TOWARDS MEANINGFUL OUTCOME MEASURES FOR HEALTH ECONOMIC EVALUATIONS IN SKIN CANCER
Author(s)
Annick Meertens, MSc1, Lieven Annemans, Prof.2, Floor Verstraete, MD3, Isabelle Hoorens, Prof.4, Nick Verhaeghe, MSc, DrPH, PhD3.
1PhD student, Ghent university, Ghent, Belgium, 2Ghent University, GENT, Belgium, 3Ghent University, Ghent, Belgium, 4Ghent University Hospital, Gent, Belgium.
1PhD student, Ghent university, Ghent, Belgium, 2Ghent University, GENT, Belgium, 3Ghent University, Ghent, Belgium, 4Ghent University Hospital, Gent, Belgium.
OBJECTIVES: Healthcare systems are facing increasing resource constraints, so robust health economic evaluations (HEE) are essential to inform evidence-based decision-making, also in skin cancer care. Selecting incomplete or inappropriate outcomes in HEE may under- or overestimate benefits for patients, misrepresent trade-offs between costs and outcomes and lead to suboptimal resource allocation. This study provides an overview of outcome measures used in skin cancer HEE and proposes a decision matrix to guide meaningful outcome selection.
METHODS: Based on literature, outcome domains applied in skin cancer HEE were categorized into quality of life based outcomes and clinical outcomes (hard and intermediate endpoints). These were assessed against predefined criteria covering measurement properties (e.g. sensitivity & validity), model integration (e.g. economic translatability & compatibility), decision relevance (e.g. interpretability for health technology assessment (HTA) & patient burden) and feasibility (e.g. data availability & generalizability). A qualitative scoring approach was used to make trade-offs between outcomes explicit.
RESULTS: The decision matrix highlights that no single outcome measure performs well across all criteria. Generic quality of life outcomes facilitate comparability and interpretability for HTA but may lack sensitivity. Disease-specific outcomes better reflect patient-relevant domains but raise challenges regarding comparability. Intermediate clinical outcomes align closely with intervention mechanisms but require additional assumptions.
CONCLUSIONS: Outcome selection in skin cancer HEE should move beyond reliance on a single metric and instead align with intervention mechanisms, patient- preferences and burden and decision context. The proposed decision matrix provides a structured framework to support transparent and meaningful outcome selection.
METHODS: Based on literature, outcome domains applied in skin cancer HEE were categorized into quality of life based outcomes and clinical outcomes (hard and intermediate endpoints). These were assessed against predefined criteria covering measurement properties (e.g. sensitivity & validity), model integration (e.g. economic translatability & compatibility), decision relevance (e.g. interpretability for health technology assessment (HTA) & patient burden) and feasibility (e.g. data availability & generalizability). A qualitative scoring approach was used to make trade-offs between outcomes explicit.
RESULTS: The decision matrix highlights that no single outcome measure performs well across all criteria. Generic quality of life outcomes facilitate comparability and interpretability for HTA but may lack sensitivity. Disease-specific outcomes better reflect patient-relevant domains but raise challenges regarding comparability. Intermediate clinical outcomes align closely with intervention mechanisms but require additional assumptions.
CONCLUSIONS: Outcome selection in skin cancer HEE should move beyond reliance on a single metric and instead align with intervention mechanisms, patient- preferences and burden and decision context. The proposed decision matrix provides a structured framework to support transparent and meaningful outcome selection.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
MSR20
Topic
Economic Evaluation, Methodological & Statistical Research, Study Approaches
Disease
Oncology