Combined survival analysis of cardiac patients by a Cox PH model and a Markov chain

Michal Shauly, Gad Rabinowitz, Harel Gilutz, Yisrael Parmet

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


The control and treatment of dyslipidemia is a major public health challenge, particularly for patients with coronary heart diseases. In this paper we propose a framework for survival analysis of patients who had a major cardiac event, focusing on assessment of the effect of changing LDL-cholesterol level and statins consumption on survival. This framework includes a Cox PH model and a Markov chain, and combines their results into reinforced conclusions regarding the factors that affect survival time. We prospectively studied 2,277 cardiac patients, and the results show high congruence between the Markov model and the PH model; both evidence that diabetes, history of stroke, peripheral vascular disease and smoking significantly increase hazard rate and reduce survival time. On the other hand, statin consumption is correlated with a lower hazard rate and longer survival time in both models. The role of such a framework in understanding the therapeutic behavior of patients and implementing effective secondary and primary prevention of heart diseases is discussed here.

Original languageEnglish
Pages (from-to)496-513
Number of pages18
JournalLifetime Data Analysis
Issue number4
StatePublished - 1 Oct 2011


  • Coronary heart disease
  • Cox PH model
  • Dyslipidemia
  • Expected survival time
  • Homogenous Markov chain
  • Major cardiac event

ASJC Scopus subject areas

  • Applied Mathematics


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