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基于放射学因素和临床病理特征建立并验证直肠癌患者侧方盆腔淋巴结转移的预测列线图。

Establishing and validating predictive nomograms for lateral pelvic lymph node metastasis in patients with rectal cancer based on radiologic factors and clinicopathologic characteristics.

作者信息

Zhou Sicheng, Yang Yingchi, Lou Zheng, Liang Jianwei, Wang Xin, Tang Jianqiang, Liu Qian

机构信息

Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.

Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing Key Laboratory of Cancer Invasion and Metastasis Research and National Clinical Research Center of Digestive Diseases, Beijing, 100050, China.

出版信息

Eur J Surg Oncol. 2023 Apr;49(4):747-754. doi: 10.1016/j.ejso.2022.12.014. Epub 2022 Dec 29.

Abstract

INTRODUCTION

It is critical to accurately predict the occurrence of lateral pelvic lymph node (LPN) metastasis. Currently, verified predictive tools are unavailable. This study aims to establish nomograms for predicting LPN metastasis in patients with rectal cancer who received or did not receive neoadjuvant chemoradiotherapy (nCRT).

MATERIALS AND METHODS

We carried out a retrospective study of patients with rectal cancer and clinical LPN metastasis who underwent total mesorectal excision (TME) and LPN dissection (LPND) from January 2012 to December 2019 at 3 institutions. We collected and evaluated their clinicopathologic and radiologic features, and constructed nomograms based on the multivariable logistic regression models.

RESULTS

A total of 472 eligible patients were enrolled into the non-nCRT cohort (n = 312) and the nCRT cohort (n = 160). We established nomograms using variables from the multivariable logistic regression models in both cohorts. In the non-nCRT cohort, the variables included LPN short diameter, cT stage, cN stage, histologic grade, and malignant features, and the C-index was 0.930 in the training cohort and 0.913 in the validation cohort. In the nCRT cohort, the variables included post-nCRT LPN short diameter, ycT stage, ycN stage, histologic grade, and post-nCRT malignant features, and the C-index was 0.836 in the training dataset and 0.827 in the validation dataset. The nomograms in both cohorts were moderately calibrated and well-validated.

CONCLUSIONS

We established nomograms for patients with rectal cancer that accurately predict LPN metastasis. The performance of the nomograms in both cohorts was high and well-validated.

摘要

引言

准确预测侧方盆腔淋巴结(LPN)转移的发生至关重要。目前,尚无经过验证的预测工具。本研究旨在建立列线图,以预测接受或未接受新辅助放化疗(nCRT)的直肠癌患者的LPN转移情况。

材料与方法

我们对2012年1月至2019年12月在3家机构接受全直肠系膜切除术(TME)和LPN清扫术(LPND)的直肠癌及临床LPN转移患者进行了一项回顾性研究。我们收集并评估了他们的临床病理和影像学特征,并基于多变量逻辑回归模型构建了列线图。

结果

共有472例符合条件的患者被纳入非nCRT队列(n = 312)和nCRT队列(n = 160)。我们在两个队列中均使用多变量逻辑回归模型中的变量建立了列线图。在非nCRT队列中,变量包括LPN短径、cT分期、cN分期、组织学分级和恶性特征,训练队列中的C指数为0.930,验证队列中的C指数为0.913。在nCRT队列中,变量包括nCRT后LPN短径、ycT分期、ycN分期、组织学分级和nCRT后恶性特征,训练数据集中的C指数为0.836,验证数据集中的C指数为0.827。两个队列中的列线图校准适度且验证良好。

结论

我们为直肠癌患者建立了能准确预测LPN转移的列线图。两个队列中列线图的性能都很高且验证良好。

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