Integration of Electronic Pathology Reporting with Clinical Trial Matching for Advanced Prostate Cancer - Beyond the Abstract
We sought to leverage population-level reporting to introduce clinical trial opportunities to a diverse population of men with advanced prostate cancer. The California Cancer Registry mandated electronic pathology reporting (e-path) of structured data elements from pathologists diagnosing cancer thereby creating an opportunity to identify and approach patients rapidly.
We integrated e-path allowing population-based early engagement with patients and our online clinical trial matching tool (called Trial LibraryTM). Trial LibraryTM is a patient-centered clinical trial matching tool built using human-centered design. We hypothesized that the novel combination of Trial LibraryTM with e-path would improve matching of underrepresented prostate cancer patients into clinical trials at time of diagnosis. To test this hypothesis, we performed a nonrandomized feasibility study among patients with a new pathologic diagnosis of high-risk prostate cancer, defined as a Gleason Score ≥8. Eligible patients were sent recruitment materials and enrolled patients were introduced to Trial LibraryTM. In the study, 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 prostate cancer. The majority (62%) of participants reported that Trial LibraryTM increased their interest in clinical trial participation.
We concluded that leveraging structured electronic pathology reporting to a population-based cancer registry to recruit men with high risk prostate cancer to clinical research is feasible and acceptable. We observed that e-path can be integrated with an online clinical trial matching tool, Trial LibraryTM. However, although we aimed to target racial/ethnic minority and under-served patients, participants still over-represent white and higher socioeconomic status patients. We encountered many challenges with the new e-path early case ascertainment system that likely contributed to difficulties in targeting minority and under-served patients. Thus, as a result of our pilot study, we recommend: 1) e-path should incorporate patient sociodemographic information; 2) future studies should prioritize recruitment from reporting facilities that serve more diverse patient populations; 3) patient navigation or similar support used in combination with Trial LibraryTM can help to increase engagement; 4) recruitment approaches should acknowledge and incorporate strategies to address medical mistrust, structural racism, and social determinants of health.
Written by: Hala T. Borno, MD; Christine Duffy, MPH; Sylvia Zhang MS; Alison J. Canchola, MS; Zinnia Loya; Todd Golden; Debora L. Oh, PhD; Anobel Y. Odisho, MD, MPH; Scarlett Gomez, MPH, PhD
Department of Medicine, Division of Hematology/Oncology, 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; 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.
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