A general approach to risk modeling using partial surrogate markers with application to perioperative acute kidney injury.

ABSTRACT:

Background

Surrogate outcomes are often utilized when disease outcomes are difficult to directly measure. When a biological threshold effect exists, surrogate outcomes may only represent disease in specific subpopulations. We refer to these outcomes as "partial surrogate outcomes." We hypothesized that risk models of partial surrogate outcomes would perform poorly if they fail to account for this population heterogeneity. We developed criteria for predictive model development using partial surrogate outcomes and demonstrate their importance in model selection and evaluation within the clinical example of serum creatinine, a partial surrogate outcome for acute kidney injury.

Methods

Data from 4737 patients who underwent cardiac surgery at a major academic center were obtained

SUBMITTER: Smith DK 

PROVIDER: S-EPMC6460789 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature