Jinxiang Hu, Xiaohang Mei, Sam Pepper, Yu Wang, Bo Zhang, Colin Cernik, Byron Gajewski
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引用次数: 0
摘要
患者报告结果（PROs）被广泛应用于生活质量（QOL）研究、健康结果研究和临床试验中。患者报告结果的重要性已得到卫生部门的重视。我们提出了这款 R 闪网络应用程序 PROpwr，它可以使用项目反应理论（GRM：分级反应模型）和模拟来估算以患者报告结果为终点的双臂临床试验的功率。PROpwr 还支持对 PRO 数据进行分析，以方便估计效应大小。PROpwr 中有七个功能选项卡：频繁分析、贝叶斯分析、GRM 功率、给定样本量的 T 检验功率、给定功率的 T 检验样本量、下载和参考文献。PROpwr 具有点选功能，使用方便。PROpwr 可帮助研究人员在没有编程知识的情况下，分析和计算临床试验中PRO终点的功率和样本量。
PROpwr: a Shiny R application to analyze patient-reported outcomes data and estimate power.
Patient Reported Outcomes (PROs) are widely used in quality of life (QOL) studies, health outcomes research, and clinical trials. The importance of PRO has been advocated by health authorities. We propose this R shiny web application, PROpwr, that estimates power for two-arm clinical trials with PRO measures as endpoints using Item Response Theory (GRM: Graded Response Model) and simulations. PROpwr also supports the analysis of PRO data for convenience of estimating the effect size. There are seven function tabs in PROpwr: Frequentist Analysis, Bayesian Analysis, GRM power, T-test Power Given Sample Size, T-test Sample Size Given Power, Download, and References. PROpwr is user-friendly with point-and-click functions. PROpwr can assist researchers to analyze and calculate power and sample size for PRO endpoints in clinical trials without prior programming knowledge.
期刊介绍：
The Journal of Biopharmaceutical Statistics, a rapid publication journal, discusses quality applications of statistics in biopharmaceutical research and development. Now publishing six times per year, it includes expositions of statistical methodology with immediate applicability to biopharmaceutical research in the form of full-length and short manuscripts, review articles, selected/invited conference papers, short articles, and letters to the editor. Addressing timely and provocative topics important to the biostatistical profession, the journal covers:
Drug, device, and biological research and development;
Drug screening and drug design;
Assessment of pharmacological activity;
Pharmaceutical formulation and scale-up;
Preclinical safety assessment;
Bioavailability, bioequivalence, and pharmacokinetics;
Phase, I, II, and III clinical development including complex innovative designs;
Premarket approval assessment of clinical safety;
Postmarketing surveillance;
Big data and artificial intelligence and applications.
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