Empirical evaluation of fundamental principles of evidence-based medicine: a meta-epidemiological study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rationale, aims and objectives 39 Evidence-based medicine (EBM) holds that estimates of effects of health interventions based on 40 high-certainty evidence (CoE) are expected to change less frequently than the effects generated 41 in low CoE studies. However, this foundational principle of EBM has never been empirically 42 tested. 43 Methods 44 We reviewed all systematic reviews and meta-analyses in Cochrane Database of Systematic 45 Reviews from January 2016 through May 2021 (n=3,323). We identified 414(207x2) and 384 46 (192x2) pairs of original and updated Cochrane reviews that assessed CoE and pooled 47 treatment effect estimates. We appraised CoE using the Grading of Recommendations 48 Assessment, Development and Evaluation (GRADE) method. We assessed the difference in 49 effect sizes between the original versus updated reviews as a function of change in CoE, which 50 we report as a ratio of odds ratio (ROR). We compared ROR generated in the studies that 51 changed CoE from very low/low (VL/L) to moderate/high (M/H) vs. MH/H VL/L. We also 52 assessed the heterogeneity and inconsistency (using the tau and I2 statistic), the change in 53 precision of effect estimates (by calculating the ratio of standard errors) (seR), and the absolute 54 deviation in estimates of treatment effects (aROR). 55 Results 56 57 We found that CoE originally appraised as VL/L had 2.1 (95%CI: 1.19 to 4.12; p=0.0091) times 58 higher odds to be changed in the future studies than M/H CoE. However, the effect size was not 59 different when CoE changed from VL/L M/H vs. M/H VL/L [ROR=1.02 (95%CI: 0.74 to 1.39) 60 vs. 1.02 (95%CI: 0.44 to 2.37); p=1 for the between subgroup differences]. aROR was similar 61 between the subgroups [median (IQR):1.12 (1.07 to 1.57) vs 1.21 (1.12 to 2.43)]. We observed 62 large inconsistency (I 2=99%) and imprecision in treatment effects (seR=1.09). 63 Conclusions 64 We provide the first empirical support for a foundational principle of EBM showing that low65 quality evidence changes more often than high CoE. However, the effect size was not different 66 between studies with low vs high CoE. The finding that the effect size did not differ between low 67 and high CoE indicate urgent need to refine current EBM critical appraisal methods
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | MetaresearchMeta-epidemiology (narrow)Meta-epidemiology (broad) Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.615 | 0.458 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.019 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.126 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it