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

Abstract

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 PARTICIPANTSProspective 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 (Յ11.1 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 MEASURESA 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. RESULTSFrom 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.

Estimated Life Expectancy Without Recurrent Cardiovascular Events in Patients With Vascular Disease: The SMART‐REACH Model

“…This resulted in accurate estimates of the REACH‐SMART model in the external validation sets. The discriminatory ability of the 3 models was moderate, which we considered acceptable, as this is in line with previous studies on models in patients with cardiovascular disease 4, 5, 29, 30…”

“…Nevertheless, this type of modeling does not account for survival up to the year of observation, which theoretically may result in biased estimates toward healthier survivors in very long‐term predictions. Third, the limited discriminatory ability of the SMART‐REACH model is comparable to previous risk scores for patients with clinically manifest vascular disease 4, 5, 29, 30. Previous studies have shown that additional risk factors are unlikely to result in relevant improvement 4, 38.…”

Protein Biomarkers of Cardiovascular Disease and Mortality in the Community

“…Using a targeted discovery proteomic platform, we were able to extend previous findings, demonstrate novel biomarker associations with incident CVD events, and validate previous genetic associations. Large‐scale mass spectrometry or newer aptamer‐based technology49, 50 may allow for profiling of many more proteins in large study samples that may refine current multimarker models. Further studies are needed to validate our findings and define clinical utility, with the ultimate goal of improving targeted strategies for CVD prevention.…”

Rationale of the FIBROTARGETS study designed to identify novel biomarkers of myocardial fibrosis

“…One of the many challenges is that fibrosis is a mechanism involved in a number of overlapping and/or coexisting risk and disease states and co‐morbidities48, 49 such as hypertension, chronic kidney disease, diabetes mellitus, obesity, atrial fibrillation, ischaemic heart disease, and prevalent HF, such that a number of circulating biomarkers can be present in these various conditions 26, 46, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61. Our hypothesis is that novel ‘mechanistic’ markers of cardiac fibrosis are differentially expressed in various risk and disease states and co‐morbidities.…”