A Novel Tool to Evaluate the Accuracy of Predicting Survival and Guiding Lung Transplantation in Cystic Fibrosis.

ABSTRACT:

Background

Effective transplantation recommendations in cystic fibrosis (CF) require accurate survival predictions, so that high-risk patients may be prioritized for transplantation. In practice, decisions about transplantation are made dynamically, using routinely updated assessments. We present a novel tool for evaluating risk prediction models that, unlike traditional methods, captures classification accuracy in identifying high-risk patients in a dynamic fashion.

Methods

Predicted risk is used as a score to rank incident deaths versus patients who survive, with the goal of ranking the deaths higher. The mean rank across deaths at a given time measures time-specific predictive accuracy; when assessed over time, it reflects time-varying accuracy.

Results

Applying th

SUBMITTER: Bansal A 

PROVIDER: S-EPMC6743328 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature