A Unified Approach to Covariate Adjustment for Survival Endpoints in Randomized Clinical Trials [0.03%]
随机试验中统一调整协变量的方法以生存终点指标为基础
Zhiwei Zhang,Ya Wang,Dong Xi
Zhiwei Zhang
Covariate adjustment aims to improve the statistical efficiency of randomized trials by incorporating information from baseline covariates. Popular methods for covariate adjustment include analysis of covariance for continuous endpoints and...
Great Wall: A Generalized Dose Optimization Design for Drug Combination Trials Maximizing Survival Benefit [0.03%]
长城：药物联合试验中最大化生存效益的剂量优化设计通用方法
Yan Han,Yingjie Qiu,Yi Zhao et al.
Yan Han et al.
Most phase I-II drug-combination trial designs assume that selecting the optimal dose combination based on early outcomes will also lead to maximum long-term survival benefits. However, this assumption is often violated in many clinical stu...
Taha Hasan,Touqeer Ahmad
Taha Hasan
In a mixture experiment, we study the behavior and properties of m mixture components, where the primary focus is on the proportions of the components that make up the mixture rather than the total amount. Mixture-amount experiments are spe...
Ruoxuan Xiang,John Scott
Ruoxuan Xiang
Basket trials in oncology assess one treatment simultaneously on multiple cancer histologies that share a common genomic aberration. A Bayesian hierarchical model (BHM) first proposed by Thall et al. is widely used to borrow information acr...
Improving Maximum Tolerated Dose Selection in Model-Assisted Designs for Phase I Trials Through Bayesian Dose-Response Model [0.03%]
基于贝叶斯剂量反应模型的I期临床试验中辅助设计的最大耐受剂量选择的改进
Rentaro Wakayama,Tomotaka Momozaki,Shuji Ando
Rentaro Wakayama
Model-assisted designs have garnered significant attention in recent years due to their high accuracy in identifying the maximum tolerated dose (MTD) and their operational simplicity. To identify the MTD, they employ estimated dose limiting...
Utility-Based Dose Optimization Approaches for Multiple-Dose Randomized Trial Designs Accounting for Multiple Endpoints [0.03%]
基于效用的剂量优化方法用于多剂量随机试验设计，考虑多个终点变量
Gina D&#x;Angelo,Guannan Chen,Di Ran
Gina D&#x;Angelo
The initiation of dose optimization has driven a paradigm shift in oncology clinical trials to determine the optimal biological dose (OBD). Early-phase trials with randomized doses can facilitate additional investigation of the identified O...
BOIN-MEM: A Two-Stage Design for Dose Optimization With Information Borrowing Across Dose Levels and Stages in Oncology Phase I/II Trials [0.03%]
一种两阶段设计：在肿瘤I/II期试验中利用各剂量水平及阶段间信息借用进行剂量优化的BOIN-MEM方法
Ryo Kitabayashi,Kentaro Takeda,Hiroyuki Sato et al.
Ryo Kitabayashi et al.
The launch of Project Optimus has shifted a paradigm in oncology early-phase trials toward identifying the optimal biological dose (OBD), considering both the drug's toxicity and efficacy. Conventional two-stage designs for dose optimizatio...
Nonparametric Inference for the Covariate-Adjusted Youden Index and Associated Cut-Off Points for Three Ordinal Diagnostic Groups [0.03%]
带协变量调整的Youden指数及三组有序诊断指标相关临界值的非参数推断方法研究
Asieh Maghami-Mehr,Hamzeh Torabi,Hossein Nadeb et al.
Asieh Maghami-Mehr et al.
In this paper, we propose point estimators and confidence intervals for the Youden index and optimal cut-off points in the context of three ordinal diagnostic groups, accounting for the presence of covariates. Using heteroscedastic regressi...
Designing and Evaluating Bayesian Advanced Adaptive Randomised Clinical Trials: A Practical Guide [0.03%]
贝叶斯自适应临床试验设计与评价实用指南
Anders Granholm,Aksel Karl Georg Jensen,Theis Lange et al.
Anders Granholm et al.
Advanced adaptive randomised clinical trials are increasingly used. Compared to their conventional counterparts, their flexibility may make them more efficient, increase the probability of obtaining conclusive results without larger samples...
Extending Multiple Testing With Unknown Test Dependency via the CoCo Test: With Applications to Cancer Studies [0.03%]
基于CoCo检验的多重比较及其在癌症研究中的应用
Jiangtao Gou,Kai Wu,Oliver Y Chén
Jiangtao Gou
Multiple testing issues are common in clinical and scientific research, particularly in clinical trials involving multple endpoints. The central challenge lies in controlling the type I error rate ( α $$ /alpha $$ -control). The beha...