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

Abstract

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 years, 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.

Methods for Communicating the Impact of Parameter Uncertainty in a Multiple-Strategies Cost-Effectiveness Comparison

“…In this case, the probability for any single strategy to outperform all other comparator strategies may be low, leading to overlapping CEACs with a very low probability of any strategy being cost-effective. An example of this problem is visible in the study by Wolff et al, 8 which compared 108 surveillance strategies of lung cancer, resulting in interpretation problems for decision makers. 9 In these types of surveillance and screening studies that compare many strategies with very similar outcomes, other factors may become important in the choice for the ''best'' strategy, such as the difficulty in implementing a strategy.…”