Improving the Face Validity and Clinical Relevance of a Cancer Epidemiology Microsimulation Model Using a Novel Advisory Group Approach
Author(s)
Oguzhan Alagoz, PhD1, Sara Fernandes-Taylor, PhD2, Natalia Arroyo, MPH2, Yichi Zhang, MS2, David O. Francis, MD, MS2, Louise Davies, MD, MS3;
1University of Wisconsin-Madison, Professor, Middleton, WI, USA, 2University of Wisconsin-Madison, Madison, WI, USA, 3Dartmouth University, Hanover, NH, USA
1University of Wisconsin-Madison, Professor, Middleton, WI, USA, 2University of Wisconsin-Madison, Madison, WI, USA, 3Dartmouth University, Hanover, NH, USA
OBJECTIVES: Cancer simulation models are valuable for addressing research and policy questions when prospective evidence is unavailable or impractical. However, the utility of these models can be constrained by unmeasurable inputs and assumptions lacking face validity or clinical relevance. To address these limitations, we systematically integrated formal advisory input during the development of a microsimulation model for papillary thyroid cancer (PATCAM).
METHODS: We employed a participatory action research approach, utilizing focus group techniques and principles of bidirectional learning.
RESULTS: A formal advisory group was established, representing diverse perspectives (medical, patient, and payor), geographic regions, and local clinical practices. This group provided essential insights into historical and current clinical beliefs and practices regarding thyroid cancer diagnosis and treatment. Their input informed critical modeling assumptions and decisions, including
• The role of nodule size in biopsy decisions,
• Trends in provider biopsy behavior,
• Specialty-specific biopsy propensities,
• Population prevalence trends for thyroid cancer,
• The proportion of malignant tumors exhibiting regression, and
• Variations in cancer epidemiology and diagnostic practices by sex and age.
Additionally, the advisory group raised key questions and concerns that will shape future research directions and strategies for effectively communicating and disseminating model results.
CONCLUSIONS: The advisory group contributed significantly to the development of PATCAM by addressing directly unobservable assumptions and enhancing the model’s face validity and transparency. Their feedback also informed plans for future research and dissemination, ensuring the model’s maximum impact in guiding clinical decisions and policymaking. This approach underscores the value of integrating diverse stakeholder input in simulation modeling to improve relevance and utility.
METHODS: We employed a participatory action research approach, utilizing focus group techniques and principles of bidirectional learning.
RESULTS: A formal advisory group was established, representing diverse perspectives (medical, patient, and payor), geographic regions, and local clinical practices. This group provided essential insights into historical and current clinical beliefs and practices regarding thyroid cancer diagnosis and treatment. Their input informed critical modeling assumptions and decisions, including
• The role of nodule size in biopsy decisions,
• Trends in provider biopsy behavior,
• Specialty-specific biopsy propensities,
• Population prevalence trends for thyroid cancer,
• The proportion of malignant tumors exhibiting regression, and
• Variations in cancer epidemiology and diagnostic practices by sex and age.
Additionally, the advisory group raised key questions and concerns that will shape future research directions and strategies for effectively communicating and disseminating model results.
CONCLUSIONS: The advisory group contributed significantly to the development of PATCAM by addressing directly unobservable assumptions and enhancing the model’s face validity and transparency. Their feedback also informed plans for future research and dissemination, ensuring the model’s maximum impact in guiding clinical decisions and policymaking. This approach underscores the value of integrating diverse stakeholder input in simulation modeling to improve relevance and utility.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
SA10
Topic
Study Approaches
Topic Subcategory
Decision Modeling & Simulation, Surveys & Expert Panels
Disease
SDC: Oncology