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Application of gap time analysis with flexible hazards to pulmonary exacerbations in the EPIC observational study.
Rice, John D; Johnson, Rachel L; Juarez-Colunga, Elizabeth; Zemanick, Edith T; Rosenfeld, Margaret; Wagner, Brandie D.
Afiliação
  • Rice JD; Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Johnson RL; Adult and Child Consortium for Health Outcomes Research and Delivery Science, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Juarez-Colunga E; Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Zemanick ET; Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Rosenfeld M; Department of Pediatrics, University of Colorado School of Medicine and Children's Health Colorado, Aurora, CO, USA.
  • Wagner BD; Division of Pulmonology, Seattle Children's Hospital, OC.7.720 - Pulmonary, Seattle, WA, USA.
Biom J ; 64(6): 1075-1089, 2022 08.
Article em En | MEDLINE | ID: mdl-35434808
Cystic fibrosis and other chronic lung disease clinical trials often use time to first pulmonary exacerbation (PEx) or total PEx count as endpoints. The use of these outcomes may fail to capture patterns or timing of multiple exacerbations and how covariates influence the risk of future exacerbations. Analysis of gap times between PEx provides a useful framework to understand risks of subsequent events, particularly to assess if there is a temporary increase in a hazard of a subsequent PEx following the occurrence of a PEx. This may be useful for estimating the amount of time needed to follow patients after a PEx and predicting which patients are more likely to have multiple PEx. We propose a smoothed hazard for gap times to account for elevated hazards after exacerbations. A simulation study was conducted to explore model performance and was able to appropriately estimate parameters in all situations with an underlying change point with independent or correlated recurrent events. Models with different change-point structures and trends are compared using Early Pseudomonas Infection Control (EPIC) observational study data, using a quasi-likelihood modification of the Akaike information criterion; a model with a change-point provided a better fit than a model without one. The analysis suggests that the change point may be 1.8 years (SE 0.09) after the end of a PEx. Models including covariates in the hazard function revealed that having one or two copies of the Δ$\Delta$ F508 mutation, female sex, and higher numbers of previous PEx were significantly associated with increased risk of another PEx.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Infecções por Pseudomonas / Fibrose Cística Tipo de estudo: Observational_studies / Prognostic_studies Limite: Female / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Infecções por Pseudomonas / Fibrose Cística Tipo de estudo: Observational_studies / Prognostic_studies Limite: Female / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article