Differential geographical risk of initial pseudomonas aeruginosa acquisition in young US children with cystic fibrosis

Kevin J. Psoter, Margaret Rosenfeld, Anneclaire J. De Roos, Jonathan D. Mayer, Jon Wakefield

Research output: Contribution to journalArticlepeer-review

Abstract

Pseudomonas aeruginosa is the sentinel respiratory pathogen in cystic fibrosis patients. We conducted a retrospective study to examine whether state of residence affected risk of P. aeruginosa acquisition among US children under 6 years of age with cystic fibrosis by using data from the Cystic Fibrosis Foundation National Patient Registry, 2003-2009. The outcome was time to first isolation of P. aeruginosa from a respiratory culture. We used a Bayesian hierarchical Weibull regression model with interval-censored outcomes. Spatial random effects, included at the state level and modeled using an intrinsic conditional autoregressive prior, allowed estimation of the residual spatial correlation. The regression portion of the model was adjusted for demographic and disease characteristics potentially affecting P. aeruginosa acquisition. A total of 3,608 children met the inclusion criteria and were followed for an average of 2.1 (standard deviation, 1.6) years. P. aeruginosa was cultured in 1,714 (48%) subjects. There was a moderately elevated spatial residual relative risk. An estimated 95% credible interval for the residual hazard ratio under 1 of the fitted models was 0.64-1.57; the strongest positive association was observed in the Southern states. The fact that risk for P. aeruginosa acquisition displayed spatial dependence suggests that regional factors, such as climate, may play an important role in P. aeruginosa acquisition.

Original languageEnglish (US)
Pages (from-to)1503-1513
Number of pages11
JournalAmerican journal of epidemiology
Volume179
Issue number12
DOIs
StatePublished - Jun 15 2014

Keywords

  • Bayesian hierarchical spatial models
  • Pseudomonas aeruginosa
  • Weibull regression
  • cystic fibrosis
  • interval censoring
  • intrinsic conditional autoregression

ASJC Scopus subject areas

  • Epidemiology

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