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.
Key words
gastric cancer /
early recurrence /
clinicopathological characteristics /
predictive model
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
[1] Tarazona N, Gambardella V, Huerta M, et al. Personalised treatment in gastric cancer: myth or reality?[J]. Curr Oncol Rep, 2016, 18(7): 41.
[2] Kim H, Hwang Y, Sung H, et al. Effectiveness of gastric cancer screening on gastric cancer incidence and mortality in a community-based prospective cohort[J]. Cancer Res Treat, 2018, 50(2): 582-589.
[3] Liu D, Lu M, Li J, et al. The patterns and timing of recurrence after curative resection for gastric cancer in China[J]. World J Surg Oncol, 2016, 14(1): 305.
[4] Lee J H, Chang K K, Yoon C, et al. Lauren histologic type is the most important factor associated with pattern of recurrence following resection of gastric adenocarcinoma[J]. Ann Surg, 2016, 267(1): 105-113.
[5] 陈万青, 郑荣寿, 张思维, 等. 2013年中国恶性肿瘤发病和死亡分析[J]. 中国肿瘤, 2017, 26 (1): 1-7.
[6] Tibshirani R. Regression shrinkage and selection via the LASSO[J]. J R Stat Soc B, 1996, 73(1):273-282.
[7] Zhu B Y, Yuan S Q. Prognostic factors and recurrence patterns in T4 gastric cancer patients after curative resection[J]. J Cancer,2019, 10(5): 1181-1188.
[8] Wang Y, Ran H, Guichao L, et al. Survival outcomes and patterns of failure after D2 dissection and adjuvant chemoradiotherapy for locally advanced gastric cancer: a retrospective study[J]. Br J Radiol, 2018,91(1089): 20170594.
[9] Bilici A, Selcukbiricik F, Seker M, et al. Prognostic significance of metastatic lymph node ratio in patients with pN3 gastric cancer who underwent curative gastrectomy[J]. Oncol Res Treat,2019, 42(4): 209-216.
[10] Kang W M, Meng Q B, Yu J C, et al. Factors associated with early recurrence after curative surgery for gastric cancer[J]. World J Gastroenterol,2015, 21(19): 5934-5940.
PDF(951 KB)
