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首页> 外文期刊>Medicine. >A nomogram for predicting the likelihood of lymph node metastasis in early gastric signet ring cell carcinoma A single center retrospective analysis with external validation
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A nomogram for predicting the likelihood of lymph node metastasis in early gastric signet ring cell carcinoma A single center retrospective analysis with external validation

机译:诺模图预测早期胃印戒细胞癌淋巴结转移的可能性单中心回顾性分析并通过外部验证

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Treatment algorithmhas not been established for early gastric cancer with signet ring cell carcinoma (SRC), which has a reported lowrate of lymph node metastasis (LNM) similar to differentiated cancer. A cohort of 256 patients with early gastric SRC at our center between January 2002 and December 2015 were retrospectively reviewed. Multivariate logistic regression analysis was used to determine the independent factors of LNM. A nomogram for predicting LNM was constructed and internally validated. Additional external validation was performed using the database from Cancer Institute Ariake Hospital in Tokyo (n = 1273). Clinical performance of the model was assessed by decision analysis of curve. The overall LNM incidence was 12.9% (33/256). The multivariate logistic model identified sex, tumor size, and LVI as covariates associated with LNM. Subsequently, a nomogramconsisted of sex, tumor size, and depth of invasion was established. The model showed qualified discrimination ability both in internal validation (area under curve, 0.801; 95% confidence interval [CI], 0.729-0.873) and in external dataset (area under curve, 0.707; 95% CI, 0.657-0.758). Based on the nomogram, treatment algorithm for early gastric SRC was proposed to assist clinicians in making better decisions. We developed a nomogrampredicting risk of LNM for early gastric SRC, which should be helpful for patient counseling and surgical decision-making.
机译:尚未建立针对印戒细胞癌(SRC)的早期胃癌的治疗算法,据报道,该信号的淋巴结转移率(LNM)较低,与分化癌相似。回顾性分析了2002年1月至2015年12月在我中心接受研究的256例早期胃SRC患者。采用多元logistic回归分析确定LNM的独立因素。构造了用于预测LNM的列线图,并在内部进行了验证。使用东京有明癌症研究所的数据库(n = 1273)进行了额外的外部验证。通过曲线的决策分析评估该模型的临床性能。 LNM的总发生率为12.9%(33/256)。多元逻辑模型将性别,肿瘤大小和LVI识别为与LNM相关的协变量。随后,建立了由性别,肿瘤大小和浸润深度组成的列线图。该模型在内部验证(曲线下面积为0.801; 95%置信区间[CI],0.729-0.873)和外部数据集(曲线下面积为0.707; 95%CI,0.657-0.758)中均显示出合格的辨别能力。基于诺模图,提出了早期胃SRC的治疗算法,以协助临床医生做出更好的决策。我们开发了诺模图预测早期胃SRC的LNM风险,这将有助于患者咨询和手术决策。

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