Published online Feb 27, 2022. doi: 10.4240/wjgs.v14.i2.143
Peer-review started: June 6, 2021
First decision: July 16, 2021
Revised: July 24, 2021
Accepted: January 6, 2022
Article in press: January 6, 2022
Published online: February 27, 2022
Processing time: 261 Days and 5.1 Hours
Patients with pathological stages T1N2-3 (pT1N2-3) and pT3N0 gastric cancer (GC) have not been routinely included in the target population for postoperative chemotherapy according to the Japanese Gastric Cancer Treatment Guideline, and their prognosis is significantly different.
To identify the high-risk patients after radical surgery by analyzing biomarkers and clinicopathological features and construct prognostic models for them.
A total of 459 patients with pT1N2-3/pT3N0 GC were retrospectively selected for the study. The Chi-square test was used to analyze the differences in the clinicopathological features between the pT1N2-3 and pT3N0 groups. The Kaplan–Meier analysis and log-rank test were used to analyze overall survival (OS). The independent risk factors for patient prognosis were analyzed by univariate and multivariate analyses based on the Cox proportional hazards regression model. The cutoff values of continuous variables were identified by receiver operating characteristic curve. The nomogram models were constructed with R studio.
There was no statistically significant difference in OS between the pT1N2-3 and pT3N0 groups (P = 0.374). Prealbumin (P = 0.040), carcino-embryonic antigen (CEA) (P = 0.021), and metastatic lymph node ratio (mLNR) (P = 0.035) were independent risk factors for prognosis in the pT1N2-3 group. Age (P = 0.039), body mass index (BMI) (P = 0.002), and gastrectomy (P < 0.001) were independent risk factors for prognosis in the pT3N0 group. The area under the curve values of the nomogram models for predicting the 5-year prognosis of the pT1N2-3 group and pT3N0 group were 0.765 and 0.699, respectively.
Nomogram model combining prealbumin, CEA, and mLNR levels can be used to predict the prognosis of pT1N2-3 GC. Nomogram model combining age, BMI, and gastrectomy can be used to predict the prognosis of pT3N0 GC.
Core Tip: Patients with pathological stage T1N2-3 (pT1N2-3) and pT3N0 gastric cancer (GC) have not been routinely included in the target population for postoperative chemotherapy, and their prognosis is significantly different. The study aimed to identify the high-risk patients after radical surgery by analyzing biomarkers and clinicopathological features and construct prognostic models for them. Our results showed that the predictive models constructed by peripheral blood biomarkers and clinicopathological features can evaluate the prognosis of patients with pT1N2-3 and pT3N0 GC, which is worthy of further validation and promotion in clinical practice.