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Identification of factors directly linked to incident chronic obstructive pulmonary disease: A causal graph modeling study.
Gregg, Robert W; Karoleski, Chad M; Silverman, Edwin K; Sciurba, Frank C; DeMeo, Dawn L; Benos, Panayiotis V.
Afiliação
  • Gregg RW; Department of Epidemiology, University of Florida, Gainesville, Florida, United States of America.
  • Karoleski CM; Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
  • Silverman EK; University of Pittsburgh Medical Center, Department of Medicine, Department of Pulmonary Allergy and Critical Care Medicine, Pittsburgh, Pennsylvania, United States of America.
  • Sciurba FC; Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
  • DeMeo DL; University of Pittsburgh Medical Center, Department of Medicine, Department of Pulmonary Allergy and Critical Care Medicine, Pittsburgh, Pennsylvania, United States of America.
  • Benos PV; Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
PLoS Med ; 21(8): e1004444, 2024 Aug.
Article em En | MEDLINE | ID: mdl-39137208
ABSTRACT

BACKGROUND:

Beyond exposure to cigarette smoking and aging, the factors that influence lung function decline to incident chronic obstructive pulmonary disease (COPD) remain unclear. Advancements have been made in categorizing COPD into emphysema and airway predominant disease subtypes; however, predicting which healthy individuals will progress to COPD is difficult because they can exhibit profoundly different disease trajectories despite similar initial risk factors. This study aimed to identify clinical, genetic, and radiological features that are directly linked-and subsequently predict-abnormal lung function. METHODS AND

FINDINGS:

We employed graph modeling on 2,643 COPDGene participants (aged 45 to 80 years, 51.25% female, 35.1% African Americans; enrollment 11/2007-4/2011) with smoking history but normal spirometry at study enrollment to identify variables that are directly linked to future lung function abnormalities. We developed logistic regression and random forest predictive models for distinguishing individuals who maintain lung function from those who decline. Of the 131 variables analyzed, 6 were identified as informative to future lung function abnormalities, namely forced expiratory flow in the middle range (FEF25-75%), average lung wall thickness in a 10 mm radius (Pi10), severe emphysema, age, sex, and height. We investigated whether these features predict individuals leaving GOLD 0 status (normal spirometry according to Global Initiative for Obstructive Lung Disease (GOLD) criteria). Linear models, trained with these features, were quite predictive (area under receiver operator characteristic curve or AUROC = 0.75). Random forest predictors performed similarly to logistic regression (AUROC = 0.7), indicating that no significant nonlinear effects were present. The results were externally validated on 150 participants from Specialized Center for Clinically Oriented Research (SCCOR) cohort (aged 45 to 80 years, 52.7% female, 4.7% African Americans; enrollment 7/2007-12/2012) (AUROC = 0.89). The main limitation of longitudinal studies with 5- and 10-year follow-up is the introduction of mortality bias that disproportionately affects the more severe cases. However, our study focused on spirometrically normal individuals, who have a lower mortality rate. Another limitation is the use of strict criteria to define spirometrically normal individuals, which was unavoidable when studying factors associated with changes in normalized forced expiratory volume in 1 s (FEV1%predicted) or the ratio of FEV1/FVC (forced vital capacity).

CONCLUSIONS:

This study took an agnostic approach to identify which baseline measurements differentiate and predict the early stages of lung function decline in individuals with previous smoking history. Our analysis suggests that emphysema affects obstruction onset, while airway predominant pathology may play a more important role in future FEV1 (%predicted) decline without obstruction, and FEF25-75% may affect both.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doença Pulmonar Obstrutiva Crônica Limite: Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: PLoS Med Assunto da revista: MEDICINA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doença Pulmonar Obstrutiva Crônica Limite: Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: PLoS Med Assunto da revista: MEDICINA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos