Interpreting network #MetaAnalysis (NMA) to decide the best treatments is challenging. #GRADE’s guidance to deciding which are among the best, intermediate, and among the worst, in the @bmj.com, by far the best approach available.
pubmed.ncbi.nlm.nih.gov/33177059/
Posts by Gordon H. Guyatt
This study in @annalsofim.bsky.social highlights ethical problems in stopping trials early for benefit: seriously inflated overestimates of treatment effect violates ethical requirements of scientific validity and social value and leads to misguided patient choices.
pubmed.ncbi.nlm.nih.gov/17577007/
Spice-GRADE: methodological breakthrough for #GRADE. New methods showing how indirect evidence from epidemiological investigations of mechanistic causal pathways can complement direct evidence.
pubmed.ncbi.nlm.nih.gov/41802581/
Researchers sometimes interested in measuring agreement. Could be in physical examination, imaging evaluation, specimen evaluation or in measurement instruments such as risk of bias or guideline quality. This step-by-step guide to conducting such a study is THE BEST
pubmed.ncbi.nlm.nih.gov/19411507/
#Guidelines often rely on the intuition of panels and can therefore remain opaque to outside observers. This paper demonstrates how a decision-analytical framework provides an explicit and transparent integration of the best available evidence on benefits and harms
pubmed.ncbi.nlm.nih.gov/41558032/
Trade-offs in #vaginal vs #caesarian delivery: #SystematicReview vaginal delivery associated with almost twofold increase in the risk of developing leakage with exertion (Stress Incontinence), smaller increase on leakage in association with urgency.
pubmed.ncbi.nlm.nih.gov/26874810/
Compelling evidence that if clinical trialists interested in the impact of treatment on health-related #qualityoflife include only generic measures & fail to include responsive & valid disease-specific measures in their #RCTs, they risk missing the crucial signal.
pubmed.ncbi.nlm.nih.gov/10210235/
A crucial – though challenging – EBM concept is the distinction between baseline risk vs effect modification/subgroup analysis. After years struggling to teach, I discovered this exercise that succeeds brilliantly. Find it in the next to latest Core #GRADE FAQ.
www.clarityresearch.ca/frequently-a...
In network #MetaAnalysis (NMA) sparse networks sometimes yield bizarrely wide #ConfidenceIntervals. The solution we discovered after trying many alternatives perhaps surprising: switch from random effects to fixed effect.
pubmed.ncbi.nlm.nih.gov/30253217/
The #JAMA Users’ Guide to the Medical Literature is the best existing tutorial on adjusted analysis taking the learner from the basic principles to regression and contrasting with propensity matching, highlighting the (limited) advantages of propensity.
pubmed.ncbi.nlm.nih.gov/28241362/
This wonderful educational plan describes how to teach learners new to #EBM to understand relative risk reductions and to differentiate them from absolute risk reduction as well as number needed to treat.
pubmed.ncbi.nlm.nih.gov/15313996/
Most useful innovation in #BMJ Core #GRADE series are algoritms to take your though #riskofbias, #imprecision, and #inconsistency. But #indirectness – nothing until publication last month of an indirectness algorithm we developed after publication of the series.
pubmed.ncbi.nlm.nih.gov/41386580/
Assessing #incoherence – differences between direct and indirect estimates in a network #MetaAnalysis (NMA) can be challenging. This lucid article describes the #GRADE approach to addressing the issue
pubmed.ncbi.nlm.nih.gov/30529648/
A few months ago – 48 years after graduation from medical school - I did my last clinical rotation in hospital-based general internal medicine and hung up my stethoscope. Now, more time for research, graduate student supervision, research, and local and international #EBM teaching.
Looking at an #RCT to decide who among #patients, #clinicians, data collectors, et al is #blinded and it’s not clear and explicit? Happens often. Fortunately, almost always enough clues that if you follow instructions in this paper you will make the right inference.
pubmed.ncbi.nlm.nih.gov/22200346/
Latest frequently asked question regarding Core #GRADE: What should a #guideline panel do when they suspect baseline difference in risk warrant different #recommendations in two groups, but no review of #prognosis available? If you have a question, email me.
www.clarityresearch.ca/frequently-a...
#Incoherence in a network #MetaAnalysis occurs when direct and indirect estimates of the effect of an intervention differ substantially: what to do, and how to use #GRADE to rate the #CertaintyofEvidence? This paper answers the questions.
pubmed.ncbi.nlm.nih.gov/30529648/
Company, new #tests for early #CancerDetection to decrease late-stage #cancer and #mortality sold 185k in 2025 at $1k a crack. Problem: just completed #RCT no benefit either outcome. Latest evidence cancer screening limitations, need to wait for evidence of benefit.
www.statnews.com/2026/02/19/g...
Compelling evidence from a #RandomizedTrial (RCT) looking at #PatientImportantOutcomes (PROMS): 7-point scales and #VisualAnalogueScales (VAS) show similar validity and responsiveness (sensitivity to change) to detect intervention effects. Either choice is fine.
pubmed.ncbi.nlm.nih.gov/2157581/
Disturbing article about how U.S. health officials have hijacked shared decision making to follow the Kennedy line to encourage vaccine hesitancy.
www.statnews.com/2026/01/20/s...
Applying GRADE to #DiagnosticTests remains challenging. Here, a summary of the #GRADE approach from the days when we succeeded in being as simple and straightforward as possible.
pubmed.ncbi.nlm.nih.gov/19043023/
Newly published #ImputationStudy demonstrates that #MissingData can often bias pooled estimates in #SystematicReviews (SR) of #PatientReportedOutcomes(#PROs)
pubmed.ncbi.nlm.nih.gov/41461360/
Addressing the #CertaintyofEvidence for #ModellingStudies is a tough nut to crack. Here, a #GRADE overview of the issues in a health context.
pubmed.ncbi.nlm.nih.gov/32980429/
Superb article addressing the controversy regarding our #EBM research – #SystematicReviews of the #evidence regarding #GenderAffirming care in #adolescence and early #adulthood – probably the best yet. Great commentary on my views versus those of #SEGM.
www.motherjones.com/politics/202...
Authors of #RCTs who actually apply concealed #randomization and #blinding failed to report transparently in their articles. Making correct deductions requires inferences from clues in the study, contacting authors to get definitive information.
pubmed.ncbi.nlm.nih.gov/15617948/
Latest frequently asked question about #BMJ Core #GRADE series, all you need to apply GRADE to treatment studies: how to deal with uncertainty around #PublicationBias, joins applying GRADE to single study, a prior hypotheses, rating down for #imprecision.
www.clarityresearch.ca/frequently-a...
Brilliant explication of #GRADE framework when to rate down once or twice for #imprecision complements and provides additional informative examples to what you’ll find in the #BMJ 2025 GRADE series’ second article.
pubmed.ncbi.nlm.nih.gov/35934265/
I’ll be speaking at world’s best #EBM conference, 22nd to 24th October 2026, focus on EBM and AI . In #Taormina, renowned, picturesque hilltop town on #Sicily 's east coast, famous for its breathtaking views of the #IonianSea and active #MountEtna
www.ebhcconference.org/home.en-GB.h...
#CompositeEndpoints frequently mislead by overestimating benefits: #death, #MyocardialInfarction (dominated), and #revascularization. Worse, add #stroke to these three and goes in opposite direction to revascularization and composite favors the wrong intervention!
pubmed.ncbi.nlm.nih.gov/17573977/
My favorite interview-based brief introduction to #EBM, the interviewer being my dear friend Jaeschke. Comment on the interview from the individual who organized ”It is well paced, illustrative and easy to follow – just the kind of conversation we were hoping for”
www.youtube.com/watch?v=I7ou...