PROpwr: a Shiny R application to analyze patient-reported outcomes data and estimate power

ABSTRACT

Abstract 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.

KEYWORDS:

• PRO
• power
• clinical trials
• Shiny app
• item response theory
• Bayesian

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors thank the University of Kansas Cancer Center P30CA168524 for providing research funding to this project.