title: Comparison of competing risks failure time methods and time-independent methods for assessing strain variations in vaccine protection.
abstract: In a preventive vaccine efficacy trial of a vaccine for a genotypically and phenotypically diverse pathogen, it is important to assess if and how vaccine protection against infection or disease varies with characteristics of the exposing pathogen. Gilbert, Self and Ashby developed statistical methods for this problem when the outcome data are counts of the number of vaccinated and unvaccinated trial participants infected by each pathogen strain. However, in many vaccine trials time-to-case information is available, and the extent to which this information improves investigation of differential vaccine protection is unclear. We describe how cause-specific proportional hazards models and other popular competing risks failure time techniques can be applied to this problem. This includes new results on the assumptions required for these methods to give valid inferences about strain-specific vaccine efficacy, and a comparison of theoretical and finite-sample properties between these methods and the time-independent methods. Theoretical considerations, a cholera vaccine trial example, and an extensive simulation study of a human immunodeficiency virus type 1 (HIV-1) vaccine trial show that information about failure times does not appreciably improve estimation or testing unless the pathogen has a high attack rate and the relative prevalence of pathogen strains shifts substantially during the trial follow-up period. An important implication is that practically optimal evaluation of strain-specific vaccine efficacy in HIV-1 vaccine trials will not require knowledge of infection times.
authors: Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, Massachusetts 02115, USA. pgilbert@hsph.harvard.edu
authors: P B
authors: PB
authors: Gilbert
mesh_terms: D016915:AIDS Vaccines / Q000276:immunology / Q000592:standards; D000328:Adult; D001459:Bangladesh / Q000453:epidemiology; D001699:Biometry / Q000379:methods; D002675:Child, Preschool; D002771:Cholera / Q000276:immunology / Q000517:prevention & control; D022121:Cholera Vaccines / Q000276:immunology / Q000592:standards; D002986:Clinical Trials as Topic; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D015658:HIV Infections / Q000276:immunology / Q000517:prevention & control; D006801:Humans; D015995:Prevalence; D016016:Proportional Hazards Models; D018570:Risk Assessment / Q000379:methods; D015819:Substance Abuse, Intravenous / Q000276:immunology; D013785:Thailand / Q000453:epidemiology; D013997:Time Factors; D014612:Vaccines / Q000276:immunology / Q000592:standards*
chemical_list: D016915:AIDS Vaccines; D022121:Cholera Vaccines; D014612:Vaccines