Mobile Clinical Trial Matching Technology in Medical Oncology Clinic: A Pilot Feasibility Study

Abstract

PURPOSE The internet is a common source of health information for patients and can be leveraged to provide patient-facing clinical trial information. This pilot study integrated an online prostate cancer clinical trial matching technology, called Trial Library (TL), in an academic medical oncology clinic from February 2019 to April 2021. PATIENTS AND METHODS This is a single-arm interventional pilot study among patients with a known prostate cancer diagnosis. Participants were given access to TL before seeing a provider. The primary and secondary study end points were the overall satisfaction with TL and the proportion of participant-initiated clinical trial discussion with providers after exposure to TL, respectively. The null hypothesis or true satisfaction rate (acceptability) was tested against a one-sided alternative and was rejected if 29 or more satisfactions were observed. RESULTS Among 272 patients approached, 66 provided informed consent to participate in the study. The mean age was 70.8 years (standard deviation = 7.9). The majority of participants were White (82%) and had metastases present at the time of enrollment (65%). The baseline clinical trial discussion rate ascertained via electronic medical record review was 28%. After accessing TL, a significantly larger proportion of participants (48.5%) discussed clinical trials during the clinic visit ( P = .007), half of which were patient-initiated. The majority of participants indicated that TL increased their interest in clinical trials (68.2%); however, satisfaction/extreme satisfaction with the technology was 38%. CONCLUSION Access to TL resulted in a significant increase in patient-initiated discussions regarding clinical trials and an increase in interest in clinical trial participation although these data do not address if this resulted in increased accrual to clinical trials. The satisfaction rate did not meet the target to reject the null hypothesis, suggesting the need for iterative design of patient-facing health information.