ArticleClinical epidemiology2020
Co-Morbidity Patterns Identified Using Latent Class Analysis of Medications Predict All-Cause Mortality Independent of Other Known Risk Factors: The COPDGene
Article in Clinical epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
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Who cites it
7 citing papers in PubMed.
- Article
- Latent Class Analysis to Identify Novel Phenotypes in Exacerbations of COPD: A Retrospective, Multicenter Cohort Study.MedComm · 2025Article
- Association of ART regimen and adherence to viral suppression: an observational study of a clinical population of people with HIV.AIDS research and therapy · 2024Observational
- Longitudinal Assessment of Multimorbidity Medication Patterns among Smokers in the COPDGene Cohort.Medicina (Kaunas, Lithuania) · 2023Article
- Identifying Individual Medications Affecting Pulmonary Outcomes When Multiple Medications are Present.Clinical epidemiology · 2022Article
- Distribution of COPD Comorbidities and Creation of Acute Exacerbation Risk Score: Results from SCICP.Journal of inflammation research · 2021Article
- Multimorbidity patterns and their relationship to mortality in the US older adult population.PloS one · 2021Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
purposeMedication patterns include all medications in an individual's clinical profile. We aimed to identify chronic co-morbidity treatment patterns through medication use among COPDGene participants and determine whether these patterns were associated with mortality, acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and quality of life. MATERIALS AND
methodsParticipants analyzed here completed Phase 1 (P1) and/or Phase 2 (P2) of COPDGene. Latent class analysis (LCA) was used to identify medication patterns and assign individuals into unobserved LCA classes. Mortality, AECOPD, and the St. George's Respiratory Questionnaire (SGRQ) health status were compared in different LCA classes through survival analysis, logistic regression, and Kruskal-Wallis test, respectively.
resultsLCA identified 8 medication patterns from 32 classes of chronic comorbid medications. A total of 8110 out of 10,127 participants with complete covariate information were included. Survival analysis adjusted for covariates showed, compared to a low medication use class, mortality was highest in participants with hypertension+diabetes+statin+antiplatelet medication group. Participants in hypertension+SSRI+statin medication group had the highest odds of AECOPD and the highest SGRQ score at both P1 and P2.
conclusionMedication pattern can serve as a good indicator of an individual's comorbidities profile and improves models predicting clinical outcomes.
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