Dynamic predictive probabilities to monitor rapid cystic fibrosis disease progression.

ABSTRACT: Cystic fibrosis (CF) is a progressive, genetic disease characterized by frequent, prolonged drops in lung function. Accurately predicting rapid underlying lung-function decline is essential for clinical decision support and timely intervention. Determining whether an individual is experiencing a period of rapid decline is complicated due to its heterogeneous timing and extent, and error component of the measured lung function. We construct individualized predictive probabilities for "nowcasting" rapid decline. We assume each patient's true longitudinal lung function, S(t), follows a nonlinear, nonstationary stochastic process, and accommodate between-patient heterogeneity through random effects. Corresponding lung-function decline at time t is defined as the rate of change, S'(t). We predi

SUBMITTER: Szczesniak RD 

PROVIDER: S-EPMC7028099 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature