Linking Clinical Added Value to Normalized Delta QALY: Insights From Therapeutic Product Analysis

OBJECTIVES: The study aimed to assess the relationship between the Clinical Added Value (CAV) and the normalized Delta QALY (Quality-Adjusted Life Years).

METHODS: Drugs with CAV ratings I to IV without major objection or global uncertainties were included. Products with missing data for time horizon or delta QALY were excluded (129 entries, 59 drugs). Analyses were performed for oncology (91 entries), non-oncology drugs (38 entries), rare diseases (20 entries), and pediatric populations (27 entries). Statistical analysis involved descriptive statistics, and Kruskal-Wallis H-tests to determine significant differences in normalized Delta QALY across CAV. Normalized Delta QALY represents Delta QALY divided by the time horizon, providing a rate of QALY gain per year, which is useful for comparing the efficiency of different treatments over time.

RESULTS: The overall analysis revealed a statistically significant difference in normalized Delta QALY between CAV I-III and IV, with the Kruskal-Wallis H-test yielding a test statistic of 16.766 and a p-value of 0.000042. This indicates that the CAV are a meaningful discriminator of normalized QALY outcomes, reflecting their link to efficacy in the cost-effectiveness model.

• Oncology Therapeutic Areas: A significant difference in normalized Delta QALY was observed (Test Statistic: 4.345, P-Value: 0.037).
• Non-Oncology Therapeutic Areas: Significant differences in normalized Delta QALY were found (Test Statistic: 15.129, P-Value: 0.0001).
• Rare Diseases: No significant differences were observed (Test Statistic: 2.428, P-Value: 0.119), possibly due to small sample size and variability.
• Pediatric Populations: A significant difference in normalized Delta QALY was noted (Test Statistic: 9.453, P-Value: 0.002).

CONCLUSIONS: The study revealed significant variation in normalized Delta QALY across CAV I-III and IV, highlighting the link between CAV and efficacy in the cost-effectiveness model. Notable differences were observed in non-oncology areas and pediatric populations.