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乳房切除术后乳腺癌相关淋巴水肿的预测模型

Predictive models for breast cancer-related lymphedema after mastectomy.

作者信息

Zhong Chunchang, Xiao Hong, Chen Birong, Lan Yan, Liu Haiying, Zhang Wenxia

机构信息

Department of Breast Surgery, Shenzhen Maternity and Child Healthcare Hospital Shenzhen 518048, Guangdong, China.

出版信息

Am J Transl Res. 2024 Sep 15;16(9):4623-4632. doi: 10.62347/ZJAZ6071. eCollection 2024.

Abstract

OBJECTIVES

To establish a nomogram incorporating clinical characteristics to predict the risk of breast cancer-related lymphedema (BCRL).

METHODS

In this retrospective study, we included 200 consecutive patients with breast cancer undergoing radical mastectomy from January 2022 to December 2023. Of these, 98 patients diagnosed with BCRL were designated as the experimental group, while 102 patients served as the control group. Logistic regression analyses were conducted to explore factors associated with clinical prognosis and to construct and validate a nomogram for predicting the risk of BCRL using R language version 4.1.2.

RESULTS

Univariate and multivariate logistic regression analyses identified six independent risk factors: the number of lymph node dissections (95% CI: 1.425-8.956, P < 0.01), radiotherapy (95% CI: 1.134-2.341, P < 0.01), lack of functional exercise (95% CI: 4.908-19.064, P = 0.001), adjuvant and neoadjuvant chemotherapy (95% CI: 1.763-4.287, P = 0.001), BMI (95% CI: 1.075-2.897, P < 0.05), and hypertension (95% CI: 1.077-2.999, P < 0.05). Using these variables, we developed a nomogram to predict the incidence of BCRL. The AUC value for the model was 0.74 (95% CI: 0.675-0.887), indicating acceptable agreement between predicted and observed outcomes. Decision curve analysis demonstrated good positive net benefits for the model.

CONCLUSION

The number of lymph node dissections, radiotherapy, lack of functional exercise, adjuvant and neoadjuvant chemotherapy, BMI, and hypertension are independent risk factors for BCRL. Moreover, the nomogram prediction model showed good predictive performance, high accuracy, and clinical applicability.

摘要

目的

建立一个纳入临床特征的列线图,以预测乳腺癌相关淋巴水肿(BCRL)的风险。

方法

在这项回顾性研究中,我们纳入了2022年1月至2023年12月期间连续200例行根治性乳房切除术的乳腺癌患者。其中,98例被诊断为BCRL的患者被指定为实验组,102例患者作为对照组。进行逻辑回归分析以探索与临床预后相关的因素,并使用R语言版本4.1.2构建和验证用于预测BCRL风险的列线图。

结果

单因素和多因素逻辑回归分析确定了六个独立危险因素:淋巴结清扫数量(95%CI:1.425 - 8.956,P < 0.01)、放疗(95%CI:1.134 - 2.341,P < 0.01)、缺乏功能锻炼(95%CI:4.908 - 19.064,P = 0.001)、辅助和新辅助化疗(95%CI:1.763 - 4.287,P = 0.001)、BMI(95%CI:1.075 - 2.897,P < 0.05)和高血压(95%CI:1.077 - 2.999,P < 0.05)。使用这些变量,我们开发了一个列线图来预测BCRL的发生率。该模型的AUC值为0.74(95%CI:0.675 - 0.887),表明预测结果与观察结果之间具有可接受的一致性。决策曲线分析表明该模型具有良好的正净效益。

结论

淋巴结清扫数量、放疗、缺乏功能锻炼、辅助和新辅助化疗、BMI和高血压是BCRL的独立危险因素。此外,列线图预测模型显示出良好的预测性能、高准确性和临床适用性。

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