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Inadequate Reporting of Cointerventions, Other Methodological Factors, and Treatment Estimates in Cardiovascular Trials: A Meta-Epidemiological Study

2023· article· en· W4379135156 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMayo Clinic Proceedings Innovations Quality & Outcomes · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersArts and Humanities Research CouncilUniversity of California, San FranciscoUniversity of BernUniversity of TorontoInselspital, Universitätsspital BernSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsBlindingMedicineMeta-analysisPublication biasPsychological interventionClinical trialOdds ratioMEDLINEConfidence intervalRelative riskPhysical therapyInternal medicine

Abstract

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ObjectiveTo assess how inadequate reporting of cointerventions influences estimated treatment effects in recent cardiovascular trials.MethodsMedline/Embase were systematically searched from January 1, 2011 to July 1, 2021 for trials evaluating pharmacologic interventions on clinical cardiovascular outcomes published in 5 high-impact journals. Information on adequate vs inadequate reporting of cointerventions, blinding, risk of bias due to deviations of intended interventions (low vs high/some concerns), funding (nonindustry vs industry), design (superiority vs noninferiority), and results were assessed by 2 reviewers. The association with effect sizes was assessed using meta-regression random-effect analysis, expressed as ratios of odds ratios (ROR). RORs of >1.0 indicated that trials with the methodological factor pointing to lower quality report larger treatment estimates.ResultsIn total, 164 trials were included. Of the 164 trials, 124 (74%) did not adequately report cointerventions; 89 of the 164 trials (54%) provided no information regarding cointerventions, and 70 of the 164 (43%) were at risk of bias due to inadequate blinding. Moreover, 86 of the 164 (53%) were at risk of bias due to deviation of intended interventions. Of the 164 trials, 144 (88%) were funded by the industries. Trials with inadequate reporting of cointerventions had larger treatment estimates for the primary end point (ROR, 1.08; 95% CI, 1.01-1.15; I2=0%). No significant association with results for blinding (ROR, 0.97; 95% CI, 0.91-1.03; I2=66%), deviation of intended interventions (ROR, 0.98; 95% CI, 0.92-1.04; I2=0%), or funding (ROR, 1.01; 95% CI, 0.93-1.09; I2=0%) was found.ConclusionWe conclude that trials with inadequate reporting of cointerventions showed larger treatment effect estimates, potentially indicating overestimation of therapeutic benefit.Trial RegistrationProspero Identifier: CRD42017072522 To assess how inadequate reporting of cointerventions influences estimated treatment effects in recent cardiovascular trials. Medline/Embase were systematically searched from January 1, 2011 to July 1, 2021 for trials evaluating pharmacologic interventions on clinical cardiovascular outcomes published in 5 high-impact journals. Information on adequate vs inadequate reporting of cointerventions, blinding, risk of bias due to deviations of intended interventions (low vs high/some concerns), funding (nonindustry vs industry), design (superiority vs noninferiority), and results were assessed by 2 reviewers. The association with effect sizes was assessed using meta-regression random-effect analysis, expressed as ratios of odds ratios (ROR). RORs of >1.0 indicated that trials with the methodological factor pointing to lower quality report larger treatment estimates. In total, 164 trials were included. Of the 164 trials, 124 (74%) did not adequately report cointerventions; 89 of the 164 trials (54%) provided no information regarding cointerventions, and 70 of the 164 (43%) were at risk of bias due to inadequate blinding. Moreover, 86 of the 164 (53%) were at risk of bias due to deviation of intended interventions. Of the 164 trials, 144 (88%) were funded by the industries. Trials with inadequate reporting of cointerventions had larger treatment estimates for the primary end point (ROR, 1.08; 95% CI, 1.01-1.15; I2=0%). No significant association with results for blinding (ROR, 0.97; 95% CI, 0.91-1.03; I2=66%), deviation of intended interventions (ROR, 0.98; 95% CI, 0.92-1.04; I2=0%), or funding (ROR, 1.01; 95% CI, 0.93-1.09; I2=0%) was found. We conclude that trials with inadequate reporting of cointerventions showed larger treatment effect estimates, potentially indicating overestimation of therapeutic benefit.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 armCategoriesStudy designConfidence
gemmaMetaresearchMeta-epidemiology (narrow)Meta-epidemiology (broad)
Domain: Reporting · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptMetaresearchMeta-epidemiology (narrow)Meta-epidemiology (broad)
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Meta-analysishigh
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.696
metaresearch head score (Gemma)0.806
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.6960.806
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0200.007
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.982
GPT teacher head0.714
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it