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Randomized Controlled Trial
. 2025 Jul 1;9(4):pkaf053.
doi: 10.1093/jncics/pkaf053.

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

Affiliations
Randomized Controlled Trial

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

Yu Yang Soon et al. JNCI Cancer Spectr. .

Abstract

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).

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Conflict of interest statement

Katrin Sjoquist

Honoraria: Bristol Myers Squibb, Merck, MSD, Servier, Novotech (institution), Astellas Pharma, Lisata (institution), Bayer (institution)

Research funding: Bayer (institution)

Other relationship: Novotech

Nick Pavlakis

Honoraria: BeiGene, Bayer, Takeda, Pierre Fabre

Consulting or advisory role: Roche, Boehringer Ingelheim, AstraZeneca, Merck KGaA, Merck Serono, Amgen, Merck Sharp & Dohme, Novartis, Pfizer, Takeda, Bristol Myers Squibb, BeiGene, Gilead Sciences, Janssen Oncology

Research funding: Bayer (institution), Pfizer (institution), Roche (institution)

David Goldstein

Honoraria: Sun Biopharma, Boehringer Ingelheim, AstraZeneca, Merck, Duo Oncology

Consulting or advisory role: Sun Biopharma, Seagen, AstraZeneca, Boehringer Ingelheim, Duo Oncology, Medison, HC Bioscience, MSD Oncology, Takeda, Amplicare

Research funding: Amgen (institution), Pfizer (institution), Celgene (institution), Bayer (institution), Zucero Therapeutics (institution), Bristol Myers Squibb (institution), Bayer (institution), AstraZeneca (institution)

Martin R. Stockler

Speakers bureau: Astellas Pharma

Research funding: Astellas, Celgene, Bayer, Bionomics, Medivation, Sanofi, Pfizer, AstraZeneca, Bristol Myers Squibb, Roche, Amgen, Merck Sharp & Dohme, Tilray, BeiGene

Expert testimony: Medivation/Pfizer

No other potential conflicts of interest were reported.

John Simes

Consulting or advisory role: FivePhusion (institution)

Research funding: Bayer (institution), AbbVie (institution), Roche (institution), Bristol Myers Squibb (institution), AstraZeneca (institution), Pfizer (institution), Amgen (institution), MSD (institution), BeiGene (institution), Astellas Pharma (institution)

Figures

Figure 1.
Figure 1.
Hazard ratios for estimands of interest. Abbreviations: HR = hazard ratio; IPCW = inverse probability of censoring weights; RPSFTM = rank-preserving structural failure time model.
Figure 2.
Figure 2.
Impact of violating the common treatment effect assumption on the hazard ratio in the rank-preserving structural failure time model (log rank, no recensoring). A larger ratio of treatment effect after progression to random assignment means that the effect of regorafenib is stronger after disease progression than at random assignment.

References

    1. Pavlakis N, Sjoquist KM, Martin AJ, et al. Regorafenib for the treatment of advanced gastric cancer (INTEGRATE): a multinational placebo-controlled phase II trial. J Clin Oncol. 2016;34:2728-2735. - PMC - PubMed
    1. Pavlakis N, Shitara K, Sjoquist K, et al. INTEGRATE IIa phase III study: regorafenib for refractory advanced gastric cancer. J Clin Oncol. 2025;43:453-463. - PubMed
    1. Lam LL, Pavlakis N, Shitara K, et al. INTEGRATE II: randomised phase III controlled trials of regorafenib containing regimens versus standard of care in refractory Advanced Gastro-Oesophageal Cancer (AGOC): A study by the Australasian Gastro-Intestinal Trials Group (AGITG). BMC Cancer. 2023;23:180. - PMC - PubMed
    1. Latimer NR, Dewdney A, Campioni M. A cautionary tale: an evaluation of the performance of treatment switching adjustment methods in a real world case study. BMC Med Res Methodol. 2024;24:17. - PMC - PubMed
    1. Sidebotham D, Barlow CJ. The winner's curse: why large effect sizes in discovery trials always get smaller and often disappear completely. Anaesthesia. 2024;79:86-90. - PubMed

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