Business School, Sichuan University, Chengdu 610064, China.
School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Int J Environ Res Public Health. 2018 Aug 21;15(9):1799. doi: 10.3390/ijerph15091799.
With the rapid development of modern medicine, therapeutic schedules of brain-metastasized non-small cell lung cancer (NSCLC) are expanding. To assist a patient who suffers from brain-metastasized NSCLC to select the most suitable therapeutic schedule, firstly, we establish an indicator system for evaluating the therapeutic schedules; then, we propose a probabilistic linguistic ELECTRE II method to handle the corresponding evaluation problem for the following reasons: (1) probabilistic linguistic information is effective to depict the uncertainty of the therapeutic process and the fuzziness of an expert's cognition; (2) the ELECTRE II method can deal with evaluation indicators that do not meet a fully compensatory relationship. Simulation tests on the parameters in the proposed method are provided to discuss their impacts on the final rankings. Furthermore, we apply the proposed method to help a patient with brain-metastasized NSCLC at the Sichuan Cancer Hospital and Institute to choose the optimal therapeutic schedule, and we present some sensitive analyses and comparative analyses to demonstrate the stability and applicability of the proposed method.
随着现代医学的快速发展，脑转移非小细胞肺癌（NSCLC）的治疗方案正在不断扩展。为了帮助患有脑转移 NSCLC 的患者选择最合适的治疗方案，我们首先建立了一个评估治疗方案的指标体系；然后，我们提出了一种概率语言 ELECTRE II 方法来处理相应的评估问题，原因如下：（1）概率语言信息有效地描述了治疗过程的不确定性和专家认知的模糊性；（2）ELECTRE II 方法可以处理不符合完全补偿关系的评价指标。我们提供了对所提出方法中的参数的仿真测试，以讨论它们对最终排名的影响。此外，我们将所提出的方法应用于帮助四川肿瘤医院和研究所的一位脑转移 NSCLC 患者选择最佳的治疗方案，并进行了一些敏感性分析和对比分析，以证明所提出方法的稳定性和适用性。
