Determinants of Added Benefit Ratings in Germany: An Econometric Analysis of Assessments From the Federal Joint Committee Between 2012 and 2024

OBJECTIVES: This study investigates the determinants of added benefit ratings by the Federal Joint Committee (Gemeinsamer Bundesausschuss, GBA).

METHODS: Data on drug name, indication, population, added benefit rating, orphan status, therapeutic area, mortality, morbidity, safety and quality of life were extracted from the G-BA Machine Readable (XML) version of resolutions “G-BA_Beschluss_Info” for all resolutions between 01.01.2012 and 01.06.2024. An ordinal logistic regression was conducted to assess the influence of drug and disease characteristics on added benefit ratings. The model was fitted using the Broyden–Fletcher–Goldfarb–Shanno (BFGS) optimization algorithm. Odds ratios were computed from the model coefficients for interpretation. To evaluate model fit, McFadden R-squared was calculated by comparing the log-likelihoods of the full model and a null model without predictors, resulting in a value indicative of a well-fitting model.

RESULTS: A total of 1,353 outcomes were identified. Orphan designation emerged as the strongest predictor, significantly increasing the likelihood of a higher added benefit (OR: 7.77, p<0.001). Mortality effect (OR: 1.87, p<0.001), morbidity effect (OR: 1.94, p<0.001), and adverse events effect (OR: 1.43, p<0.001) also showed significant positive associations with the extent of added benefit. Oncology treatments (relative to non-oncology) were significant but less robust predictors (OR: 1.54, p=0.009). The model's McFadden R-squared value of 0.416 indicates a strong fit, explaining approximately 41.6% of the variability in the extent of added benefit, demonstrating the model's efficacy in capturing the impact of these predictors.

CONCLUSIONS: G-BA added benefit ratings are most commonly associated with recognised improvements in morbidity and mortality endpoints, while improvements in safety and quality of life feature less prominently as predictors. Orphan products have a strong correlation with higher added benefit ratings, likely a reflection of the orphan drug benefit assessment pathway within the G-BA.