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. 2024 Apr;3(4):100868.
doi: 10.1016/j.jacadv.2024.100868. Epub 2024 Feb 17.

Cardiometabolic Disease Staging and Major Adverse Cardiovascular Event Prediction in 2 Prospective Cohorts

Carrie R Howell  1 , Li Zhang  2 , Tapan Mehta  3 , Lua Wilkinson  4 , April P Carson  5 , Emily B Levitan  6 , Andrea L Cherrington  1 , Nengjun Yi  2 , W Timothy Garvey  7
Affiliations

Cardiometabolic Disease Staging and Major Adverse Cardiovascular Event Prediction in 2 Prospective Cohorts

Carrie R Howell et al. JACC Adv. 2024 Apr.

Abstract

Background: Cardiometabolic risk prediction models that incorporate metabolic syndrome traits to predict cardiovascular outcomes may help identify high-risk populations early in the progression of cardiometabolic disease.

Objectives: The purpose of this study was to examine whether a modified cardiometabolic disease staging (CMDS) system, a validated diabetes prediction model, predicts major adverse cardiovascular events (MACE).

Methods: We developed a predictive model using data accessible in clinical practice [fasting glucose, blood pressure, body mass index, cholesterol, triglycerides, smoking status, diabetes status, hypertension medication use] from the REGARDS (REasons for Geographic And Racial Differences in Stroke) study to predict MACE [cardiovascular death, nonfatal myocardial infarction, and/or nonfatal stroke]. Predictive performance was assessed using receiver operating characteristic curves, mean squared errors, misclassification, and area under the curve (AUC) statistics.

Results: Among 20,234 REGARDS participants with no history of stroke or myocardial infarction (mean age 64 ± 9.3 years, 58% female, 41% non-Hispanic Black, and 18% diabetes), 2,695 developed incident MACE (13.3%) during a median 10-year follow-up. The CMDS development model in REGARDS for MACE had an AUC of 0.721. Our CMDS model performed similarly to both the ACC/AHA 10-year risk estimate (AUC 0.721 vs 0.716) and the Framingham risk score (AUC 0.673).

Conclusions: The CMDS predicted the onset of MACE with good predictive ability and performed similarly or better than 2 commonly known cardiovascular disease prediction risk tools. These data underscore the importance of insulin resistance as a cardiovascular disease risk factor and that CMDS can be used to identify individuals at high risk for progression to cardiovascular disease.

Keywords: cardiometabolic disease; cardiovascular events; risk stratification.

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Conflict of interest statement

This research project is supported by cooperative agreement U01 NS041588 co-funded by the National Institute of Neurological Disorders and Stroke (NINDS) and the National Institute on Aging (NIA), the National Institutes of Health, and the Department of Health and Human Services. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NINDS or the NIA. Representatives of the NINDS were involved in the review of the manuscript but were not directly involved in the collection, management, analysis, or interpretation of the data. The authors thank the other investigators, the staff, and the participants of the REGARDS study for their valuable contributions. A full list of participating REGARDS investigators and institutions can be found at: https://www.uab.edu/soph/regardsstudy/. Additional funding was provided by R01 HL80477 and R01 HL165452 from the National Heart, Lung, and Blood Institute (NHLBI). Representatives from NHLBI did not have any role in the design and conduct of the study, the collection, management, analysis, and interpretation of the data, or the preparation or approval of the manuscript. This manuscript was prepared using ARIC research materials obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center and does not necessarily reflect the opinions or views of the ARIC or the NHLBI. Additional funding was provided by American Heart Association Grant # 931540/Carrie R. Howell/2022, the National Institute on Minority Health and Health Disparities (Howell - 1K01 MD0172706), and the UAB Diabetes Research Center (P30 DK079626). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies supporting this work. Dr Wilkinson is an employee of Novo Nordisk. Dr Mehta has received consulting fees from Novo Nordisk, The Obesity Society, and PLOS One. Dr Levitan has received funding from Amgen Inc outside of the current research. Dr Garvey has served as a consultant on advisory boards for Boehringer Ingelheim, Eli Lilly, Novo Nordisk, Pfizer, Fractyl Health, Alnylam Pharmaceuticals, Inogen, and Merck, and as a site principal investigator for multicentered clinical trials sponsored by his university and funded by Novo Nordisk, Eli Lilly, Epitomee, Neurovalens, and Pfizer. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Figures

None
Graphical abstract
Figure 1
Figure 1
Flow of Participant Assessments in the REGARDS Study After excluding participants with a history of heart disease or stroke, or were missing clinical data, there were N = 20,234 available for analysis. REGARDS = reasons for geographic and racial differences in stroke.
Figure 2
Figure 2
Odds Ratio Plots for MACE Outcome Odds ratio plots per standard deviation increase for Individual risk factors for MACE. The points and lines present the estimated values and 95% CIs, and the values at the right side are P values. MACE = major adverse cardiac events.
Figure 3
Figure 3
Odds Ratio Plots for Cardiovascular Mortality Odds ratio plots per standard deviation increase for Individual risk factors for CVD mortality. The points and lines present the estimated values and 95% CIs and the values at the right side are P values. CVD = cardiovascular disease.
Figure 4
Figure 4
Receiver Operating Characteristic Curves for MACE Models Receiver operating Characteristic curves for CMDS model, ACC/AHA PCE, and the Framingham risk score for MACE outcome using REGARDS data. ACC/AHA = American College of Cardiology/American Heart Association; MACE = major adverse cardiac events; PCE = pooled cohort risk equations; REGARDS = REasons for Geographic And Racial Differences in Stroke.
Figure 5
Figure 5
Receiver Operating Characteristic Curves for CVD Mortality Models Receiver operating Characteristic curves for the CMDS model, ACC/AHA PCE, and the Framingham risk score for CVD mortality outcome using REGARDS data.
Central Illustration
Central Illustration
Cardiometabolic Staging Predicts Diabetes Incidence and Major Adverse Cardiovascular Events Cardiometabolic staging (CMDS), originally developed to predict diabetes incidence, robustly predicts the 10-year onset of major adverse cardiovascular events (MACE). The CMDS can be used to risk stratify patients based on risk of developing cardiometabolic disease to aid in the cost/benefit of interventions. Pooled Cohort Risk Equation in the figure refers to the ACC/AHA Pooled Cohort Risk Equations.
See this image and copyright information in PMC

Comment in

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