{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,1,30]],"date-time":"2024-01-30T22:40:09Z","timestamp":1706654409088},"reference-count":22,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2005,10,11]],"date-time":"2005-10-11T00:00:00Z","timestamp":1128988800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2006,5,30]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>A decision\u2010theoretic framework is proposed for designing sequential dose\u2010finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose\u2010finding studies involving<jats:italic>k<\/jats:italic>doses, the computational complexity is the same as the bandit problem with<jats:italic>k<\/jats:italic>\u2010dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I\/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available. Copyright \u00a9 2005 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/sim.2322","type":"journal-article","created":{"date-parts":[[2005,10,11]],"date-time":"2005-10-11T12:16:53Z","timestamp":1129033013000},"page":"1699-1714","source":"Crossref","is-referenced-by-count":9,"title":["Decision\u2010theoretic designs for dose\u2010finding clinical trials with multiple outcomes"],"prefix":"10.1002","volume":"25","author":[{"given":"Shenghua K.","family":"Fan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"You\u2010Gan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2005,10,11]]},"reference":[{"key":"e_1_2_1_2_2","doi-asserted-by":"publisher","DOI":"10.2307\/2533377"},{"key":"e_1_2_1_3_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006-341X.1999.00971.x"},{"key":"e_1_2_1_4_2","doi-asserted-by":"publisher","DOI":"10.2307\/2534011"},{"key":"e_1_2_1_5_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006-341X.2001.01089.x"},{"key":"e_1_2_1_6_2","doi-asserted-by":"publisher","DOI":"10.1111\/1541-0420.00047"},{"key":"e_1_2_1_7_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780140904"},{"key":"e_1_2_1_8_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.970"},{"key":"e_1_2_1_9_2","doi-asserted-by":"publisher","DOI":"10.1080\/03610929108830531"},{"key":"e_1_2_1_10_2","doi-asserted-by":"crossref","unstructured":"JonesPW.Multiobjective Bayesian bandits. 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