Role of socioeconomic status measures in long-term mortality risk prediction after myocardial infarction

Noa Molshatzki, Yaacov Drory, Vicki Myers, Uri Goldbourt, Yael Benyamini, David M. Steinberg, Yariv Gerber*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Background: The relationship of risk factors to outcomes has traditionally been assessed by measures of association such as odds ratio or hazard ratio and their statistical significance from an adjusted model. However, a strong, highly significant association does not guarantee a gain in stratification capacity. Using recently developed model performance indices, we evaluated the incremental discriminatory power of individual and neighborhood socioeconomic status (SES) measures after myocardial infarction (MI). Methods: Consecutive patients aged ≤65 years (N=1178) discharged from 8 hospitals in central Israel after incident MI in 1992 to 1993 were followed-up through 2005. A basic model (demographic variables, traditional cardiovascular risk factors, and disease severity indicators) was compared with an extended model including SES measures (education, income, employment, living with a steady partner, and neighborhood SES) in terms of Harrell c statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Results: During the 13-year follow-up, 326 (28%) patients died. Cox proportional hazards models showed that all SES measures were significantly and independently associated with mortality. Furthermore, compared with the basic model, the extended model yielded substantial gains (all P<0.001) in c statistic (0.723 to 0.757), NRI (15.2%), IDI (5.9%), and relative IDI (32%). Improvement was observed both for sensitivity (classification of events) and specificity (classification of nonevents). Conclusions: This study illustrates the additional insights that can be gained from considering the IDI and NRI measures of model performance and suggests that, among community patients with incident MI, incorporating SES measures into a clinical-based model substantially improves long-term mortality risk prediction.

Original languageEnglish
Pages (from-to)673-678
Number of pages6
JournalMedical Care
Issue number7
StatePublished - Jul 2011


  • Integrated discrimination improvement
  • myocardial infarction
  • net reclassification improvement
  • risk prediction
  • socioeconomic status
  • survival analysis


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