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Target Trial Emulation Using Real World Data In the present study, researchers emulated a target trial assessing associations between different GLP-1RA treatment scenarios and MACE risk

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Forecasting Methods Time-series modelling S-curve and diffusion models (for emerging technologies) Driver-based forecasting (GDP, disposable income, adoption rates, regulatory changes) Price elasticity models Market maturity and lifecycle-based projections Scenario Analysis Given inherent uncertainties, three scenarios were constructed: Base-Case Scenario: Expected trajectory under current conditions Optimistic Scenario: High adoption, favourable regulation, strong economic tailwinds Conservative Scenario: Slow adoption, regulatory delays, economic constraints Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption