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目的：探究前列腺癌患者发生盆腔淋巴结转移的危险因素，构建预测盆腔淋巴结转移列线图预测模型并进行外部验证。方法：本研究回顾性收集2017年1月至2020年12月于解放军总医院第一医学中心行机器人辅助根治性前列腺切除术（RARP）的前列腺癌患者437例的临床资料作为训练集，2021年1月至2022年12月解放军总医院第三医学中心行RARP的前列腺癌患者74例的临床资料作为外部验证集。根据训练集患者术后病理盆腔淋巴结转移情况分为盆腔淋巴结转移组（n=48），和盆腔淋巴结未转移组（n=389），采用单因素和多因素Logistic回归筛选发生盆腔淋巴结转移的独立危险因素，构建列线图并进行外部验证。结果：训练集和验证集的临床资料差异无统计学意义，单因素及多因素Logistic分析结果显示，训练集中437例前列腺癌患者的Gleason评分（P=0.017）、总前列腺特异性抗原（tPSA）水平（P<0.001）、阳性核心针数百分比（P<0.001）、临床分期（P<0.001）与其淋巴结转移有关。预测模型受试者工作特征曲线（ROC）计算训练集ROC曲线下面积（AUC）为0.787(95%CI:0.704～0.807)，外部验证集AUC为0.774(95%CI:0.613～0.935)，校准曲线显示，列线图预测的淋巴结转移概率与实际情况相符（训练集C-index:0.787）。决策曲线显示模型净获益较好。结论：通过外部验证证实构建的预测淋巴结转移概率的列线图简单实用，准确性较高，可为临床应用提供参考。
Abstract：Objective: To investigate the risk factors for pelvic lymph node metastasis in prostate cancer patients, construct a nomogram prediction model for pelvic lymph node metastasis, and perform external validation.Methods: This retrospective study collected clinical data from 437 prostate cancer patients who underwent robot-assisted radical prostatectomy(RARP) at the First Medical Center of the General Hospital of the People's Liberation Army from January 2017 to December 2020 as the training set. Clinical data from 74 prostate cancer patients who underwent RARP at the Third Medical Center of the General Hospital of the People's Liberation Army from January 2021 to December 2022 were used as the external validation set. Based on the postoperative pathological results, the training set was divided into two groups: the pelvic lymph node metastasis group(n=48) and the non-metastasis group(n=389). Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for pelvic lymph node metastasis. A nomogram was constructed and externally validated. Results: There were no statistically significant differences in the clinical characteristics between the training and validation sets. Univariate and multivariate logistic regression analyses showed that Gleason score(P=0.017), total prostate-specific antigen(tPSA) level(P<0.001), percentage of positive core biopsies(P<0.001), and clinical stage(P<0.001) were independently associated with lymph node metastasis in the training set. The area under the receiver operating characteristic curve(AUC) for the training set was 0.787(95%CI:0.704-0.807), and for the external validation set, it was 0.774(95%CI:0.613-0.935). Calibration curves demonstrated that the predicted probabilities of lymph node metastasis by the nomogram were consistent with the actual outcomes(training set C-index:0.787). Decision curve analysis indicated that the model provided good net benefit. Conclusion: The constructed nomogram for predicting the probability of pelvic lymph node metastasis was simple, practical, and highly accurate, as confirmed by external validation.This nomogram can serve as a valuable reference for clinical decision-making.
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基本信息:
DOI：10.19558/j.cnki.10-1020/r.2025.03.006
中图分类号:R737.25
引用信息:
[1]赵堃,安子彦,邵金鹏,等.机器人辅助根治性前列腺切除术发生淋巴结转移的危险因素及列线图预测模型的构建与评价[J].微创泌尿外科杂志().DOI:10.19558/j.cnki.10-1020/r.2025.03.006.
2025-06-27
2025-06-27
2025-06-27