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Article

Longitudinal Assessment of Multimorbidity Medication Patterns among Smokers in the COPDGene Cohort

by
Yisha Li
1,
Sarah J. Schmiege
2,
Heather Anderson
3,
Nicole E. Richmond
1,
Kendra A. Young
1,
John E. Hokanson
1,
Stephen I. Rennard
4,
Tessa L. Crume
1,
Erin Austin
5,
Katherine A. Pratte
6,
Rebecca Conway
1 and
Gregory L. Kinney
1,*
1
Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
2
Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
3
Department of Clinical Pharmacy, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
4
Division of Pulmonary, Critical Care and Sleep Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA
5
Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
6
Division of Biostatistics and Bioinformatics, National Jewish Health, Denver, CO 80206, USA
*
Author to whom correspondence should be addressed.
Medicina 2023, 59(5), 976; https://doi.org/10.3390/medicina59050976
Submission received: 15 March 2023 / Revised: 8 May 2023 / Accepted: 15 May 2023 / Published: 18 May 2023
(This article belongs to the Section Epidemiology & Public Health)
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Abstract

Background and objectives: Chronic obstructive pulmonary disease (COPD) is usually comorbid with other chronic diseases. We aimed to assess the multimorbidity medication patterns and explore if the patterns are similar for phase 1 (P1) and 5-year follow-up phase 2 (P2) in the COPDGene cohort. Materials and Methods: A total of 5564 out of 10,198 smokers from the COPDGene cohort who completed 2 visits, P1 and P2 visits, with complete medication use history were included in the study. We conducted latent class analysis (LCA) among the 27 categories of chronic disease medications, excluding COPD treatments and cancer medications at P1 and P2 separately. The best number of LCA classes was determined through both statistical fit and interpretation of the patterns. Results: We found four classes of medication patterns at both phases. LCA showed that both phases shared similar characteristics in their medication patterns: LC0: low medication; LC1: hypertension (HTN) or cardiovascular disease (CVD)+high cholesterol (Hychol) medication predominant; LC2: HTN/CVD+type 2 diabetes (T2D) +Hychol medication predominant; LC3: Hychol medication predominant. Conclusions: We found similar multimorbidity medication patterns among smokers at P1 and P2 in the COPDGene cohort, which provides an understanding of how multimorbidity medication clustered and how different chronic diseases combine in smokers.
Keywords: chronic diseases; medication patterns; latent class analysis; smoker chronic diseases; medication patterns; latent class analysis; smoker

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MDPI and ACS Style

Li, Y.; Schmiege, S.J.; Anderson, H.; Richmond, N.E.; Young, K.A.; Hokanson, J.E.; Rennard, S.I.; Crume, T.L.; Austin, E.; Pratte, K.A.; et al. Longitudinal Assessment of Multimorbidity Medication Patterns among Smokers in the COPDGene Cohort. Medicina 2023, 59, 976. https://doi.org/10.3390/medicina59050976

AMA Style

Li Y, Schmiege SJ, Anderson H, Richmond NE, Young KA, Hokanson JE, Rennard SI, Crume TL, Austin E, Pratte KA, et al. Longitudinal Assessment of Multimorbidity Medication Patterns among Smokers in the COPDGene Cohort. Medicina. 2023; 59(5):976. https://doi.org/10.3390/medicina59050976

Chicago/Turabian Style

Li, Yisha, Sarah J. Schmiege, Heather Anderson, Nicole E. Richmond, Kendra A. Young, John E. Hokanson, Stephen I. Rennard, Tessa L. Crume, Erin Austin, Katherine A. Pratte, and et al. 2023. "Longitudinal Assessment of Multimorbidity Medication Patterns among Smokers in the COPDGene Cohort" Medicina 59, no. 5: 976. https://doi.org/10.3390/medicina59050976

APA Style

Li, Y., Schmiege, S. J., Anderson, H., Richmond, N. E., Young, K. A., Hokanson, J. E., Rennard, S. I., Crume, T. L., Austin, E., Pratte, K. A., Conway, R., & Kinney, G. L. (2023). Longitudinal Assessment of Multimorbidity Medication Patterns among Smokers in the COPDGene Cohort. Medicina, 59(5), 976. https://doi.org/10.3390/medicina59050976

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