DOES PRIMARY ENDPOINT TYPE INFLUENCE REGULATORY AND HTA OUTCOMES FOR EMA APPROVED ONCOLOGY MEDICINES IN ITALY?
Author(s)
Francesca De Santis, PharmD1, Alessandro d'Audino, PharmD2, Federico Tartarelli, MSc3, Olivia Ramdin, MSc4, Elena Chaiter, MSc5, Valeria Viola, MSc6, Beatrice Sacchi, PharmD7.
1Università del Piemonte Orientale, Novara, Italy, 2Pharma Value s.r.l., Roma, Italy, 3Pharma Value s.r.l., ROMA, Italy, 4Pharma Value, Rome, Italy, 5Pharma Value srl, Roma, Italy, 6Pharma Value srl, Rome, Italy, 7University of Turin: Turin, Piemonte, IT, Torino, Italy.
1Università del Piemonte Orientale, Novara, Italy, 2Pharma Value s.r.l., Roma, Italy, 3Pharma Value s.r.l., ROMA, Italy, 4Pharma Value, Rome, Italy, 5Pharma Value srl, Roma, Italy, 6Pharma Value srl, Rome, Italy, 7University of Turin: Turin, Piemonte, IT, Torino, Italy.
OBJECTIVES: Oncology medicines increasingly reach the market on surrogate endpoints rather than overall survival (OS). Whether endpoint type influences national HTA decisions remains unclear. Under the EU Joint Clinical Assessment (JCA), OS is the final patient-centered outcome in oncology, while Time-to-Event and Response-Rate endpoints are surrogates. This study aimed to describe the primary endpoint supporting European Medicines Agency (EMA) authorization for oncological and onco-hematological indications and to explore endpoint distribution among indications assessed for innovativeness in Italy by the Italian Medicines Agency (AIFA).
METHODS: A database was created including new authorizations and extensions of indication of oncology medicines issued by EMA from 2016 to 2024. Publicly available data were extracted from European Public Assessment Reports, AIFA innovativeness reports and the Italian Official Journal. We collected trial-level data. Primary endpoints were classified according to the JCA approach, distinguishing between OS-endpoints and non-OS-endpoints. Statistical analysis was performed using the R software; categorical associations were assessed with chi-square test.
RESULTS: The study dataset included 403 indications. Non-OS-based endpoints predominated and obtained conditional approval far more often than OS-based endpoints: 51/52 (98.1%; p<0.001). As expected, OS-based endpoints were more frequently adopted in solid than in hematological malignancies (p=0.002). In Italy, 373/403 (92.6%) indications requested reimbursement, of which 169 submitted for innovative status. Reimbursement was granted to 319/373 (85.5%); similar rates were established for non-OS-based (237/274, 86.5%) and OS-based (82/99, 82.8%) indications (p=0.47). Among the 169 indications submitted for innovativeness, OS-based endpoints were more common among innovative than non-innovative indications (34.4% vs 20.2%; p=0.0598).
CONCLUSIONS: Surrogate-based evidence underpins conditional EMA marketing authorization, reflecting residual uncertainty, yet does not penalize Italian reimbursement. In innovativeness-status assessment, OS-based endpoints trended toward more frequent recognition, warranting further analysis. Ongoing analyses will further explore endpoint selection according to disease-setting (early vs advanced), tumor-type and extend the dataset with second cutoff overall-survival data.
METHODS: A database was created including new authorizations and extensions of indication of oncology medicines issued by EMA from 2016 to 2024. Publicly available data were extracted from European Public Assessment Reports, AIFA innovativeness reports and the Italian Official Journal. We collected trial-level data. Primary endpoints were classified according to the JCA approach, distinguishing between OS-endpoints and non-OS-endpoints. Statistical analysis was performed using the R software; categorical associations were assessed with chi-square test.
RESULTS: The study dataset included 403 indications. Non-OS-based endpoints predominated and obtained conditional approval far more often than OS-based endpoints: 51/52 (98.1%; p<0.001). As expected, OS-based endpoints were more frequently adopted in solid than in hematological malignancies (p=0.002). In Italy, 373/403 (92.6%) indications requested reimbursement, of which 169 submitted for innovative status. Reimbursement was granted to 319/373 (85.5%); similar rates were established for non-OS-based (237/274, 86.5%) and OS-based (82/99, 82.8%) indications (p=0.47). Among the 169 indications submitted for innovativeness, OS-based endpoints were more common among innovative than non-innovative indications (34.4% vs 20.2%; p=0.0598).
CONCLUSIONS: Surrogate-based evidence underpins conditional EMA marketing authorization, reflecting residual uncertainty, yet does not penalize Italian reimbursement. In innovativeness-status assessment, OS-based endpoints trended toward more frequent recognition, warranting further analysis. Ongoing analyses will further explore endpoint selection according to disease-setting (early vs advanced), tumor-type and extend the dataset with second cutoff overall-survival data.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
HTA173
Topic
Clinical Outcomes, Health Policy & Regulatory, Health Technology Assessment
Topic Subcategory
Decision & Deliberative Processes
Disease
Oncology, Rare & Orphan Diseases