Assessing pharmacokinetic marker correlates of outcome, with application to antibody prevention efficacy trials

Abstract

The Antibody Mediated Prevention efficacy trials are the first studies to evaluate whether passive administration of a broadly neutralizing monoclonal antibody can prevent human immunodeficiency virus (HIV) acquisition. The trials randomize 4600 HIV‐negative volunteers to receive 10 infusions of the monoclonal antibody VRC01 or placebo. The primary objective compares the incidence of HIV infection between the study groups. The secondary objective assesses whether and how a marker defined as the serum concentration of VRC01 over time associates with the instantaneous rate of HIV infection, using a two‐phase sampling design, a pharmacokinetic model for the time‐concentration curve, and an estimator of HIV infection times. While a Cox model with a time‐dependent covariate constitutes an important approach to this problem, the low interindividual versus intraindividual marker variability limits its power, motivating us to develop two alternative methods that condition on outcome status: (1) an indirect method that checks whether HIV‐infected cases have unexpectedly long times from the most recent infusion to the estimated infection date and (2) a direct method that checks whether the marker itself is unexpectedly low at estimated infection dates. In simulations and a pseudo Antibody Mediated Prevention application, we find that method (2) (but not (1)) has greater power than the Cox model. We also find that the quality of the infection time estimator majorly impacts method performance, and thus, incorporating details of an optimized estimator is critical. The methods apply more generally for assessing a time‐dependent longitudinal marker as a correlate of risk when the marker trajectory is modeled pharmacokinetically.

Pharmacokinetics and predicted neutralisation coverage of VRC01 in HIV-uninfected participants of the Antibody Mediated Prevention (AMP) trials

“…One key secondary objective of AMP is to assess, through a case-control study, marker correlates (or predictors) of instantaneous HIV-1 risk (see [21] and [23] for further details), e.g. VRC01 serum concentration and serum neutralisation titre to panels of HIV-1 isolates.…”

Generating Survival Times Using Cox Proportional Hazards Models with Cyclic and Piecewise Time-Varying Covariates

“…This further confirms that data simulated using our proposed method maintain the intended nature and effect size of the cyclic and piecewise time-varying covariate. In addition, our proposed methods have been applied to simulate survival data in the evaluation of pharmacokinetics marker correlates of outcome [31]. popPK models were used to estimate the marker value over time [2].…”

Review of preventative HIV vaccine clinical trials in South Africa

“… 2015 [ 55 ] IMPAACT P1112 (I) VRC01, VRC01LS or VRC07-523LS, monoclonal antibodies in single or multiple doses N = 40 HIV-exposed infants, SA, Zimbabwe, US Single and multiple doses of subcutaneous VRC01 were generally safe and well tolerated in infants. 2016 [ 59 ] HVTN 703 (IIb) VRC01, a monoclonal antibody, at M0, 2, 4, 6, 8, 10, 12, 14, 16, 18 N = 1926 at-risk women, SA, Malawi, Mozambique, Zambia, Zimbabwe Infusions concluded. Follow-up ongoing.…”