Evidence map›Paper›PMID 26763556›Full record

ArticleStatistics in medicine2016

Evaluating predictors of competing risk outcomes when censoring depends on time-dependent covariates, with application to safety and efficacy of HIV treatment.

Judith J Lok, Michael D Hughes

Open access · greenAbstract read
In one paragraph

Article in Statistics in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 41% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
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

2 authors at 1 institution in 1 country.

Judith J LokDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, MA, 65502115, U.S.A.
Michael D HughesDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Huntington Avenue, Boston, MA, 65502115, U.S.A.
Harvard University · US

Funding

Statistical and Data Management Center (SDMC), AIDS Clinical Trials Group (ACTG)UM1AI068634 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Marlene Ann Cooper, Michael David Hughes · 2011 to 2026
$246.6M
Statistical and Data Management Center for the AIDS Clinical Trials GroupU01AI068634 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI HUGHES, MICHAEL DAVID · 2006 to 2010
$71.9M
STATISTICAL METHODS IN AIDS RESEARCHR37AI024643 · NIAID · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI HUGHES, MICHAEL DAVID · 2001 to 2010
$2.8M
STATISTICAL METHODS IN AIDS RESEARCHR01AI024643 · NIAID · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI HUGHES, MICHAEL DAVID · 1987 to 2014
$1.7M
NIAID NIH HHS R01 AI024643NIAID NIH HHS R37 AI024643NIAID NIH HHS U01 AI068634NIAID NIH HHS UM1 AI068634
6 · The paper itself

Abstract

We propose a prediction model for the cumulative incidence functions of competing risks, based on a logit link. Because of a concern about censoring potentially depending on time-varying covariates in our motivating human immunodeficiency virus (HIV) application, we describe an approach for estimating the parameters in the prediction models using inverse probability of censoring weighting under a missingness at random assumption. We then illustrate the application of this methodology to identify predictors of the competing outcomes of virologic failure, an efficacy outcome, and treatment limiting adverse event, a safety outcome, among human immunodeficiency virus-infected patients first starting antiretroviral treatment. Copyright © 2016 John Wiley & Sons, Ltd.

Indexed as

Models, StatisticalAnti-HIV AgentsData Interpretation, StatisticalHIV InfectionsHumansProbabilityRisk AssessmentTime FactorsTreatment FailureTreatment OutcomeAnti-HIV Agentscompeting risksHIV/AIDSlogit linkmissing at randompersonalized medicinesafety and efficacy

Identifiers

PMID26763556
PMCPMC4853244
OpenAlexW2269228786

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.