{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T02:51:48Z","timestamp":1773283908572,"version":"3.50.1"},"reference-count":34,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T00:00:00Z","timestamp":1678838400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P30 CA08270"],"award-info":[{"award-number":["P30 CA08270"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R21 CA264257"],"award-info":[{"award-number":["R21 CA264257"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Stat Methods Med Res"],"published-print":{"date-parts":[[2023,5]]},"abstract":"<jats:p> The \u201cone-size-fits-all\u2019\u2019 paradigm is inappropriate for phase II clinical trials evaluating biotherapies, which are often expected to have substantial heterogeneous treatment effects among different subgroups defined by biomarker. For these biotherapies, the objective of phase II clinical trials is often to evaluate subgroup-specific treatment effects. In this article, we propose a simple yet efficient Bayesian adaptive phase II biomarker-guided design, referred to as the Bayesian-order constrained adaptive design, to detect the subgroup-specific treatment effects of biotherapies. The Bayesian order constrained adaptive design combines the features of the enrichment design and sequential design. It starts with a \u201call-comers\u201d stage, and subsequently switches to an enrichment stage for either the marker-positive subgroup or marker-negative subgroup, depending on the interim analysis results. The go\/no go enrichment criteria are determined by two posterior probabilities utilizing the inherent ordering constraint between two subgroups. We also extend the Bayesian-order constrained adaptive design to handle the missing biomarker situation. We conducted comprehensive computer simulation studies to investigate the operating characteristics of the Bayesian order constrained adaptive design, and compared it with other existing and conventional designs. The results shown that the Bayesian order constrained adaptive design yielded the best overall performance in detecting the subgroup-specific treatment effects by jointly considering the efficiency and cost-effectiveness of the trials. The software for simulation and trial implementation are available for free download. <\/jats:p>","DOI":"10.1177\/09622802231158738","type":"journal-article","created":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T07:40:13Z","timestamp":1678866013000},"page":"885-894","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["Bayesian order constrained adaptive design for phase II clinical trials evaluating subgroup-specific treatment effect"],"prefix":"10.1177","volume":"32","author":[{"given":"Mu","family":"Shan","sequence":"first","affiliation":[{"name":"Department of Biostatistics and Health Data Science, Indiana University, Indianapolis, IN, USA"},{"name":"Eli Lilly and Company, Indianapolis, IN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9921-5535","authenticated-orcid":false,"given":"Beibei","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Experimental Statistics, Louisiana State University, Baton Rouge, LA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Epidemiology, Cancer Institute of New Jersey, Rutgers University, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, St. Jude Children\u2019s Research Hospital, Memphis, TN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5036-5815","authenticated-orcid":false,"given":"Yong","family":"Zang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Health Data Science, Indiana University, Indianapolis, IN, USA"},{"name":"Center of Computational Biology and Bioinformatics, Indiana University, Indianapolis, IN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2023,3,15]]},"reference":[{"key":"bibr1-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-1586-3"},{"key":"bibr2-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1201\/EBK1439825488"},{"key":"bibr3-09622802231158738","volume-title":"Clinical trials: a methodologic perspective","author":"Piantadosi S","year":"2017"},{"key":"bibr4-09622802231158738","first-page":"57","volume":"2","author":"Wu HC","year":"2006","journal-title":"J Cancer Mol"},{"key":"bibr5-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.immunol.25.022106.141527"},{"key":"bibr6-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2014.59.6023"},{"key":"bibr7-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1186\/s40164-019-0150-0"},{"key":"bibr8-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0221-5"},{"key":"bibr9-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1186\/s40364-020-00209-0"},{"key":"bibr10-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejca.2019.11.019"},{"key":"bibr11-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa060467"},{"key":"bibr12-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(08)61758-4"},{"key":"bibr13-09622802231158738","doi-asserted-by":"publisher","DOI":"10.3816\/CLC.2008.n.050"},{"key":"bibr14-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1177\/1740774510373120"},{"key":"bibr15-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1634\/theoncologist.7-2-163"},{"key":"bibr16-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1158\/1078-0432.CCR-04-0496"},{"key":"bibr17-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1093\/biostatistics\/kxt010"},{"key":"bibr18-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1016\/0197-2456(89)90015-9"},{"key":"bibr19-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780131704"},{"key":"bibr20-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0258(19971215)16:23<2701::AID-SIM704>3.0.CO;2-1"},{"key":"bibr21-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1016\/S0197-2456(99)00028-8"},{"key":"bibr22-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1016\/S0197-2456(01)00142-8"},{"key":"bibr23-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1081\/BIP-120005739"},{"key":"bibr24-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006-341X.2004.00193.x"},{"key":"bibr25-09622802231158738","doi-asserted-by":"publisher","DOI":"10.2307\/2533377"},{"key":"bibr26-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780140404"},{"key":"bibr27-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0258(19970830)16:16<1791::AID-SIM609>3.0.CO;2-E"},{"key":"bibr28-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1177\/1740774508089279"},{"key":"bibr29-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1177\/1740774509105221"},{"key":"bibr30-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1002\/sim.7128"},{"key":"bibr31-09622802231158738","first-page":"6080","volume":"13","author":"Pusztai L","year":"2007","journal-title":"Am Assoc Cancer Res"},{"key":"bibr32-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1016\/j.cct.2007.02.008"},{"key":"bibr33-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1002\/pst.1742"},{"key":"bibr34-09622802231158738","doi-asserted-by":"publisher","DOI":"10.1002\/pst.1896"}],"container-title":["Statistical Methods in Medical Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/09622802231158738","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/09622802231158738","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/09622802231158738","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T07:06:49Z","timestamp":1740812809000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/09622802231158738"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,15]]},"references-count":34,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2023,5]]}},"alternative-id":["10.1177\/09622802231158738"],"URL":"https:\/\/doi.org\/10.1177\/09622802231158738","relation":{},"ISSN":["0962-2802","1477-0334"],"issn-type":[{"value":"0962-2802","type":"print"},{"value":"1477-0334","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,15]]}}}