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BAGS：具有亚组特异生存比较的贝叶斯自适应群序贯试验设计AI 解读

Ruitao Lin, Peter F. Thall* & Ying YuanDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TXSupplementary materials for this article are available online. Please go to www.tandfonline.com/r/JASA.CONTACT Peter F. Thall rex@mdanderson.org Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TA 77030.AbstractA Bayesian group sequential design is proposed that performs survival comparisons within patient…

优化动态治疗方案的贝叶斯机器学习方法AI 解读

Medical therapy often consists of multiple stages, with a treatment chosen by the physician at each stage based on the patient's history of treatments and clinical outcomes. These decisions can be formalized as a dynamic treatment regime. This paper describes a new approach for optimizing dynamic treatment regimes that bridges the gap between Bayesian inference and existing approaches, like Q-learning. The proposed approach fits a series of Bayesian regression models, one…

基于半竞争风险效用的非小细胞肺癌稳健治疗比较AI 解读

A design is presented for a randomized clinical trial comparing two second-line treatments, chemotherapy versus chemotherapy plus reirradiation, for treatment of recurrent non-small-cell lung cancer. The central research question is whether the potential efficacy benefit that adding reirradiation to chemotherapy may provide justifies its potential for increasing the risk of toxicity. The design uses two co-primary outcomes: time to disease progression or death, and time to…

带序贯转移时间的动态治疗方案的贝叶斯非参数估计AI 解读

We analyze a dataset arising from a clinical trial involving multi-stage chemotherapy regimes for acute leukemia. The trial design was a 2 × 2 factorial for frontline therapies only. Motivated by the idea that subsequent salvage treatments affect survival time, we model therapy as a dynamic treatment regime (DTR), that is, an alternating sequence of adaptive treatments or other actions and transition times between disease states. These sequences may vary substantially…

晚期前列腺癌序贯随机试验中可实施动态治疗策略的评估AI 解读

We present new statistical analyses of data arising from a clinical trial designed to compare two-stage dynamic treatment regimes (DTRs) for advanced prostate cancer. The trial protocol mandated that patients were to be initially randomized among four chemotherapies, and that those who responded poorly were to be rerandomized to one of the remaining candidate therapies. The primary aim was to compare the DTRs' overall success rates, with success defined by the occurrence of…