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Record W2084652988 · doi:10.1177/1740774507079439

Monitoring the randomized trials of the Women's Health Initiative: the experience of the Data and Safety Monitoring Board

2007· article· en· W2084652988 on OpenAlexaff
Janet Wittes, Elizabeth Barrett‐Connor, Eugene Braunwald, Margaret A. Chesney, Harvey Jay Cohen, David L. DeMets, Leo J. Dunn, Johanna Dwyer, Robert P. Heaney, Victor G. Vogel, LeRoy Walters, Salim Yusuf

Bibliographic record

VenueClinical Trials · 2007
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSafety monitoringMedicineClinical trialRandomized controlled trialData monitoring committeeAdverse effectWomen's Health InitiativePostmenopausal womenBioinformaticsPharmacologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Data Safety Monitoring Committees (DSMB) for large, long-term randomized trials of agents in common use face challenging problems especially when the emerging data indicate unanticipated effects. The DSMB for the Women's Health Initiative Clinical Trials, on observing early indication of a surprising adverse cardiovascular effect of post-menopausal hormones, spent several years deliberating what recommendations it should make. This paper describes the dilemmas faced by the DSMB and the considerations it made over the course of its existence. The paper concludes with some recommendations for other DSMBs.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.840
metaresearch head score (Gemma)0.832
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.160
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.8400.832
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0060.011
Science and technology studies0.0080.021
Scholarly communication0.0220.019
Open science0.0080.010
Research integrity0.0250.053
Insufficient payload (model declined to judge)0.0030.002

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 head0.561
GPT teacher head0.588
Teacher spread0.027 · 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

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainEvaluation
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations46
Published2007
Admission routes1
Has abstractyes

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