ArticleStatistics in medicine2020
Point and interval estimation in two-stage adaptive designs with time to event data and biomarker-driven subpopulation selection.
Article in Statistics in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Confidence Intervals for Adaptive Trial Designs I: A Methodological Review.Statistics in medicine · 2025Pooled it
- Adjusting for treatment selection in phase II/III clinical trials with time to event data.Statistics in medicine · 2023Trial
- Confidence intervals and point estimates for treatment effects in adaptive enrichment designs.Statistical methods in medical research · 2026Article
- A Seamless Hybrid Phase II/III Design With Bayesian Interim Subgroup Selection.Statistics in medicine · 2025Article
- Point estimation for adaptive trial designs I: A methodological review.Statistics in medicine · 2023Review
Corrections and comments
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Authors and funding
7 authors at 6 institutions in 3 countries.
Funding
Abstract
In personalized medicine, it is often desired to determine if all patients or only a subset of them benefit from a treatment. We consider estimation in two-stage adaptive designs that in stage 1 recruit patients from the full population. In stage 2, patient recruitment is restricted to the part of the population, which, based on stage 1 data, benefits from the experimental treatment. Existing estimators, which adjust for using stage 1 data for selecting the part of the population from which stage 2 patients are recruited, as well as for the confirmatory analysis after stage 2, do not consider time to event patient outcomes. In this work, for time to event data, we have derived a new asymptotically unbiased estimator for the log hazard ratio and a new interval estimator with good coverage probabilities and probabilities that the upper bounds are below the true values. The estimators are appropriate for several selection rules that are based on a single or multiple biomarkers, which can be categorical or continuous.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.