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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Development and Validation of Novel Residual Risk Scores for Patients With ASCVD
Olga Mineeva1, Chunying Li2, Franco Giulianini2
1Department of Computer Science, ETH Zurich, Zurich, Switzerland; Max Planck Institute for Intelligent Systems, Tuebingen, Germany.
Insights
New risk scores, RRS16 and RRS24, accurately predict 10-year cardiovascular death risk in patients with established atherosclerotic cardiovascular disease (ASCVD). These scores outperform current American Heart Association (AHA) guidelines.
Area of Science:
- Cardiovascular Medicine
- Biostatistics
- Epidemiology
Background:
- Personalized risk stratification for established atherosclerotic cardiovascular disease (ASCVD) remains a clinical challenge.
- Existing risk scores often lack precision for predicting long-term outcomes in high-risk populations.
Purpose of the Study:
- To develop and validate novel 10-year residual risk scores for cardiovascular death.
- To improve risk prediction in patients with established ASCVD beyond current guideline-based models.
Main Methods:
- Prospective observational cohort study utilizing the UK Biobank (UKB) for development and Mass General Brigham (MGB) for external validation.
- Elastic-net Cox and gradient-boosted tree models were employed to identify predictive factors.
- Risk scores (RRS16 and RRS24) were developed using clinical factors, biomarkers, and self-reported health.
Main Results:
- RRS16 and RRS24 were developed, incorporating 16 and 24 factors, respectively.
- RRS16 demonstrated superior performance (C-statistics: UKB=0.752, MGB=0.750) compared to the 2018 AHA guideline model (UKB=0.658, MGB=0.580).
- RRS24 achieved a C-statistic of 0.784 in the UKB cohort, with both models showing good calibration.
Conclusions:
- The developed residual risk scores (RRS16 and RRS24) significantly outperform the current AHA guideline model for established ASCVD.
- These scores offer enhanced clinical applicability for estimating residual cardiovascular risk.
- Further validation in diverse patient populations is recommended to confirm generalizability.
Background:
Despite clinical need, personalized risk scores for established atherosclerotic cardiovascular disease (ASCVD) are scarce.
Objectives:
The objective of the study was to develop and validate 10-year residual risk scores for cardiovascular death in patients with established ASCVD.
Methods:
Prospective observational cohort study. Models developed and validated in U.K. Biobank (UKB) (baseline 2006-2010; follow-up through 2021) and externally validated in Mass General Brigham cohort (MGB) (baseline 2007; follow-up through 2018). Analyzed on October 2022-February 2024. Eligible participants had established ASCVD. Guideline-based clinical factors plus additional biomarkers and self-reported health ratings.
Primary Outcome:
10-year cardiovascular death. Elastic-net Cox and gradient-boosted tree models. C statistics and goodness-of-fit assessed in holdout set.
Results:
UKB: 32,994 participants (mean age 61; 11,727 [35.5%] women; 2,660 [8.0%] cardiovascular deaths), with 9,899 (30%) randomly selected as a holdout validation set. MGB: 54,969 patients (mean age 71; 22,738 [41.4%] women; 6,927 [12.6%] cardiovascular deaths). Median follow-up: 10 years (IQR 10-10) in UKB; 9.4 years (5-10) in MGB. We developed 2 residual risk scores, RRS16 and RRS24, incorporating 16 and 24 algorithmically selected factors. RRS16 used routinely available factors; RRS24 also included self-reported health and additional biomarkers. RRS16 achieved C statistics of 0.752 (95% CI: 0.736-0.768) in UKB and 0.750 (0.744-0.756) in MGB, outperforming the 2018 the American Heart Association (AHA) guideline model (0.658 [0.642-0.674] in UKB, 0.580 [0.574-0.586] in MGB). RRS24 achieved 0.784 (0.768-0.800) in UKB. Both models well calibrated (P > 0.1). RRS16 calculator: https://mora.bwh.harvard.edu/rrs16/.
Conclusions:
RRS16 and RRS24 outperformed AHA guideline model in estimating the residual risk in patients with established ASCVD. Both are clinically applicable but require further validation in diverse populations.
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