<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Wu J</submitter><funding>National Cancer Institute</funding><funding>American Lebanese Syrian Associated Charities</funding><funding>NCI NIH HHS</funding><pagination>1235-1248</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9502026</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>20(6)</volume><pubmed_abstract>For the cancer clinical trials with immunotherapy and molecularly targeted therapy, time-to-event endpoint is often a desired endpoint. In this paper, we present an event-driven approach for Bayesian one-stage and two-stage single-arm phase II trial designs. Two versions of Bayesian one-stage designs were proposed with executable algorithms and meanwhile, we also develop theoretical relationships between the frequentist and Bayesian designs. These findings help investigators who want to design a trial using Bayesian approach have an explicit understanding of how the frequentist properties can be achieved. Moreover, the proposed Bayesian designs using the exact posterior distributions accommodate the single-arm phase II trials with small sample sizes. We also proposed an optimal two-stage a</pubmed_abstract><journal>Pharmaceutical statistics</journal><pubmed_title>Bayesian single-arm phase II trial designs with time-to-event endpoints.</pubmed_title><pmcid>PMC9502026</pmcid><funding_grant_id>P30 CA177558</funding_grant_id><funding_grant_id>P30CA177558</funding_grant_id><pubmed_authors>Pan H</pubmed_authors><pubmed_authors>Wu J</pubmed_authors><pubmed_authors>Hsu CW</pubmed_authors></additional><is_claimable>false</is_claimable><name>Bayesian single-arm phase II trial designs with time-to-event endpoints.</name><description>For the cancer clinical trials with immunotherapy and molecularly targeted therapy, time-to-event endpoint is often a desired endpoint. In this paper, we present an event-driven approach for Bayesian one-stage and two-stage single-arm phase II trial designs. Two versions of Bayesian one-stage designs were proposed with executable algorithms and meanwhile, we also develop theoretical relationships between the frequentist and Bayesian designs. These findings help investigators who want to design a trial using Bayesian approach have an explicit understanding of how the frequentist properties can be achieved. Moreover, the proposed Bayesian designs using the exact posterior distributions accommodate the single-arm phase II trials with small sample sizes. We also proposed an optimal two-stage a</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021 Nov</publication><modification>2025-04-18T20:52:12.638Z</modification><creation>2025-04-07T08:56:04.989Z</creation></dates><accession>S-EPMC9502026</accession><cross_references><pubmed>34085764</pubmed><doi>10.1002/pst.2143</doi></cross_references></HashMap>