multivariate) but not for ‘adequate concealment of random allocation’ nor ‘complete follow-up’ (neither uni- nor multivariate). Univariate analyses showed significant associations between three composite quality measures (A: Jadad scale > 2; B: Internal validity score > 4.5; C: A and B) and effect estimate. On the other hand, scatter plots of the Jadad scale and internal validity score against odds ratios showed no clear linear relationships (Suppl. Table 27 ).

Linde (1997) [ 6 ] / Sterne [ 36 ]: The authors analysed uni- and multivariate associations between ‘English language publication’ and ‘Medline-indexed publication’, respectively, and effect estimates: two of four analyses showed significant associations (‘English language’, univariate + ‘Medline-indexed’, multivariate Suppl. Table 27 ).

Shang [ 9 ] analysed univariate associations between six single quality components and effect estimates, and significant associations were found for three (‘Medline-indexed’, ‘double-blinding’, ‘adequate generation of allocation sequence’). Likewise, a significant association was found for high-quality trials (Suppl. Table 27 ). In multivariate analyses, as summarised by the authors ‘the standard error of the log odds ratio (asymmetry coefficient) was the dominant variable. Coefficients of other variables, including study quality, were attenuated and became non-significant’ (Shang [ 9 ], pp.929-930).

The MAs conducted by Mathie (2014 [ 10 ] and 2017 [ 11 ]) revealed no significant associations between ‘publication free of vested interest’ and effect estimates (both MAs, Suppl. Table 27 ).

Risk of bias of meta-analyses

According to our ROBIS [ 13 ] assessments, the risk of bias was low in three MAs (Linde 1997, Mathie 2014 & 2017 [ 6 , 10 , 11 ]) and high in three MAs (Linde 1998, Cucherat, Shang [ 7 , 8 , 9 ]) (Table 10 ). ROBIS assessments of each MA with our comments on individual items are presented in Additional file 1 .

AMSTAR [ 14 ] items 7 (list of excluded studies), 10 (funding sources for included studies) and 16 (conflict of interest of review authors) received the poorest ratings possible (0) for the first three MAs (Linde 1997 & 1998, Cucherat [ 6 , 7 , 8 ]) and the best ratings possible (1 or 2) in the most recent MAs (Mathie 2014 [ 10 ] and 2017 [ 11 ]). The MA conducted by Shang [ 9 ] had two ‘0’ ratings and one ‘1’ (0–2 possible) (Table 11 ).

Primary outcome of this systematic review

All trials with extractable data for meta-analysis.

Effect estimates—or for the MA conducted by Cucherat [ 8 ]: combined p values—for all trials with extractable data were reported in five MAs (not from Shang [ 9 ]). All analyses showed a significant positive effect of homoeopathy compared to placebo (Table 12 ).

Sample restriction to high-quality trials

Effect estimates for high-quality trials Data items / Primary outcome were available for four MAs (not for the MAs conducted by Linde (1998) [ 7 ] and Cucherat [ 8 ]). Three MAs (Linde 1997, Shang/Lüdtke, Mathie 2014 [ 6 , 9 , 10 , 32 ]) showed a significant positive effect of homoeopathy compared to placebo, and one MA (Mathie 2017) [ 11 ] showed no significant difference between homoeopathy and placebo (Table 12 ).

Secondary outcomes

Sensitivity analyses: sample restriction to trials fulfilling quality criteria.

Sample restriction to trials fulfilling 1 quality criterion

Sensitivity analyses with sample restriction to trials fulfilling 1 quality criterion were reported in four MAs [ 6 , 7 , 10 , 11 ], with a total of 12 analyses based on 7 different single quality components (‘explicitly randomised’, ‘adequate concealment of random allocation’, ‘double-blinding stated’, ‘follow-up adequate/complete’, ‘main outcome predefined’, ‘Medline-listed’, ‘free of [funding-related] vested interest’). Of the 12 analyses, 11 showed a significant positive effect of homoeopathy compared to placebo (Suppl. Table 28 ).

Sample restriction regarding 2–4 quality components

Sensitivity analyses with sample restriction regarding 2–4 quality components were reported in 3 MAs. In the MA conducted by Linde (1997) [ 6 ], trials with a Jadad score > 2 had a significant positive effect of homoeopathy. In the MA conducted by Linde (1998) [ 7 ], the effect estimate for trials fulfilling 3 criteria (Medline-indexed + double-blind + “no other obvious relevant flaws”) did not differ significantly from placebo. In the MA conducted by Shang [ 9 ] and analysed by Lüdtke [ 32 ], the effect estimates for high-quality trials (interpreted as based on 3 components) fulfilling one additional criterion (Medline-listed, English language, Intention-to-treat principle, respectively) analysed with random-effects or meta-regression did not differ significantly from placebo (Suppl. Table 29 ).

Sample restriction regarding ≥ 5 quality components

Sensitivity analyses with sample restriction regarding 5 or more quality components were reported in 3 MAs with one analysis each. In the MA conducted by Linde (1997) [ 6 ], trials with an internal validity score > 4.5 ( n  = 7 components) had a significant positive effect of homoeopathy. In the MAs conducted by Mathie (2014 and 2017) [ 10 , 11 ], high-quality trials and A- and B-rated trials (trials rated as having low or uncertain risk of bias in all seven domains of Cochrane RoB), respectively, both sets in addition rated as free from publication-rated vested interests ( n  = 8 components each) showed no significant effect differences between homoeopathy and placebo (Suppl. Table 29 ).

Cumulative MA with stepwise removal of trials by risk-of-bias ratings

Cumulative MA with stepwise removal of trials by risk-of-bias ratings was performed in four MAs, including three (Linde 1997/1999, Mathie 2014 and 2017 [ 6 , 7 , 10 , 11 ]) using incremental removal according to interval-scaled instruments and one (Cucherat [ 8 ]) using a rank-ordered scale. The scales used by Linde (1997/1999 [ 6 , 30 ]) were additive (sum of score points), while the remaining scales were in part [ 10 , 11 ] or fully [ 8 ] hierarchically constructed.

In the MA conducted by Linde (1997/1999) [ 6 , 30 ], two cumulative MAs were performed: (1) For the Jadad score (range 0–5, 5 points indicating highest possible quality), a significant positive effect of homoeopathy was retained with a score of 5 points ( n  = 10 trials). For the internal validity score (range 1–7, 7.0 points indicating highest possible quality), significant positive effects of homoeopathy were retained up to 6.5 points ( n  = 7 trials), while no significant difference was observed for 7.0 points ( n  = 5 trials) (Suppl. Table 31 ).

In the MA conducted by Cucherat [ 8 ], a cumulative MA was performed using a rank-ordered scale, with step 4 indicating the highest possible quality assessed by the authors. Significant positive effects of homoeopathy were retained up to step 3 (double-blind + dropout rate < 10%, n  = 9 trials), while no significant difference was observed at step 4 (double-blind + dropout rate < 5%, n  = 5 trials) (Suppl. Table 33 ).

In the MAs conducted by Mathie (2013/2014 [ 10 , 28 ] and Mathie (2017) [ 11 ]), one cumulative MA was performed based on the Cochrane RoB tool (2011 version), with 7 items for which the risk of bias was rated as low (A), uncertain (B) or high (C). Trials with 7 × A were rated A, trials with 7x (A or B) were rated as B and trials with ≥ 1 × C were rated as C. In addition to this hierarchical classification, Mathie counted the number of A- and B-rated items for each trial, allowing for a more differentiated assessment.

In the MA conducted by Mathie (2014) [ 10 ], significant positive effects of homoeopathy were retained throughout the range up to high-quality trials (criteria in Sect. 3.2.2.5, n  = 3 trials) (Suppl. Table 31 ).

In the MA conducted by Mathie (2017) [ 11 ], significant positive effects of homoeopathy were retained up to two steps below high-quality trials ( n  = 14 trials), while no significant difference was observed at one step below high-quality trials ( n  = 13 trials) (Suppl. Table 32 ).

Supplementary analyses: risk of bias across trials (meta-bias)

Statistical adjustment for possible publication bias or other small trial effects

Statistical adjustment for possible publication bias or small trial bias—without any additional sensitivity analysis—was performed for two MAs (Linde 1997, Mathie 2017 [ 6 , 11 ]). In both cases, a significant positive effect of homoeopathy was retained after adjustment (Suppl. Table 34 ).

Sensitivity analyses with sample restriction to trials with a higher sample size

Sample restriction to trials with a higher sample size—without any additional sensitivity analysis—was performed for two MAs (Mathie 2014 and 2017) [ 10 , 11 ]. In both cases, the sample was restricted to trials with a sample size above the median, and in both cases, a significant positive effect of homoeopathy was retained (Suppl. Table 30 ).

Combined sensitivity analyses

Sample restriction regarding methodological quality + restriction to trials with a higher sample size was performed in two MAs (Shang [ 9 ]: high-quality trials + “large” trials; Mathie (2017) [ 11 ]: A- and B-rated trials + sample size above the median for all trials). In both cases, no significant difference between homoeopathy and placebo was observed (Suppl. Table 35 ).

Lüdtke [ 32 ] performed a cumulative analysis, varying the cut-off point for ‘large trials’ among the 21 high-quality trials included in the MA conducted by Shang [ 9 ]: a significant effect of homoeopathy compared to placebo was observed with a sample restriction to the 20, 19, 18, 16, 15 and 14 largest trials, respectively, while no significant difference was found with a sample restriction to the 17, 13 and 1–12 largest trials, respectively [ 32 ].

In the MA conducted by Shang [ 9 ], meta-regression analyses of ‘predicted effect in trials as large as the largest trials included in the study’ (without further specification; we assume the authors meant the intercept from the regression of odds ratios on the standard error) showed no significant difference between homoeopathy and placebo (Additional file 2 ).

Tests for interactions

Subgroup interactions were analysed in 3 MAs (Shang, Mathie 2014 and 2017 [ 9 , 10 , 11 ]). No significant associations were found for duration of follow-up, indication type (acute/chronic/prophylaxis) or type of homoeopathy (4 groups) (Suppl. Table 36 ).

Effect estimates

Effect estimates were analysed in a total of 23 subgroups, pertaining to indication (acute or chronic), type of homoeopathy ( n  = 10 subgroups), homoeopathic potency ( n  = 6) and outcome metric in trials ( n  = 5) (Suppl. Table 37 ). Of these 23 analyses, 21 showed a significant positive effect of homoeopathy, while two showed no significant difference from placebo: potencies < 12C in the MA conducted by Mathie (2014) [ 10 ], which was restricted to I-HOM; homoeopathic combination products in the MA conducted by Mathie (2017) [ 11 ] (a category only described and evaluated in this MA, cf. Suppl. Table 10 ). No subgroup analyses were performed on patient age groups.

Statistical homogeneity/heterogeneity, funnel plot inspection and related tests

Neither statistical homogeneity/heterogeneity nor funnel plot inspection with related statistical tests were reported in any subgroup as defined in Section ' Methods / Subgroup analyses '. However, withstanding that Mathie (2014) [ 10 ] and Mathie (2017) [ 11 ] were part of one MA programme, these two MAs can be considered subgroup analyses pertaining to the type of homoeopathy. For I-HOM (Mathie 2014 [ 10 ], n  = 22 trials), neither heterogeneity nor FPA was found. For NI-HOM (Mathie 2017 [ 11 ], n  = 54 trials), significant heterogeneity as well as FPA were found (cf. Section ' Assessments of bias and heterogeneity ', above).

Of the 23 subgroup analyses, 15 were specified in a prepublished protocol (Mathie 2014 and 2017 [ 10 , 11 ]), while 8 analyses—albeit from MAs based on predefined protocols—were not explicitly stated to be prespecified (Linde 1997 [ 6 ], Cucherat 2000 [ 8 ]). Of the 15 former analyses, 14 showed a significant positive effect of homoeopathy, while 1 did not (Mathie 2014 [ 10 ], see above).

Additional data: Shang [ 9 ]

Data for the comparison of MAs of placebo-controlled trials of homoeopathic and conventional treatment in Shang [ 9 ] are presented in Additional file 2 .

Additional data: Gartlehner [ 34 ]

After literature searches and data collection for this SR had been completed, an additional subgroup analysis of the MA conducted by Mathie (2017) [ 11 ] was published, which we decided to include, as it concerned an item that had not been analysed for any of the MAs: trial registration (Gartlehner 2022) [ 34 ]).

The 54 trials included in the MA conducted by Mathie (2017) [ 11 ] were published in the period from 1976 to 2014, and 20 of those trials were published from 2002 to 2014. Of this group, Gartlehner et al. analysed 19 trials, stratified according to clinical trial registration, which had been available at ClinicalTrials.gov since 2000. A random effects MA showed a positive significant effect of homoeopathy compared to placebo in n  = 6 registered trials (SMD 0.53, 95% CI 0.20–0.87) and no significant difference from placebo in n = 13 unregistered trials (SMD 0.14, 95% CI − 0.07 to + 0.35). However, the between-group difference in effect estimates was not significant (meta-regression: SMD 0.39, 95% CI − 0.09 to + 0.87) [ 34 ]. It is not clear why trial #A93 of the MA conducted by Mathie (2017 [ 11 ], Lewith 2002, listed in Gartlehner [ 34 ], Supplement Table 3 as ‘not registered’) was not included in these analyses.

The proportion of registered trials was 100% ( n  = 3/3) among high-quality trials and 19% ( n  = 3/16) among the other trials (Suppl. Table 38 ).

Confidence in cumulative evidence

The assessment of confidence in cumulative evidence for research questions 1 and 2 (cf. Section ' Research questions ', above) according to the GRADE framework (cf. Section ' Confidence in cumulative evidence/Certainty assessment ') is presented in Additional file 3 . Conclusions are summarised in the following Sections:

Conclusion 1: Positive effect of homoeopathy beyond placebo?

The quality of evidence (high/moderate/low/very low) for significant positive effects of homoeopathy beyond placebo is moderate for ALL-HOM and NI-HOM and high for I-HOM.

If the data sources were restricted to MAs with a low risk of bias [ 6 , 10 , 11 ], the quality of evidence would be changed to high for ALL-HOM and remain high for I-HOM and moderate for NI-HOM.

The available data yield no support for the alternative hypothesis of no outcome difference between homoeopathy and placebo.

Conclusion 2: Common effect across different treatments and indications?

Different types of homoeopathic treatment.

The notion of a common positive effect is

supported for effects across different homoeopathy types, including different subtypes of NI-HOM,

supported for effects of I-HOM,

not supported for effects of NI-HOM.

As the MA of NI-HOM (Mathie 2017 [ 11 ]) comprised different indications treated with different homoeopathic products, the latter finding suggests that the effects of NI-HOM may differ across different indications and/or different homoeopathic products used. Such effect differences may include significant positive effects of NI-HOM as well as no significant difference between NI-HOM and placebo in different subgroups.

Different types of indications

The limited data available support the notion of a common positive effect of homoeopathy for acute as well as chronic indications. The issue of effect differences among different diagnoses or diagnosis groups is outside the scope of this SR.

Main findings

In this first SR of MAs of placebo-controlled randomised trials of homoeopathy for any disorder in humans, homoeopathy had a significant positive effect compared to placebo for all eligible trials in 5 of 5 evaluable MAs and for high-quality trials in 3 of 4 MAs. Assessed by the GRADE system, the quality of evidence for positive effects (high/moderate/low/very low) was high for I-HOM and moderate for ALL-HOM as well as for NI-HOM. There was no support for the alternative hypothesis of no outcome difference between homoeopathy and placebo.

Strengths and limitations

This systematic review as such.

The strengths of this SR include a detailed, prepublished PRISMA-P [ 12 ] -compliant protocol with two focused research questions, comprehensive presentation of findings, the use of well-established assessment instruments (ROBIS [ 13 ], GRADE [ 20 ]) and adherence to standard reporting guidelines (PRISMA 2020 [ 27 ]).

The scope of this review had two clear limitations: it was restricted to efficacy in placebo-controlled trials and did not address results for specific indications or indication groups.

We used the GRADE system to assess confidence in the cumulative evidence and found it very helpful. Nonetheless, there are three relevant differences between the GRADE approach and this SR: (1) The GRADE approach is indication- and outcome-specific, while we studied MAs with effect estimates for trials with different indications and outcomes. (2) The GRADE framework is tailored to comparative effectiveness, while we assessed MAs of placebo-controlled trials. (3) The GRADE assessment of confidence in cumulative evidence refers to the magnitude of effects, while our research question concerned the existence of significant effects of homoeopathy beyond placebo (yes/no). Accordingly, our conclusions on confidence in the cumulative evidence may not be directly comparable to those of other SRs in the same research field.

The meta-analyses included in the review

According to the ROBIS framework, the risk of bias of the six included MAs was rated as low for Linde (1997) [ 6 ], Mathie (2014 [ 10 ]) and Mathie (2017 [ 11 ]) and high for Linde (1998) [ 7 ], Cucherat [ 8 ] and Shang [ 9 ].

A particular feature of the MA conducted by Linde (1997/1999 [ 6 , 30 ]) was the detailed assessment of associations between risk of bias and effect estimates in the second paper. Low risk of bias.

The MA conducted by Linde (1998) [ 7 ] was an update on the MA conducted by Linde (1997) [ 6 ] but restricted to I-HOM. Compared to the 1997 MA, the 1998 MA had a more descriptive and discursive outlook. Having relied on formal and statistical assessments in the 1997 paper, in 1998, the authors made conscious use of subjective judgement, also for the assessment of the risk of bias. Some of these features are not reflected in the ROBIS framework. High risk of bias.

The MA conducted by Cucherat [ 8 ] had two particular design features: Because of the expected heterogeneity, p value combination was used instead of effect estimation. While other MAs have used a hierarchical algorithm for the selection of outcomes for MAs, the authors restricted eligibility to trials with a single primary outcome. This led to a substantial loss of information that was unaccounted for in the discussion. High risk of bias.

The MA conducted by Shang [ 9 ] had an additional comparison between placebo-controlled HOM and CON trials matched for indication and outcome type. Regrettably, the only published effect estimates were those of small subsamples from extreme scenario analyses with severely compromised matching. The authors aimed to demonstrate that effects of homoeopathy could be due to bias. Thereby, they strongly relied on funnel plot-based analyses that had been developed by the senior author [ 43 ]. Their approach and the published results were marred by an underlying circular logic, which can be expressed as follows: ‘We assume homoeopathy doesn’t work and found FPA, which may be due to publication bias and small study bias. Admittedly, there are many causes for FPA other than bias, and we know that the funnel plot-based approach cannot prove that results are due to bias (as conceded elsewhere [ 36 ]). However, because we assume homoeopathy doesn’t work anyway, we feel confident that the FPA in our MA was due to bias.’ High risk of bias .

The MAs conducted by Mathie (2014 [ 10 ] and 2017 [ 11 ]) were a predefined MA pair, covering individualised (2014) and nonindividualised (2017) homoeopathy. The problem of persistent heterogeneity and FPA in the earlier MAs could now be clearly localised to the NI-HOM trials, while the I-HOM trials had neither heterogeneity nor FPA. The work also benefited from advances in methodology, guidance and reporting standards. Low risk of bias for both MAs.

The evidence generated in this systematic review

The evidence generated in this SR is based on 6 MAs, of which the risk of bias was rated as low for 3 and high for 3. If the data were restricted to the 3 MAs with a low risk of bias, the quality of evidence would be rated high for ALL-HOM and I-HOM and moderate for NI-HOM (Additional file 3 ).

Compared with trials of nonhomoeopathic interventions, which were assessed with identical rating instruments, the methodological quality of the homoeopathy trials in the MAs of this SR was similar for the MAs conducted by Mathie (2014 and 2017 [ 10 , 11 ]) and higher for the MA conducted by Shang [ 9 ]. Significant associations between methodological quality and effect estimates were found in 12 of 24 analyses. After restricting the sample to high-quality trials according to predefined criteria, effect estimates were reduced [ 6 , 11 ] or increased [ 10 ], with 3 of 4 MAs showing significant effects of homoeopathy compared to placebo. When adding a 5 th MA (Cucherat [ 8 ]) to the assessment and applying the same high-quality criteria as in the 3-component model of Shang [ 9 ], 4 of 5 MAs showed significant benefit of homoeopathy.

As assessed by the GRADE system, the quality of evidence for positive effects (high/moderate/low/very low) was high for I-HOM and moderate for NI-HOM and ALL-HOM. In comparison, among 608 Cochrane reviews published from January 2013 to June 2014, the GRADE-assessed quality of evidence for the primary outcome was high in only 13% of reviews, moderate in 31%, low in 32% and very low in 24% [ 44 ]. In a randomised sample of Cochrane reviews up until 2021, 90% of 1567 GRADE-assessed interventions were not supported by evidence of high quality [ 45 ].

This SR had two limitations. (1) As this was a SR of MAs rather than of individual trials, the trials examined herein were limited to those included in the MAs. Thus, eligible trials published after 2011 and 2014 for I-HOM and NI-HOM, respectively, could not be included. (2) Differential effects of homoeopathy on different indications and patient groups were only assessed for acute and chronic indications and for adults and children, with very limited data available.

Interpretation of the results in the context of other evidence

According to this SR, homoeopathy can have positive effects beyond placebo on disease in humans. This is in accordance with laboratory experiments showing partially replicable effects of homoeopathically potentised preparations in physico-chemical [ 46 ], in vitro [ 47 ], plant-based [ 48 , 49 ] and animal-based [ 50 , 51 , 52 ] test systems.

Implications of the results for practice and policy

In contrast to frequent claims, the available MAs of homoeopathy in placebo-controlled randomised trials for any indication show significant positive effects beyond placebo. Compared to other medical interventions, the quality of evidence for efficacy of homoeopathy was similar or higher than for 90% of interventions across medicine [ 45 ]. Accordingly, the efficacy evidence from placebo-controlled randomised trials provides no justification for regulatory or political actions against homoeopathy in health-care systems.

Recommendations for future research

For I-HOM, an update of the MA conducted by Mathie (2014 [ 10 ]) would be warranted to reassess efficacy evidence after inclusion of trials published after 2011. For NI-HOM, the results of the MA conducted by Mathie (2017 [ 11 ]) with 54 trials were heterogeneous. Accordingly, future research on the efficacy of NI-HOM should focus on specific nonindividualised forms of homoeopathic therapy or specific interventions therein for specific indications. Recommendations for comparative effectiveness research on homoeopathy are beyond the scope of this review.

Availability of data and materials

The complete protocol is permanently available on the website of the institution of the corresponding author: https://www.ifaemm.de/Abstract/PDFs/SMAP-HOM_Protocol_2020_11_25.pdf . All data extracted from the MA publications as well as analyses performed by the authors of this SR are presented in Tables 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 and Additional files 1 , 2 , 3 , 4 , 5 .

Amendments, additional analyses and data

Amendments to the protocol from 25 Nov. 2020 are listed and explained in Suppl. Table 39 . Additional analyses and data, not described in the protocol, are listed and explained in Suppl. Table 40 .

Duplicate publications

The content of the manuscript has not been published or submitted for publication elsewhere.

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Acknowledgements

We thank Gunver S. Kienle (GSK) for the assistance with data extraction and assessment of risk of bias of the MAs.

Open Access funding enabled and organized by Projekt DEAL. Funding specifically for this SR was provided by Christophorus-Stiftung (No. 393 CST), Stiftung Marion Meyenburg (Date 24.09.2020), Dr. Hauschka Stiftung (Date 16.11.2020) and Gesellschaft für Pluralität im Gesundheitswesen (Dates 11.06.2021, 22.06.2021). General funding for IFAEMM was provided by the Software-AG Stiftung (SE-P 13544). The funders had no influence on the writing of the protocol or on the planning, conduct and publication of this SR.

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HJH: Literature search and screening, assessment of literature records for inclusion, data collection, assessment of risk of bias of MA, manuscript drafting and revision. AG: Literature search and screening, assessment of literature records for inclusion, data collection, coding of indications, additional analyses, manuscript drafting and revision. KvA: Manuscript drafting and revision. DSR: Manuscript drafting and revision. HK: Data collection, manuscript drafting and revision. All authors of the manuscript have read and agreed to its content and are accountable for all aspects of the accuracy and integrity of the manuscript in accordance with ICMJE criteria. All authors have approved the manuscript for submission.

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Competing interests

In the past 3 years, HJH has received research grants from two manufacturers of anthroposophic medicinal products (Wala Heilmittel GmbH, Bad Boll/Eckwälden, Germany; Weleda AG, Arlesheim Switzerland). Anthroposophic medicine is not based on the homoeopathic simile principle or on drug provings, but some anthroposophic medicinal products are potentized. The two manufacturers had no involvement with the present SR. Anthroposophic medicinal products were not part of the intervention in any of the trials evaluated in the MAs of this SR (Suppl. Table 15 ). DSR has received a development grant from Heel GmbH (manufacturer of homoeopathic products) for online training in case report writing. AG, KvA and HK declare that they have no competing interests.

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Supplementary Information

Additional file 1. .

Risk of bias of meta-analyses: ROBIS assessments of individual items with comments by the authors of this systematic review.

Additional file 2. 

 Additional data on the comparison of MA of placebo-controlled trials of homoeopathic and conventional treatment, respectively in Shang (2005).

Additional file 3. 

 Confidence in cumulative evidence for research questions 1 and 2, assessed according to the GRADE framework.

Additional file 4. 

Supplementary Tables.

Additional file 5. 

PRISMA 2020 flow diagram for updated systematic reviews which included searches of databases, registers and other sources.

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Hamre, H.J., Glockmann, A., von Ammon, K. et al. Efficacy of homoeopathic treatment: Systematic review of meta-analyses of randomised placebo-controlled homoeopathy trials for any indication. Syst Rev 12 , 191 (2023). https://doi.org/10.1186/s13643-023-02313-2

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A systematic review of systematic reviews of homeopathy

Homeopathy remains one of the most controversial subjects in therapeutics. This article is an attempt to clarify its effectiveness based on recent systematic reviews. Electronic databases were searched for systematic reviews/meta-analysis on the subject. Seventeen articles fulfilled the inclusion/exclusion criteria. Six of them related to re-analyses of one landmark meta-analysis. Collectively they implied that the overall positive result of this meta-analysis is not supported by a critical analysis of the data. Eleven independent systematic reviews were located. Collectively they failed to provide strong evidence in favour of homeopathy. In particular, there was no condition which responds convincingly better to homeopathic treatment than to placebo or other control interventions. Similarly, there was no homeopathic remedy that was demonstrated to yield clinical effects that are convincingly different from placebo. It is concluded that the best clinical evidence for homeopathy available to date does not warrant positive recommendations for its use in clinical practice.

Introduction

Homeopathy is a therapeutic method using preparations of substances whose effects when administered to healthy subjects correspond to the manifestations of the disorder (symptoms, clinical signs, pathological states) in the individual patient. The method was developed by Samuel Hahnemann (1755–1843) and is now practised throughout the world [ 1 ]. Homeopathy is based on two main principals [ 1 – 3 ]. According to the ‘like cures like’ principle, patients with particular signs and symptoms can be helped by a homeopathic remedy that produces these signs and symptoms in healthy individuals. According to the second principle, homeopathic remedies retain biological activity after repeated dilution and sucussion even when diluted beyond Avogadro's number.

Few therapies have attracted more debate and controversy than homeopathy. Throughout its 200-year history, critics have pointed out that its very principles fly in the face of science, while proponents have maintained that it is narrow minded to reject an overtly helpful approach to healing only because one cannot explain how it might work [ 2 ]. Similarly, proponents have quoted seemingly rigorous trials that suggest efficacy, while critics had little trouble citing equally rigorous studies that implied the opposite.

The existence of contradicting evidence is not unusual in therapeutics. One solution to resolve such contradictions is to conduct systematic reviews and meta-analyses of rigorous studies. In 1997, Linde et al. [ 3 ] did just that. The conclusions of this technically superb meta-analysis expressed the notion that homeopathic medicines are more than mere placebos. The authors also stated that no indication was identified in which homeopathy is clearly superior to placebo. Despite this and other caveats, homeopaths worldwide celebrated this publication as the ultimate proof of their treatment. Since then, a flurry of interest in homeopathy has emerged, and several further systematic reviews have been published. This article is an attempt to critically evaluate all such papers published since 1997 with a view to defining the clinical effectiveness of homeopathic medicines.

Literature searches were carried out in the following databases: Medline (via Pubmed), Embase, Amed, CISCOM (from inception to October 2001). The search terms used were homeopath . . . , homoeopath . . . , clinical trial, meta-analysis, systematic review, efficacy, effectiveness. In addition, other experts in the field ( n  = 5) were consulted and my own, extensive files were studied. The bibliographies of all articles thus located were scanned for further relevant references. No language restrictions were applied.

Only systematic reviews (including meta-analyses) of controlled clinical trials of homeopathy with human patients or volunteers were included. Non-systematic reviews, overviews, clinical trials and reviews of non-clinical investigations were excluded. All articles were evaluated by the present author. The following information was extracted from the original articles: inclusion/exclusion criteria, total sample size, assessment of methodological quality, results of meta-analyses, overall conclusion of the authors.

Six re-analyses of Linde et al. 's original meta-analysis [ 3 ] were located [ 4 – 9 ]. Table 1 summarizes key data from these publications. The results of these re-analyses demonstrate that the more rigorous trials are associated with smaller effect sizes which, in turn, render the overall effect insignificant [ 5 , 6 , 8 ]. One re-analysis suggests that the initial positive meta-analytic result [ 3 ] was largely due to publication bias [ 9 ], a notion that had been considered by the original authors but was rejected by them. Most notably, perhaps, the authors of the original meta-analysis [ 3 ] concluded that their re-analysis ‘weakened the findings of their original meta-analysis’[ 6 ]. Collectively these re-analyses imply that the initial conclusions of Linde et al. [ 3 ] was not supported by critical evaluation of their data.

The systematic review by Linde et al. [ 3 ] and its subsequent re-analyses.

RCT = randomized clinical trial, OR = odds ratio,

In addition, 11 independent systematic reviews were located [ 10 – 20 ]. Table 2 summarizes key data from these publications. Collectively the findings do not provide strong evidence in favour of homeopathy. With the exception of postoperative ileus [ 10 ] and influenza [ 17 ] (see below) there is no condition for which homeopathy is convincingly effective [ 10 , 11 , 13 , 18 – 20 ]. Arnica, the most frequently tested homeopathic remedy, is not demonstrably different from placebo [ 12 , 15 ]. One homeopathic remedy (oscillococcinum) was found to be superior to placebo as a treatment and prevention of influenza but the effect size was small and therefore of debatable clinical relevance [ 17 ]. Moreover, the volume of the evidence for oscillococcinum is small and therefore not fully conclusive. Our systematic review of various homeopathic medicines for postoperative ileus produced an overall positive result [ 10 ]. Yet several caveats need to be taken into account, most importantly the fact that the definitive study designed as a multicentre trial to replicate several of smaller studies failed to demonstrate a positive effect [ 10 ]. One independent review of all homeopathic RCTs regardless of indication or type of remedy yielded a positive result [ 16 ]. Yet the statistical approach to generate this result was of debatable validity and the authors are keen to point out that their overall result is weak and not sufficient for definitive recommendations.

Independent systematic reviews of homeopathy.

RCT = randomized clinical trial, OR = odds ratio, RR = relative risk.

Collectively these data do not provide sound evidence that homeopathic remedies are clinically different from placebos. However, the present analysis has several limitations that should be kept in mind when interpreting its conclusions. Even though a thorough search strategy was adopted, there is no absolute guarantee that all relevant articles were located. Many of the included reviews are from the present author's team, and this could have introduced bias. Finally the validity of conducting a systematic review of systematic reviews has its limitations; most importantly it does not create any information that was not available before.

The clinical evidence summarized above is not dissimilar from the preclinical data. Vickers recently conducted a systematic review of preclinical investigations of homeopathy [ 21 ]. Even though 120 papers could be included in the evaluation, this author found that lack of independent replications, serious methodological flaws, and contradictory results precluded any firm conclusion. This systematic review therefore casts considerable doubt on one of the main assumptions of homeopathy, namely that homeopathic remedies retain biological activity even when diluted beyond Avogadro's number (see above).

Perhaps the most recent trial evidence, not yet included in systematic reviews, helps clarify the question whether homeopathic remedies are more than placebos. Since the publication of the systematic reviews, both positive,  e.g.  [ 22 – 24 ].  as  well  as  negative  clinical  trials e.g. [ 25 – 27 ] have emerged. It seems therefore unlikely that these new findings would substantially change the results of any of the systematic reviews were they to be up-dated.

The recent observation of solute clusters in highly diluted water has been interpreted by several homeopaths as increasing the plausibility of homeopathy [ 28 ]. This novel finding requires independent replication. Furthermore, this observation (if confirmed) does not lend itself to explaining how solute clusters could have any effects on human health. Thus both the clinical evidence and the basic research underpinning homeopathy remain unconvincing.

If one accepts this conclusion, one might ask what its implications for future research may be. Two opposing views exist. One holds that the definitive trial of homeopathy should be conducted to once and for all settle the question [ 29 ]. The other states that ‘new trials . . . are no longer a research priority’ and advocates ‘outcome studies to evaluate the individual treatment decisions . . . and compare outcomes to orthodox treatment’[ 30 ]. Such outcome studies exist. They are burdened with a myriad of methodological weaknesses, most importantly a proneness to selection bias, and usually report findings which are convincingly in favour of the homeopathic approach [ 31 ]. This could imply that the individualized, empathetic and time-intensive approach most homeopaths adopt to healthcare yields good clinical results. This emphasizes the importance of the therapeutic encounter and is in accordance with a wealth of information in this area [ 32 ]. It does not, however, answer the ‘placebo question’. I insist that this question does require an answer – for the sake of scientific honesty and possibly in the name of clinical progress.

In conclusion, the hypothesis that any given homeopathic remedy leads to clinical effects that are relevantly different from placebo or superior to other control interventions for any medical condition, is not supported by evidence from systematic reviews. Until more compelling results are available, homeopathy cannot be viewed as an evidence-based form of therapy.

Conflict of interest : The author is a trained homeopath; he has no financial interests in this area.