(308) Prevalence, Comorbidities, and Healthcare Costs of Rare Genetic Diseases in Germany: A Claims Database Study

Background: Research on rare genetic diseases is challenging due to their low prevalence and complex clinical manifestations. Despite their individual rarity, the cumulative burden of these diseases is substantial, warranting a closer examination of their distribution and associated economic impact. Larger claims databases could enable a quantification and characterization of patients with rare diseases and contribute to determining their specific healthcare needs.

Objectives: This study examines the prevalence, comorbidities, and annual direct costs of cystic fibrosis (CF), Huntington's disease (HD), hereditary retinal dystrophy (HRD), beta-thalassemia (BT), and spinal muscular atrophy type I (SMA) in Germany.

Methods: Utilizing anonymized claims data from the InGef research database, we conducted a cross-sectional analysis for each disease from 2017 to 2022. Patients and comorbidities were identified based on ICD-10-GM-codes. Prevalence was extrapolated to the German population. Costs were analyzed as average direct costs per patient.

Results: Prevalences for the selected diseases were 14.94 (CF), 7.14 (HD), 43.38 (HRD), 13.66 (BT), and 1.53 (SMA) patients per 100,000 persons in 2022. Those underlying case numbers allow a reliable estimate of prevalence in terms of gender and different age groups. The most frequent comorbidities identified are strongly related to the specific disease. For instance, in 2022, among the most common diagnoses were acute upper respiratory infections in CF patients (52.62%); depression in HD patients (40.53%); disorders of refraction and accommodation in HRD patients (71.26%); dorsalgia in BT patients (38.93%); and acute upper respiratory infections in SMA patients (38.36%). Average total direct costs in 2022 were 75,917€ (CF), 10,370€ (HD), 6,331€ (HRD), 6,633€ (BT), and 218,706€ (SMA).

Conclusions: Comprehensive identification and characterization of cases is crucial to define treatment standards or to conduct post-approval studies. The prevalences and frequent comorbidities for the selected rare diseases found in claims data correspond to those reported in existing literature. Therefore, using the full potential of claims data analyses can provide reliable insights into rare disease prevalence, patient characteristics, and healthcare utilization.