title: Patient-specific decision modeling to guide the use of drotrecogin alpha (activated) in patients with severe sepsis.
abstract: OBJECTIVE
  The expected benefit of treating severe sepsis with drotrecogin alpha (activated) for an individual patient may depend upon several clinical factors including disease severity. Our objective was to create a decision support tool incorporating patient-specific inputs to estimate the balance between treatment risks and benefits for individual patients with severe sepsis.
  
  
  METHODS
  Logistic regression models were developed to calculate patient-specific mortality risk with and without treatment, which were then used as inputs into a 75-state Markov model. Patient-specific inputs included patient age, sex, and 12 readily available clinical characteristics.
  
  
  RESULTS
  The expected benefit from drotrecogin alpha (activated) treatment was most dependent upon the underlying disease severity. For example, for a 56-year-old white man with severe sepsis and a 28-day mortality risk of 29%, the model predicted a treatment-related gain of 1.2 quality-adjusted life years (17.3 vs 16.1). Probabilistic sensitivity analyses demonstrated that this patient would benefit from therapy 85% of the time.
  
  
  CONCLUSIONS
  A customizable decision model using patient-specific inputs can be used to inform the treatment decision when considering the use of drotrecogin alpha (activated) therapy by weighing the risks vs the benefits of therapy in the treatment of severe sepsis.
authors.affiliation: Division of General Internal Medicine, University of Cincinnati Medical Center, Cincinnati, OH 45267-0535, USA. daniel.schauer@uc.edu
authors.forename: Daniel P
authors.initials: DP
authors.lastname: Schauer
authors.forename: Anthony C
authors.initials: AC
authors.lastname: Leonard
authors.forename: Richard W
authors.initials: RW
authors.lastname: Hornung
authors.forename: Joseph A
authors.initials: JA
authors.lastname: Johnston
authors.forename: Mark H
authors.initials: MH
authors.lastname: Eckman
mesh_terms: D018806:APACHE; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000890:Anti-Infective Agents / Q000008:administration & dosage / Q000627:therapeutic use*; D020000:Decision Support Systems, Clinical; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D011486:Protein C / Q000008:administration & dosage / Q000627:therapeutic use*; D011994:Recombinant Proteins / Q000008:administration & dosage / Q000627:therapeutic use; D015203:Reproducibility of Results; D012307:Risk Factors; D018805:Sepsis / Q000188:drug therapy*; D012737:Sex Factors
chemical_list: D000890:Anti-Infective Agents; D011486:Protein C; D011994:Recombinant Proteins; C421124:drotrecogin alfa activated