Mark-specific hazard ratio model with missing multivariate marks

Lifetime Data Analysis volume 22, pages606–625(2016)Cite this article

Abstract

An objective of randomized placebo-controlled preventive HIV vaccine efficacy (VE) trials is to assess the relationship between vaccine effects to prevent HIV acquisition and continuous genetic distances of the exposing HIVs to multiple HIV strains represented in the vaccine. The set of genetic distances, only observed in failures, is collectively termed the ‘mark.’ The objective has motivated a recent study of a multivariate mark-specific hazard ratio model in the competing risks failure time analysis framework. Marks of interest, however, are commonly subject to substantial missingness, largely due to rapid post-acquisition viral evolution. In this article, we investigate the mark-specific hazard ratio model with missing multivariate marks and develop two inferential procedures based on (i) inverse probability weighting (IPW) of the complete cases, and (ii) augmentation of the IPW estimating functions by leveraging auxiliary data predictive of the mark. Asymptotic properties and finite-sample performance of the inferential procedures are presented. This research also provides general inferential methods for semiparametric density ratio/biased sampling models with missing data. We apply the developed procedures to data from the HVTN 502 ‘Step’ HIV VE trial.

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Acknowledgments

The authors thank the participants, investigators, and sponsors of the HVTN 502 Step HIV vaccine trial. Research reported in this publication was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Numbers UM1AI068635 and R37AI054165 and by the Bill and Melinda Gates Foundation (BMGF) Award Number OPP1110049. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or BMGF.

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Affiliations

  1. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Mail Stop M2-C200, Seattle, WA, 98109, USA

    Michal Juraska

  2. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, and Department of Biostatistics, University of Washington, 1100 Fairview Avenue North, Mail Stop M2-C200, Seattle, WA, 98109, USA

    Peter B. Gilbert

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  1. Michal Juraska
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Correspondence to Michal Juraska.

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Ethical statement

Institutional review board approval for the HVTN 502 Step study was obtained at all study sites. The study was undertaken in conformance with applicable local and country requirements, and participants gave written informed consent.

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Juraska, M., Gilbert, P.B. Mark-specific hazard ratio model with missing multivariate marks. Lifetime Data Anal 22, 606–625 (2016). https://doi.org/10.1007/s10985-015-9353-9

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Keywords

  • Augmented inverse probability weighting
  • Biased sampling model
  • Competing risks
  • Cox model
  • Density ratio model
  • Missing data
  • Semiparametric model