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. 2020 Oct 27:12:1171-1181.
doi: 10.2147/CLEP.S279075. eCollection 2020.

Co-Morbidity Patterns Identified Using Latent Class Analysis of Medications Predict All-Cause Mortality Independent of Other Known Risk Factors: The COPDGene® Study

Yisha Li  1 , Margaret Ragland  1 , Erin Austin  2 , Kendra Young  1 , Katherine Pratte  3 , John E Hokanson  1 , Terri H Beaty  4 , Elizabeth A Regan  3 , Stephen I Rennard  5 , Christina Wern  6 , Michael R Jacobs  7 , Ruth Tal-Singer  8 , Barry J Make  3 , Gregory L Kinney  1 ; theCOPDGene investigators
Affiliations

Co-Morbidity Patterns Identified Using Latent Class Analysis of Medications Predict All-Cause Mortality Independent of Other Known Risk Factors: The COPDGene® Study

Yisha Li et al. Clin Epidemiol. .

Abstract

Purpose: Medication 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 methods: Participants 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.

Results: LCA 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.

Conclusion: Medication pattern can serve as a good indicator of an individual's comorbidities profile and improves models predicting clinical outcomes.

Keywords: COPDGene; co-morbidities; latent class analysis; medication patterns; mortality.

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Conflict of interest statement

COPDGene is also supported by the COPD Foundation through contributions made to an Industry Advisory Board comprised of AstraZeneca, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Novartis, Pfizer, Siemens, and Sunovion. Kendra Young reports grants from NIH, during the conduct of the study. Terri H Beaty reports grants from NIHBI, during the conduct of the study. Elizabeth A Regan reports grants from National Heart Lung and Blood Institute, during the conduct of the study. Stephen I Rennard reports salary and shareholder from AstraZeneca, personal fees from GlaxoSmithKline, nothing from BerGenBio, nothing from Verona Pharma, outside the submitted work., Ruth Tal-Singer is a former employee and current shareholder of GSK, reports personal fees form Immunomet, Vocalis Health, and ENA Pharmaceuticals, and consultancy for Ena respiratory and Vocalis, outside the submitted work. Barry J Make reports funding from the NHLBI, grants and medical advisory board work from Boehringer Ingelheim, GlaxoSmithKline, AstraZeneca and Sunovion, personal fees from Spiration, Shire, Circassia, CME personal fees from WebMD, National Jewish Health, American College of Chest Physicians, Projects in Knowledge, Hybrid Communications, Ultimate Medical Academy, Catamount Medical, Eastern Pulmonary Society, Medscape, Eastern VA Medical Center, Academy Continued Healthcare Learning, Mt. Sinai Medical Center, Theravance, Third Pole, Novartis, Phillips, Science 24/7, Wolter Kluwer Health and Verona, grants from Pearl, during the conduct of the study. The authors report no other potential conflicts of interest for this work.

Figures

Figure 1
Figure 1
ACEi=Angiotensin-converting enzyme inhibitors, ARB=Angiotensin II receptor blockers, DRI= dopamine reuptake inhibitor, LCA=Latent class analysis, PPI=Proton pump inhibitor, SNRI= Serotonin and norepinephrine reuptake inhibitors, SSRI= Selective serotonin reuptake inhibitors. Membership in other classes were labeled in Appendix 1. LCA posterior probability of each class of medication was shown in Appendix 2. Appendix 5: SGRQ= St. George’s Respiratory Questionnaire, P1=Phase 1.
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