Abstract：Objective To construct a predictive model of early recurrence for gastric patients after radical gastrectomy based on clinicopathological characteristics and guide individualized adjuvant therapy and follow-up.Methods A total of 114 patients with gastric cancer who underwent radical surgery were enrolled.Least absolute shrinkage and selection operator regression analysis was used to screen for factors associated with recurrence-free survival (RFS) and a predictive model was constructed based on the factors through COX regression analysis. The model was validated by receiver operating characteristic curve, log-rank test, univariate and multivariate analyses. In addition, a nomogram based on the model was generated and evaluated by calibration curves.Results A predictive model was developed and recurrence indexes (RI=0.019×age+0.438×male+(-0.813)×mucinous adenocarcinoma+(-0.446)× moderately differentiated adenocarcinoma+0.30×Lauren mixed type+0.472×lymphovascular or neural invasion+0.224×pathological N stage+0.168×pathological stage) were calculated. The areas under the ROC curves of RI to predict 1-year and 2-year recurrence were greater than 0.7. The patients with low RI had a longer RFS. The RI was also an independent marker to predictor early recurrence. The nomogram can predict probabilities of 1-year and 2-year recurrence accurately.Conclusions This model can accurately predict the risk of early recurrence after radical surgery in patients with gastric cancer, which is worthy of further confirmation and wide application in clinical practice.
陈健, 闫滢, 钱小军, 韩兴华, 何义富. 基于临床病理特征构建胃癌根治术后早期复发风险预测模型[J]. 武警医学, 2019, 30(9): 776-779.
CHEN Jian, YAN Ying, QIAN Xiaojun, HAN Xinghua, HE Yifu. A clinicopathological characteristics based model to predict early recurrence of patients with gastric cancer after radical surgery. Med. J. Chin. Peop. Armed Poli. Forc., 2019, 30(9): 776-779.
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2019, Vol. 30 
