Challenges in Defining Target Populations: An Analysis of Orphan Drug Health Technology Assessments in Germany 2024
Author(s)
Matthias Roll, M.Sc., Bernhardt Guentert, Prof. Dr.oec.
Private University in the Principality of Liechtenstein (UFL), Triesen, Liechtenstein.
Private University in the Principality of Liechtenstein (UFL), Triesen, Liechtenstein.
OBJECTIVES: This study aims to identify patterns and differences in the use of epidemiological data sources for defining target populations as presented in dossiers submitted by pharmaceutical manufacturers for health technology assessments (HTAs) of orphan drugs in Germany. It compares source selection between oncological and non-oncological indications and examines methodological comments issued by the HTA body IQWiG.
METHODS: All 31 orphan drug assessments initiated in 2024 were included. Epidemiological data sources were categorised as claims data, registry data, literature, or other. Indications were classified as oncological or non-oncological. Descriptive statistics were used to summarise the distribution of data sources. A chi-squared test was conducted to identify differences between indication types. IQWiG’s comments were extracted and thematically coded using a structured keyword framework.
RESULTS: Claims data (e.g. from GKV or InGef) were used in 22.6 % of dossiers, registry data in 25.8 %, and literature in 35.5 %. A significant difference was observed in the choice of data sources between oncological and non-oncological assessments (p = 0.026). Oncological dossiers relied more often on registries and literature, whereas non-oncological cases used a broader mix, including more frequent use of claims data. All dossiers received methodological criticism by IQWiG; most commonly on population size (77 %), transparency (74 %), and methodological quality (45 %). These concerns were raised regardless of the data source used. The focus of criticism focused more on data handling than on source type.
CONCLUSIONS: Defining the size of the target population remains a challenge in orphan drug HTAs. To improve the quality and acceptance of epidemiological estimates, both data availability and methodological standards must be strengthened. This includes up-to-date and well-structured registries, accurate coding in claims data, and clear guidance on data source selection, calculation methods, and the handling of uncertainty—particularly for rare diseases. Further analysis of previous assessments may help identify persistent methodological gaps.
METHODS: All 31 orphan drug assessments initiated in 2024 were included. Epidemiological data sources were categorised as claims data, registry data, literature, or other. Indications were classified as oncological or non-oncological. Descriptive statistics were used to summarise the distribution of data sources. A chi-squared test was conducted to identify differences between indication types. IQWiG’s comments were extracted and thematically coded using a structured keyword framework.
RESULTS: Claims data (e.g. from GKV or InGef) were used in 22.6 % of dossiers, registry data in 25.8 %, and literature in 35.5 %. A significant difference was observed in the choice of data sources between oncological and non-oncological assessments (p = 0.026). Oncological dossiers relied more often on registries and literature, whereas non-oncological cases used a broader mix, including more frequent use of claims data. All dossiers received methodological criticism by IQWiG; most commonly on population size (77 %), transparency (74 %), and methodological quality (45 %). These concerns were raised regardless of the data source used. The focus of criticism focused more on data handling than on source type.
CONCLUSIONS: Defining the size of the target population remains a challenge in orphan drug HTAs. To improve the quality and acceptance of epidemiological estimates, both data availability and methodological standards must be strengthened. This includes up-to-date and well-structured registries, accurate coding in claims data, and clear guidance on data source selection, calculation methods, and the handling of uncertainty—particularly for rare diseases. Further analysis of previous assessments may help identify persistent methodological gaps.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
HTA70
Topic
Epidemiology & Public Health, Health Policy & Regulatory, Health Technology Assessment
Topic Subcategory
Decision & Deliberative Processes
Disease
Rare & Orphan Diseases