Faculty Collaboration Database

Trial prospector: matching patients with cancer research studies using an automated and scalable approach. Cancer Inform 2014;13:157-66

Date

12/17/2014

Pubmed ID

25506198

Pubmed Central ID

PMC4259509

DOI

10.4137/CIN.S19454

Scopus ID

2-s2.0-84919391508   13 Citations

Abstract

Cancer is responsible for approximately 7.6 million deaths per year worldwide. A 2012 survey in the United Kingdom found dramatic improvement in survival rates for childhood cancer because of increased participation in clinical trials. Unfortunately, overall patient participation in cancer clinical studies is low. A key logistical barrier to patient and physician participation is the time required for identification of appropriate clinical trials for individual patients. We introduce the Trial Prospector tool that supports end-to-end management of cancer clinical trial recruitment workflow with (a) structured entry of trial eligibility criteria, (b) automated extraction of patient data from multiple sources, (c) a scalable matching algorithm, and (d) interactive user interface (UI) for physicians with both matching results and a detailed explanation of causes for ineligibility of available trials. We report the results from deployment of Trial Prospector at the National Cancer Institute (NCI)-designated Case Comprehensive Cancer Center (Case CCC) with 1,367 clinical trial eligibility evaluations performed with 100% accuracy.

Author List

Sahoo SS, Tao S, Parchman A, Luo Z, Cui L, Mergler P, Lanese R, Barnholtz-Sloan JS, Meropol NJ, Zhang GQ

Author

Jake Luo Ph.D. Associate Professor; Director, Center for Biomedical Data and Language Processing (BioDLP) in the Health Informatics & Administration department at University of Wisconsin - Milwaukee