Background: Persistent Pseudomonas aeruginosa (PPA) infection promotes lung function deterioration in children with cystic fibrosis (CF). Although early CF diagnosis through newborn screening (NBS) has been shown to provide nutritional/growth benefit, it is unclear whether NBS lowers the risk of PPA infection and how the effect of NBS vary with age. Modeling the onset age of PPA infection is challenging because 1) the onset age of PPA infection is interval censored in patient registry data; and 2) some risk factors such as NBS may have time-varying effects.
Methods: This problem fits into the framework of a recently developed Bayesian dynamic Cox model for interval censored data, where each regression coefficient is allowed to be time-varying to an extent determined by the data.
Results: Application of the methodology to data from the CF Foundation Patient Registry revealed interesting findings. Compared with patients with meconium ileus or diagnosed through signs or symptoms, patients diagnosed through NBS had significantly lower risks of acquiring PPA infection between age 1 and 2 years, and the benefit in survival rate was found to last up to age 4 years. Two cohorts of five years apart were compared. Patients born in cohort 2003-2004 had significantly lower risks of the PPA infections at any age up to 4 years than those born in 1998-1999.
Conclusions: The study supports benefits of NBS on PPA infection in early childhood. In addition, our analyses demonstrate that patients in the more recent cohort had significantly lower risks of acquiring PPA infection up to age 4 years, which suggests improved CF treatment and care over time.
Keywords: Cox model; Dynamic model; Reversible jump Markov chain Monte Carlo; Time-varying effect.