Evidence map›Paper›PMID 39115164›Full record

ArticleClinical trials (London, England)2024

Statistical approaches for component-wise censored composite endpoints.

Anne Eaton

Abstract read
In one paragraph

Article in Clinical trials (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Anne EatonDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0001-5900-9745

Funding

Women's CancerP30CA077598 · NCI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI Jeffrey S. Miller · 1998 to 2026
$100.4M
NCI NIH HHS P30 CA077598
6 · The paper itself

Abstract

Composite endpoints defined as the time to the earliest of two or more events are often used as primary endpoints in clinical trials. Component-wise censoring arises when different components of the composite endpoint are censored differently. We focus on a composite of death and a non-fatal event where death time is right censored and the non-fatal event time is interval censored because the event can only be detected during study visits. Such data are most often analysed using methods for right censored data, treating the time the non-fatal event was first detected as the time it occurred. This can lead to bias, particularly when the time between assessments is long. We describe several approaches for estimating the event-free survival curve and the effect of treatment on event-free survival via the hazard ratio that are specifically designed to handle component-wise censoring. We apply the methods to a randomized study of breastfeeding versus formula feeding for infants of mothers infected with human immunodeficiency virus.

Indexed as

Endpoint DeterminationHIV InfectionsRandomized Controlled Trials as TopicBiasBreast FeedingData Interpretation, StatisticalFemaleHumansInfantInfant FormulaModels, StatisticalProportional Hazards ModelsResearch DesigncensoringComposite endpointsprogression-free survivaltime-to-event

Identifiers

PMID39115164
PMCPMC11533687

What OpenQuestion holds

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Registered trials

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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.