Leveraging Real World Radiation Medicine Health Data to Drive Evidence-Based Cancer Care Policies: An Insights From the IAEA SUNRISE Project
Author(s)
Daniel Berger, Sr., PhD.
Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna, Austria.
Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna, Austria.
OBJECTIVES: The aim of this The SUNRISE (Sustainable Unified Network for Radiation Medicine Innovation and Scientific Excellence) study was to assess the feasibility and importance of radiation medicine data collection across diverse cancer care institutions through a global survey, with the goal of informing cancer care policies and guiding equitable resource allocation
METHODS: The global survey combined 5-point Likert-scale and open-ended questions on patient care, treatment, outcomes, infrastructure, and workforce. Countries were classified using the World Bank’s 2025 income groups (LIC, LMIC, UMIC, HIC). The mean of the Likert scores were calculated. Descriptive statistics summarized respondents’ ratings of each data domain, while thematic analysis of open responses identified key barriers — such as infrastructure gaps, manual workflows, and limited interoperability — and highlighted priorities like improved workflow integration and investment in digital capabilities, personnel, platforms, and data systems.
RESULTS: Responses came from 82 professionals (32% medical physicists, 28% radiation oncologists) across 75 institutes in 49 countries: 43% LMICs, 24% UMICs, 20% HICs, and 12% LICs. Mean rating scores revealed gaps between perceived importance and feasibility across data. Survival outcomes (4.2 ± 0.09 vs. 3.3 ± 0.20), nutrition (3.8 ± 0.15 vs. 3.3 ± 0.20), and economic data (3.7 ± 0.11 vs. 3.1 ± 0.21) were most affected. While 90% of institutions collect basic data, only 60% record staging and comorbidities. Equipment uptime is tracked in 40% of centres, though 80% consider it essential. LICs reported the highest importance scores but lowest feasibility. Although 90% value data sharing, only half have interoperable systems.
CONCLUSIONS: Survival outcomes and patient-reported data were highly valued but difficult to collect, with socioeconomic and nutritional metrics underused. SUNRISE addresses these gaps through a scalable data framework that strengthens infrastructure, workforce, and systems to support equitable, evidence-based cancer care. Future phases will integrate patient input to align data with lived experiences.
METHODS: The global survey combined 5-point Likert-scale and open-ended questions on patient care, treatment, outcomes, infrastructure, and workforce. Countries were classified using the World Bank’s 2025 income groups (LIC, LMIC, UMIC, HIC). The mean of the Likert scores were calculated. Descriptive statistics summarized respondents’ ratings of each data domain, while thematic analysis of open responses identified key barriers — such as infrastructure gaps, manual workflows, and limited interoperability — and highlighted priorities like improved workflow integration and investment in digital capabilities, personnel, platforms, and data systems.
RESULTS: Responses came from 82 professionals (32% medical physicists, 28% radiation oncologists) across 75 institutes in 49 countries: 43% LMICs, 24% UMICs, 20% HICs, and 12% LICs. Mean rating scores revealed gaps between perceived importance and feasibility across data. Survival outcomes (4.2 ± 0.09 vs. 3.3 ± 0.20), nutrition (3.8 ± 0.15 vs. 3.3 ± 0.20), and economic data (3.7 ± 0.11 vs. 3.1 ± 0.21) were most affected. While 90% of institutions collect basic data, only 60% record staging and comorbidities. Equipment uptime is tracked in 40% of centres, though 80% consider it essential. LICs reported the highest importance scores but lowest feasibility. Although 90% value data sharing, only half have interoperable systems.
CONCLUSIONS: Survival outcomes and patient-reported data were highly valued but difficult to collect, with socioeconomic and nutritional metrics underused. SUNRISE addresses these gaps through a scalable data framework that strengthens infrastructure, workforce, and systems to support equitable, evidence-based cancer care. Future phases will integrate patient input to align data with lived experiences.
Conference/Value in Health Info
2025-09, ISPOR Real-World Evidence Summit 2025, Tokyo, Japan
Value in Health Regional, Volume 49S (September 2025)
Code
RWD32
Topic Subcategory
Distributed Data & Research Networks
Disease
SDC: Oncology