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Performance of Traditional Cardiovascular Risk Scores and Objective Optimization in Cancer Survivors.

Harsh A Patel1, Saifullah Syed2, Pranathi Tella3

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Current Oncology (Toronto, Ont.)
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Standard cardiovascular disease risk scores do not accurately predict mortality in cancer survivors. New cardio-oncology models are needed to account for cancer treatments and survivor-specific risks.

Keywords:
National Health and Nutrition Examination Survey (NHANES)Youden Indexcancer survivorscardiovascular mortalitycardiovascular risk scores

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Area of Science:

  • Cardiology
  • Oncology
  • Epidemiology

Background:

  • Cardiovascular disease (CVD) is a major cause of death in cancer survivors.
  • Existing CVD risk prediction tools (ASCVD, Framingham, PREVENT) do not include cancer-specific factors.
  • Cardiotoxic cancer therapies and increased cardiovascular risk factors contribute to CVD in survivors.

Purpose of the Study:

  • To evaluate the predictive performance of general population CVD risk models in cancer survivors.
  • To determine if statistical optimization improves the accuracy of these models for cardiovascular mortality prediction in this cohort.
  • To highlight the need for cancer-specific cardiovascular risk assessment.

Main Methods:

  • Retrospective analysis of National Health and Nutrition Examination Survey (NHANES) data linked with National Death Index (NDI) mortality data (2001-2018).
  • Included cancer survivors without baseline cardiovascular disease.
  • Assessed discrimination of ASCVD, Framingham Score, and PREVENT using standard and Youden-optimized thresholds, with Area Under the Curve (AUC) comparisons via DeLong test.

Main Results:

  • Standard thresholds showed suboptimal discrimination (AUCs: ASCVD 0.56, Framingham 0.53, PREVENT 0.64).
  • Youden-optimized thresholds improved AUCs (ASCVD: 0.68; PREVENT: 0.71), but increased "low-risk" mortality rate, indicating overestimation.
  • Optimized thresholds outperformed conventional ones, suggesting limitations of current models.

Conclusions:

  • General CVD risk scores inadequately predict cardiovascular mortality in cancer survivors.
  • While threshold recalibration improves statistical fit, it doesn't address the fundamental issue of unaddressed cardiotoxic exposures.
  • Development of specialized cardio-oncology risk models incorporating oncologic exposures is essential for accurate risk stratification.