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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| John Ioannidis | 2/5 | https://en.wikipedia.org/wiki/John_Ioannidis | reference | science, encyclopedia | 2026-05-05T03:42:37.127948+00:00 | kb-cron |
=== Meta-analysis === Ioannidis has developed and popularized several methods for meta-analysis and has made several conceptual advances in this field. These include methods for assessing heterogeneity and its uncertainty, methods for meta-analysis involving multiple treatments, methods and processes for umbrella reviews, and several approaches to identifying bias and adjusting the results of meta-analyses for bias, such as publication bias and reporting bias resulting in funnel-plot asymmetry. He has also alerted about the misuse and misinterpretation of bias tests. Along with David Chavalarias, he catalogued 235 biases across the entire publication record of biomedical research. Ioannidis has been critical of flawed, misleading and redundant meta-analyses, estimating that few meta-analyses in medicine are both bias-free and clinically useful. He has performed empirical evaluations of the concordance of results between meta-analyses and large trials and between randomized trials and non-randomized studies.
=== Evidence-based medicine === Ioannidis has been one of the strong proponents and earlier advocates of evidence-based medicine. However, he has alerted that, over the years, as evidence-based medicine acquired more prominence and influence, it was hijacked to serve other agendas that are often biased. In an essay written to honor his late mentor David Sackett, he stated that:
Influential randomized trials are largely done by and for the benefit of the industry. Meta-analyses and guidelines have become a factory, mostly also serving vested interests. National and federal research funds are funneled almost exclusively to research with little relevance to health outcomes. We have supported the growth of principal investigators who excel primarily as managers absorbing more money. Diagnosis and prognosis research and efforts to individualize treatment have fueled recurrent spurious promises. Risk factor epidemiology has excelled in salami-sliced, data-dredged articles with gift authorship and has become adept to dictating policy from spurious evidence. Under market pressure, clinical medicine has been transformed to finance-based medicine. In many places, medicine and health care are wasting societal resources and becoming a threat to human well-being. Science denialism and quacks are also flourishing and leading more people astray in their life choices, including health. Evidence-based medicine still remains an unmet goal, worthy to be attained. He has described four inter-related problems that create what he calls the Medical Misinformation Mess:
First, much published medical research is not reliable or is of uncertain reliability, offers no benefit to patients, or is not useful to decision makers. Second, most healthcare professionals are not aware of this problem. Third, they also lack the skills necessary to evaluate the reliability and usefulness of medical evidence. Finally, patients and families frequently lack relevant, accurate medical evidence and skilled guidance at the time of medical decision-making. He has supported these views by contributing to a meta-epidemiological study which found that only 1 in 20 interventions tested in Cochrane Reviews have benefits that are supported by high-quality evidence and a related study showing that the quality of this evidence does not seem to improve over time.
=== Statistical methods and inference === Ioannidis has made methodological and conceptual contributions to the debates surrounding the use and misuse of statistical methods and inference. He has been an advocate of the approach to redefine statistical significance by requesting more stringent statistical significance thresholds; he has proposed and empirically validated stringent thresholds for genome-wide significance in genetics; and has been critical of the approach to entirely abandon statistical significance.
=== Reporting guidelines === Ioannidis has contributed to several influential guidelines for reporting different types of research, such as PRISMA for meta-analyses, TRIPOD for multivariable prognostic and diagnostic models, and others on clinical trials and observational research. He is the lead author of the CONSORT for harms, a guideline that provides guidance on how to properly report on harms in randomized trials and has contributed to PRISMA for harms, a guideline for reporting of harms in meta-analyses.
=== Genetic and molecular epidemiology === Ioannidis was one of the first to advocate the use of meta-analysis in genetic epidemiology to assess replication and the incorporation of meta-analysis in large-scale consortia of multiple investigators performing genome-wide association studies. He led and contributed to many such efforts in diverse areas of genetic epidemiology and in other areas of molecular epidemiology.
=== Nutrition === Ioannidis has been critical of nutritional epidemiology research practices and has recommended reforms to improve the credibility of research in the field. By means of empirical reviews, he has highlighted that there are studies suggesting that almost every nutrient is associated with cancer risk, which is an implausible situation He has also suggested that more attention is needed for proper disclosures of both financial and non-financial conflicts of interest in nutrition research. He also co-authored the DIETFITS randomized trial that showed no difference between a low-fat and a low-carb diet.
=== Association studies and big data === In an effort to improve the credibility of research on risk factors, Ioannidis has proposed that exposure-wide or environment-wide association studies should be performed and he has outlined the similarities and differences between such studies and genome-wide association studies in genetics. By assessing all risk factors together instead of one at a time, this practice aims to reduce selective reporting and publication bias. He has also advocated for the use of large national population databases with systematically collected data to minimize bias and improve yield of trustworthy discoveries. He has worked on the potential uses of such approaches in big data and artificial intelligence.
=== Psychiatry === Ioannidis has performed critical assessments of the evidence behind mental health interventions (pharmacotherapy and psychotherapy). He co-authored a network meta-analysis on more than 500 randomized trials of anti-depressants showing a modest benefit from these medications for major depression. He has identified the potential for sponsorship bias in meta-analyses in mental health and has empirically assessed the totality of meta-analyses on mental health interventions, estimating that beneficial effects do exist, but they tend to be modest and thus a research agenda is needed to identify more effective interventions.