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

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Abstract

Purpose:

The expected benefit of treating severe sepsis with drotrecogin α (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.

Materials and 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 α (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 α (activated) therapy by weighing the risks vs the benefits of therapy in the treatment of severe sepsis.

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