ABSTRACTHost adaptive immune responses may protect against infection or disease when a pathogen is repeatedly encountered. The hazard ratio of infection or disease, given previous infection, is typically sought to estimate the strength of protective immunity. However, variation in individual exposure or susceptibility to infection may introduce frailty bias, whereby a tendency for infections to recur among individuals with greater risk confounds the causal association between previous infection and susceptibility. We introduce a self-matched “case-only” inference method to control for unmeasured individual heterogeneity, making use of negative-control endpoints not attributable to the pathogen of interest. To control for confounding, this method compares event times for endpoints due to the pathogen of interest and negative-control endpoints during counterfactual risk periods, defined according to individuals’ infection history. We derive a standard Mantel-Haenszel (matched) odds ratio conveying the effect of prior infection on time to recurrence. We compare performance of this approach to several proportional hazards modeling frameworks, and estimate statistical power of the proposed strategy under various conditions. In an example application, we use the proposed method to re-estimate naturally-acquired protection against rotavirus gastroenteritis using data from previously-published cohort studies. This self-matched negative-control design may present a flexible alternative to existing approaches for analyzing naturally-acquired immunity, as well as other exposures affecting the distribution of recurrent event times.
Dependence modeling for recurrent event times subject to right‐censoring with D‐vine copulas
