SEEING THE FULL PICTURE: STRUCTURED MODEL CONCEPTUALISATION TO INCORPORATE THE DUAL BURDEN OF TUMOUR PROGRESSION AND VISUAL MORBIDITY IN CHOROIDAL MELANOMA
Author(s)
Alisha Angdembe, MPH1, Noemi Muszbek, MSc2, Ross Goldstein, MD, MBA3, Joseph Birkett, PhD3.
1Senior Health Economist, Visible Analytics Ltd, Oxford, United Kingdom, 2Visible Analytics Ltd, Reading, United Kingdom, 3Aura Biosciences, Boston, MA, USA.
1Senior Health Economist, Visible Analytics Ltd, Oxford, United Kingdom, 2Visible Analytics Ltd, Reading, United Kingdom, 3Aura Biosciences, Boston, MA, USA.
OBJECTIVES: Choroidal melanoma (CM) is a rare malignant tumour, with treatments evolving from primary enucleation toward eye-preserving approaches. Current cost-effectiveness models (CEMs) tend to focus on oncological aspects overlooking visual morbidity. The aim was to develop a CEM structure, that incorporates both aspects of the disease through structured model conceptualisation.
METHODS: The structured model conceptualisation process undertaken included: 1) review of clinical guidelines, previous health technology assessments, and published economic models evaluating whether existing approaches adequately reflect the dual burden of disease, 2) development of influence diagram, 3) model conceptualisation, 4) elicitation of clinical/patient experience and validation of model assumptions and 5) model finalisation.
RESULTS: Review of prior HTA submissions and published economic models confirmed that no existing model has structurally incorporated both visual morbidity and oncological outcomes. A novel cohort state-transition model was developed tracking and linking cancer and visual acuity outcomes over time. Clinical/patient experience highlighted the importance of treatment related complication and the effect of visual impairment besides visual acuity, and the model concept was revised.
The final model’s oncological dimension tracks patients from primary tumour control through to progression and death, with impacts of adverse events and metastasis captured within this structure. The visual dimension tracks patients across visual impairment (VI) categories (including visual acuity and other complications) , with time-dependent transition probabilities reflecting the natural trajectory of vision loss following treatment. Whilst modelled independently, the two dimensions interact: progression triggers subsequent treatment, shaping the VI trajectory. Enucleation is captured separately, reflecting quality of life impacts beyond VI category alone.
CONCLUSIONS: Structured model conceptualisation with early clinical and patient expert involvement is essential to capture all dimensions of complex diseases. In CM, this resulted in a novel model structure incorporating both tumour progression and visual morbidity, allowing the evaluation of the full impact of treatments.
METHODS: The structured model conceptualisation process undertaken included: 1) review of clinical guidelines, previous health technology assessments, and published economic models evaluating whether existing approaches adequately reflect the dual burden of disease, 2) development of influence diagram, 3) model conceptualisation, 4) elicitation of clinical/patient experience and validation of model assumptions and 5) model finalisation.
RESULTS: Review of prior HTA submissions and published economic models confirmed that no existing model has structurally incorporated both visual morbidity and oncological outcomes. A novel cohort state-transition model was developed tracking and linking cancer and visual acuity outcomes over time. Clinical/patient experience highlighted the importance of treatment related complication and the effect of visual impairment besides visual acuity, and the model concept was revised.
The final model’s oncological dimension tracks patients from primary tumour control through to progression and death, with impacts of adverse events and metastasis captured within this structure. The visual dimension tracks patients across visual impairment (VI) categories (including visual acuity and other complications) , with time-dependent transition probabilities reflecting the natural trajectory of vision loss following treatment. Whilst modelled independently, the two dimensions interact: progression triggers subsequent treatment, shaping the VI trajectory. Enucleation is captured separately, reflecting quality of life impacts beyond VI category alone.
CONCLUSIONS: Structured model conceptualisation with early clinical and patient expert involvement is essential to capture all dimensions of complex diseases. In CM, this resulted in a novel model structure incorporating both tumour progression and visual morbidity, allowing the evaluation of the full impact of treatments.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EE714
Topic
Economic Evaluation, Patient-Centered Research
Disease
Oncology, Rare & Orphan Diseases, Sensory System Disorders (Ear, Eye, Dental, Skin)