Randomization-based covariance analysis for hypothesis testing of treatment comparisons based on restricted mean survival time with categorized time-to-event data [0.03%]
基于限制平均生存时间的假设检验的随机化协方差分析（用于分类的时间到事件数据）
Taylor J Krajewski,Gary G Koch
Taylor J Krajewski
This paper introduces randomization-based analysis of covariance (RB-ANCOVA) for hypothesis testing of restricted mean survival time (RMST) differences between two randomized treatments in trials with categorized time-to-event data. RMST tr...
A phase II, seamless single-arm to two-arm Bayesian design for a time-to-event endpoint [0.03%]
一种序贯试验设计：基于事件发生时间终点的单臂至双臂贝叶斯二期临床试验
Yun Qing,Ruitao Lin
Yun Qing
Phase II oncology trials often face challenges such as patient recruitment difficulties and limited resources, leading to the use of single-arm designs without concurrent controls. This study introduces a novel two-stage Bayesian design bri...
Balancing sample size and accuracy of dose selection in phase 1 oncology trials - designs tiered by cohort size and maximum number of patients treated per dose [0.03%]
一期肿瘤试验中样本量和剂量选择准确性的平衡-通过队列规模和每个剂量的最大患者数分级的设计
Ping Gao,Xun Zhang,Weidong Zhang et al.
Ping Gao et al.
The objective of phase 1 oncology dose‑escalation trials is to identify the dose with a toxicity rate that matches or is the closest to the target dose‑limiting toxicity (DLT). There are mainly two categories of design methods for phase 1...
Why the minimum effective dose is unidentifiable - and how a DOR→OOD standard delivers label-ready dosing in oncology [0.03%]
为何最小起效剂量无法识别以及如何通过DOR→OOD标准在肿瘤学中实现可直接用于标签的给药剂量
Haitao Pan,Naitee Ting
Haitao Pan
Oncology dose optimization has moved beyond the maximum tolerated dose paradigm, yet many programs still implicitly target a threshold-style minimum effective dose (MED). In serious cancers, deliberately sub-therapeutic comparators are rare...
Augmented match weighted estimators: new methods for estimating average treatment effects under extreme propensity scores [0.03%]
增强匹配加权估计量：在极端倾向得分下估计平均处理效应的新方法
Tanchumin Xu,Yunshu Zhang,Shu Yang
Tanchumin Xu
Propensity score matching (PSM) and augmented inverse propensity weighting (AIPW) are used in observational studies to estimate causal effects. The AIPW estimator is doubly robust and locally efficient but can be unstable when the propensit...
Industrialization of Bayesian decision-making for proof-of-commercial-concept study designs [0.03%]
贝叶斯决策工业化的商业概念验证研究设计方法
Fan Wu,Pascal Minini,Gang Han et al.
Fan Wu et al.
HERALD (Holistic Evolving ReAssessment-Leveraged Decision-making) is a Bayesian decision-making framework anchored in the prediction of phase 3 efficacy success. At the proof-of-commercial-concept (POCC) study design stage, HERALD links ava...
Accounting for effect size uncertainty in sample size determination: From simple cases to hierarchical linear models for multi-regional clinical trials [0.03%]
考虑效应量不确定性的样本量计算方法：从简单情况到分层线性模型的多区域临床试验中的应用
Dongmin Jang,Junhui Park
Dongmin Jang
Accurate sample size determination (SSD) is critical in clinical trial design, yet traditional methods that assume a fixed effect size overlooks estimation uncertainty, risking under- or over-powered studies. The assurance-based SSD approac...
Statistical analysis plan considerations for autologous cell and cell-based gene therapy clinical trials [0.03%]
自体细胞和基于细胞的基因疗法临床试验统计分析计划考量点
Patricia Anderson,Revathi Ananthakrishnan,Zhenzhen Xu et al.
Patricia Anderson et al.
By early 2023, there were over 100 gene, cell and RNA products approved globally (Chancellor et al. 2023). The way in which autologous cell and cell-based gene therapy products are administered can include multiple treatment stages, at time...
Nonparametric testing methods based on relative effect in non-inferiority clinical trial with multiple experimental drugs [0.03%]
非劣效临床试验中多重实验药物相对效应的非参数检验方法研究
Jieun Park,Jae Won Lee
Jieun Park
Conventional non-inferiority (NI) clinical trials often rely on large sample sizes and parametric methods with a single experimental drug. However, rare diseases pose challenges in obtaining large datasets, and data normality cannot always ...
Revathi Ananthakrishnan,Bambang Adiwijaya,Alan Y Chiang et al.
Revathi Ananthakrishnan et al.
This manuscript provides an overview of recent and relevant dose-finding designs for cell and gene therapies (CGT). We start with an introduction of dose-finding. We then provide a brief overview of CGT, what dose‑escalation designs have a...