Comparing SF-36® scores versus biomarkers to predict mortality in primary cardiac prevention patients

Eur J Intern Med. 2017 Dec:46:47-55. doi: 10.1016/j.ejim.2017.05.026. Epub 2017 Jul 29.

Abstract

Background: Risk stratification plays an important role in evaluating patients with no known cardiovascular disease (CVD). Few studies have investigated health-related quality of life questionnaires such as the Medical Outcomes Study Short Form-36 (SF-36®) as predictive tools for mortality, particularly in direct comparison with biomarkers. Our objective is to measure the relative effectiveness of SF-36® scores in predicting mortality when compared to traditional and novel biomarkers in a primary prevention population.

Methods: 7056 patients evaluated for primary cardiac prevention between January 1996 and April 2011 were included in this study. Patient characteristics included medical history, SF-36® questionnaire and a laboratory panel (total cholesterol, triglycerides, HDL, LDL, ApoA, ApoB, ApoA1/ApoB ratio, homocysteine, lipoprotein (a), fibrinogen, hsCRP, uric acid and urine ACR). The primary outcome was all-cause mortality.

Results: A low SF-36® physical score independently predicted a 6-fold increase in death at 8years (above vs. below median Hazard Ratio [95% confidence interval] 5.99 [3.86-9.35], p<0.001). In a univariate analysis, SF-36® physical score had a c-index of 0.75, which was superior to that of all the biomarkers. It also carried incremental predictive ability when added to non-laboratory risk factors (Net Reclassification Index=59.9%), as well as Framingham risk score components (Net Reclassification Index=61.1%). Biomarkers added no incremental predictive value to a non-laboratory risk factor model when combined to SF-36 physical score.

Conclusion: The SF-36® physical score is a reliable predictor of mortality in patients without CVD, and outperformed most studied traditional and novel biomarkers. In an era of rising healthcare costs, the SF-36® questionnaire could be used as an adjunct simple and cost-effective predictor of mortality to current predictors.

Keywords: Biomarkers; Mortality; Primary prevention; Surveys and questionnaires.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Biomarkers / blood*
  • Cardiovascular Diseases / mortality*
  • Cardiovascular Diseases / prevention & control*
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Ohio / epidemiology
  • Primary Prevention / methods*
  • Proportional Hazards Models
  • Quality of Life
  • Risk Assessment
  • Risk Factors
  • Severity of Illness Index
  • Surveys and Questionnaires*

Substances

  • Biomarkers