Evidence map›Paper›PMID 40044489›Full record

ArticleInternational journal of epidemiology2025

Software Application Profile: CaseCohortCoxSurvival-an R package for case-cohort inference for relative hazard and pure risk under the Cox model.

Lola Etiévant, Mitchell H Gail

Abstract read
In one paragraph

Article in International journal of epidemiology, 2025. 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

2 authors.

Lola EtiévantDivision of Cancer Epidemiology and Genetics, Biostatistics Branch, National Cancer Institute, Rockville, MD, USA.ORCID 0000-0001-7562-3550
Mitchell H GailDivision of Cancer Epidemiology and Genetics, Biostatistics Branch, National Cancer Institute, Rockville, MD, USA.ORCID 0000-0002-3919-3263

Funding

National Cancer Institute, National Institutes of Health, USANCI NIH HHS
6 · The paper itself

Abstract

motivationThe case-cohort design only requires covariate measurements for individuals experiencing the outcome of interest (cases) and individuals in a subcohort randomly selected from the cohort. Stratified subcohort sampling and calibration of the design weights increase efficiency of relative hazard and pure risk estimates, but require specifically adapted variance estimators. Yet, the 'robust' variance formula is often inappropriately used with stratified case-cohort data. Also, weight calibration and pure risk estimation are underused, possibly because of the lack of convenient software. IMPLEMENTATION: An influence-based method for inference of case-cohort Cox model relative hazards and pure risks is implemented in the CaseCohortCoxSurvival R package. GENERAL FEATURES: CaseCohortCoxSurvival allows estimation of parameter and variance of Cox model relative hazards and pure risks from case-cohort data. It can handle stratified subcohort sampling and calibrate the design weights. Both features are properly accounted for in the variance estimation. AVAILABILITY: CaseCohortCoxSurvival is available on the Comprehensive R Archive Network at [https://cran.r-project.org/package=CaseCohortCoxSurvival].

Indexed as

SoftwareCohort StudiesHumansProportional Hazards ModelsRisk AssessmentCase-cohort inferencedesign weight calibrationR packagestratificationtwo-phase samplingvariance estimation

Identifiers

PMID40044489
PMCPMC11882301

What OpenQuestion holds

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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.