<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>41(20)</volume><submitter>Dehbi HM</submitter><pubmed_abstract>Selection trials are used to compare potentially active experimental treatments without a control arm. While sample size calculation methods exist for binary endpoints, no such methods are available for time-to-event endpoints, even though these are ubiquitous in clinical trials. Recent selection trials have begun using progression-free survival as their primary endpoint, but have dichotomized it at a specific time point for sample size calculation and analysis. This changes the clinical question and may reduce power to detect a difference between the arms. In this article, we develop the theory for sample size calculation in selection trials where the time-to-event endpoint is assumed to follow an exponential or Weilbull distribution. We provide a free web application for sample size calculation, as well as an R package, that researchers can use in the design of their studies.</pubmed_abstract><journal>Statistics in medicine</journal><pagination>4022-4033</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9544500</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Sample size calculation for randomized selection trials with a time-to-event endpoint and a margin of practical equivalence.</pubmed_title><pmcid>PMC9544500</pmcid><pubmed_authors>McCaw ZR</pubmed_authors><pubmed_authors>Dehbi HM</pubmed_authors><pubmed_authors>Embleton-Thirsk A</pubmed_authors></additional><is_claimable>false</is_claimable><name>Sample size calculation for randomized selection trials with a time-to-event endpoint and a margin of practical equivalence.</name><description>Selection trials are used to compare potentially active experimental treatments without a control arm. While sample size calculation methods exist for binary endpoints, no such methods are available for time-to-event endpoints, even though these are ubiquitous in clinical trials. Recent selection trials have begun using progression-free survival as their primary endpoint, but have dichotomized it at a specific time point for sample size calculation and analysis. This changes the clinical question and may reduce power to detect a difference between the arms. In this article, we develop the theory for sample size calculation in selection trials where the time-to-event endpoint is assumed to follow an exponential or Weilbull distribution. We provide a free web application for sample size calculation, as well as an R package, that researchers can use in the design of their studies.</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Sep</publication><modification>2025-04-22T12:11:47.056Z</modification><creation>2025-04-06T00:13:53.863Z</creation></dates><accession>S-EPMC9544500</accession><cross_references><pubmed>35688463</pubmed><doi>10.1002/sim.9490</doi></cross_references></HashMap>