Implementation of a dynamic model updating pipeline provides a systematic process for maintaining performance of prediction models.

OBJECTIVES: We describe the steps for implementing a dynamic updating pipeline for clinical prediction models and illustrate the proposed methods in an application of 5-year survival prediction in cystic fibrosis. STUDY DESIGN AND SETTING: Dynamic model updating refers to the process of repeated updating of a clinical prediction model with new information to counter performance degradation. We describe 2 types of updating pipeline: "proactive updating" where candidate model updates are tested any time new data are available, and "reactive updating" where updates are only made when performance of the current model declines or the model structure changes. Methods for selecting the best candidate updating model are based on measures of predictive performance under the 2 pipelines. The methods are illustrated in our motivating example of a 5-year survival prediction model in cystic fibrosis. Over a dynamic updating period of 10 years, we report the updating decisions made and the performance of the prediction models selected under each pipeline. RESULTS: Both the proactive and reactive updating pipelines produced survival prediction models that overall had better performance in terms of calibration and discrimination than a model that was not updated. Further, use of the dynamic updating pipelines ensured that the prediction model's performance was consistently and frequently reviewed in new data. CONCLUSION: Implementing a dynamic updating pipeline will help guard against model performance degradation while ensuring that the updating process is principled and data-driven.

Demographic factors associated with within-individual variability of lung function for adults with cystic fibrosis: A UK registry study.

BACKGROUND: Lung function is a key outcome used in the evaluation of disease progression in cystic fibrosis. The variability of individual lung function measurements over time (within-individual variability) has been shown to predict subsequent lung function changes. Nevertheless, the association between within-individual lung function variability and demographic and genetic covariates has not been quantified. METHODS: We performed a longitudinal analysis of data from a cohort of 7099 adults with cystic fibrosis (between 18 and 49 years old) from the UK cystic fibrosis registry, containing annual review data between 1996 and 2020. A mixed-effects location-scale model is used to quantify mean FEV1 (forced expiratory volume in 1 s) trajectories and FEV1 within-individual variability as a function of sex, age at annual review, diagnosis after first year of life, homozygous F508 genotype and birth cohort. RESULTS: Mean FEV1 decreased with age and lung function variability showed a near-quadratic trend by age. Males showed higher FEV1 mean and variability than females across the whole age range. Earlier diagnosis and homozygous F508 genotype were also associated with higher FEV1 mean and variability. Individuals who died during follow-up showed on average higher lung function variability than those who survived. CONCLUSIONS: Key variables known to be linked with mean lung function in cystic fibrosis are also associated with an individual's lung function variability. This work opens new avenues to understand the role played by lung function variability in disease progression and its utility in predicting key outcomes such as mortality.

Social-environmental phenotypes of rapid cystic fibrosis lung disease progression in adolescents and young adults living in the United States.

Background: Cystic fibrosis (CF) is a genetic disease but is greatly impacted by non-genetic (social/environmental and stochastic) influences. Some people with CF experience rapid decline, a precipitous drop in lung function relative to patient- and/or center-level norms. Those who experience rapid decline in early adulthood, compared to adolescence, typically exhibit less severe clinical disease but greater loss of lung function. The extent to which timing and degree of rapid decline are informed by social and environmental determinants of health (geomarkers) is unknown. Methods: A longitudinal cohort study was performed (24,228 patients, aged 6-21 years) using the U.S. CF Foundation Patient Registry. Geomarkers at the ZIP Code Tabulation Area level measured air pollution/respiratory hazards, greenspace, crime, and socioeconomic deprivation. A composite score quantifying social-environmental adversity was created and used in covariate-adjusted functional principal component analysis, which was applied to cluster longitudinal lung function trajectories. Results: Social-environmental phenotyping yielded three primary phenotypes that corresponded to early, middle, and late timing of peak decline in lung function over age. Geographic differences were related to distinct cultural and socioeconomic regions. Extent of peak decline, estimated as forced expiratory volume in 1 s of % predicted/year, ranged from 2.8 to 4.1 % predicted/year depending on social-environmental adversity. Middle decliners with increased social-environmental adversity experienced rapid decline 14.2 months earlier than their counterparts with lower social-environmental adversity, while timing was similar within other phenotypes. Early and middle decliners experienced mortality peaks during early adolescence and adulthood, respectively. Conclusion: While early decliners had the most severe CF lung disease, middle and late decliners lost more lung function. Higher social-environmental adversity associated with increased risk of rapid decline and mortality during young adulthood among middle decliners. This sub-phenotype may benefit from enhanced lung-function monitoring and personalized secondary environmental health interventions to mitigate chemical and non-chemical stressors.

Emulated trial investigating effects of multiple treatments: estimating combined effects of mucoactive nebulisers in cystic fibrosis using registry data.

INTRODUCTION: People with cystic fibrosis (CF) are often on multiple long-term treatments, including mucoactive nebulisers. In the UK, the most common mucoactive nebuliser is dornase alfa (DNase). A common therapeutic approach for people already on DNase is to add hypertonic saline (HS). The effects of DNase and HS used alone have been studied in randomised trials, but their effects in combination have not. This study investigates whether, for people already prescribed DNase, adding HS has additional benefit for lung function or use of intravenous antibiotics. METHODS: Using UK CF Registry data from 2007 to 2018, we emulated a target trial. We included people aged 6 years and over who were prescribed DNase without HS for 2 years. We investigated the effects of combinations of DNase and HS over 5 years of follow-up. Inverse-probability-of-treatment weighting was used to control confounding. The period predated triple combination CF transmembrane conductance regulator modulators in routine care. RESULTS: 4498 individuals were included. At baseline, average age and forced expiratory volume in 1 s (FEV1%) predicted were 21.1 years and 69.7 respectively. During first year of follow-up, 3799 individuals were prescribed DNase alone; 426 added HS; 57 switched to HS alone and 216 were prescribed neither. We found no evidence that adding HS improved FEV1% at 1-5 years, or use of intravenous antibiotics at 1-4 years, compared with DNase alone. CONCLUSION: For individuals with CF prescribed DNase, we found no evidence that adding HS had an effect on FEV1% or prescription of intravenous antibiotics. Our study illustrates the emulated target trial approach using CF Registry data.

Causal inference in survival analysis using longitudinal observational data: Sequential trials and marginal structural models.

Longitudinal observational data on patients can be used to investigate causal effects of time-varying treatments on time-to-event outcomes. Several methods have been developed for estimating such effects by controlling for the time-dependent confounding that typically occurs. The most commonly used is marginal structural models (MSM) estimated using inverse probability of treatment weights (IPTW) (MSM-IPTW). An alternative, the sequential trials approach, is increasingly popular, and involves creating a sequence of "trials" from new time origins and comparing treatment initiators and non-initiators. Individuals are censored when they deviate from their treatment assignment at the start of each "trial" (initiator or noninitiator), which is accounted for using inverse probability of censoring weights. The analysis uses data combined across trials. We show that the sequential trials approach can estimate the parameters of a particular MSM. The causal estimand that we focus on is the marginal risk difference between the sustained treatment strategies of "always treat" vs "never treat." We compare how the sequential trials approach and MSM-IPTW estimate this estimand, and discuss their assumptions and how data are used differently. The performance of the two approaches is compared in a simulation study. The sequential trials approach, which tends to involve less extreme weights than MSM-IPTW, results in greater efficiency for estimating the marginal risk difference at most follow-up times, but this can, in certain scenarios, be reversed at later time points and relies on modelling assumptions. We apply the methods to longitudinal observational data from the UK Cystic Fibrosis Registry to estimate the effect of dornase alfa on survival.

Lung Function Decline in Cystic Fibrosis: Impact of Data Availability and Modeling Strategies on Clinical Interpretations.

Rationale: Studies estimating the rate of lung function decline in cystic fibrosis have been inconsistent regarding the methods used. How the methodology used impacts the validity of the results and comparability between studies is unknown. Objectives: The Cystic Fibrosis Foundation established a work group whose tasks were to examine the impact of differing approaches to estimating the rate of decline in lung function and to provide analysis guidelines. Methods: We used a natural history cohort of 35,252 individuals with cystic fibrosis aged ⩾6 years in the Cystic Fibrosis Foundation Patient Registry (CFFPR), 2003-2016. Modeling strategies using linear and nonlinear forms of marginal and mixed-effects models, which have previously quantified the rate of forced expiratory volume in 1 second (FEV1) decline (percent predicted per year), were evaluated under clinically relevant scenarios of available lung function data. Scenarios varied by sample size (overall CFFPR, medium-sized cohort of 3,000 subjects, and small-sized cohort of 150), data collection/reporting frequency (encounter, quarterly, and annual), inclusion of FEV1 during pulmonary exacerbation, and follow-up length (<2 yr, 2-5 yr, entire duration). Results: Rate of FEV1 decline estimates (percent predicted per year) differed between linear marginal and mixed-effects models; overall cohort estimates (95% confidence interval) were 1.26 (1.24-1.29) and 1.40 (1.38-1.42), respectively. Marginal models consistently estimated less rapid lung function decline than mixed-effects models across scenarios, except for short-term follow-up (both were ∼1.4). Rate of decline estimates from nonlinear models diverged by age 30. Among mixed-effects models, nonlinear and stochastic terms fit best, except for short-term follow-up (<2 yr). Overall CFFPR analysis from a joint longitudinal-survival model implied that an increase in rate of decline of 1% predicted per year in FEV1 was associated with a 1.52-fold (52%) increase in the hazard of death/lung transplant, but the results exhibited immortal cohort bias. Conclusions: Differences were as high as 0.5% predicted per year between rate of decline estimates, but we found estimates were robust to lung function data availability scenarios, except short-term follow-up and older age ranges. Inconsistencies among previous study results may be attributable to inherent differences in study design, inclusion criteria, or covariate adjustment. Results-based decision points reported herein will support researchers in selecting a strategy to model lung function decline most reflective of nuanced, study-specific goals.

Built environment factors predictive of early rapid lung function decline in cystic fibrosis.

BACKGROUND: The extent to which environmental exposures and community characteristics of the built environment collectively predict rapid lung function decline, during adolescence and early adulthood in cystic fibrosis (CF), has not been examined. OBJECTIVE: To identify built environment characteristics predictive of rapid CF lung function decline. METHODS: We performed a retrospective, single-center, longitudinal cohort study (n = 173 individuals with CF aged 6-20 years, 2012-2017). We used a stochastic model to predict lung function, measured as forced expiratory volume in 1 s (FEV1 ) of % predicted. Traditional demographic/clinical characteristics were evaluated as predictors. Built environmental predictors included exposure to elemental carbon attributable to traffic sources (ECAT), neighborhood material deprivation (poverty, education, housing, and healthcare access), greenspace near the home, and residential drivetime to the CF center. MEASUREMENTS AND MAIN RESULTS: The final model, which included ECAT, material deprivation index, and greenspace, alongside traditional demographic/clinical predictors, significantly improved fit and prediction, compared with only demographic/clinical predictors (Likelihood Ratio Test statistic: 26.78, p < 0.0001; the difference in Akaike Information Criterion: 15). An increase of 0.1 µg/m3 of ECAT was associated with 0.104% predicted/yr (95% confidence interval: 0.024, 0.183) more rapid decline. Although not statistically significant, material deprivation was similarly associated (0.1-unit increase corresponded to additional decline of 0.103% predicted/year [-0.113, 0.319]). High-risk regional areas of rapid decline and age-related heterogeneity were identified from prediction mapping. CONCLUSION: Traffic-related air pollution exposure is an important predictor of rapid pulmonary decline that, coupled with community-level material deprivation and routinely collected demographic/clinical characteristics, enhance CF prognostication and enable personalized environmental health interventions.

Trajectories of early growth and subsequent lung function in cystic fibrosis: An observational study using UK and Canadian registry data.

BACKGROUND: Understanding the pulmonary impact of changes in early life nutritional status over time in a paediatric CF population may help inform how to use nutritional assessment to guide clinical care. National registry data provides an opportunity to study patterns of weight gain over time at the level of the individual, and thus to gain detailed understanding of the relationship between early weight trajectories and later lung function in children with Cystic Fibrosis (CF). METHODS: Using data from the United Kingdom (UK) and Canadian CF Registries, a mixed effects linear regression model was used to describe children's weight and BMI z-score trajectories from age 1 to 5 years. The intercept (weight-for-age at age 1) and slope (weight-for-age trajectory) from this model were then used as covariates in a linear regression of first lung function measurement at age 6 years. RESULTS: In both the UK and Canadian data, greater weight-for-age z-score at age 1 year and greater change in weight-for-age over time were associated with higher FEV1% predicted. A greater weight-for-age z-score at age 1 year was associated with a higher FEV1% predicted (UK: 3.78% (95% CI: 1.76; 4.70); Canada: 3.20% (95%CI: 1.76, 4.70)). These associations were reproduced for BMI z-scores and FVC% predicted. CONCLUSIONS: Early weight-for-age, specifically at age 1 year, and weight-for-age trajectories across early childhood are associated with later lung function. This relationship persists after adjustment for potential confounders. Current guidelines may need to be updated to place less emphasis on a specific cut-off (such as the 10th percentile) and encourage tracking of weight-for-age over time.

The long-term effects of insulin use in incident cystic fibrosis-related diabetes: a target trial emulated using longitudinal national registry data.

Introduction: Cystic fibrosis-related diabetes (CFRD) is a common complication of cystic fibrosis and is associated with deleterious clinical outcomes. Insulin is recommended as a treatment by international guidelines. However, there are scarce clinical trial data to support the use of insulin, and little is known about the long-term outcomes of treatment. The aim of this study was to compare the long-term impacts of insulin use versus non-use in CFRD. Methods: We used data from the national UK Cystic Fibrosis Registry and adopted a target trial framework. Eligible individuals included those 12 years and older with a new diagnosis of CFRD. Outcomes were change in % predicted forced expiratory volume in 1 s (FEV1 %) and body mass index z-scores (BMI) over a 5-year follow-up period. Treatment strategies were to receive insulin or not for the duration of follow-up. Treatment effect estimates were obtained using two methods to control for confounding: inverse-probability-of-treatment weighted estimation of marginal structural models and the G-formula. Results: We identified 1613 individuals diagnosed with CFRD between 2008 and 2016 and included 1196 and 1192 in the FEV1 % and BMI outcome analyses respectively. We found no evidence of an effect of insulin on FEV1 % over the 5-year study period. Similarly, we found no overall effect of insulin on BMI; however, there was some evidence for a positive treatment effect in patients with lower baseline BMI. Conclusion: Using well-established national registry data, we found no evidence of long-term treatment effects for insulin on FEV1 % or BMI in people with incident CFRD.

Mediation of the total effect of cystic fibrosis-related diabetes on mortality: A UK Cystic Fibrosis Registry cohort study.

AIM: To investigate whether the effect of cystic fibrosis-related diabetes (CFRD) on the composite outcome of mortality or transplant could act through lung function, pulmonary exacerbations and/or nutritional status. METHODS: A retrospective cohort of adult cystic fibrosis (CF) patients who had not been diagnosed with CFRD were identified from the UK Cystic Fibrosis Registry (n = 2750). Rate of death or transplant was compared between patients who did and did not develop CFRD (with insulin use) during follow-up using Poisson regression, separately by sex. Causal mediation methods were used to investigate whether lung function, pulmonary exacerbations and nutritional status lie on the causal pathway between insulin-treated CFRD and mortality/transplant. RESULTS: At all ages, the mortality/transplant rate was higher in both men and women diagnosed with CFRD. Pulmonary exacerbations were the strongest mediator of the effect of CFRD on mortality/transplant, with an estimated 15% [95% CI: 7%, 28%] of the effect at 2 years post-CFRD diagnosis attributed to exacerbations, growing to 24% [95% CI: 9%, 46%] at 4 years post-diagnosis. Neither lung function nor nutritional status were found to be significant mediators of this effect. Estimates were similar but with wider confidence intervals in a cohort that additionally included people with CFRD but not using insulin. CONCLUSION: There is evidence that pulmonary exacerbations mediate the effect of CFRD on mortality but, as they are estimated to mediate less than one-quarter of the total effect, the mechanism through which CFRD influences survival may involve other factors.

Time-varying Comparison of All-cause Mortality After Liver Transplantation Between Recipients With and Without Hepatocellular Carcinoma: A Population-based Cohort Study Using the United Kingdom Liver Transplant Registry.

BACKGROUND: Accurately identifying time-varying differences in the hazard of all-cause mortality after liver transplantation (LT) between recipients with and without hepatocellular carcinoma (HCC) may inform patient selection and organ allocation policies as well as post-LT surveillance protocols. METHODS: A UK population-based study was carried out using 9586 LT recipients. The time-varying association between HCC and post-LT all-cause mortality was estimated using an adjusted flexible parametric model (FPM) and expressed as hazard ratios (HRs). Differences in this association by transplant year were then investigated. Non-cancer-specific mortality was compared between HCC and non-HCC recipients using an adjusted subdistribution hazard model. RESULTS: The HR comparing HCC recipients with non-HCC recipients was below one immediately after LT (1-mo HR = 0.76; 95% confidence interval [CI], 0.59-0.99; P = 0.044). The HR then increased sharply to a maximum at 1.3 y (HR = 2.07; 95% CI, 1.70-2.52; P < 0.001) before decreasing. The hazard of death was significantly higher in HCC recipients than in non-HCC recipients between 4 mo and 7.4 y post-LT. There were no notable differences in the association between HCC and the post-LT hazard of death by transplant year. The estimated non-cancer-specific subdistribution HR for HCC was 0.93 (95% CI, 0.80-1.09; P = 0.390) and not found to vary over time. CONCLUSIONS: FPMs can provide a more precise comparison of post-LT hazards of mortality between HCC and non-HCC patients. The results provide further evidence that some HCC patients have extra-hepatic spread at the time of LT, which has implications for optimal post-LT surveillance protocols.

Methods of analysis for survival outcomes with time-updated mediators, with application to longitudinal disease registry data.

Mediation analysis is a useful tool to illuminate the mechanisms through which an exposure affects an outcome but statistical challenges exist with time-to-event outcomes and longitudinal observational data. Natural direct and indirect effects cannot be identified when there are exposure-induced confounders of the mediator-outcome relationship. Previous measurements of a repeatedly-measured mediator may themselves confound the relationship between the mediator and the outcome. To overcome these obstacles, two recent methods have been proposed, one based on path-specific effects and one based on an additive hazards model and the concept of exposure splitting. We investigate these techniques, focusing on their application to observational datasets. We apply both methods to an analysis of the UK Cystic Fibrosis Registry dataset to identify how much of the relationship between onset of cystic fibrosis-related diabetes and subsequent survival acts through pulmonary function. Statistical properties of the methods are investigated using simulation. Both methods produce unbiased estimates of indirect and direct effects in scenarios consistent with their stated assumptions but, if the data are measured infrequently, estimates may be biased. Findings are used to highlight considerations in the interpretation of the observational data analysis.

Oral Bisphosphonates Are Associated With Increased Risk of Severe Acute Kidney Injury in Elderly Patients With Complex Health Needs: A Self-Controlled Case Series in the United Kingdom.

Although oral bisphosphonates (BP) are commonly used, there is conflicting evidence for their safety in the elderly. Safety concerns might trump BP use in older patients with complex health needs. Our study evaluated the safety of BP, focusing on severe acute kidney injury (AKI), gastrointestinal ulcer (GI ulcer), osteonecrosis of the jaw (ONJ), and femur fractures. We used UK primary care data (Clinical Practice Research Datalink [CPRD GOLD]), linked to hospital (Hospital Episode Statistics [HES] inpatient) and ONS mortality data. We included all patients aged >65 with complex health needs and no BP use in the year before study start (January 1, 2010). Complex health needs were defined in three cohorts: an electronic frailty index score ≥3 (frailty cohort), one or more unplanned hospitalization/s (hospitalization cohort); and prescription of ≥10 different medicines in 2009 (polypharmacy cohort). Incidence rates were calculated for all outcomes. Subsequently, all individuals who experienced AKI or GI ulcer anytime during follow-up were included for Self-Controlled Case Series (SCCS) analyses. Incidence rate ratios (IRRs) were estimated separately for AKI and GI ulcer, comparing event rates between BP-exposed and unexposed time windows. No SCCS were conducted for ONJ and femur fractures. We identified 94,364 individuals in the frailty cohort, as well as 78,184 and 95,621 persons in the hospitalization and polypharmacy cohorts. Of those, 3023, 1950, and 2992 individuals experienced AKI and 1403, 1019, and 1453 had GI ulcer/s during follow-up, respectively. Age-adjusted SCCS models found evidence of increased risk of AKI associated with BP use (frailty cohort: IRR 1.65; 95% confidence interval [CI], 1.25-2.19), but no association with GI ulcers (frailty cohort: IRR 1.24; 95% CI, 0.86-1.78). Similar results were obtained for the hospitalization and polypharmacy cohorts. Our study found a 50% to 65% increased risk of AKI associated with BP use in elderly patients with complex health needs. Future studies should further investigate the risk-benefit of BP use in these patients. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Treatment patterns in people with cystic fibrosis: have they changed since the introduction of ivacaftor?

BACKGROUND: In late 2012, ivacaftor became available in the UK for people with cystic fibrosis (CF) aged 6 years and over with a G551D mutation. Long-term changes in treatment patterns have not previously been reported. We investigated long-term treatment patterns in people with CF with a G551D mutation who took ivacaftor and compared these with non-ivacaftor-treated cohorts using the UK Cystic Fibrosis Registry. METHODS: Using 2007-2018 data we compared treatment patterns between four cohorts: 1: ivacaftor-treated; 2: ivacaftor era (2013-2018), ineligible genotype (no G551D mutation); 3: pre-ivacaftor era (2007-2012), eligible genotype (G551D mutation); 4: pre-ivacaftor era, ineligible genotype. Treatments included: inhaled antibiotics, dornase alfa, hypertonic saline, chronic oral antibiotics and supplementary feeding. RESULTS: Up to 2012 the percentages of people taking each treatment were similar between the two cohorts defined by genotype and tended to increase by year with a similar slope. Once ivacaftor was introduced, the use of other treatments tended to decrease or remain stable by year for the ivacaftor-treated cohort, whereas it remained stable or increased in the non-ivacaftor-treated cohort. This led to differences in treatment use between the two cohorts in the ivacaftor-era, which became more marked over time. CONCLUSIONS: We have shown a clear divergence in treatment patterns since the introduction of ivacaftor in a number of key treatments widely used in CF. Further research is needed to investigate whether the differences in treatment patterns are associated with changes in health outcomes.

Using Negative Control Outcomes and Difference-in-Differences Analysis to Estimate Treatment Effects in an Entirely Treated Cohort: The Effect of Ivacaftor in Cystic Fibrosis.

When an entire cohort of patients receives a treatment, it is difficult to estimate the treatment effect in the treated because there are no directly comparable untreated patients. Attempts can be made to find a suitable control group (e.g., historical controls), but underlying differences between the treated and untreated can result in bias. Here we show how negative control outcomes combined with difference-in-differences analysis can be used to assess bias in treatment effect estimates and obtain unbiased estimates under certain assumptions. Causal diagrams and potential outcomes are used to explain the methods and assumptions. We apply the methods to UK Cystic Fibrosis Registry data to investigate the effect of ivacaftor, introduced in 2012 for a subset of the cystic fibrosis population with a particular genotype, on lung function and annual rate (days/year) of receiving intravenous (IV) antibiotics (i.e., IV days). We consider 2 negative control outcomes: outcomes measured in the pre-ivacaftor period and outcomes among persons ineligible for ivacaftor because of their genotype. Ivacaftor was found to improve lung function in year 1 (an approximately 6.5-percentage-point increase in ppFEV1), was associated with reduced lung function decline (an approximately 0.5-percentage-point decrease in annual ppFEV1 decline, though confidence intervals included 0), and reduced the annual rate of IV days (approximately 60% over 3 years).

Projecting the impact of triple CFTR modulator therapy on intravenous antibiotic requirements in cystic fibrosis using patient registry data combined with treatment effects from randomised trials.

BACKGROUND: Cystic fibrosis (CF) is a life-threatening genetic disease, affecting around 10 500 people in the UK. Precision medicines have been developed to treat specific CF-gene mutations. The newest, elexacaftor/tezacaftor/ivacaftor (ELEX/TEZ/IVA), has been found to be highly effective in randomised controlled trials (RCTs) and became available to a large proportion of UK CF patients in 2020. Understanding the potential health economic impacts of ELEX/TEZ/IVA is vital to planning service provision. METHODS: We combined observational UK CF Registry data with RCT results to project the impact of ELEX/TEZ/IVA on total days of intravenous (IV) antibiotic treatment at a population level. Registry data from 2015 to 2017 were used to develop prediction models for IV days over a 1-year period using several predictors, and to estimate 1-year population total IV days based on standards of care pre-ELEX/TEZ/IVA. We considered two approaches to imposing the impact of ELEX/TEZ/IVA on projected outcomes using effect estimates from RCTs: approach 1 based on effect estimates on FEV1% and approach 2 based on effect estimates on exacerbation rate. RESULTS: ELEX/TEZ/IVA is expected to result in significant reductions in population-level requirements for IV antibiotics of 16.1% (~17 800 days) using approach 1 and 43.6% (~39 500 days) using approach 2. The two approaches require different assumptions. Increased understanding of the mechanisms through which ELEX/TEZ/IVA acts on these outcomes would enable further refinements to our projections. CONCLUSIONS: This work contributes to increased understanding of the changing healthcare needs of people with CF and illustrates how Registry data can be used in combination with RCT evidence to estimate population-level treatment impacts.

Lung function in children with cystic fibrosis in the USA and UK: a comparative longitudinal analysis of national registry data.

RATIONALE: A previous analysis found significantly higher lung function in the US paediatric cystic fibrosis (CF) population compared with the UK with this difference apparently decreasing in adolescence and adulthood. However, the cross-sectional nature of the study makes it hard to interpret these results. OBJECTIVES: To compare longitudinal trajectories of lung function in children with CF between the USA and UK and to explore reasons for any differences. METHODS: We used mixed effects regression analysis to model lung function trajectories in the study populations. Using descriptive statistics, we compared early growth and nutrition (height, weight, body mass index), infections (Pseudomonas aeruginosa, Staphylococcus aureus) and treatments (rhDnase, hypertonic saline, inhaled antibiotics). RESULTS: We included 9463 children from the USA and 3055 children from the UK with homozygous F508del genotype. Lung function was higher in the USA than in the UK when first measured at age six and remained higher throughout childhood. We did not find important differences in early growth and nutrition, or P.aeruginosa infection. Prescription of rhDNase and hypertonic saline was more common in the USA. Inhaled antibiotics were prescribed at similar levels in both countries, but Tobramycin was prescribed more in the USA and colistin in the UK. S. aureus infection was more common in the USA than the UK. CONCLUSIONS: Children with CF and homozygous F508del genotype in the USA had better lung function than UK children. These differences do not appear to be explained by early growth or nutrition, but differences in the use of early treatments need further investigation.

Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study.

OBJECTIVES: To derive and validate risk prediction algorithms to estimate the risk of covid-19 related mortality and hospital admission in UK adults after one or two doses of covid-19 vaccination. DESIGN: Prospective, population based cohort study using the QResearch database linked to data on covid-19 vaccination, SARS-CoV-2 results, hospital admissions, systemic anticancer treatment, radiotherapy, and the national death and cancer registries. SETTINGS: Adults aged 19-100 years with one or two doses of covid-19 vaccination between 8 December 2020 and 15 June 2021. MAIN OUTCOME MEASURES: Primary outcome was covid-19 related death. Secondary outcome was covid-19 related hospital admission. Outcomes were assessed from 14 days after each vaccination dose. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance was evaluated in a separate validation cohort of general practices. RESULTS: Of 6 952 440 vaccinated patients in the derivation cohort, 5 150 310 (74.1%) had two vaccine doses. Of 2031 covid-19 deaths and 1929 covid-19 hospital admissions, 81 deaths (4.0%) and 71 admissions (3.7%) occurred 14 days or more after the second vaccine dose. The risk algorithms included age, sex, ethnic origin, deprivation, body mass index, a range of comorbidities, and SARS-CoV-2 infection rate. Incidence of covid-19 mortality increased with age and deprivation, male sex, and Indian and Pakistani ethnic origin. Cause specific hazard ratios were highest for patients with Down's syndrome (12.7-fold increase), kidney transplantation (8.1-fold), sickle cell disease (7.7-fold), care home residency (4.1-fold), chemotherapy (4.3-fold), HIV/AIDS (3.3-fold), liver cirrhosis (3.0-fold), neurological conditions (2.6-fold), recent bone marrow transplantation or a solid organ transplantation ever (2.5-fold), dementia (2.2-fold), and Parkinson's disease (2.2-fold). Other conditions with increased risk (ranging from 1.2-fold to 2.0-fold increases) included chronic kidney disease, blood cancer, epilepsy, chronic obstructive pulmonary disease, coronary heart disease, stroke, atrial fibrillation, heart failure, thromboembolism, peripheral vascular disease, and type 2 diabetes. A similar pattern of associations was seen for covid-19 related hospital admissions. No evidence indicated that associations differed after the second dose, although absolute risks were reduced. The risk algorithm explained 74.1% (95% confidence interval 71.1% to 77.0%) of the variation in time to covid-19 death in the validation cohort. Discrimination was high, with a D statistic of 3.46 (95% confidence interval 3.19 to 3.73) and C statistic of 92.5. Performance was similar after each vaccine dose. In the top 5% of patients with the highest predicted covid-19 mortality risk, sensitivity for identifying covid-19 deaths within 70 days was 78.7%. CONCLUSION: This population based risk algorithm performed well showing high levels of discrimination for identifying those patients at highest risk of covid-19 related death and hospital admission after vaccination.

Seasonality, mediation and comparison (SMAC) methods to identify influences on lung function decline.

This study develops a comprehensive method to assess seasonal influences on a longitudinal marker and compare estimates between cohorts. The method extends existing approaches by (i) combining a sine-cosine model of seasonality with a specialized covariance function for modeling longitudinal correlation; (ii) performing mediation analysis on a seasonality model. An example dataset and R code are provided. The bundle of methods is referred to as seasonality, mediation and comparison (SMAC). The case study described utilizes lung function as the marker observed on a cystic fibrosis cohort but SMAC can be used to evaluate other markers and in other disease contexts. Key aspects of customization are as follows.•This study introduces a novel seasonality model to fit trajectories of lung function decline and demonstrates how to compare this model to a conventional model in this context.•Steps required for mediation analyses in the seasonality model are shown.•The necessary calculations to compare seasonality models between cohorts, based on estimation coefficients, are derived in the study.