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J Cyst Fibros. 2019 Jan 11. pii: S1569-1993(18)30943-3. doi: 10.1016/j.jcf.2018.12.005. [Epub ahead of print]

Application of multiple event analysis as an alternative approach to studying pulmonary exacerbations as an outcome measure.

Author information

1
Department of Biostatistics and Informatics, University of Colorado School of Public Health, USA; Adult and Child Consortium for Health Outcomes Research and Delivery Science, USA. Electronic address: Elizabeth.juarez-colunga@ucdenver.edu.
2
Department of Pediatrics, Seattle Children's Hospital, University of Washington, 4800 Sand Point Way NE Seattle, WA 98105, USA.
3
Department of Pediatrics, Children's Hospital Colorado, University of Colorado Anschutz Medical Center, Aurora, CO, USA.
4
Department of Biostatistics and Informatics, University of Colorado School of Public Health, USA; Department of Pediatrics, Children's Hospital Colorado, University of Colorado Anschutz Medical Center, Aurora, CO, USA.

Abstract

BACKGROUND:

Pulmonary exacerbations (PEx) are important contributors to morbidity and mortality in cystic fibrosis (CF). Understanding risk factors for PEx is critical to improve treatment; pulmonary exacerbations also serve as an important outcome in CF clinical trials. Current risk estimates generally only evaluate time to the first PEx. Methods accounting for multiple exacerbations during the observation period could provide more power to detect significant risk factors.

METHODS:

The Early Pseudomonas Infection Control (EPIC) Observational Study enrolled participants between 2004 and 2006 who were ≤ 12 years of age and negative for Pseudomonas aeruginosa. First and multiple event analyses were used to investigate risk factors for pulmonary exacerbations.

RESULTS:

We evaluated a total of 5129 PEx from 1734 CF patients in the EPIC study. Multiple event analysis identified 2 more factors associated with occurrence of PEx compared to first event analysis. After adjusting for multiple factors, the following were associated with higher occurrence of PExs: female gender, older age at enrollment, household cigarette smoke exposure, increased cough at the most recent encounter, having used antibiotics since the previous encounter, a positive culture for any CF organism at the most recent encounter, and having had a PEx in the last 30 days.

CONCLUSIONS:

Multiple event analyses use all PEx events and may identify more risk factors for PEx than analysis of time to first PEx. We have provided an example of how to apply this type of analysis and how to interpret estimates in the context of the EPIC study.

KEYWORDS:

Andersen-Gill model; Cox model; Recurrent event analysis; Time-varying covariates

PMID:
30642785
DOI:
10.1016/j.jcf.2018.12.005

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