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The estimator allows the failure time to be conditionally independent of censoring and dependent on the treatment decision times, supports a flexible number of treatment arms and treatment stages, and can maximize either the mean survival time or the survival probability at a certain time-point. The estimator is constructed using generalized random survival forests and can have polynomial rates of convergence. Simulations and analysis of the Atherosclerosis Risk in Communities study data suggest that the new estimator brings higher expected outcomes than existing methods in various settings.<\/jats:p>","DOI":"10.1093\/biomet\/asac047","type":"journal-article","created":{"date-parts":[[2022,8,13]],"date-time":"2022-08-13T14:07:47Z","timestamp":1660399667000},"page":"395-410","source":"Crossref","is-referenced-by-count":13,"title":["Multi-stage optimal dynamic treatment regimes for survival outcomes with dependent censoring"],"prefix":"10.1093","volume":"110","author":[{"given":"Hunyong","family":"Cho","sequence":"first","affiliation":[{"name":"University of North Carolina Department of Biostatistics, , 135 Dauer Drive, Chapel Hill, North Carolina 27599, U.S.A"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shannon T","family":"Holloway","sequence":"additional","affiliation":[{"name":"North Carolina State University Department of Statistics, , 2311 Stinson Drive, Raleigh, North Carolina 27607, U.S.A"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David J","family":"Couper","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of North Carolina Collaborative Studies Coordinating Center, , 123 W. 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