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Introduction: We aimed to develop a clinical tool for predicting 1- and 2-year risk of death for patients with cystic fibrosis (CF). The model considers patients' overall health status as well as risk of intermittent shock events in calculating the risk of death., Methods: Canadian CF Registry data from 1982 to 2015 were used to develop a predictive risk model using threshold regression. A 2-year risk of death estimated conditional probability of surviving the second year given survival for the first year. UK CF Registry data from 2007 to 2013 were used to externally validate the model., Results: The combined effect of CF chronic health status and CF intermittent shock risk provided a simple clinical scoring tool for assessing 1-year and 2-year risk of death for an individual CF patient. At a threshold risk of death of ≥20%, the 1-year model had a sensitivity of 74% and specificity of 96%. The area under the receiver operating curve (AUC) for the 2-year mortality model was significantly greater than the AUC for a model that predicted survival based on forced expiratory volume in 1 s <30% predicted (AUC 0.95 versus 0.68 respectively, p<0.001). The Canadian-derived model validated well with the UK data and correctly identified 79% of deaths and 95% of survivors in a single year in the UK., Conclusions: The prediction models provide an accurate risk of death over a 1- and 2-year time horizon. The models performed equally well when validated in an independent UK CF population., Competing Interests: Conflict of interest: S. Stanojevic has nothing to disclose. Conflict of interest: J. Sykes has nothing to disclose. Conflict of interest: A.L. Stephenson has nothing to disclose. Conflict of interest: S.D. Aaron has nothing to disclose. Conflict of interest: G.A. Whitmore has nothing to disclose., (Copyright ©ERS 2019.)

Background: We previously identified factors associated with a greater risk of death post-transplant. The purpose of this study was to develop a clinical tool to estimate the risk of death after transplant based on pre-transplant variables., Methods: We utilized the Canadian CF registry to develop a nomogram that incorporates pre-transplant clinical measures to assess post-lung transplant survival. The 1-, 3-, and 5-year survival estimates were calculated using Cox proportional hazards models., Results: Between 1988 and 2012, 539 adult Canadians with CF received a lung transplant with 208 deaths in the study period. Four pre-transplant factors most predictive of poor post-transplant survival were older age at transplantation, infection with B. cepacia complex, low FEV 1 percent predicted, and pancreatic sufficiency. A nonlinear relationship was found between risk of death and FEV 1 percent predicted, age at transplant, and BMI. We constructed a risk calculator based on our model to estimate the 1-, 3-, and 5-year probability of survival after transplant which is available online., Conclusions: Our risk calculator quantifies the risk of death associated with lung transplant using pre-transplant factors. This tool could aid clinicians and patients in the decision-making process and provide information regarding the timing of lung transplantation., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Objectives: We constructed a statistical model to assess the risk of death for cystic fibrosis (CF) patients between scheduled annual clinical visits. Our model includes a CF health index that shows the influence of risk factors on CF chronic health and on the severity and frequency of CF exacerbations., Study Design and Setting: Our study used Canadian CF registry data for 3,794 CF patients born after 1970. Data up to 2010 were analyzed, yielding 44,390 annual visit records. Our stochastic process model postulates that CF health between annual clinical visits is a superposition of chronic disease progression and an exacerbation shock stream. Death occurs when an exacerbation carries CF health across a critical threshold. The data constitute censored survival data, and hence, threshold regression was used to connect CF death to study covariates. Maximum likelihood estimates were used to determine which clinical covariates were included within the regression functions for both CF chronic health and CF exacerbations., Results: Lung function, Pseudomonas aeruginosa infection, CF-related diabetes, weight deficiency, pancreatic insufficiency, and the deltaF508 homozygous mutation were significantly associated with CF chronic health status. Lung function, age, gender, age at CF diagnosis, P aeruginosa infection, body mass index <18.5, number of previous hospitalizations for CF exacerbations in the preceding year, and decline in forced expiratory volume in 1 second in the preceding year were significantly associated with CF exacerbations. When combined in one summative model, the regression functions for CF chronic health and CF exacerbation risk provided a simple clinical scoring tool for assessing 1-year risk of death for an individual CF patient. Goodness-of-fit tests of the model showed very encouraging results. We confirmed predictive validity of the model by comparing actual and estimated deaths in repeated hold-out samples from the data set and showed excellent agreement between estimated and actual mortality., Conclusion: Our threshold regression model incorporates a composite CF chronic health status index and an exacerbation risk index to produce an accurate clinical scoring tool for prediction of 1-year survival of CF patients. Our tool can be used by clinicians to decide on optimal timing for lung transplant referral., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Background: Contemporary studies evaluating post-transplant survival are limited and often include data from single centers or selected sub-groups. The purpose of this study was to evaluate overall transplant survival and to identify risk factors associated with death after transplant., Methods: The Canadian Cystic Fibrosis Registry, a population-based cohort, was used to describe survival after lung transplant. Pre-transplant factors associated with post-transplant survival were estimated using Cox proportional hazards models., Results: Between 1988 and 2012, 580 patients received a lung transplant. In the entire cohort, post-lung transplant 1-year survival was 87.8%, 5-year survival was 66.7%, and 10-year survival was 50.2%. Median post-transplant survival was 3.3 years (95% confidence interval [CI] = 2.13-6.56) in patients infected with Burkholderia cepacia complex compared with 12.36 years (95% CI = 10.34-17.96) in patients without B cepacia infection (hazard ratio [HR] = 2.63, 95% CI = 2.0-3.44). After adjustment, there was a non-significant trend toward better post-transplant survival with increasing year of transplant (HR = 0.98, 95% CI = 0.96-1.00). Pancreatic sufficiency (HR = 2.13, 95% CI = 1.41-3.20) and age at transplant such that youngest and oldest had the poorest survival (p < 0.001) were significant negative predictors of survival. The risk of death after transplant for patients infected with B cepacia was highest within the first year (HR = 6.29, 95% CI = 3.87-10.21) but remained elevated >1 year after transplant (HR = 1.92, 95% CI = 1.33-2.77) compared with patients without B cepacia infection., Conclusions: After lung transplantation, 5-year survival in Canadians with CF is 67%, and 50% of patients live >10 years. Despite these impressive probabilities, age at transplant, pancreatic sufficiency and B cepacia infection remain important determinants of survival after lung transplantation., (Copyright © 2015 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.)

Previously established predictors of survival may no longer apply in the current era of cystic fibrosis (CF) care. Our objective was to identify risk factors associated with survival in a contemporary CF population. We used the Canadian CF Registry, a population-based cohort, to calculate median age of survival and summarise patient characteristics from 1990 to 2012. Clinical, demographic and geographical factors, and survival were estimated for a contemporary cohort (2000-2012) using Cox proportional hazards models. There were 5787 individuals in the registry between 1990 and 2012. Median survival age increased from 31.9 years (95% CI 28.3-35.2 years) in 1990 to 49.7 years (95% CI 46.1-52.2 years) in the most current 5-year window ending in 2012. Median forced expiratory volume in 1 s improved (p=0.04) and fewer subjects were malnourished (p<0.001) over time. Malnourished patients (hazard ratio (HR) 2.1, 95% CI 1.6-2.8), those with multiple exacerbations (HR 4.5, 95% CI 3.2-6.4) and women with CF-related diabetes (HR 1.8, 95% CI 1.2-2.7) were at increased risk of death. Life expectancy in Canadians with CF is increasing. Modifiable risk factors such as malnutrition and pulmonary exacerbations are associated with an increased risk of death. The sex gap in CF survival may be explained by an increased hazard for death in women with CF-related diabetes., (Copyright ©ERS 2015.)