Prediction of Non-sentinel Node Status in Patients with Melanoma and Positive Sentinel Node Biopsy: An Italian Melanoma Intergroup (IMI) Study
Prediction of Non-sentinel Node Status in Patients with Melanoma and Positive Sentinel Node Biopsy: An Italian Melanoma Intergroup (IMI) Study
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DOI：
10.1245/s10434-017-6143-5
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发表时间：
2018-01-01
影响因子：
3.7
通讯作者：
Ribero, Simone
中科院分区：
文献类型：
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作者：
Rossi, Carlo Riccardo;Mocellin, Simone;Ribero, Simone
大约20%的黑色素瘤患者在前哨淋巴结活检（SNB）阳性后在非前哨淋巴结（NSN）中存在转移，最近的证据质疑完成淋巴结清扫（CLND）的治疗益处。我们建立了一个nomogram预测黑色素瘤患者的NSN状态与阳性SNB.Data的人体测量和临床病理特征的皮肤黑色素瘤患者进行CLND后，一个积极的SNB收集了来自9个意大利中心。利用多变量logistic回归在训练集中识别NSN状态的预测因子，同时在验证集中验证模型效率。数据来自2000年至2016年接受治疗的1220例患者。在训练集（n = 810）中，当（1）原发性黑色素瘤较厚或（2）位于躯干/头颈部;（3）切除的淋巴结较少和（4）累及的淋巴结较多;（5）淋巴结转移较大或（6）位置较深时，NSN受累的风险较高。该模型在验证集（n = 410）中显示出高区分度（受试者工作特征曲线下面积0.74，95%置信区间[CI] 0.70-0.79）和校准（Brier评分0.16，95% CI 0.15-0.17）性能。包括这六个临床病理变量的诺模图表现出显着优于其他五个先前发表的模型在歧视和calibration.Our诺模图可能是有用的后续个性化在临床实践中，并进行临床试验或分析其结果的患者风险分层。
Approximately 20% of melanoma patients harbor metastases in non-sentinel nodes (NSNs) after a positive sentinel node biopsy (SNB), and recent evidence questions the therapeutic benefit of completion lymph node dissection (CLND). We built a nomogram for prediction of NSN status in melanoma patients with positive SNB.Data on anthropometric and clinicopathological features of patients with cutaneous melanoma who underwent CLND after a positive SNB were collected from nine Italian centers. Multivariate logistic regression was utilized to identify predictors of NSN status in a training set, while model efficiency was validated in a validation set.Data were available for 1220 patients treated from 2000 through 2016. In the training set (n = 810), the risk of NSN involvement was higher when (1) the primary melanoma is thicker or (2) sited in the trunk/head and neck; (3) fewer nodes are excised and (4) more nodes are involved; and (5) the lymph node metastasis is larger or (6) is deeply located. The model showed high discrimination (area under the receiver operating characteristic curve 0.74, 95% confidence interval [CI] 0.70-0.79) and calibration (Brier score 0.16, 95% CI 0.15-0.17) performance in the validation set (n = 410). The nomogram including these six clinicopathological variables performed significantly better than five other previously published models in terms of both discrimination and calibration.Our nomogram could be useful for follow-up personalization in clinical practice, and for patient risk stratification while conducting clinical trials or analyzing their results.