AUTHOR=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 ,  the RARECAREnet working group 

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

JOURNAL=Frontiers in Oncology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1219111

DOI=10.3389/fonc.2023.1219111

ISSN=2234-943X

ABSTRACT=Background: The head and neck cancers (HNC) incidence differs between Europe and East Asia. Our objective was to determine whether also survival of HNC differ between Europe 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 modelled RS with a generalised 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 lower RS than both Japan and Taiwan. HNC subsites and histologies distribution and survival differed between the 3 areas. Differences between Europe and both Asian countries persisted even after adjustments tors 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.
Funding:
Italian Ministry of Health, Ministry of Health and Welfare of Taiwan, Health and Labor Sciences Research Grant, Netherlands Comprehensive Cancer Organisation.