Comparing costs associated with risk stratification rules for t-year survival

Tianxi Cai*, Lu Tian, Donald M. Lloyd-Jones

*Corresponding author for this work

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Accurate risk prediction is an important step in developing optimal strategies for disease prevention and treatment. Based on the predicted risks, patients can be stratified to different risk categories where each category corresponds to a particular clinical intervention. Incorrect or suboptimal interventions are likely to result in unnecessary financial and medical consequences. It is thus essential to account for the costs associated with the clinical interventions when developing and evaluating risk stratification (RS) rules for clinical use. In this article, we propose to quantify the value of an RS rule based on the total expected cost attributed to incorrect assignment of risk groups due to the rule. We have established the relationship between cost parameters and optimal threshold values used in the stratification rule that minimizes the total expected cost over the entire population of interest. Statistical inference procedures are developed for evaluating and comparing given RS rules and examined through simulation studies. The proposed procedures are illustrated with an example from the Cardiovascular Health Study.

Original languageEnglish (US)
Pages (from-to)597-609
Number of pages13
JournalBiostatistics
Volume12
Issue number4
DOIs
StatePublished - Oct 2011

Keywords

  • Disease prognosis
  • Optimal risk stratification
  • Risk prediction

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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