4.8 Article

Predictive performance of a competing risk cardiovascular prediction tool CRISK compared to QRISK3 in older people and those with comorbidity: population cohort study

期刊

BMC MEDICINE
卷 20, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s12916-022-02349-6

关键词

Cardiovascular risk; Primary prevention; Risk prediction; QRISK3; Competing risk

资金

  1. National Institute for Health Research (NIHR) Health Services and Delivery Research Programme [15/12/22]
  2. HDR-UK Precision Medicine programme
  3. Wellcome Trust Clinical Research Development Fellowship

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This study aimed to develop and validate a competing risk model (CRISK) to predict incident cardiovascular disease (CVD) and compare its performance with QRISK3. The study found that CRISK and CRISK-CCI performed better than QRISK3, with CRISK-CCI recommending fewer individuals for treatment and having a lower number needed to treat (NNT) to prevent a new CVD event. Therefore, it is recommended to use competing risk models for primary prevention treatment recommendations for CVD.
Background Recommended cardiovascular disease (CVD) prediction tools do not account for competing mortality risk and over-predict incident CVD in older and multimorbid people. The aim of this study was to derive and validate a competing risk model (CRISK) to predict incident CVD and compare its performance to that of QRISK3 in UK primary care. Methods We used UK linked primary care data from the Clinical Practice Research Datalink (CPRD) GOLD to identify people aged 25-84 years with no previous CVD or statin treatment split into derivation and validation cohorts. In the derivation cohort, we derived models using the same covariates as QRISK3 with Fine-Gray competing risk modelling alone (CRISK) and with Charlson Comorbidity score (CRISK-CCI) as an additional predictor of non-CVD death. In a separate validation cohort, we examined discrimination and calibration compared to QRISK3. Reclassification analysis examined the number of patients recommended for treatment and the estimated number needed to treat (NNT) to prevent a new CVD event. Results The derivation and validation cohorts included 989,732 and 494,865 women and 946,784 and 473,392 men respectively. Overall discrimination of CRISK and CRISK-CCI were excellent and similar to QRISK3 (for women, C-statistic = 0.863/0.864/0.863 respectively; for men 0.833/0.819/0.832 respectively). CRISK and CRISK-CCI calibration overall and in younger people was excellent. CRISK over-predicted in older and multimorbid people although performed better than QRISK3, whilst CRISK-CCI performed the best. The proportion of people reclassified by CRISK-CCI varied by QRISK3 risk score category, with 0.7-9.7% of women and 2.8-25.2% of men reclassified as higher risk and 21.0-69.1% of women and 27.1-57.4% of men reclassified as lower risk. Overall, CRISK-CCI recommended fewer people for treatment and had a lower estimated NNT at 10% risk threshold. Patients reclassified as higher risk were younger, had lower SBP and higher BMI, and were more likely to smoke. Conclusions CRISK and CRISK-CCI performed better than QRISK3. CRISK-CCI recommends fewer people for treatment and has a lower NNT to prevent a new CVD event compared to QRISK3. Competing risk models should be recommended for CVD primary prevention treatment recommendations.

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