{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T03:02:36Z","timestamp":1789614156226,"version":"build-2803163510"},"reference-count":19,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T00:00:00Z","timestamp":1786665600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T00:00:00Z","timestamp":1786665600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pharmaceutical Statistics"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Several study designs for identifying optimal biological dose (OBD) have been proposed for phase I, II, and I\/II clinical trials, considering toxicity and efficacy of anticancer drugs, especially molecular\u2010targeted therapies and immune checkpoint inhibitors. Among these, the multiple\u2010dose randomized phase II trial (MERIT) design selects OBD candidates using hypothesis testing for toxicity and efficacy outcomes. However, it does not consistently control the type I error rate below the significance level, as the null hypothesis is defined only at specific points in a two\u2010dimensional null space. To address this limitation, we developed a design treating toxicity and efficacy as co\u2010primary endpoints, ensuring strict dose\u2010level type I error control across the entire null space. A Bonferroni correction addressed multiplicity in dose selection, providing overall type I error control. Unlike the existing method, the rejection region is determined analytically rather than by simulation, reducing computational costs. The type I error rate of the existing method exceeds the significance level in regions outside points considered in its sample size calculation. By contrast, the proposed method maintains the type I error rate below the significance level across the null space, though conservatively due to the co\u2010primary endpoint framework and Bonferroni adjustment. Required sample sizes of the proposed method tend to be larger than those of the existing one.<\/jats:p>","DOI":"10.1002\/pst.70112","type":"journal-article","created":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T09:55:51Z","timestamp":1786701351000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dose Optimization Design for Randomized Phase\n                    <scp>II<\/scp>\n                    Trials With Toxicity and Efficacy Endpoints"],"prefix":"10.1002","volume":"25","author":[{"given":"Ryuta","family":"Tabata","sequence":"first","affiliation":[{"name":"Department of Information and Computer Technology, Graduate School of Engineering Tokyo University of Science  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9630-5882","authenticated-orcid":false,"given":"Tomohiro","family":"Ohigashi","sequence":"additional","affiliation":[{"name":"Department of Information and Computer Technology, Faculty of Engineering Tokyo University of Science  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9857-5819","authenticated-orcid":false,"given":"Takashi","family":"Sozu","sequence":"additional","affiliation":[{"name":"Department of Information and Computer Technology, Faculty of Engineering Tokyo University of Science  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,14]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.molonc.2014.07.025"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1158\/1078-0432.CCR-15-1295"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1158\/1078-0432.CCR-15-1855"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1177\/1758835920936932"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.2147\/CMAR.S326255"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.3390\/cancers12041010"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1177\/1740774514529848"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12885-021-07782-z"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/pst.1864"},{"key":"e_1_2_10_11_1","article-title":"BOIN12: Bayesian Optimal Interval 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