Patient-specific decision modeling to guide the use of drotrecogin alpha (activated) in patients with severe sepsis

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.

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.

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.

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.