Simulating the contribution of a biospecimen and clinical data repository in a phase II clinical trial: A value of information analysis. (August 2016)

• Record Type: Journal Article
• Authors: Craig, Benjamin M; Han, Gang; Munkin, Murat K; Fenstermacher, David
• Other Names: Lawson Andrew B guest-editor.; Lee Duncan guest-editor.; MacNab Ying guest-editor.
• Is Part Of: Statistical methods in medical research. Volume 25:Number 4(2016:Aug.)
• Page Start: 1303
• Page End: 1312
• Publication Date: 2016-08
• Subjects: value of information -- clinical trials -- phase II -- neoplasms -- biorepository; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280213480282
• Languages: English
• ISSNs: 0962-2802

Abstract

The potential contributions of a centralized data warehouse or repository in clinical research include the expedited accrual of subjects for phase II trials. Understanding the contribution of data warehouses that integrate clinical, biospecimen, and molecular data for the conduct of clinical trials is essential to inform private and public decisions on resource allocation and investment. We conducted a value of information analysis using data from recent trials at the Moffitt Cancer Center and simulated the potential reductions in trial size due to possible alternative scenarios of expedited accrual. In this study, we compared alternative data sets using a single model to assess value of information. Our findings suggest that the reductions in trial size range from 0% to 43%, depending on the amount of censoring in overall survival. The ability to expedite the accrual of patients for clinical trial studies using large data repositories that store data on inclusion/exclusion criteria and response to standard of care therapies demonstrated significant improvement in reducing the number of subjects needed to achieve similar end-results, as evaluated using value of information analysis with a limited number of parameters and a parsimonious model of overall survival.