ARE POST-LAUNCH DATA FROM RARE DISEASE REGISTRIES FIT FOR HTA POLICY DECISIONS? LESSONS FROM THE DUTCH CYSTIC FIBROSIS REGISTRY
Author(s)
Jelle Stoelinga, PharmD1, Daniala Weir, PhD1, Carla Hollak, MD, PhD2, Regina Hofland, PhD MD3, Hettie Janssens, PhD MD4, Karin Winter-de Groot, PhD MD5, Christine Leopold, PhD1, Wim Goettsch, MSc, PhD6, Domenique Zomer-van Ommen, PhD7.
1Division of Pharmacoepidemiology and Clinical Pharmacology, Department of Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands, 2RARE-NL foundation at Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands; Department of Endocrinology and Metabolism, Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Research Institute, Expertise center, Amsterdam, Netherlands, 3Department of Pulmonary Medicine, University Medical Center Utrecht, Utrecht, Netherlands, 4Department of Pediatrics, div of Respiratory Medicine and Allergology, Erasmus University Medical Center, Sophia Children's Hospital, Rotterdam, Netherlands, 5Department of Pediatric Pulmonology, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, Utrecht, Netherlands, 6Zorginstituut Nederland, Diemen, the Netherlands; Division of Pharmacoepidemiology and Clinical Pharmacology, Department of Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands, 7Dutch Cystic Fibrosis Foundation, Soest, Netherlands.
1Division of Pharmacoepidemiology and Clinical Pharmacology, Department of Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands, 2RARE-NL foundation at Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands; Department of Endocrinology and Metabolism, Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Research Institute, Expertise center, Amsterdam, Netherlands, 3Department of Pulmonary Medicine, University Medical Center Utrecht, Utrecht, Netherlands, 4Department of Pediatrics, div of Respiratory Medicine and Allergology, Erasmus University Medical Center, Sophia Children's Hospital, Rotterdam, Netherlands, 5Department of Pediatric Pulmonology, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, Utrecht, Netherlands, 6Zorginstituut Nederland, Diemen, the Netherlands; Division of Pharmacoepidemiology and Clinical Pharmacology, Department of Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands, 7Dutch Cystic Fibrosis Foundation, Soest, Netherlands.
OBJECTIVES: Real-world evidence is increasingly used to evaluate medication effectiveness in everyday clinical practice, yet the suitability of rare disease registry data for this purpose remains uncertain. Using the Dutch Cystic Fibrosis Registry (NCFR) as a case study, this study evaluates the feasibility of rare disease registry data for estimating medicine effectiveness post-reimbursement in the context of health technology assessment (HTA).
METHODS: We evaluated the NCFR using the EMA data quality framework across three domains. First, we assessed system reliability by rating the maturity of registry elements related to data collection and governance on a three-level scale. Second, we evaluated data quality using metrics of timeliness, extensiveness, and reliability. Third, as one key parameter of the registry’s data fit-for-purposeness, we assessed the precision of a relative effectiveness estimation by estimating the number of patients transitioning from dual to triple Cystic Fibrosis Transmembrane Regulator (CFTR) modulator therapy.
RESULTS: On system reliability, nine out of eleven are relevant for the NCFR, five of these reached the lowest maturity level (level 1) and four reached level 2; none achieved level 3. Despite this, the NCFR performed well across all data quality metrics: timeliness (mean 15-year follow-up, annual updates), extensiveness (>95% population coverage; 100% completeness for date of birth, sex, and triple CFTR modulator prescription date), and reliability (<0.4% implausible values; <0.002% time-related logical inconsistencies). Of 1,739 individuals in the registry, 932 had initiated both dual and triple CFTR modulator therapy, suggesting an adequate sample size for effectiveness estimation.
CONCLUSIONS: These findings suggest it is potentially feasible to use the NCFR to estimate the relative effectiveness of triple versus dual CFTR modulators in clinical practice, supported by strong data quality metrics and an adequate sample size. System reliability could be improved by enhancing data collection and governance process descriptions, for example, through standardised reporting tools such as REQueST.
METHODS: We evaluated the NCFR using the EMA data quality framework across three domains. First, we assessed system reliability by rating the maturity of registry elements related to data collection and governance on a three-level scale. Second, we evaluated data quality using metrics of timeliness, extensiveness, and reliability. Third, as one key parameter of the registry’s data fit-for-purposeness, we assessed the precision of a relative effectiveness estimation by estimating the number of patients transitioning from dual to triple Cystic Fibrosis Transmembrane Regulator (CFTR) modulator therapy.
RESULTS: On system reliability, nine out of eleven are relevant for the NCFR, five of these reached the lowest maturity level (level 1) and four reached level 2; none achieved level 3. Despite this, the NCFR performed well across all data quality metrics: timeliness (mean 15-year follow-up, annual updates), extensiveness (>95% population coverage; 100% completeness for date of birth, sex, and triple CFTR modulator prescription date), and reliability (<0.4% implausible values; <0.002% time-related logical inconsistencies). Of 1,739 individuals in the registry, 932 had initiated both dual and triple CFTR modulator therapy, suggesting an adequate sample size for effectiveness estimation.
CONCLUSIONS: These findings suggest it is potentially feasible to use the NCFR to estimate the relative effectiveness of triple versus dual CFTR modulators in clinical practice, supported by strong data quality metrics and an adequate sample size. System reliability could be improved by enhancing data collection and governance process descriptions, for example, through standardised reporting tools such as REQueST.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
RWD64
Topic
Clinical Outcomes, Methodological & Statistical Research, Real World Data & Information Systems
Topic Subcategory
Data Protection, Integrity, & Quality Assurance, Reproducibility & Replicability
Disease
Rare & Orphan Diseases, Respiratory-Related Disorders (Allergy, Asthma, Smoking, Other Respiratory), Systemic Disorders/Conditions (Anesthesia, Auto-Immune Disorders (n.e.c.), Hematological Disorders (non-oncologic), Pain)