Data accuracy, consistency and completeness of the national Swiss cystic fibrosis patient registry: Lessons from an ECFSPR data quality project.

BACKGROUND: Good data quality is essential when rare disease registries are used as a data source for pharmacovigilance studies. This study investigated data quality of the Swiss cystic fibrosis (CF) registry in the frame of a European Cystic Fibrosis Society Patient Registry (ECFSPR) project aiming to implement measures to increase data reliability for registry-based research. METHODS: All 20 pediatric and adult Swiss CF centers participated in a data quality audit between 2018 and 2020, and in a re-audit in 2022. Accuracy, consistency and completeness of variables and definitions were evaluated, and missing source data and informed consents (ICs) were assessed. RESULTS: The first audit included 601 out of 997 Swiss people with CF (60.3 %). Data quality, as defined by data correctness ≥95 %, was high for most of the variables. Inconsistencies of specific variables were observed because of an incorrect application of the variable definition. The proportion of missing data was low with <5 % for almost all variables. A considerable number of missing source data occurred for CFTR variants. Availability of ICs varied largely between centers (10 centers had >5 % of missing documents). After providing feedback to the centers, availability of genetic source data and ICs improved. CONCLUSIONS: Data audits demonstrated an overall good data quality in the Swiss CF registry. Specific measures such as support of the participating sites, training of data managers and centralized data collection should be implemented in rare disease registries to optimize data quality and provide robust data for registry-based scientific research.

Frailty predicts outcomes in cystic fibrosis patients listed for lung transplantation.

BACKGROUND: Survival predictors are not established for cystic fibrosis (CF) patients listed for lung transplantation (LT). Using the deficit accumulation approach, we developed a CF-specific frailty index (FI) to allow risk stratification for adverse waitlist and post-LT outcomes. METHODS: We studied adult CF patients listed for LT in the Toronto LT Program (development cohort 2005-2015) and the Swiss LT centres (validation cohort 2008-2017). Comorbidities, treatment, laboratory results and social support at listing were utilized to develop a lung disease severity index (LI deficits, d = 18), a frailty index (FI, d = 66) and a lifestyle/social vulnerability index (LSVI, d = 10). We evaluated associations of the indices with worsening waitlist status, hospital and ICU length of stay, survival and graft failure. RESULTS: We studied 188 (Toronto cohort, 176 [94%] transplanted) and 94 (Swiss cohort, 89 [95%] transplanted) patients. The median waitlist times were 69 and 284 days, respectively. The median follow-up post-transplant was 5.3 and 4.7 years. At listing, 44.7% of patients were frail (FI ≥ 0.25) in the Toronto and 21.3% in the Swiss cohort. The FI was significantly associated with all studied outcomes in the Toronto cohort (FI and post-LT mortality, multivariable HR 1.74 [95%CI:1.24-2.45] per 0.1 point of the FI). In the Swiss cohort, the FI was associated with worsening waitlist status, post-LT mortality and graft failure. CONCLUSIONS: In CF patients listed for LT, FI risk stratification was significantly associated with waitlist and post-LT outcomes. Studying frailty in young populations with advanced disease can provide insights on how frailty and deficit accumulation impacts survival.

A prevalent and culturable microbiota links ecological balance to clinical stability of the human lung after transplantation.

There is accumulating evidence that the lower airway microbiota impacts lung health. However, the link between microbial community composition and lung homeostasis remains elusive. We combine amplicon sequencing and bacterial culturing to characterize the viable bacterial community in 234 longitudinal bronchoalveolar lavage samples from 64 lung transplant recipients and establish links to viral loads, host gene expression, lung function, and transplant health. We find that the lung microbiota post-transplant can be categorized into four distinct compositional states, 'pneumotypes'. The predominant 'balanced' pneumotype is characterized by a diverse bacterial community with moderate viral loads, and host gene expression profiles suggesting immune tolerance. The other three pneumotypes are characterized by being either microbiota-depleted, or dominated by potential pathogens, and are linked to increased immune activity, lower respiratory function, and increased risks of infection and rejection. Collectively, our findings establish a link between the lung microbial ecosystem, human lung function, and clinical stability post-transplant.