Efficient and equitable recruitment into clinical trials using the PREDICTEE algorithm
Channel: Alexander Gutfraind
Date: 2023-01-26

Can we make clinical trials faster, less expensive and more representative?
Abstract of our recent study follows. 
Background: Development of a vaccine for HCV remains a priority for preventing further transmission, especially among high risk groups such as people who inject drugs (PWID). As new vaccine candidates require well-designed clinical trials, limitations such as immense costs and disparities in trial access for certain demographic groups pose a potential barrier to conducting a successful HCV vaccine clinical trial. Here we address these issues using computational modeling, and propose a strategy for robust HCV vaccine trials termed PREDICTEE - Predictive Recruitment and Enrichment method balancing Demographics and Incidence for Clinical Trial Equity and Efficiency. Methods: PREDICTEE identifies and recruits PWID with a high incidence of HCV, thereby decreasing required sample size and associated costs. It utilizes a survival analysis model that is applied to candidates’ demographic, network, and injection characteristics, collected via questionnaire. In turn, the model outputs a probability the candidate will be infected with HCV during the trial. The decision to recruit considers both the candidate’s predicted incidence and the vaccine’s target population. To evaluate the sample size and equity benefits of PREDICTEE, we first generated a recruitment pool of PWID via a 10-year simulation using the HepCEP model. PREDICTEE recruitment was then simulated using this pool with susceptible Chicago PWID as the target population. We compare these results to conventional recruitment of high-risk PWID in terms of sample size, representation, and number of candidates needed to screen. Results. Our simulations expressed a reduction in required sample size from 802 (95%: 642–1010) with conventional methods to 280 (95%: 206–398) with PREDICTEE. Trial cohorts also more closely resembled the susceptible PWID population in age, sex and race, as illustrated by an increase in participation-to-prevalence ratio from .475 (95%: .356–.568) to .772 (95%: .522–.928). These benefits were achieved by screening 12% (95: 3%-26%) more candidates compared to high-risk PWID recruitment. Similar benefits were observed even in scenarios with dissimilar target populations or when more demographics were considered. Appendix Log Graphs Spreadsheet AASLD 2022 Cover letter 4 Conclusion: PREDICTEE presents a promising strategy for recruitment into HCV clinical trials, achieving a reduction in sample size, while ensuring equitable trial recruitment.

Code is available in https://github.com/sashagutfraind/vaccinetrials/
Full paper: in review