"John Ioannidis" from_date:2012

ScholarFootnotesContributors The author had the idea for the analysis and wrote the manuscript and is the guarantor.Funding METRICS has been supported by a grant from the Laura and John Arnold Foundation. The work of John Ioannidis has been supported by an unrestricted gift from Sue and Bob O’Donnell.Competing interests None declared.Provenance and peer review Not commissioned; externally peer reviewed.Other content

Are most published research findings false in a continuous universe? Diagnostic screening models for the interpretation of null hypothesis significance test (NHST) results have been influential in highlighting the effect of selective publication on the reproducibility of the published literature, leading to John Ioannidis' much-cited claim that most published research findings are false

, Montgomery SA, Nil R, Lader M. Discontinuation symptoms in depression and anxiety disorders. International Journal of Neuropsychopharmacology. 2007 Feb 1;10(1):73-84.Cook C, Heath F, Thompson RL. A meta-analysis of response rates in web-or internet-based surveys. Educational and psychological measurement. 2000 Dec;60(6):821-36.Mayor S. (2016) Five minutes with… John Ioannidis. BMJDavies, J et al. (2018

All science should inform policy and regulation. In the context of a recent proposal to exclude research from consideration at the Environmental Protection Agency, John Ioannidis points out that "perceived perfection is not a characteristic of science, but of dogma" and envisions how governments can promote a standard of openness in science.

Evidence-based medicine was bound to fail: a report to Alvan Feinstein. John Ioannidis has provided a lucid account, in the form of a report to David Sackett, of how evidence-based medicine (EBM) was hijacked to serve vested interests: major randomized controlled trials are largely done by and for the benefit of the industry; meta-analyses and guidelines are flooded with conflicts of interest

? And would we be better off to demand a test of proof that is ten times stronger? In fact this would make surprisingly little difference, as John Ioannidis explains in this classic essay, which is open-access and well worth downloading.JAMA Intern MedMar 2018Treating postmenopausal vulvovaginal symptomsI can’t do better than quote the Key Points section of this trial“302 postmenopausal women with moderate

Cochrane famously once did in front of an audience of cardiologists? No, I haven’t: usual care was a lot more effective than regular badgering. There is a lesson in here somewhere. Precisely how abnormal are you?You’re not normal: get used to it. The long-predicted day when enough tests can be done to ensure universal abnormality has been reached, even without invoking genomics. But John Ioannidis

Cochrane famously once did in front of an audience of cardiologists? No, I haven’t: usual care was a lot more effective than regular badgering. There is a lesson in here somewhere. Precisely how abnormal are you?You’re not normal: get used to it. The long-predicted day when enough tests can be done to ensure universal abnormality has been reached, even without invoking genomics. But John Ioannidis

in their wake.In the last few weeks I’ve been pottering away on a post of tips for gauging the value of a systematic review/meta-analysis. And so I was particularly interested in a group of these that appeared this month. The first came from Sylvie Chevret, Niall D. Ferguson, and Rinaldo Bellamo. The second, fromMorten Hylander Møller, John Ioannidis, and Michael Darmon. That paper relied on data from a previous

were The BMJ and PLOS Medicine. Six years on, they come under friendly scrutiny from John Ioannidis and his team. Of 37 randomised controlled trials published in the two journals, 17/37 satisfied the definition of data availability and 14 of the 17 were fully reproduced on all their primary outcomes when the data were reanalyzed. This was never going to be an overnight revolution. But it is a start

to nudge some important reforms along.It’s a child of the “research waste” agenda kicked off by a 2009 paper in which Iain Chalmers and Paul Glasziou estimated 85% of health research was a waste of time. In some ways that was a later generation of John Ioannidis’ 2005 “most published research findings are false” provocation. (I wrote about that here.) The “research waste” banner swings over the same

además sus trampas y atajos, desenmascarar estos es precisamente el objetivo del artículo de John Ioannidis, que con el gráfico título de “Una guía del usuario para inflar y manipular los factores de impacto”se publica en la revista European Journal of Clinical Investigation. En este articulo se pone de manifiesto los trucos que utilizan los directores de revistas médicas para aumentar el factor de

to chemotherapy!) EBM (Evidence Based Medicine) is essentially a scam as it relies on fraudulent studies. As I noted previously, John Ioannidis’ 2005 article “Why Most Published Research Findings Are False” shows intentional fraud behind pharmaceutical “research” (choke) and how the public and physicians have been hoodwinked into believing that dangerous drugs/devices are the solution for just about every ill

Why Most Clinical Research Is Not Useful. John Ioannidis argues that problem base, context placement, information gain, pragmatism, patient centeredness, value for money, feasibility, and transparency define useful clinical research. He suggests most clinical research is not useful and reform is overdue.

is Harlan Krumholz, who with Rod Hayward in 2012-3 persuaded the American College of Cardiology/American Heart Association to adopt a risk-based rather than a lipid-level-based approach to the use of statins. Nonetheless the title of his viewpoint is “Treatment of Cholesterol in 2017”. I won’t try to explain: everybody should read this piece for themselves.Nightingale number two is John Ioannidis, whose

by John Ioannidis, entitled Why Most Published Research is False, uses mathematical modelling to show that the factors we have described here contribute far more to the uncertainty of a specific, scientific result than the alpha level. [8]We understand the desire for patients, with life threatening cancers and few therapeutic options, to attempt drugs that only possibly provide meaningful benefits

of those clinical biomarker studies that are a dime a dozen, particularly in abstract form. Inflammatory markers are a favorite used in this type of study. As John Ioannidis has shown, such studies are frequently wrong. Moreover, they don't reach the next step, which is to show actual concrete health benefits caused by changing the biomarkers measured. This is tricky enough to do in cancer, where overall

. A variety of techniques for measuring gene expression were used as well, from just using reverse transcriptase polymerase chain reaction (RT-PCR) to examine two to twenty-three genes to using Affymetrix or Illumina cDNA microarrays, to using next generation sequencing methods like RNASeq. Of course, as we've learned from John Ioannidis, reproducibility is a major problem in whole genome gene expression