Introduction
We ran a complex Comparative Effectiveness project as part of the value demonstration of an immunotherapy medicine in advanced endometrial cancer. The project employed the Match-Adjusted Indirect Comparison (MAIC) methodology, guided by NICE DSU TSD 18 to ensure adherence to guidelines. This approach bridges evidence gaps where head-to-head trials are absent, supports HTA submissions and reimbursement decisions, and delivers tailored solutions backed by scientific rigor and transparency.
Objective
Comparative effectiveness and value assessment of immunotherapy for advanced endometrial cancer.
Method
Match-Adjusted Indirect Comparison (MAIC).
Purpose
Inform reimbursement discussions and health technology assessments (HTA).
Key Insights
Relative progression-free survival (PFS) benefits were estimated between two active treatments using a common comparator arm.
Guided by NICE DSU TSD 18 to ensure methodological rigour and transparency of approach.
Our Approach
- Aligned inclusion/exclusion criteria and identified relevant effect modifiers.
- Applied propensity score-based reweighting to adjust for population-level differences.
- Used individual patient data to mirror baseline characteristics from comparator trial aggregate data.
- Implemented a weighted Cox proportional hazards model for treatment effect estimation.
- Digitized Kaplan-Meier curves validated population adjustments visually.
Why This Matters
- Bridges evidence gaps where head-to-head trials are absent.
- Supports HTA submissions and reimbursement decisions with robust methodologies.
- Delivers tailored solutions backed by scientific rigor and transparency.
Capabilities Highlighted
- Expertise in advanced evidence synthesis.
- Survival modelling proficiency.
- Utility of pseudo-IPD generation for visual analytics.
Outcome
- Confident interpretation of comparative effectiveness.
- High-quality indirect treatment comparisons (ITCs) tailored for strategic market access.
Services Provided
- Evidence and Value Generation
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