The relevance of competing risk adjustment in cardiovascular risk prediction models for clinical practice

Author:

Hageman Steven H J1ORCID,Dorresteijn Jannick A N1,Pennells Lisa23ORCID,van Smeden Maarten4ORCID,Bots Michiel L4,Di Angelantonio Emanuele235678ORCID,Visseren Frank L J1ORCID

Affiliation:

1. Department of Vascular Medicine, University Medical Centre Utrecht , Heidelberglaan 100, Postbus 85500 3508 GA Utrecht , The Netherlands

2. British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge , Papworth Road, Trumpington, Cambridge CB2 0BB , UK

3. Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge , Papworth Road, Trumpington, Cambridge CB2 0BB , UK

4. Julius Centre for Health Science and Primary Care, University Medical Centre Utrecht, University of Utrecht , Heidelberglaan 100, Postbus 85500 3508 GA Utrecht , The Netherlands

5. British Heart Foundation Centre of Research Excellence, University of Cambridge , CB2 0BB Cambridge , UK

6. National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge , CB2 0BB Cambridge , UK

7. Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge , CB10 1SA Cambridge , UK

8. Health Data Science Research Centre , Human Technopole, 20157 Milan , Italy

Abstract

Abstract Background Many models developed for predicting the risk of cardiovascular disease (CVD) are adjusted for the competing risk of non-CVD mortality, which has been suggested to reduce potential overestimation of cumulative incidence in populations where the risk of competing events is high. The objective was to evaluate and illustrate the clinical impact of competing risk adjustment when deriving a CVD prediction model in a high-risk population. Methods and results Individuals with established atherosclerotic CVD were included from the Utrecht Cardiovascular Cohort—Secondary Manifestations of ARTerial disease (UCC-SMART). In 8355 individuals, followed for a median of 8.2 years (IQR 4.2–12.5), two similar prediction models for the estimation of 10-year residual CVD risk were derived: with competing risk adjustment using a Fine and Gray model and without competing risk adjustment using a Cox proportional hazards model. On average, predictions were higher from the Cox model. The Cox model predictions overestimated the cumulative incidence [predicted–observed ratio 1.14 (95% CI 1.09–1.20)], which was most apparent in the highest risk quartiles and in older persons. Discrimination of both models was similar. When determining treatment eligibility on thresholds of predicted risks, more individuals would be treated based on the Cox model predictions. If, for example, individuals with a predicted risk > 20% were considered eligible for treatment, 34% of the population would be treated according to the Fine and Gray model predictions and 44% according to the Cox model predictions. Interpretation Individual predictions from the model unadjusted for competing risks were higher, reflecting the different interpretations of both models. For models aiming to accurately predict absolute risks, especially in high-risk populations, competing risk adjustment must be considered.

Funder

BHF Programme

BHF Chair award

Cambridge British Health Foundation Centre of Research Excellence

National Institute for Health

Care Research Cambridge Biomedical Research Centre

Publisher

Oxford University Press (OUP)

Subject

Cardiology and Cardiovascular Medicine,Epidemiology

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