Observation indicators and endpoints
Tumour, cancer, death, tumour
METASTASIS, TUMOUR, CANCER, TUMOUR, REGRESSION
The main observation indices of this study included the demographics of the patients (sex, age, race, marital status at diagnosis), the clinicopathological features of the cancer (tumour location, size, tumour differentiation, histology, gastrectomy type, depth of invasion, lymph node metastasis, distant metastasis, tumour stage, chemotherapy record) and survival data (survival time and death reason). According to the specific circumstances and goals of the study, as well as the nature of the data and the relationship between the variables, this study converted the continuous variables into categorical variables in the regression analysis. It should be noted that categorizing continuous variables can be helpful in cases where there is a nonlinear relationship between the predictor and outcome variables, and it may be difficult to find a suitable model to fit. While splines can be used as an alternative, they can be computationally intensive. X-tile is a bioinformatics tool for risk factor assessment assessment and outcome-based cut-point optimization. As an alternative, the optimal cut-off values of age, tumour size and lymph node ratio (LNR) were determined using the X-tile program (X-tile software version 3.6.1, Yale University) [Age was categorized into three groups: 65 ~ 70 years old, 71 ~ 80 years old, and ≥ 81 years old. Race was divided into four groups: white, black, Asian or Pacific Islander and Indian or unknown. The two marriage categories were married and unmarried (including single, widowed, divorced and informal union). Tumour size was divided into three groups (< 3.5, 3.5 ≤ tumour size < 9.5, and ≥ 9.5). The location of the tumour was divided into the cardia/fundus, body and antrum/pylorus. Tumour differentiation was defined according to the cellular differentiation degree, which may be classified as I-II and III-IV [