The clinical performance of an office-based risk scoring system for fatal cardiovascular diseases in North-East of Iran

PLoS One. 2015 May 26;10(5):e0126779. doi: 10.1371/journal.pone.0126779. eCollection 2015.

Abstract

Background: Cardiovascular diseases (CVD) are becoming major causes of death in developing countries. Risk scoring systems for CVD are needed to prioritize allocation of limited resources. Most of these risk score algorithms have been based on a long array of risk factors including blood markers of lipids. However, risk scoring systems that solely use office-based data, not including laboratory markers, may be advantageous. In the current analysis, we validated the office-based Framingham risk scoring system in Iran.

Methods: The study used data from the Golestan Cohort in North-East of Iran. The following risk factors were used in the development of the risk scoring method: sex, age, body mass index, systolic blood pressure, hypertension treatment, current smoking, and diabetes. Cardiovascular risk functions for prediction of 10-year risk of fatal CVDs were developed.

Results: A total of 46,674 participants free of CVD at baseline were included. Predictive value of estimated risks was examined. The resulting Area Under the ROC Curve (AUC) was 0.774 (95% CI: 0.762-0.787) in all participants, 0.772 (95% CI: 0.753-0.791) in women, and 0.763 (95% CI: 0.747-0.779) in men. AUC was higher in urban areas (0.790, 95% CI: 0.766-0.815). The predicted and observed risks of fatal CVD were similar in women. However, in men, predicted probabilities were higher than observed.

Conclusion: The AUC in the current study is comparable to results of previous studies while lipid profile was replaced by body mass index to develop an office-based scoring system. This scoring algorithm is capable of discriminating individuals at high risk versus low risk of fatal CVD.

Publication types

  • Research Support, N.I.H., Intramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Cardiovascular Diseases / mortality*
  • Cohort Studies
  • Female
  • Humans
  • Iran / epidemiology
  • Male
  • Middle Aged
  • Proportional Hazards Models
  • ROC Curve
  • Regression Analysis
  • Research Design*
  • Risk Factors
  • Sensitivity and Specificity