Format

Send to

Choose Destination
Stat Med. 2015 May 30;34(12):1981-92. doi: 10.1002/sim.6462. Epub 2015 Mar 9.

Analysis of repeated low-dose challenge studies.

Author information

1
RTI International, The Research Triangle Park, NC, 27709, U.S.A.

Abstract

Preclinical evaluation of candidate human immunodeficiency virus (HIV) vaccines entails challenge studies whereby non-human primates such as macaques are vaccinated with either an active or control vaccine and then challenged (exposed) with a simian-version of HIV. Repeated low-dose challenge (RLC) studies in which each macaque is challenged multiple times (either until infection or some maximum number of challenges is reached) are becoming more common in an effort to mimic natural exposure to HIV in humans. Statistical methods typically employed for the testing for a vaccine effect in RLC studies include a modified version of Fisher's exact test as well as large sample approaches such as the usual log-rank test. Unfortunately, these methods are not guaranteed to provide a valid test for the effect of vaccination. On the other hand, valid tests for vaccine effect such as the exact log-rank test may not be easy to implement using software available to many researchers. This paper details which statistical approaches are appropriate for the analysis of RLC studies, and how to implement these methods easily in SAS or R.

KEYWORDS:

HIV; macaque; permutation test; pre-clinical studies; randomization inference; vaccine

PMID:
25752266
PMCID:
PMC4420691
DOI:
10.1002/sim.6462
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for PubMed Central
Loading ...
Support Center