Abstract
Gastric cancer results in malignant tumors with high morbidity and mortality, and seriously affects the health and life quality of patients. Early detection and appropriate treatment for early-stage gastric cancer patients are very helpful to reducing the recurrence rate and improving survival rates. Hence, the selection of a suitable surgical treatment is an important part. At present, surgical treatment selection has been researched in numerous studies, but there is no study integrating fuzzy decision-making theory with quantitative analysis, considering the patient’s conditions with other relative conditions, and which can handle multisource heterogeneous information at the same time. Hence, this paper proposes a novel selection model of surgical treatments for early gastric cancer based on heterogeneous multiple-criteria group decision-making (MCGDM), which is helpful to selecting the most appropriate surgery in the case of asymmetric information between doctors and patients. Subjective and objective criteria are comprehensively taken into account in the index system of the selection model for early gastric cancer, which combines fuzzy theory with quantitative data analysis. Moreover, the evaluation information obtained from the patient’s conditions, the surgery, and the hospital’s medical status, etc., including crisp numbers, interval numbers, neutrosophic numbers, and probabilistic linguistic labels, is more complete and real, so the surgical treatment selection is accurate and reliable. Furthermore, the technique for order of preference by similarity to ideal solution (TOPSIS) method is employed to solve the prioritization of early gastric cancer surgical treatments. Finally, an empirical study of surgical treatment selection for early gastric cancer surgery is conducted, and the results of sensitivity analysis and comparative analysis suggest that the proposed selection model of surgical treatments for early gastric cancer patients is reliable and effective.
Highlights
Gastric cancer is a very common disease in the world with high morbidity and the second most frequent cause of cancer death, affecting about one million people per year [1]
The TOPSIS method was proposed by Hwang and Yoon [49] to deal with multicriteria decision-making problems
A selection model of surgical treatments for early gastric cancer patients has been developed in this paper, which is helpful to solving the problem of surgical treatment selection in the case of asymmetric information between doctors and patients
Summary
Gastric cancer is a very common disease in the world with high morbidity and the second most frequent cause of cancer death, affecting about one million people per year [1]. The contributions of this paper are summarized as follows: (1) An index system of early gastric cancer surgery comprehensively considering subjective criteria and objective criteria is established It combines fuzzy theory with quantitative data analysis; (2) Heterogeneous information including crisp numbers, interval numbers, neutrosophic numbers, and probabilistic linguistic labels is considered to evaluate surgical treatments. It makes evaluation results more complete and reliable; (3) The TOPSIS method for heterogeneous multicriteria group decision-making is employed to solve the priorities of surgical treatments, which can help experts and the patient to select the most appropriate surgical treatment.
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