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Cluster Analysis of Cardiovascular Phenotypes in Patients With Type 2 Diabetes and Established Atherosclerotic Cardiovascular Disease: A Potential Approach to Precision Medicine.

Publication ,  Conference
Sharma, A; Zheng, Y; Ezekowitz, JA; Westerhout, CM; Udell, JA; Goodman, SG; Armstrong, PW; Buse, JB; Green, JB; Josse, RG; Kaufman, KD ...
Published in: Diabetes Care
January 1, 2022

OBJECTIVE: Phenotypic heterogeneity among patients with type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD) is ill defined. We used cluster analysis machine-learning algorithms to identify phenotypes among trial participants with T2DM and ASCVD. RESEARCH DESIGN AND METHODS: We used data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) study (n = 14,671), a cardiovascular outcome safety trial comparing sitagliptin with placebo in patients with T2DM and ASCVD (median follow-up 3.0 years). Cluster analysis using 40 baseline variables was conducted, with associations between clusters and the primary composite outcome (cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for unstable angina) assessed by Cox proportional hazards models. We replicated the results using the Exenatide Study of Cardiovascular Event Lowering (EXSCEL) trial. RESULTS: Four distinct phenotypes were identified: cluster I included Caucasian men with a high prevalence of coronary artery disease; cluster II included Asian patients with a low BMI; cluster III included women with noncoronary ASCVD disease; and cluster IV included patients with heart failure and kidney dysfunction. The primary outcome occurred, respectively, in 11.6%, 8.6%, 10.3%, and 16.8% of patients in clusters I to IV. The crude difference in cardiovascular risk for the highest versus lowest risk cluster (cluster IV vs. II) was statistically significant (hazard ratio 2.74 [95% CI 2.29-3.29]). Similar phenotypes and outcomes were identified in EXSCEL. CONCLUSIONS: In patients with T2DM and ASCVD, cluster analysis identified four clinically distinct groups. Further cardiovascular phenotyping is warranted to inform patient care and optimize clinical trial designs.

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Published In

Diabetes Care

DOI

EISSN

1935-5548

Publication Date

January 1, 2022

Volume

45

Issue

1

Start / End Page

204 / 212

Location

United States

Related Subject Headings

  • Risk Factors
  • Precision Medicine
  • Phenotype
  • Male
  • Humans
  • Female
  • Endocrinology & Metabolism
  • Diabetes Mellitus, Type 2
  • Cluster Analysis
  • Cardiovascular Diseases
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Sharma, A., Zheng, Y., Ezekowitz, J. A., Westerhout, C. M., Udell, J. A., Goodman, S. G., … Holman, R. R. (2022). Cluster Analysis of Cardiovascular Phenotypes in Patients With Type 2 Diabetes and Established Atherosclerotic Cardiovascular Disease: A Potential Approach to Precision Medicine. In Diabetes Care (Vol. 45, pp. 204–212). United States. https://doi.org/10.2337/dc20-2806
Sharma, Abhinav, Yinggan Zheng, Justin A. Ezekowitz, Cynthia M. Westerhout, Jacob A. Udell, Shaun G. Goodman, Paul W. Armstrong, et al. “Cluster Analysis of Cardiovascular Phenotypes in Patients With Type 2 Diabetes and Established Atherosclerotic Cardiovascular Disease: A Potential Approach to Precision Medicine.” In Diabetes Care, 45:204–12, 2022. https://doi.org/10.2337/dc20-2806.
Sharma A, Zheng Y, Ezekowitz JA, Westerhout CM, Udell JA, Goodman SG, Armstrong PW, Buse JB, Green JB, Josse RG, Kaufman KD, McGuire DK, Ambrosio G, Chuang L-M, Lopes RD, Peterson ED, Holman RR. Cluster Analysis of Cardiovascular Phenotypes in Patients With Type 2 Diabetes and Established Atherosclerotic Cardiovascular Disease: A Potential Approach to Precision Medicine. Diabetes Care. 2022. p. 204–212.

Published In

Diabetes Care

DOI

EISSN

1935-5548

Publication Date

January 1, 2022

Volume

45

Issue

1

Start / End Page

204 / 212

Location

United States

Related Subject Headings

  • Risk Factors
  • Precision Medicine
  • Phenotype
  • Male
  • Humans
  • Female
  • Endocrinology & Metabolism
  • Diabetes Mellitus, Type 2
  • Cluster Analysis
  • Cardiovascular Diseases