Abstract
BACKGROUND: To investigate various patient-level variables, specifically socioeconomic status, as risk factors for withdrawal in a recently completed clinical study. We specifically investigated a non-interventional prospective study assessing the role of novel imaging as a biomarker for cancer upgradation in prostate cancer for this objective. METHODS: In this retrospective analysis, we assessed the association between various patient-level factors including clinic-demographic factors, socioeconomic status, and the number of non-adherences with the participants' retention or withdrawal from the study. For socioeconomic status (SES), we used the zip code-based Economic Innovation Group Distressed Community Index (DCI) which classifies into five even distress tiers: prosperous, comfortable, mid-tier, at-risk, or distressed. Low SES was defined as those with a DCI Distress tier of at-risk or distressed. We compared values between the two retention and withdrawal groups using t-test, chi-square test, and logistic regression analysis. RESULTS: Of 273 men screened, 123 men were enrolled. Among them, 86.2% (106/123) retained through the study whereas 13.8% (17/123) withdrew from the study. The mean (SD) age was 64 (6.4) years. Overall, 31.7% (39/123) were Hispanics and 24.3% (30/123) were African Americans. The median (IQR) DCI score was 34 (10.3, 68.1) and 30.8% (38/123) of patients belonged to low SES. The median DCI score in participants who retained in the study was statistically similar to those who withdrew from the study (p=0.4). Neither the DCI tiers (p=0.7) nor the low SES (p=0.9) were associated with participants' retention or withdrawal of the study. In terms of non-adherence, all participants in the withdrawn group had at least one non-adherent event compared to 48.1% in the retained group (p<0.001). Repetitive non-adherence was significantly higher in participants who withdrew from the study vs those who retained in the study [88.2% vs 16.9%, p <0.001]. On multivariate logistic regression analysis, the number of non-adherences (OR=12.5, p<0.001) and not DCI (OR=0.99, p=0.7) appeared to be an independent predictor for participants' retention or withdrawal from the study. CONCLUSIONS: Expanding diverse inclusion and limiting withdrawal with real-time non-adherence monitoring will lead to more efficient clinical research and greater generalizability of results.