Uncovering symptom progression history from disease registry data with application to young cystic fibrosis patients

Onset of persistent pseudomonas aeruginosa infection in children with cystic fibrosis with interval censored data

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.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-016-0220-5) contains supplementary material, which is available to authorized users.

An overview of international literature from cystic fibrosis registries. Part 4: update 2011

A total of 53 national cystic fibrosis (CF) patient registry studies published between July 2008 and November 2011 have been reviewed, focusing on the following topics: CF epidemiology, nutrition, microbiology, clinical complications, factors influencing diagnosis and lung disease, effects of socioeconomic status, therapeutic strategy evaluation, clinical trial methodology. The studies describe the clinical characteristics of CF patients, the incidence and prevalence of disease and role of gender gap, as well as the influence of socioeconomic status and environmental factors on clinical outcomes, covering a variety of countries and ethnic groups. Original observations describe patients as they get older, with special reference to the adult presentation of CF and long-term survival. Methodological aspects are discussed, covering the design of clinical trials, survival analysis, auxometry, measures of quality of life, follow up of lung disease, predictability of disease progression and life expectancy. Microbiology studies have investigated the role of selected pathogens, such as Burkholderia species and MRSA. Pulmonary exacerbations are discussed both as a factor influencing morbidity and an endpoint in clinical trials. Finally, some studies give insights on complications, such as CF-related diabetes and hemoptysis, and emerging problems, such as chronic nephropathy.

Quantile regression for doubly censored data

Double censoring often occurs in registry studies when left censoring is present in addition to right censoring. In this work, we propose a new analysis strategy for such doubly censored data by adopting a quantile regression model. We develop computationally simple estimation and inference procedures by appropriately using the embedded martingale structure. Asymptotic properties, including the uniform consistency and weak convergence, are established for the resulting estimators. Moreover, we propose conditional inference to address the special identifiability issues attached to the double censoring setting. We further show that the proposed method can be readily adapted to handle left truncation. Simulation studies demonstrate good finite-sample performance of the new inferential procedures. The practical utility of our method is illustrated by an analysis of the onset of the most commonly investigated respiratory infection, Pseudomonas aeruginosa, in children with cystic fibrosis through the use of the U.S. Cystic Fibrosis Registry.