Cost-Effectiveness of Surveillance Scanning Strategies after Curative Treatment of Non-Small-Cell Lung Cancer.

Medical decision making : an international journal of the Society for Medical Decision Making(2020)

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摘要
BACKGROUND:After curative treatment of primary non-small-cell lung cancer (NSCLC), patients undergo intensive surveillance with the aim to detect recurrences from the primary tumor or metachronous second primary lung cancer as early as possible and improve overall survival. However, the benefit of surveillance is debated. Available evidence is of low quality and conflicting. Microsimulation modeling facilitates the exploration of the impact of different surveillance strategies and provides insight into the cost-effectiveness of surveillance. METHODS:A microsimulation model was used to simulate a range of computed tomography (CT)-based surveillance schedules, differing in the frequency and duration of CT surveillance. The impact on survival, quality-adjusted life-years, costs, and cost-effectiveness of each schedule was assessed. RESULTS:Ten of 108 strategies formed the cost-effectiveness frontier; that is, these were the strategies with the optimal cost-health benefit balance. Per person, the discounted QALYs of these strategies varied between 5.72 and 5.81 y, and discounted costs varied between €9892 and €19,259. Below a willingness-to-pay threshold of €50,000/QALY, no scanning is the preferred option. For a willingness-to-pay threshold of €80,000/QALY, surveillance scanning every 2 y starting 1 y after curative treatment becomes the best option, with €11,860 discounted costs and 5.76 discounted QALYs per person. The European Society for Medical Oncology guideline strategy was more expensive and less effective than several other strategies. CONCLUSION:Model simulations suggest that limited CT surveillance scanning after the treatment of primary NSCLC is cost-effective, but the incremental health-benefit remains marginal. However, model simulations do suggest that the guideline strategy is not cost-effective.
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