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可解释的动态治疗方案AI 解读

Precision medicine is currently a topic of great interest in clinical and intervention science. A key component of precision medicine is that it is evidence-based, i.e., data-driven, and consequently there has been tremendous interest in estimation of precision medicine strategies using observational or randomized study data. One way to formalize precision medicine is through a treatment regime, which is a sequence of decision rules, one per stage of clinical intervention,…

删失临床数据中两阶段随机化设计的生存分布半参数有效估计AI 解读

Two-stage randomisation designs are useful in the evaluation of combination therapies where patients are initially randomised to an induction therapy and then, depending upon their response and consent, are randomised to a maintenance therapy. In this paper we derive the best regular asymptotically linear estimator for the survival distribution and related quantities of treatment regimes. We propose an estimator which is easily computable and is more efficient than existing…

治疗时长可能右删失的观察性时长—响应研究中的半参数推断AI 解读

Once treatment is found to be effective in clinical studies, attention often focuses on optimum or efficacious treatment delivery. In treatment duration-response studies, the optimum treatment delivery refers to the treatment length that optimises the mean response. In many studies, the treatment length is often left to the discretion of an attending investigator or physician but may be abruptly terminated because of treatment-terminating events. Thus, a recommended…

高度分层数据的修正对数秩检验AI 解读

Clinical trials often employ a stratified randomization so that treatment arms are balanced within prognostic factors. In these circumstances the use of the ordinary log rank test for comparing treatment groups with respect to survival is invalid. The stratified log rank test, although valid, loses efficiency as the number of strata increases. This paper proposes a modified log rank test that is fully efficient when there is no strata effect and is more efficient than the…

适用于高度分层数据的修正对数秩检验AI 解读

Clinical trials often employ a stratified randomization so that treatment arms are balanced within prognostic factors. In these circumstances the use of the ordinary log rank test for comparing treatment groups with respect to survival is invalid. The stratified log rank test, although valid, loses efficiency as the number of strata increases. This paper proposes a modified log rank test that is fully efficient when there is no strata effect and is more efficient than the…