Head and neck cancers survival in Europe, Taiwan, and Japan: results from RARECAREnet Asia based on a privacy-preserving federated infrastructure

• Published in: Frontiers in oncology Vol. 13; p. 1219111
• Main Authors: Botta, Laura, Matsuda, Tomohiro, Charvat, Hadrien, Chiang, Chun-ju, Lee, Wen-Chung, van Gestel, Anna Jacoba, Martin, Frank, Geleijnse, Gijs, Cellamare, Matteo, Bonfarnuzzo, Simone, Marcos-Gragera, Rafael, Guevara, Marcela, Mousavi, Mohsen, Craig, Stephanie, Rodrigues, Jessica, Rubió-Casadevall, Jordi, Licitra, Lisa, Cavalieri, Stefano, Resteghini, Carlo, Gatta, Gemma, Trama, Annalisa
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 13.09.2023
• Subjects: federated learning approach; geographical differences; head and neck cancers; Oncology; population-based cancer registry; survival
• ISSN: 2234-943X; 2234-943X
• DOI: 10.3389/fonc.2023.1219111

Background The head and neck cancers (HNCs) incidence differs between Europe and East Asia. Our objective was to determine whether survival of HNC also differs between European and Asian countries. Methods We used population-based cancer registry data to calculate 5-year relative survival (RS) for the oral cavity, hypopharynx, larynx, nasal cavity, and major salivary gland in Europe, Taiwan, and Japan. We modeled RS with a generalized linear model adjusting for time since diagnosis, sex, age, subsite, and histological grouping. Analyses were performed using federated learning, which enables analyses without sharing sensitive data. Findings Five-year RS for HNC varied between geographical areas. For each HNC site, Europe had a lower RS than both Japan and Taiwan. HNC subsites and histologies distribution and survival differed between the three areas. Differences between Europe and both Asian countries persisted even after adjustments for all HNC sites but nasal cavity and paranasal sinuses, when comparing Europe and Taiwan. Interpretation Survival differences can be attributed to different factors including different period of diagnosis, more advanced stage at diagnosis, or different availability/access of treatment. Cancer registries did not have stage and treatment information to further explore the reasons of the observed survival differences. Our analyses have confirmed federated learning as a feasible approach for data analyses that addresses the challenges of data sharing and urge for further collaborative studies including relevant prognostic factors.