Evidence map›Paper›PMID 25752266›Full record

ArticleStatistics in medicine2015

Analysis of repeated low-dose challenge studies.

Tracy L Nolen, Michael G Hudgens, Pranab K Senb, Gary G Koch

Abstract read
In one paragraph

Article in Statistics in medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 15 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Tracy L NolenRTI International, The Research Triangle Park, NC, 27709, U.S.A.
Michael G Hudgens
Pranab K Senb
Gary G Koch
University of North Carolina at Chapel Hill · USRTI International · US

Funding

Virology, Immunology, and Microbiology CoreP30AI050410 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVID M. MARGOLIS · 2001 to 2026
$76.9M
Statistical Methods in HIV Vaccine Efficacy TrialsR37AI054165 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Peter B. Gilbert · 2010 to 2026
$6.7M
NIAID NIH HHS P30 AI050410NIAID NIH HHS P30 AI50410NIAID NIH HHS R37 AI054165
6 · The paper itself

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.

Indexed as

Dose-Response Relationship, DrugAnimalsComputer SimulationDisease Models, AnimalDrug Evaluation, PreclinicalHumansMacaca mulattaMonte Carlo MethodSAIDS VaccinesSimian Acquired Immunodeficiency SyndromeSimian Immunodeficiency VirusSAIDS VaccinesHIVmacaquepermutation testpre-clinical studiesrandomization inferencevaccine

Identifiers

PMID25752266
PMCPMC4420691
OpenAlexW2105685363

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.