Evidence map›Paper›PMID 29771274›Full record

Observational studyAmerican journal of epidemiology2018

Identification of Chronic Obstructive Pulmonary Disease Axes That Predict All-Cause Mortality: The COPDGene Study.

Gregory L Kinney, Stephanie A Santorico, Kendra A Young, Michael H Cho, Peter J Castaldi, Raul San José Estépar, James C Ross, Jennifer G Dy, Barry J Make, Elizabeth A Regan and 8 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in American journal of epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
–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

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  12. Observational
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  14. Unravelling the mechanisms driving multimorbidity in COPD to develop holistic approaches to patient-centred care.European respiratory review : an official journal of the European Respiratory Society · 2021
    Review
  15. Article
  16. Review
  17. Letter to the Editor: Response by Authors.Chronic obstructive pulmonary diseases (Miami, Fla.) · 2020
    Article
  18. Article
  19. When Harry Met Sally, or When Machine Learning Met Chronic Obstructive Pulmonary Disease.American journal of respiratory and critical care medicine · 2020
    Article
  20. 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

18 authors.

Gregory L KinneyDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado.
Stephanie A SantoricoDepartment of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, Colorado.
Kendra A YoungDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado.
Michael H ChoChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Peter J CastaldiChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Raul San José EstéparChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
James C RossChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Jennifer G DyDepartment of Electrical & Computer Engineering, Northeastern University, Boston, Massachusetts.
Barry J MakeDepartment of Medicine, National Jewish Health, Denver, Colorado.
Elizabeth A ReganDepartment of Medicine, National Jewish Health, Denver, Colorado.
David A LynchDepartment of Radiology, National Jewish Health, Denver, Colorado.
Douglas C EverettDivision of Biostatistics and Bioinformatics, Office of Academic Affairs, National Jewish Health, Denver, Colorado.
Sharon M LutzDepartment of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, Colorado.
Edwin K SilvermanChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
George R WashkoChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
James D CrapoDepartment of Medicine, National Jewish Health, Denver, Colorado.
John E HokansonDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado.
COPDGene Investigators

Funding

Genetic Epidemiology of COPDU01HL089897 · NHLBI · NATIONAL JEWISH HEALTH · PI CRAPO, JAMES D · 2007 to 2021
$56.9M
Metabolomic signatures of empysema and COPD progression in the COPDGene cohortR01HL089897 · NHLBI · NATIONAL JEWISH HEALTH · PI CRAPO, JAMES D · 2012 to 2016
$31.1M
Genetic Epidemiology of COPDU01HL089856 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2007 to 2021
$20.7M
(2 of 2) Genetic Epidemiology of COPDR01HL089856 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2012 to 2016
$18.9M
Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTLR01HL124233 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI CASTALDI, PETER · 2014 to 2024
$7.1M
Common Genetic Pathways Underlying CVD and COPDK01HL125858 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI LUTZ, SHARON MARIE · 2015 to 2019
$721k
APPROACHES TO IDENTIFY RARE AND COMMON GENETIC DETERMINANTS IN SEVERE COPDK08HL097029 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI CHO, MICHAEL H. · 2010 to 2013
$548k
NHLBI NIH HHS K01 HL125858NHLBI NIH HHS K08 HL097029NHLBI NIH HHS R01 HL089856NHLBI NIH HHS R01 HL089897NHLBI NIH HHS R01 HL124233NHLBI NIH HHS U01 HL089856NHLBI NIH HHS U01 HL089897
6 · The paper itself

Abstract

Chronic obstructive pulmonary disease (COPD) is a syndrome caused by damage to the lungs that results in decreased pulmonary function and reduced structural integrity. Pulmonary function testing (PFT) is used to diagnose and stratify COPD into severity groups, and computed tomography (CT) imaging of the chest is often used to assess structural changes in the lungs. We hypothesized that the combination of PFT and CT phenotypes would provide a more powerful tool for assessing underlying morphologic differences associated with pulmonary function in COPD than does PFT alone. We used factor analysis of 26 variables to classify 8,157 participants recruited into the COPDGene cohort between January 2008 and June 2011 from 21 clinical centers across the United States. These factors were used as predictors of all-cause mortality using Cox proportional hazards modeling. Five factors explained 80% of the covariance and represented the following domains: factor 1, increased emphysema and decreased pulmonary function; factor 2, airway disease and decreased pulmonary function; factor 3, gas trapping; factor 4, CT variability; and factor 5, hyperinflation. After more than 46,079 person-years of follow-up, factors 1 through 4 were associated with mortality and there was a significant synergistic interaction between factors 1 and 2 on death. Considering CT measures along with PFT in the assessment of COPD can identify patients at particularly high risk for death.

Indexed as

AdultAgedAged, 80 and overCause of DeathFactor Analysis, StatisticalFemaleHumansLungMaleMiddle AgedPhenotypePredictive Value of TestsProportional Hazards ModelsPulmonary Disease, Chronic ObstructiveRespiratory Function TestsRisk Assessment

Identifiers

PMID29771274
PMCPMC6166205

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.