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A clinical model to predict distant metastasis in patients with superficial gastric cancer with negative lymph node metastasis and a survival analysis for patients with metastasis

BACKGROUND: Distant metastasis (DM) is relatively rare in superficial gastric cancer (SGC), especially in patients without lymph node metastasis. This study aimed to explore the main clinical risk factors for DM in patients with superficial gastric cancer‐no lymph node metastasis (SGC‐NLNM) and the...

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Detalles Bibliográficos
Autores principales: Chen, Jingyu, Wu, Lunpo, Zhang, Zizhen, Zheng, Sheng, Lin, Yifeng, Ding, Ning, Sun, Jiawei, Shi, Liuhong, Xue, Meng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7897959/
https://www.ncbi.nlm.nih.gov/pubmed/33350173
http://dx.doi.org/10.1002/cam4.3680
Descripción
Sumario:BACKGROUND: Distant metastasis (DM) is relatively rare in superficial gastric cancer (SGC), especially in patients without lymph node metastasis. This study aimed to explore the main clinical risk factors for DM in patients with superficial gastric cancer‐no lymph node metastasis (SGC‐NLNM) and the prognostic factors for patients with DM. METHODS: Records of patients with SGC‐NLNM between 2004 and 2015 were collected from the public Surveillance, Epidemiology, and End Results (SEER) database. Both univariate and multivariate logistic regressions were performed to analyze the clinical risk factors for DM. The Kaplan–Meier method and Cox regression model were used to identify prognostic factors for patients with DM. A nomogram was built based on multivariate logistic regression and evaluated by the C‐index, the calibration, and the area under the receiver operating characteristic curve (AUC). RESULTS: We developed and validated a nomogram to predict DM in patients with SGC‐NLNM, showing that race, age, primary site, depth, size, and grade were independent risk factors. The built nomogram had a good discriminatory performance, with a C‐index of 0.836 (95% confidence interval [CI]: 0.813–0.859). Calibration plots showed that the predicted DM probability was identical to the actual observations in both the training and validation sets. AUC was 0.846 (95% CI: 0.820–0.871) and 0.801 (95% CI: 0.751–0.850) in the training and validation sets, respectively. The results of the survival analysis revealed that surgery (hazard ratio [HR] = 0.249; 95% CI, 0.125–0.495), chemotherapy (HR = 0.473; 95% CI, 0.353–0.633), and grade (HR = 1.374; 95% CI, 1.018–1.854) were independent prognostic factors associated with cancer‐specific survival (CSS), but radiotherapy was not (log‐rank test, p = 0.676). CONCLUSIONS: We constructed a sensitive and discriminative nomogram to identify high‐risk patients with SGC‐NLNM who may harbor dissemination at initial diagnosis. The tumor size and primary site were the largest contributors to DM prediction. Compared with radiotherapy, aggressive surgery, and chemotherapy may be better options for patients with DM.