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We evaluated a multivariable logistic regression model predicting 5-year survival derived from a 1993-1997 cohort from the United States Cystic Fibrosis (CF) Foundation Patient Registry to assess whether therapies introduced since 1993 have altered applicability in cohorts, non-overlapping in time, from 1993-1998, 1999-2004, 2005-2010 and 2011-2016. We applied Kaplan-Meier statistics to assess unadjusted survival. We tested logistic regression model discrimination using the C-index and calibration using Hosmer-Lemeshow tests to examine original model performance and guide updating as needed. Kaplan-Meier age-adjusted 5-year probability of death in the CF population decreased substantially during 1993-2016. Patients in successive cohorts were generally healthier at entry, with higher average age, weight and lung function and fewer pulmonary exacerbations annually. CF-related diabetes prevalence, however, steadily increased. Newly derived multivariable logistic regression models for 5-year survival in new cohorts had similar estimated coefficients to the originals. The original model exhibited excellent calibration and discrimination when applied to later cohorts despite improved survival and remains useful for predicting 5-year survival. All models may be used to stratify patients for new studies, and the original coefficients may be useful as a baseline to search for additional but rare events that affect survival in CF.

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Calibration, Cohort Studies, Cystic Fibrosis, Humans, Kaplan-Meier Estimate, Logistic Models, Models, Biological, Multivariate Analysis, Registries, Survival Analysis, Time Factors