ArticleJournal of evaluation in clinical practice2025
What is the probability that higher versus lower quality of evidence represents true effects estimates?
Article in Journal of evaluation in clinical practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- How to determine the optimal duration of anticoagulation for VTE: an evidence-based decision-analytical approach.Blood advances · 2026Article
- Converting Evidence-Based Summary of Findings Evidence Tables Into Decision Analytical, Quality Adjusted Life Years (QALY) and Life Expectancies Metrics: A Tutorial.Journal of evaluation in clinical practice · 2025Article
- What is the probability that higher versus lower quality of evidence represents true effects estimates?Journal of evaluation in clinical practice · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
RATIONALE, AIMS, AND
objectivesThe previous studies demonstrated that the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system, a leading method for evaluating the certainty (quality) of scientific evidence (CoE), cannot reliably differentiate between various levels of CoE when the objective is to accurately assess the magnitude of the treatment effect. An estimated effect size is a function of multiple factors, including the true underlying treatment effect, biases, and other nonlinear factors that affect the estimate in different directions. We postulate that non-weighted, simple linear tallying can provide more accurate estimates of the probability of a true estimate of treatment effects as a function of CoE.
methodsWe reasoned that stable treatment effect estimates over time indicate truthfulness. We compared odds ratios (ORs) from meta-analyses (MAs) before and after updates, hypothesising that a ratio of odds ratios (ROR) equal to 1 will be more commonly observed in higher versus lower CoE. We used a subset of a previously analysed data set consisting of 82 Cochrane pairs of MAs in which CoE has not changed with the updated MA. If the linear model is valid, we would expect a decrease in the number of ROR = 1 cases as we move from high to moderate, low, and very low CoE.
resultsWe found a linear relationship between the probability of a potentially 'true' estimate of treatment effects as a function of CoE (assuming a 10% ROR error margin) (R
conclusionThis study confirmed linear relationship between CoE and the probability of potentially 'true' estimates. We found that the probability of potentially "true" estimates decreases by about 20% for each drop in CoE (from about 80% for high to 55% for moderate to 35% to low and 15% to very low CoE).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.