Cited by 364Lipoproteins and Cardiovascular HealthAcute Myocardial Infarction ResearchCardiovascular Health and Risk Factors

Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients With Stable Coronary Heart Disease

Ganz, Peter, Heidecker, Bettina, Hveem, Kristian, Jonasson, Christian, Kato, Shintaro, Segal, Mark R., Sterling, David G., Williams, Stephen A.·2016·JAMA

Abstract

IMPORTANCE: Precise stratification of cardiovascular risk in patients with coronary heart disease (CHD) is needed to inform treatment decisions. OBJECTIVE: To derive and validate a score to predict risk of cardiovascular outcomes among patients with CHD, using large-scale analysis of circulating proteins. DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort study of participants with stable CHD. For the derivation cohort (Heart and Soul study), outpatients from San Francisco were enrolled from 2000 through 2002 and followed up through November 2011 (≤11.1 years). For the validation cohort (HUNT3, a Norwegian population-based study), participants were enrolled from 2006 through 2008 and followed up through April 2012 (5.6 years). EXPOSURES: Using modified aptamers, 1130 proteins were measured in plasma samples. MAIN OUTCOMES AND MEASURES: A 9-protein risk score was derived and validated for 4-year probability of myocardial infarction, stroke, heart failure, and all-cause death. Tests, including the C statistic, were used to assess performance of the 9-protein risk score, which was compared with the Framingham secondary event model, refit to the cohorts in this study. Within-person change in the 9-protein risk score was evaluated in the Heart and Soul study from paired samples collected 4.8 years apart. RESULTS: From the derivation cohort, 938 samples were analyzed, participants' median age at enrollment was 67.0 years, and 82% were men. From the validation cohort, 971 samples were analyzed, participants' median age at enrollment was 70.2 years, and 72% were men. In the derivation cohort, C statistics were 0.66 for refit Framingham, 0.74 for 9-protein, and 0.75 for refit Framingham plus 9-protein models. In the validation cohort, C statistics were 0.64 for refit Framingham, 0.70 for 9-protein, and 0.71 for refit Framingham plus 9-protein models. Adding the 9-protein risk score to the refit Framingham model increased the C statistic by 0.09 (95% CI, 0.06-0.12) in the derivation cohort, and in the validation cohort, the C statistic was increased by 0.05 (95% CI, 0.02-0.09). Compared with the refit Framingham model, the integrated discrimination index for the 9-protein model was 0.12 (95% CI, 0.08-0.16) in the derivation cohort and 0.08 (95% CI, 0.05-0.10) in the validation cohort. In analysis of paired samples among 139 participants with cardiovascular events after the second sample, absolute within-person annualized risk increased more for the 9-protein model (median, 1.86% [95% CI, 1.15%-2.54%]) than for the refit Framingham model (median, 1.00% [95% CI, 0.87%-1.19%]) (P = .002), while among 375 participants without cardiovascular events, both scores changed less and similarly (P = .30). CONCLUSIONS AND RELEVANCE: Among patients with stable CHD, a risk score based on 9 proteins performed better than the refit Framingham secondary event risk score in predicting cardiovascular events, but still provided only modest discriminative accuracy. Further research is needed to assess whether the score is more accurate in a lower-risk population.

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Crossref · 10.1001/jama.2016.5951

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  • Proteins have shown great clinical utility and promise as prognostic biomarkers in many settings relevant to ageing, prominently in heart, kidney, liver, metabolic, inflammatory and neurodegenerative disease risk.

    “Additionally, they have shown great clinical utility and promise as prognostic biomarkers in many settings relevant to ageing, prominently in heart, kidney, liver, metabolic, inflammatory and neurodegenerative disease risk101,161,162.”

    From Measuring biological age using omics data (2022) · cites this paper as [161]

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Authors
Ganz, P., Heidecker, B., Hveem, K., Jonasson, C., Kato, S., Segal, M. R., Sterling, D. G., & Williams, S. A.
Affiliations
  • San Francisco General Hospital (US)
  • University of California, San Francisco (US)
  • Norwegian University of Science and Technology (NO)
  • NEC (United States) (US)
  • SomaLogic (United States) (US)
Corresponding author
Ganz, Peter
Venue
JAMA
Published
2016-06-21
Volume
315
Issue
23
Pages
2532
ISSN
  • 0002-9955 (ISSN-L)
  • 0098-7484
OpenAlex
W2462540433
Cited by
364
References
37
Citations by year
2026: 32 · 2025: 29 · 2024: 40 · 2023: 44 · 2022: 35 · 2021: 39 · 2020: 49 · 2019: 31 · 2018: 31 · 2017: 26 · 2016: 7
FWCI
35.43
Type
journal article
Language
en
Open access
closed
Locations
  • JAMA (publishedVersion)
  • PubMed (publishedVersion)
Funders
National Heart, Lung, and Blood Institute (R01HL079235)
Topics
  • Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Acute Myocardial Infarction Research
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
Keywords
stable coronary artery disease, cardiovascular risk stratification, circulating proteins, plasma proteomics, myocardial infarction, stroke, heart failure, all-cause mortality, Framingham risk equation, risk prediction model, Heart and Soul Study, HUNT3
MeSH terms
Aged, Blood Proteins, Cause of Death, Coronary Artery Disease, Female, Heart Failure, Humans, Male, Myocardial Infarction, Norway, Prospective Studies, San Francisco, Risk Assessment, Stroke, Proteomics

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