UK Cystic Fibrosis Registry Research Articles

P080 Temporal disparity between hospital episode statistics and the UK cystic fibrosis Registry

P080 Temporal disparity between hospital episode statistics and the UK cystic fibrosis Registry

WS08.4 An investigation of the effect of ivacaftor on survival using UK cystic fibrosis Registry data

WS08.4 An investigation of the effect of ivacaftor on survival using UK cystic fibrosis Registry data

P067 Mechanisms for the effect of CFRD on mortality: a causal mediation analysis using UK cystic fibrosis Registry data

P067 Mechanisms for the effect of CFRD on mortality: a causal mediation analysis using UK cystic fibrosis Registry data

Dynamic Survival Prediction Combining Landmarking with a Machine Learning Ensemble: Methodology and Empirical Comparison

AbstractDynamic prediction models provide predicted survival probabilities that can be updated over time for an individual as new measurements become available. Two techniques for dynamic survival prediction with longitudinal data dominate the statistical literature: joint modelling and landmarking. There is substantial interest in the use of machine learning methods for prediction; however, their use in the context of dynamic survival prediction has been limited. We show how landmarking can be combined with a machine learning ensemble—the Super Learner. The ensemble combines predictions from different machine learning and statistical algorithms with the goal of achieving improved performance. The proposed approach exploits discrete time survival analysis techniques to enable the use of machine learning algorithms for binary outcomes. We discuss practical and statistical considerations involved in implementing the ensemble. The methods are illustrated and compared using longitudinal data from the UK Cystic Fibrosis Registry. Standard landmarking and the landmark Super Learner approach resulted in similar cross-validated predictive performance, in this case, outperforming joint modelling.

Trends in nontuberculous mycobacteria infection in children and young people with cystic fibrosis

Nontuberculous mycobacteria (NTM) infection is of growing concern in cystic fibrosis (CF). UK CF Registry data were analyzed from 2016 to 2018. Prevalence of infection stabilized in the pediatric age-group during this period but remained substantially higher than in 2010. Allergic bronchopulmonary aspergillosis and Pseudomonas aeruginosa infection were associated with NTM infection.

Long-term safety study of colistimethate sodium (Colobreathe®): Findings from the UK Cystic Fibrosis Registry

BackgroundAs part of the risk management plan in Europe, a long-term observational study was conducted to monitor the safety of colistimethate sodium dry powder for inhalation (CMS-DPI) compared to other inhaled antibiotics. MethodsA cohort of CMS-DPI patients and a matched cohort were identified from the UK Cystic Fibrosis Registry (UKCFR) from 2014-2018. The primary outcome was a composite endpoint, defined as adverse events (AEs) or new cystic fibrosis (CF) complications. Other outcomes included pulmonary exacerbations and treatment discontinuations. ResultsOf 1466 and 3503 patients in the CMS-DPI and comparator cohorts, respectively, 82.7% and 79.4% had AEs. Among the most common new CF complications were osteopenia, CF-related diabetes, and increased liver enzymes. The adjusted event rate ratio (ERR) for the primary outcome was 1.25 (95% confidence interval [CI]: 1.18-1.33, p<0.001). After excluding new CF complications, there was no difference between cohorts (ERR=1.04, 95% CI: 0.79-1.38, p=0.785). Pulmonary exacerbations were common in CMS-DPI and comparator cohorts (78.0% and 79.9% of patients, respectively), with adjusted ERR of 1.02 (95% CI: 0.95-1.10, p=0.523). Rates of discontinuation were similar in the CMS-DPI and Tobramycin inhalation powder comparator cohorts (37.8% and 39.8% of patients, respectively). ConclusionsThere was no difference in the rate of adverse events between CMS-DPI and comparator cohorts. The safety profile of CMS-DPI is similar to those of other inhaled antibiotics, supporting its long-term safety in people with CF. The UKCFR has developed a successful model for partnership with industry to conduct long-term studies aimed at assessing drug safety.

Identifying children with Cystic Fibrosis in population-scale routinely collected data in Wales: A Retrospective Review.

IntroductionThe challenges in identifying a cohort of people with a rare condition can be addressed by routinely collected, population-scale electronic health record (EHR) data, which provide large volumes of data at a national level. This paper describes the challenges of accurately identifying a cohort of children with Cystic Fibrosis (CF) using EHR and their validation against the UK CF Registry.ObjectivesTo establish a proof of principle and provide insight into the merits of linked data in CF research; to identify the benefits of access to multiple data sources, in particular the UK CF Registry data, and to demonstrate the opportunity it represents as a resource for future CF research.MethodsThree EHR data sources were used to identify children with CF born in Wales between 1st January 1998 and 31st August 2015 within the Secure Anonymised Information Linkage (SAIL) Databank. The UK CF Registry was later acquired by SAIL and linked to the EHR cohort to validate the cases and explore the reasons for misclassifications.ResultsWe identified 352 children with CF in the three EHR data sources. This was greater than expected based on historical incidence rates in Wales. Subsequent validation using the UK CF Registry found that 257 (73%) of these were true cases. Approximately 98.7% (156/158) of individuals identified as CF cases in all three EHR data sources were confirmed as true cases; but this was only the case for 19.8% (20/101) of all those identified in just a single data source. ConclusionIdentifying health conditions in EHR data can be challenging, so data quality assurance and validation is important or the merit of the research is undermined. This retrospective review identifies some of the challenges in identifying CF cases and demonstrates the benefits of linking cases across multiple data sources to improve quality.

Explaining the Sex Effect on Survival in Cystic Fibrosis: a Joint Modeling Study of UK Registry Data.

Male sex is associated with better lung function and survival in people with cystic fibrosis but it is unclear whether the survival benefit is solely due to the sex-effect on lung function. This study analyzes data between 1996 and 2015 from the longitudinal registry study of the UK Cystic Fibrosis Registry. We jointly analyze repeated measurements and time-to-event outcomes to assess how much of the sex effect on lung function also explains survival. These novel methods allow examination of association between percent of forced expiratory volume in 1 second (%FEV1) and covariates such as sex and genotype, and survival, in the same modeling framework. We estimate the probability of surviving one more year with a probit model. The dataset includes 81,129 lung function measurements of %FEV1 on 9,741 patients seen between 1996 and 2015 and captures 1,543 deaths. Males compared with females experienced a more gradual decline in %FEV1 (difference 0.11 per year 95% confidence interval [CI] = 0.08, 0.14). After adjusting for confounders, both overall level of %FEV1 and %FEV1 rate of change are associated with the concurrent hazard for death. There was evidence of a male survival advantage (probit coefficient 0.15; 95% CI = 0.10, 0.19) which changed little after adjustment for %FEV1 using conventional approaches but was attenuated by 37% on adjustment for %FEV1 level and slope in the joint model (0.09; 95% CI = 0.06, 0.12). We estimate that about 37% of the association of sex on survival in cystic fibrosis is mediated through lung function.

The changing demography of the cystic fibrosis population: forecasting future numbers of adults in the UK

Improvements in management of cystic fibrosis (CF) through specialist centres in the UK have been associated with a step-change in life expectancy. With increasing numbers of adult patients there is a need to review health care provision to ensure it is sufficient to meet future needs. We used UK CF Registry data to project the number of patients aged 16–17 and 18 and older up to 2030, and numbers therefore requiring specialist adult CF care. Survival modelling was used to estimate age-specific mortality rates. New-diagnosis rates were estimated using diagnoses observed in the Registry and national population figures. Uncertainty in projections was captured through 95% prediction intervals (PI). The number of adults (aged 18 and older) is expected to increase by 28% from 6,225 in 2017 to 7,988 in 2030 (95% PI 7,803–8,169), assuming current mortality rates. If mortality rates improve at the rate seen over recent years, the projected number increases to 8,579 (95% PI 8,386–8,764). The age distribution is also expected to change, with 36% of CF adults being over 40 in 2030, versus 21% in 2017. There is an urgent requirement to review adult CF health care provision, due to both increasing numbers and the changing care needs of an older population.

WS23.3 The average rate of lung function decline in adults with cystic fibrosis in the United Kingdom: data from the UK Cystic Fibrosis Registry

WS23.3 The average rate of lung function decline in adults with cystic fibrosis in the United Kingdom: data from the UK Cystic Fibrosis Registry

Average rate of lung function decline in adults with cystic fibrosis in the United Kingdom: Data from the UK CF registry

BackgroundRate of change in lung function is used as a measure of disease progression and a predictor of mortality in individuals with cystic fibrosis (CF). The aim of this study was to determine the national rate of decline in percent predicted Forced Expiratory Volume in 1 second (ppFEV1) in adults in the UK accounting for age, sex and pancreatic status. MethodsData on ppFEV1 for adults with CF, excluding those post lung transplantation, was extracted from the UK CF registry between 2015 and 2017. Multilevel modelling was conducted to calculate the annual rate of change in ppFEV1 accounting for age, sex and pancreatic status. ResultsOverall annual ppFEV1 decline was -1.52% (95% CI: -1.66 to -1.38%) and -0.55% (95% CI: -0.86 to -0.23%) in pancreatic insufficient (PI) and sufficient (PS) adults respectively. In PI individuals, females had a greater rate of decline in ppFEV1. There were differences between age groups. The fastest rate of decline was observed in the 18–28 years group, declining -1.76% (95% CI: -2.06 to -1.46) and -1.61% (95% CI: -1.91 to -1.31) per year in PI females and males respectively. The pattern between the sexes and age categories was more inconsistent in the PS group. ConclusionsThe average annual rates of decline in lung function in adults with CF in the UK are similar to reports from other large international cohorts. Pancreatic status has a marked impact on average rate of decline. Younger adults, especially females, have a faster rate of decline and need close monitoring.

Real-World Outcomes Among Patients with Cystic Fibrosis Treated with Ivacaftor: 2012-2016 Experience.

IntroductionIn this long-term, postapproval, observational study, data from the US Cystic Fibrosis Foundation Patient Registry and the UK Cystic Fibrosis Registry were used to evaluate the impact of ivacaftor treatment on cystic fibrosis (CF) by comparing outcomes in ivacaftor-treated patients with those in matched untreated comparator patients. Registry data from up to 5 years of ivacaftor availability in the US and up to 4 years of availability in the UK were evaluated.MethodsStarting in the first year of ivacaftor availability, ivacaftor-treated patients in each registry were matched 1:5 to comparator patients who never received ivacaftor. Clinical endpoints were evaluated in annual cross-sectional safety analyses. The key endpoints were death, organ transplants, pulmonary exacerbation, and hospitalization. Relative risks and 95% CIs were calculated to compare the ivacaftor and comparator cohorts in each registry.ResultsHere, we report the complete and final results of the annual cross-sectional safety analyses across the duration of the study, with up to 5 years of follow-up. Data show a pattern of lower risk of death, transplant, pulmonary exacerbation, and hospitalization among ivacaftor-treated patients in both registries.ConclusionsIvacaftor-treated patients had consistently favorable clinical outcomes relative to untreated comparators, and no new safety concerns were identified. While general limitations of observational research apply, these findings support disease modification by CF transmembrane conductance regulator (CFTR) modulator therapy with ivacaftor. Future research of novel CFTR modulators will need to explore alternative methods for comparator selection for evaluation of clinical data given the evolving landscape of CF treatment.

Impact of newborn screening on outcomes and social inequalities in cystic fibrosis: a UK CF registry-based study

BackgroundNewborn bloodspot screening (NBS) for cystic fibrosis (CF) was introduced across the UK in 2007 but the impact on clinical outcomes and health inequalities for children with CF is unclear.MethodsWe...

Adjusting for time-varying confounders in survival analysis using structural nested cumulative survival time models.

Accounting for time‐varying confounding when assessing the causal effects of time‐varying exposures on survival time is challenging. Standard survival methods that incorporate time‐varying confounders as covariates generally yield biased effect estimates. Estimators using weighting by inverse probability of exposure can be unstable when confounders are highly predictive of exposure or the exposure is continuous. Structural nested accelerated failure time models (AFTMs) require artificial recensoring, which can cause estimation difficulties. Here, we introduce the structural nested cumulative survival time model (SNCSTM). This model assumes that intervening to set exposure at time t to zero has an additive effect on the subsequent conditional hazard given exposure and confounder histories when all subsequent exposures have already been set to zero. We show how to fit it using standard software for generalized linear models and describe two more efficient, double robust, closed‐form estimators. All three estimators avoid the artificial recensoring of AFTMs and the instability of estimators that use weighting by the inverse probability of exposure. We examine the performance of our estimators using a simulation study and illustrate their use on data from the UK Cystic Fibrosis Registry. The SNCSTM is compared with a recently proposed structural nested cumulative failure time model, and several advantages of the former are identified.

Ivacaftor Is Associated with Reduced Lung Infection by Key Cystic Fibrosis Pathogens. A Cohort Study Using National Registry Data.

Rationale: Ivacaftor can greatly improve clinical outcomes in people with cystic fibrosis (CF) and has been shown to have in vitro antibacterial properties, yet the long-term microbiological outcomes of treatment are unknown.Objectives: To investigate changes in respiratory microbiology associated with long-term ivacaftor use.Methods: This was a retrospective cohort study using data from the UK CF Registry 2011-2016. Primary outcome was the annual prevalence ratios for key CF pathogens between ivacaftor users and their contemporaneous comparators. Multivariable log-binomial regression models were designed to adjust for confounders. Changes in Pseudomonas aeruginosa status were compared between groups using nonparametric maximum likelihood estimate for the purposes of Kaplan-Meier approximation.Results: Ivacaftor use was associated with early and sustained reduction in P. aeruginosa rates (2016 adjusted prevalence ratio, 0.68; 95% confidence interval, 0.58-0.79; P < 0.001) via a combination of increased clearance in those with infection (ivacaftor: 33/87 [37.9%] vs. nonivacaftor: 432/1,872 [22.8%]; P < 0.001) and reduced acquisition in those without infection (49/134 [36.6%] vs. 1,157/2,382 [48.6%]; P = 0.01). The improved prevalence of P. aeruginosa infection was independent of reduced sampling in the ivacaftor cohort. Ivacaftor was also associated with reduced prevalence of Staphylococcus aureus and Aspergillus spp. but not Burkholderia cepacia complex.Conclusions: In this study, long-term ivacaftor use was associated with reduced infection with important CF pathogens including P. aeruginosa. These findings have implications for antibiotic stewardship and the need for ongoing chronic antimicrobial therapy in this cohort.

P068 Describing treatment burden in people with cystic fibrosis: analysis of the UK Cystic Fibrosis Registry

P068 Describing treatment burden in people with cystic fibrosis: analysis of the UK Cystic Fibrosis Registry

P085 Investigating time between annual review encounters in the UK Cystic Fibrosis Registry

P085 Investigating time between annual review encounters in the UK Cystic Fibrosis Registry

EPS2.05 Incidence and risk factors of cancer: a UK cystic fibrosis Registry study

ePS2.05 Incidence and risk factors of cancer: a UK cystic fibrosis Registry study

P071 Linkage of the UK cystic fibrosis Registry with electronic health records in Wales: a new resource for research

P071 Linkage of the UK cystic fibrosis Registry with electronic health records in Wales: a new resource for research

P055 Symptoms in early infancy and impact of subsequent growth and infection on lung function age 6: pathway analysis of UK Cystic Fibrosis Registry

P055 Symptoms in early infancy and impact of subsequent growth and infection on lung function age 6: pathway analysis of UK Cystic Fibrosis Registry