What is the clinical evidence from this study?

Study design: Cohort. Population: Cardiovascular disease (n=325815). Intervention: Addition of depressive symptom score to PREVENT equations vs. PREVENT equations alone. Primary outcome: C-index for 10-year risk of incident cardiovascular disease (C-index difference 0.005, 95% CI 0.004-0.006).

What does this research mean for the field?

Adding depressive symptom scores and other measures of anxiety and depression to the PREVENT equations produces only a very modest improvement in predicting 10-year cardiovascular disease risk, suggesting their inclusion may not be clinically worthwhile at the population level. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

January 12, 2025Open Access

Refining PREVENT prediction models for 10-year risk of cardiovascular disease using measures of anxiety and depression

SNShinya NakadaUniversity of Glasgow PWPaul WelshPreventive Cardiology CCCarlos Celis‐MoralesPreventive Cardiology

Key Result

Adding depressive symptom score to the PREVENT equations produced a very modest improvement in the C-index (difference of 0.005) for predicting 10-year cardiovascular disease risk.

Study Design

Type

Cohort (n=325,815)

Multicenter

Yes

Structured PICO

Does adding measures of anxiety and depression to the PREVENT equations improve the prediction of 10-year incident cardiovascular disease risk in adults without prior CVD?

Population

325,815 adults aged 40-69 years from the UK Biobank general population without a history of cardiovascular disease before baseline assessment (195,489 in derivation set, 130,326 in validation set).

Intervention

Addition of mental health predictors (baseline depressive symptom score via PHQ-9, self-reported and record-based history of anxiety and depression diagnoses) to the AHA PREVENT risk prediction equations.

Comparator

Original AHA PREVENT risk prediction equations (core predictors: age, sex, systolic blood pressure, HDL-C, non-HDL-C, eGFR, diabetes, current smoking, antihypertensive treatment, and statin treatment).

Outcome

Incident cardiovascular disease (composite of coronary artery disease, stroke, and heart failure) over a 10-year follow-up period.composite

Adding measures of depression and anxiety to the AHA PREVENT equations provides only marginal improvements in 10-year CVD risk prediction and is likely not clinically worthwhile at the population level.

Main Result

Effect estimate: C-index difference 0.005 (95% CI 0.004-0.006)

Absolute Event Rate: 0.741% vs 0.736%

Limitations

UK Biobank participants are more likely to be White, affluent, and healthy than the general population of the United Kingdom.
Splitting data into derivation and validation sets reduced the sample size.
Results are sensitive to the defined minimum risk threshold for considering statin therapy initiation.
Recorded anxiety and depression diagnoses identified only a small number of participants, likely capturing only severe cases requiring hospital admission.
Exclusion of participants with missing predictors could bias the results.

Abstract

BACKGROUND: Anxiety and depression are associated with cardiovascular disease (CVD). We aimed to investigate whether adding measures of anxiety and depression to the American Heart Association Predicting Risk of Cardiovascular Disease Events (PREVENT) predictors improves the prediction of CVD risk. METHODS: We developed and internally validated risk prediction models using 60% and 40% of the cohort data from the UK Biobank, respectively. Mental health predictors included baseline depressive symptom score and self-reported and record-based history of anxiety and depression diagnoses before the baseline. We identified CVD events using hospital admission and death certificate data over a 10-year period from baseline. We determined incremental predictive values by adding the mental health predictors to the PREVENT predictors using Harrell's C-indices, sensitivity, specificity, and net reclassification improvement indices. We used a threshold of 10-year risk of incident CVD of greater than 5%. RESULTS: Of the 502 366 UK Biobank participants, we included 195 489 in the derivation set and 130 326 in the validation set. In the validation set, the inclusion of all mental health measures, except self-reported anxiety, produced a very modest increase in the C-index and specificity while sensitivity remained unchanged. Among these mental health predictors, depressive symptom score produced the greatest improvements in both C-index (difference of 0.005, 95% confidence interval 0.004-0.006) and specificity (difference of 0.89%). Depressive symptom score showed similar small improvements in female and male validation sets. INTERPRETATION: Our findings suggest that the inclusion of measures of depression and anxiety in PREVENT would have little additional effect on the risk classification of CVD at the population level and may not be worthwhile.

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