Estimating the effectiveness in HIV prevention trials by incorporating the exposure process: application to HPTN 035 data.
Estimating the effectiveness of a new intervention is usually the primary objective for HIV prevention trials. The Cox proportional hazard model is mainly used to estimate effectiveness by assuming that participants share the same risk under the covariates and the risk is always non-zero. In fact, the risk is only non-zero when an exposure event occurs, and participants can have a varying risk to transmit due to varying patterns of exposure events. Therefore, we propose a novel estimate of effectiveness adjusted for the heterogeneity in the magnitude of exposure among the study population, using a latent Poisson process model for the exposure path of each participant. Moreover, our model considers the scenario in which a proportion of participants never experience an exposure event and adopts a zero-inflated distribution for the rate of the exposure process. We employ a Bayesian estimation approach to estimate the exposure-adjusted effectiveness eliciting the priors from the historical information. Simulation studies are carried out to validate the approach and explore the properties of the estimates. An application example is presented from an HIV prevention trial.
Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, M2-C200, Seattle, Washington 98109, U.S.A.
Jingyang
J
Zhang
Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, M2-C200, Seattle, Washington 98109, U.S.A.|Department of Biostatistics, University of Washington, Seattle, Washington 98109, U.S.A.
Elizabeth R
ER
Brown
D000349:Africa / Q000453:epidemiology; D019380:Anti-HIV Agents / Q000627:therapeutic use*; D001499:Bayes Theorem; D015982:Bias; D015986:Confounding Factors, Epidemiologic; D003627:Data Interpretation, Statistical; D015658:HIV Infections / Q000453:epidemiology* / Q000517:prevention & control*; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000379:methods*; D065129:Pre-Exposure Prophylaxis / Q000706:statistics & numerical data*; D015995:Prevalence; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods; D012680:Sensitivity and Specificity; D012725:Sexual Behavior / Q000706:statistics & numerical data*; D016896:Treatment Outcome
D019380:Anti-HIV Agents
HIV prevention; Hierarchical models; Intercourse; Markov chain Monte Carlo; Per‐exposure effectiveness; Zero‐inflated gamma