Integration of electronic pathology reporting with clinical trial matching for advanced prostate cancer

This article was originally published here

Urol Oncol. 2021 Jan 5:S1078-1439(20)30639-6. doi: 10.1016/j.urolonc.2020.12.010. Online ahead of print.

ABSTRACT

INTRODUCTION: Racial/ethnic diversity in prostate cancer (CaP) clinical trials (CTs) is essential to address CaP disparities. California Cancer Registry mandated electronic reporting (e-path) of structured data elements from pathologists diagnosing cancer thereby creating an opportunity to identify and approach patients rapidly. This study tested the utility of an online CT matching tool (called Trial Library) used in combination with e-path to improve matching of underrepresented CaP patients into CTs at time of diagnosis.

METHODS: This was a nonrandomized, single-arm feasibility study among patients with a new pathologic diagnosis of high-risk CaP (Gleason Score ≥8). Eligible patients were sent recruitment materials and enrolled patients were introduced to Trial Library.

RESULTS: A total of 419 case listings were assessed. Patients were excluded due to physician contraindication, not meeting baseline eligibility, or unable to be reached. Final participants (N = 52) completed a baseline survey. Among study participants, 77% were White, 10% were Black/Hispanic/Missing, and 14% were Asian. The majority of the study participants were over 65 years of age (81%) and Medicare insured (62%). Additionally, 81% of participants reported using the Internet to learn about CaP. The majority (62%) of participants reported that Trial Library increased their interest in CT participation.

CONCLUSIONS: The current study demonstrated that leveraging structured e-path data reporting to a population-based cancer registry to recruit men with high risk CaP to clinical research is feasible and acceptable. We observed that e-path may be linked with an online CT matching tool, Trial Library. Future studies will prioritize recruitment from reporting facilities that serve more racially/ethnically diverse patient populations.

PMID:33419644 | DOI:10.1016/j.urolonc.2020.12.010