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.
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.
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.
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.
Urologic oncology. 2021 Jan 05 [Epub ahead of print]
Hala T Borno, Christine Duffy, Sylvia Zhang, Alison J Canchola, Zinnia Loya, Todd Golden, Debora L Oh, Anobel Y Odisho, Scarlett Gomez
Department of Medicine, Division of Hematology/Oncology, University of California San Francisco, San Francisco, CA; Helen Diller Family Comprehensive Cancer Center, San Francisco, CA. Electronic address: ., Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA; Greater Bay Area Cancer Registry, University of California San Francisco, San Francisco, CA., Helen Diller Family Comprehensive Cancer Center, San Francisco, CA., Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA., Helen Diller Family Comprehensive Cancer Center, San Francisco, CA; Department of Urology, University of California San Francisco, San Francisco, CA; Center for Digital Health Innovation, University of California, San Francisco, CA., Helen Diller Family Comprehensive Cancer Center, San Francisco, CA; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA; Greater Bay Area Cancer Registry, University of California San Francisco, San Francisco, CA.
PubMed http://www.ncbi.nlm.nih.gov/pubmed/33419644