改进胃癌临床T分期模型的建立与评价.

Objective To establish a new clinical T staging model for patients with gastric cancer (GC) and to evaluate its predictive effect, so as to provide the basis for improving the predictive value of clinical T staging. Methods A total of 227 GC patients underwent radical surgery in our hospital were enrolled in this study. Among them, 102 cases were pT1-pT2 gastric cancer, 125 cases were pT3-pT4 gastric cancer. All patients underwent endoscopic ultrasonography (EUS) and multislice spiral computed tomography (CT) examination before operation. Univariate analysis was used to compare the clinical and pathological data, including gender, age, tumor location, Borrmann classification, CT based T staging, the layers of tumor invading the gastric wall under EUS and the maximum short diameter of longitudinal section of tumor under EUS, between pT1-pT2 and pT3-pT4 patients. According to the clinical experience, CT-based T staging and the layers of tumor invading the gastric wall under EUS were included to establish the traditional conventional clinical T staging model (CCTSM). Multivariate Logistic regression analysis was used to further evaluate the risk factors of pT3-pT4 after univariate analysis, and the significant variables were included in the revised clinical T staging model (RCTSM). The receiver operating characteristic (ROC) curve was constructed to assess the performance of two prediction models. Results The corresponding Logistic regression equation was Logit (P)= -2.599+2.409× CT based T staging + 2.553× the layers of tumor invading the gastric wall under EUS. The results of univariate analysis and multivariate Logistic regression analysis showed that CT based T3-T4 staging (OR=12.528, 95%CI: 4.347-36.109), the 5th layer of tumor invading the gastric wall under EUS (OR=7.533, 95%CI: 2.539-22.353), the longer maximum of the short diameter of tumor longitudinal section under EUS (OR=31.084, 95%CI: 8.681-111.307) were independent risk factors of pT3-pT4 stage in the GC patients. The Logistic regression equation of the revised clinical T staging model was established with these three variables: Logit (P)= -7.884+2.528× CT based T staging + 2.019× the layers of tumor invading the gastric wall under EUS + 3.437×the maximum short diameter of longitudinal section of tumor under EUS. The clinical value of the RCTSM in predicting pT3~pT4 was better than that of the CCTSM (AUC: 0.952 vs. 0.891, Z=3.870, P＜0.01). In the lymph node positive subgroup, the predictive value of the RCTSM was also better than that of the CCTSM (AUC: 0.916 vs. 0.864, Z=2.058，P＜0.05). Conclusion The RCTSM can better predict the pathological T staging in patients with gastric cancer and provide reliable basis for individualized treatment of GC patients. [ABSTRACT FROM AUTHOR]