Implementation of clinician-facing prostate cancer therapeutic clinical trial decision tool at a comprehensive cancer center.

Abstract

19 Background: The conventional model for clinical trial (CT) recruitment relies on clinicians to identify potential CTs for patients. Internet technology can be leveraged as a decision tool to enhance the CT recruitment process. Methods: An internet-based, clinician-facing decision tool was developed in genitourinary medical oncology clinic at a Comprehensive Cancer Center (CCC). The tool provided access to a real-time, tailored list of treatment CTs actively recruiting patients with PCa at the CCC based on clinical characteristics inputted by user. The clinical data was summarized. All clinicians (n = 9) with access to the decision tool completed a survey to assess effectiveness and satisfaction. Results: During a 9-month pilot period, user engagement increased from a baseline of 36 to 136 cases per month, with a total of 644 cases overall. Among cases, 525 had metastatic disease, 436 of which were metastatic castration resistant PCa (mCRPC). Overall, 145 cases were classified as having oligo-metastatic ( < = 3) PCa, 93 of whom were also mCRPC. Prior treatments received included abiraterone in hormone-sensitive PCa (HSPC 19.3%, CRPC 48.7%); enzalutamide (HSPC 3.7%, CRPC 34.9%) apalutamide (HSPC 1.3%, CRPC 6.9%), taxane (HSPC 17.2%, CRPC 27.8%), radium-223 (6.1%), sipuleucel-T (18.3%), parp inhibitors (4%), or check-point inhibitors (6%). Clinician-inputted genomics of cases included CDK12 (20.9%), MSI-high disease (13.6%), BRCA1/2 (32.7%), ARID1a (7.3%), ATM (21.8%), FANCA (4.5%), or CHEK2 (6.4%) and HDAC2 (0.9%). Among survey respondents, use of tool in clinic was reported sometimes (22%), often/always (78%). Results of decision tool were reported to inform treatment sometimes (22%) or often/always (78%). Respondents confidence in often/always knowing all available CTs increased from a baseline of 0% to 89%, and 89% of users reported very/complete satisfaction with decision tool. Conclusions: An internet-based CT decision tool for provides detailed clinical characteristics of patients for whom CTs are being considered at a CCC. Clinicians using the decision tool report high levels of satisfaction. The tool was effective in increasing confidence in knowledge of current available CTs. Data gathered in the decision tool may inform future CT development. Future research with expanded use of decision tool among referring clinicians will assess its impact in promoting diversity among CT participants.