Evidence map›Paper›PMID 39512808›Full record

ArticleGlobal epidemiology2024

Estimating effects of aging and disease progression in current and former smokers using longitudinal models.

Matthew Strand, Surya Bhatt, Matthew Moll, David Baraghoshi

Abstract read
In one paragraph

Article in Global epidemiology, 2024. 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
–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

1 citing paper in PubMed.

  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

4 authors.

Matthew StrandDivision of Biostatistics and Bioinformatics, National Jewish Health, Denver, CO, United States.
Surya BhattLung Health Center, University of Alabama at Birmingham, Birmingham, AL, United States.
Matthew MollChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, United States.
David BaraghoshiDivision of Biostatistics and Bioinformatics, National Jewish Health, Denver, CO, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To separate estimates of mean change in a health outcome into components of aging and disease progression for different severity groups of chronic obstructive pulmonary disease (COPD). Study design and methods: A longitudinal model can be used to estimate mean change in a health outcome over time. Methods to separate this change into portions due to aging and disease progression are discussed, including conditions that allow for accurate estimation. Linear mixed models were used to estimate these changes for Results: Based on an analysis of 4967 subjects, age-related loss in FEV Discussion: Effects of disease progression separate from aging can be estimated in observational studies, although care should be taken in order to make sure assumptions involving this separation are reasonable for a given study. This article demonstrates methods to estimate such effects using temporal changes in lung function for subjects in the COPDGene study.

Indexed as

AgingDisease progressionFEV1LongitudinalMixed modelsObservational study

Identifiers

PMID39512808
PMCPMC11541677

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.