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- W2765267002 abstract "To assess long-term survival outcomes predicted by a discrete event simulation model (DES) for nivolumab in renal cell carcinoma (RCC) and to compare the results with a more traditional partitioned survival model (PSM) approach. Two model structures were developed in Microsoft Excel and populated using data from an analysis of 24-month patient-level data from the CheckMate 025 trial. Both models comprised three key health states: progression-free (PF), progressed disease, and death. The DES models patients individually, and their journey through time is characterized as a series of events. Patient history and patient heterogeneity are incorporated by deriving a set of predictive equations to estimate the time to an event (progression, death) based on patient characteristics at baseline and progression. The PSM uses a cohort-based approach to estimate state occupancy based on an ‘area under the curve’ approach using overall survival (OS) and PF survival curves derived from the overall trial population in CheckMate 025. Using Akaike information criterion (AIC) to select curves best fitting the observed trial data, over a 25-year time horizon and using a 3.5% discount rate, the DES estimated 2.82 quality-adjusted life years (QALYs) and 3.64 Life Years (LYs) per person compared to 2.57 QALYs and 3.30 LYs from the PSM. The difference in survival between these models was driven by post-progression survival time (2.83 vs 2.34 LYs, respectively). Both model structures provided a good fit to the trial data, but differences were seen in predictions of long-term outcomes. The PLS model predicted longer post-progression survival, which is consistent with longer term trials in RCC, suggesting that a PLS model may present a more appropriate approach to modelling immunotherapies that, due to their unique mechanism of action, require consideration of patient characteristics and changing hazards over time." @default.
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- W2765267002 date "2017-10-01" @default.
- W2765267002 modified "2023-09-27" @default.
- W2765267002 title "Survival Outcomes Predicted By A Discrete Event Simulation Model For Renal Cell Carcinoma For Use In A Cost Effectiveness Analysis: A Comparison With A Traditional Partitioned Survival Model" @default.
- W2765267002 doi "https://doi.org/10.1016/j.jval.2017.08.2082" @default.
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