前列腺癌患者淋巴结转移术前模型的构建

毕泗成; 毛昕; 吴世菊; 张鹏; 黄炳伟; 买铁军; 李喆

doi:10.13201/j.issn.1001-1420.2021.08.009

前列腺癌患者淋巴结转移术前模型的构建

- 1. 应急总医院泌尿外科(北京, 100028);
- 2. 青岛大学附属医院泌尿外科

详细信息

通讯作者: 毕泗成,E-mail:psbybscly@163.com

中图分类号: R737.25

收稿日期: 2020-10-16

Construction and analysis of preoperative model of lymph node metastasis in patients with prostate cancer

- 1. Department of Urology, Emergency General Hospital, Beijing, 100028, China;
- 2. Department of Urology, Affiliated Hospital of Qingdao University

More Information

Corresponding author: BI Sicheng, E-mail: psbybscly@163.com

Received Date: 16 October 2020

摘要

摘要: 目的:通过建立前列腺癌患者淋巴结转移术前模型,指导临床制定扩大盆腔淋巴结清扫范围的临床决策。方法:回顾性收集2017年1月—2020年1月136例前列腺癌患者的临床资料,发现31例患者出现转移,将其作为转移组,将其余105例未出现转移的患者作为对照组,比较两组患者临床资料、实验室检查资料及影像学资料等,并采用多因素Logistic回归分析影响前列腺癌患者淋巴结转移的危险因素;使用逻辑回归构建模型,分析该模型在术前预测前列腺癌患者淋巴结转移的诊断效能,另随机收集同期接受根治术治疗的50例前列腺癌患者的临床资料,采用最临近匹配法,匹配比例1∶1,卡钳值设为0.02,以50例前列腺癌患者的临床资料为基准进行匹配,最终纳入50例未转移患者的临床资料,作为验证集验证预测效能。结果:转移组血清总前列腺特异性抗原(tPSA)[(50.46±10.72)ng/mL vs.(46.34±6.87)ng/mL]、游离PSA百分比[(0.57±0.12) vs.(0.51±0.13)]、前列腺体积[(65.84±20.58)mL vs.(57.85±16.70)mL]、格里森得分[(5.54±1.07)vs.(5.00±1.08)]均高于对照组(P＜0.05),Logistic多因素分析筛选出tPSA(OR=1.066)、前列腺体积(OR=1.059)及格里森得分(OR=1.682)为前列腺癌患者淋巴结转移的独立危险因素;使用逻辑回归对tPSA、前列腺体积及格里森得分指标构建预测模型,分析显示列线图模型预测发生淋巴结转移的C-index为0.913,且校正曲线显示列线图模型预测可能性绝对误差为0.018。结论:构建逻辑回归预测模型能够用于早期评估前列腺癌患者淋巴结转移风险,能为前列腺癌根治术扩大盆腔淋巴结清扫范围提供一定参考。
- 前列腺癌 /
- 淋巴转移 /
- 淋巴结清扫 /
- 前列腺特异性抗原
Abstract: Objective: To establish a preoperative model of lymph node metastasis in patients with prostate cancer to guide the clinical decision to expand the scope of pelvic lymph node dissection.Methods: The clinical data of 136 patients with prostate cancer from January 2017 to January 2020 were retrospectively collected. Thirty-one patients with metastases were studied as the metastasis group, and 105 patients without metastasis were studied as the control group. The clinical data, laboratory examination data and imaging data of the two groups of patients were used to analyze the risk factors of lymph node metastasis in prostate cancer patients by multivariate logistic regression. Logistic regression was used to construct a model, and the model to predict the lymph nodes in prostate cancer patients before surgery for the diagnostic efficiency of metastasis was analyzed. The clinical data of 50 prostate cancer patients who underwent radical resection during the same period were randomly collected. The nearest matching method was adopted. The matching ratio was 1:1, and the caliper value was set to 0.02. The clinical data of 50 prostate cancer patients as a benchmark for matching, the clinical data of 50 non-metastatic patients were finally included as a validation set to verify the predictive performance.Results: The total prostate specific antigen [(50.46±10.72)ng/mL vs.(46.34±6.87)ng/mL], percentage of free PSA [(0.57±0.12)vs.(0.51±0.13)], prostate volume [(65.84±20.58)mL vs.(57.85±16.70)mL], Gleason scores [(5.54±1.07)vs.(5.00±1.08)] of the metastasis group were higher than those of the control group(P＜0.05). Logistic multivariate analysis screened tPSA(OR=1.066), prostate volume(OR=1.059) and Gleason score(OR=1.682) as independent risk factors for lymph node metastasis in prostate cancer patients. Logistic regression was used to construct a predictive model for tPSA, prostate volume and Gleason score. Analysis showed that the C-index of the nomogram model to predict lymph node metastasis was 0.913, and the calibration curve showed that the absolute error of the nomogram model's prediction probability was 0.018.Conclusion: Based on a variety of clinical information from patients, the construction of a logistic regression prediction model can be used for early assessment of the risk of lymph node metastasis in patients with prostate cancer, and can provide reference for expanding the scope of pelvic lymph node dissection during radical prostatectomy.
- prostate cancer /
- lymphatic metastasis /
- lymph node dissection /
- prostate specific antigen

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