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用于预测子宫内膜癌患者淋巴结转移的列线图预测模型。

A nomogram prediction model for lymph node metastasis in endometrial cancer patients.

机构信息

Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong Province, 250012, P. R. China.

Department of Obstetrics and Gynecology, Jinan Central Hospital Affiliated to Shandong University, Jinan, 250013, Shandong Province, China.

出版信息

BMC Cancer. 2021 Jun 29;21(1):748. doi: 10.1186/s12885-021-08466-4.

Abstract

BACKGROUND

This study aimed to explore the risk factors for lymph node metastasis (LNM) in patients with endometrial cancer (EC) and develop a clinically useful nomogram based on clinicopathological parameters to predict it.

METHODS

Clinical information of patients who underwent staging surgery for EC was abstracted from Qilu Hospital of Shandong University from January 1st, 2005 to June 31st, 2019. Parameters including patient-related, tumor-related, and preoperative hematologic examination-related were analyzed by univariate and multivariate logistic regression to determine the correlation with LNM. A nomogram based on the multivariate results was constructed and underwent internal and external validation to predict the probability of LNM.

RESULTS

The overall data from the 1517 patients who met the inclusion criteria were analyzed. 105(6.29%) patients had LNM. According the univariate analysis and multivariate logistic regression analysis, LVSI is the most predictive factor for LNM, patients with positive LVSI had 13.156-fold increased risk for LNM (95%CI:6.834-25.324; P < 0.001). The nomogram was constructed and incorporated valuable parameters including histological type, histological grade, depth of myometrial invasion, LVSI, cervical involvement, parametrial involvement, and HGB levels from training set. The nomogram was cross-validated internally by the 1000 bootstrap sample and showed good discrimination accuracy. The c-index for internal and external validation of the nomogram are 0.916(95%CI:0.849-0.982) and 0.873(95%CI:0.776-0.970), respectively.

CONCLUSIONS

We developed and validated a 7-variable nomogram with a high concordance probability to predict the risk of LNM in patients with EC.

摘要

背景

本研究旨在探讨子宫内膜癌(EC)患者发生淋巴结转移(LNM)的危险因素,并基于临床病理参数建立一个临床实用的列线图来预测其发生。

方法

从 2005 年 1 月 1 日至 2019 年 6 月 31 日,从山东大学齐鲁医院提取了接受分期手术的 EC 患者的临床信息。通过单因素和多因素 logistic 回归分析患者相关、肿瘤相关和术前血液检查相关的参数,以确定与 LNM 的相关性。基于多因素结果构建列线图,并进行内部和外部验证以预测 LNM 的概率。

结果

对符合纳入标准的 1517 例患者的总数据进行了分析。105(6.29%)例患者发生 LNM。根据单因素分析和多因素 logistic 回归分析,LVSI 是 LNM 最具预测性的因素,LVSI 阳性患者发生 LNM 的风险增加了 13.156 倍(95%CI:6.834-25.324;P<0.001)。构建了列线图,并纳入了训练集中有价值的参数,包括组织学类型、组织学分级、肌层浸润深度、LVSI、宫颈受累、宫旁受累和 HGB 水平。该列线图通过 1000 次 bootstrap 样本进行了内部交叉验证,显示出良好的区分准确性。该列线图的内部和外部验证的 c 指数分别为 0.916(95%CI:0.849-0.982)和 0.873(95%CI:0.776-0.970)。

结论

我们开发并验证了一个 7 变量列线图,该列线图具有较高的一致性概率,可以预测 EC 患者发生 LNM 的风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7652/8243766/377856f335c1/12885_2021_8466_Fig1_HTML.jpg

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