Predictive factors of survival in people with cystic fibrosis from a Spanish rare disease registry.

Abstract

Background:Cystic fibrosis (CF) is the most common multisystem, chronic, and life-threatening rare disease in the Caucasian population. Progressive loss of lung function remains the leading cause of death. However, improvementsin prognosis and survival have caused CF to go from being a lethal disease in childhood to becoming an increasingly frequent pathology in adults. In Spain, the factors that influence survival have not been determined. The objective of the study is to analyse survival and determine the factors associated with it in people with CF from a region in southeastern Spain based on information from a rare disease registry. Methods: A cross-sectional study was carried out in people with a confirmed diagnosis of CF up to December 31 2018, who were registered in the Rare Disease Information System of the Region of Murcia (SIERrm). The Kaplan‒Meier method and the log-rank test were used to estimate and compare survival curves. Predictors of survival were calculated using the Cox proportional hazards model. Results:Of the 192 patients registered in SIERrm with a confirmed diagnosis of CF, 39 patients died with a median age of 22 years (IQR: 15.0 - 33.0), of which 77% were classified within high-risk genotypes. The median survival age was 26.0 years (95% CI: 22.0 - 30.0),and the 10-year survival from diagnosis was 87.6%. In addition, high-risk genotype [HR: 5.8 (95% CI: 1.97 - 16.94)], pancreatic insufficiency [HR: 5.4 (95% CI: 1.24 - 23.48)], chronic colonization by Pseudomonas aeruginosa [HR: 6.8 (95% CI: 1.21 - 38.54)], the development of CF-related liver disease [HR: 5.0 (95% CI: 1.61 - 15.61)] and bone anomalies [HR: 6.4 (95% CI: 1.91 - 21.61)] were associated with decreased survival (p<0.05). Conclusions: In the Regionof Murcia, people with a high-risk genotype, pancreatic insufficiency, chronic colonization by Pseudomonas aeruginosa, and the development of CF-related bone and liver complications predict a higher risk of dying or being transplanted and therefore a decrease in survival. The use of population registries is useful for estimating survival and showing the factors associated with it, which is important for planning care needs and implementing personalized medicine that influences these factors.