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Record W4410975707 · doi:10.1093/jncics/pkaf053

INTEGRATE pooled phase 2/3 results are robust to postprogression switching and the winner’s curse

2025· article· en· W4410975707 on OpenAlexfundno aff
Yu Yang Soon, Katrin Marie Sjoquist, Ian C. Marschner, I. Manjula Schou, Nick Pavlakis, David Goldstein, Kohei Shitara, Martin R. Stockler, R. J. Simes, Andrew Martin

Bibliographic record

VenueJNCI Cancer Spectrum · 2025
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsnot available
FundersNational Medical Research CouncilNational Health and Medical Research CouncilCancer AustraliaCanadian Cancer SocietyMedical Research CouncilAustralian GovernmentBayer
KeywordsCensoring (clinical trials)MedicinePoolingBayesian probabilityHazard ratioStatisticsConfidence intervalEconometricsInternal medicineMathematicsArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: The INTEGRATE phase 3 trial in advanced gastric and esophagogastric junction cancer involved pooling overall survival data with its preceding phase 2 trial, raising concerns about misalignment due to treatment switching in phase 2, or the "winner's curse." We evaluated phase 2 results, adjusted for these opposing effects, against phase 3 according to the prespecified statistical analysis plan. METHODS: Overall survival estimates were adjusted for treatment switching using the rank-preserving structural failure time model (RPSFTM) and inverse probability of censoring weights (IPCW) method. A novel shrinkage approach mitigated overestimation from the winner's curse, and Bayesian prediction methods predicted phase 3 outcomes from phase 2 estimates. A simulation study modeled 10 000 seamless phase 2/3 trials to quantify bias in the pooled estimate. RESULTS: The observed phase 3 hazard ratio (HR = 0.71, 95% CI = 0.54 to 0.93) for overall survival was more conservative than the adjusted phase 2 estimates (RPSFTM and novel shrinkage approach: HR = 0.61, 95% CI = 0.29 to 1.29; RPSFTM and Bayesian prediction: HR = 0.59, 95% CI = 0.48 to 0.73; IPCW and novel shrinkage approach: HR = 0.55, 95% CI = 0.31 to 0.99; IPCW and Bayesian prediction: HR = 0.58, 95% CI = 0.46 to 0.72). Simulations indicated negligible bias in the pooled log hazard ratio of ‒0.011 and 0.005 under the null and alternative hypotheses, respectively. CONCLUSION: Adjusting phase 2 estimates for both treatment switching and the winner's curse produced point estimates similar to the unadjusted phase 3 results. A prospective plan to pool trial data under a closed testing procedure may be a reasonable strategy when a recruitment shortfall in phase 3 is anticipated, provided that potential sources of misalignment are thoroughly assessed. CLINICAL TRIAL INFORMATION: ACTRN12612000239864 (INTEGRATE I)NCT02773524 (INTEGRATE IIA).

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 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)0.003
metaresearch head score (Gemma)0.041
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.345
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.041
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.299
GPT teacher head0.562
Teacher spread0.263 · 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; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
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

Citations0
Published2025
Admission routes1
Has abstractyes

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