Prognostic value of a predictive model comprising preoperative inflammatory response and nutritional indexes in patients with gastric cancer.
10.3760/cma.j.cn441530-20221018-00415
- VernacularTitle:术前炎性反应和营养指标对胃癌预后的预测价值及其模型构建
- Author:
Liang Liang WU
1
;
Ming Zhi CAI
1
;
Bao Gui WANG
1
;
Jing Yu DENG
1
;
Bin KE
1
;
Ru Peng ZHANG
1
;
Han LIANG
1
;
Xiao Na WANG
1
Author Information
1. Department of Gastric Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China.
- Publication Type:Journal Article
- MeSH:
Male;
Humans;
Middle Aged;
Aged;
Female;
Prognosis;
Retrospective Studies;
Stomach Neoplasms/pathology*;
Neoplasm Staging;
Gastrectomy;
Serum Albumin
- From:
Chinese Journal of Gastrointestinal Surgery
2023;26(7):680-688
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To investigate the prognostic value of preoperative inflammatory and nutritional condition detection in the postoperative survival, and establish a prognostic model for predicting the survival of patients with gastric cancer. Methods: The clinicopathological data of 1123 patients with gastric cancer who had undergone radical gastrectomy in Tianjin Medical University Cancer Institute & Hospital from January 2005 to December 2014 were retrospectively analyzed. Patients with history of other malignancy, with history of gastrectomy, who had received preoperative treatment, who died during the initial hospital stay or first postoperative month, and missing clinical and pathological information were excluded. Cox univariate and multivariate analyses were used to identify independent clinicopathological factors associated with the survival of these gastric cancer patients. Cox univariate analysis was used to identify preoperative inflammatory and nutritional indexes related to the survival of patients with gastric cancer after radical gastrectomy. Moreover, the Cox proportional regression model for multivariate survival analysis (forward stepwise regression method based on maximum likelihood estimation) was used. The independent clinicopathological factors that affect survival were incorporated into the following three new prognostic models: (1) an inflammatory model: significant preoperative inflammatory indexes identified through clinical and univariate analysis; (2) a nutritional model: significant preoperative nutritional indexes identified through clinical and univariate analysis; and (3) combined inflammatory/nutritional model: significant preoperative inflammatory and nutritional indexes identified through clinical and univariate analysis. A model that comprised only pT and pN stages in tumor TNM staging was used as a control model. The integrated area under the receiver operating characteristic curve (iAUC) and C-index were used to evaluate the discrimination of the model. Model fitting was evaluated by Akaike information criterion analysis. Calibration curves were used to assess agreement between the predicted probabilities and actual probabilities at 3-year or 5-year overall survival (OS). Results: The study cohort comprised 1 123 patients with gastric cancer. The mean age was 58.9±11.6 years, and 783 were males. According to univariate analysis, age, surgical procedure, extent of lymph node dissection, tumor location, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, and nerve invasion were associated with 5-year OS after radical gastrectomy for gastric cancer (all P<0.050). Multivariate analysis further identified age (HR: 1.18, 95%CI: 1.03-1.36, P=0.019), maximum tumor size (HR: 1.19, 95%CI: 1.03-1.38, P=0.022), number of examined lymph nodes (HR: 0.79, 95%CI: 0.68-0.92, P=0.003), pT stage (HR: 1.40, 95%CI: 1.26-1.55, P<0.001) and pN stage (HR: 1.28, 95%CI: 1.21-1.35, P<0.001) as independent prognostic factors for OS of gastric cancer patients. Additionally, according to univariate survival analysis, the preoperative inflammatory markers of neutrophil count, percentage of neutrophils, neutrophil/lymphocyte ratio, platelet/neutrophil ratio and preoperative nutritional indicators of serum albumin and body mass index were potential prognostic factors for gastric cancer (all P<0.05). On the basis of the above results, three models for prediction of prognosis were constructed. Variables included in the three models are as follows. (1) Inflammatory model: age, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, percentage of neutrophils, and neutrophil-lymphocyte ratio; (2) nutritional model: age, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, and serum albumin; and (3) combined inflammatory/nutritional model: age, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, percentage of neutrophils, neutrophil-lymphocyte ratio, and serum albumin. We found that the predictive accuracy of the combined inflammatory/nutritional model, which incorporates both inflammatory indicators and nutrition indicators (iAUC: 0.676, 95% CI: 0.650-0.719, C-index: 0.698),was superior to that of the inflammation model (iAUC: 0.662, 95% CI: 0.673-0.706;C-index: 0.675), nutritional model (iAUC: 0.666, 95% CI: 0.642-0.698, C-index: 0.672), and TNM staging control model (iAUC: 0.676, 95% CI: 0.650-0.719, C-index: 0.658). Furthermore, the combined inflammatory/nutritional model had better fitting performance (AIC: 10 762) than the inflammatory model (AIC: 10 834), nutritional model (AIC: 10 810), and TNM staging control model (AIC: 10 974). Conclusions: Preoperative percentage of neutrophils, NLR, and BMI have predictive value for the prognosis of gastric cancer patients. The inflammatory / nutritional model can be used to predict the survival and prognosis of gastric cancer patients on an individualized basis.
