Melanoma Institute Australia (formerly Sydney Melanoma Unit), Sydney, NSW, Australia.
Ann Surg Oncol. 2010 Aug;17(8):1995-2005. doi: 10.1245/s10434-010-1049-5. Epub 2010 May 20.
Completion lymph node dissection (CLND) following positive sentinel node biopsy (SNB) for melanoma detects additional nonsentinel node (NSN) metastases in approximately 20% of cases. This study aimed to establish whether NSN status can be predicted, to determine its effect on survival, and to develop survival tree models for the sentinel node (SN) positive population.
Sydney Melanoma Unit (SMU) patients with at least 1 positive SN, meeting inclusion criteria and treated between October 1992 and June 2005, were identified from the Unit database. Survival characteristics, potential predictors of survival, and NSN status were assessed using the Kaplan-Meier method, Cox regression model, and logistic regression analyses, respectively. Classification tree analysis was performed to identify groups with distinctly different survival characteristics.
A total of 323 SN-positive melanoma patients met the inclusion criteria. On multivariate analysis, age, gender, primary tumor thickness, mitotic rate, number of positive NSNs, or total number of positive nodes were statistically significant predictors of survival. NSN metastasis, found at CLND in 19% of patients, was only predicted to a statistically significant degree by ulceration. Multivariate analyses demonstrated that survival was more closely related to number of positive NSNs than total number of positive nodes. Classification tree analysis revealed 4 prognostically distinct survival groups.
Patients with NSN metastases could not be reliably identified prior to CLND. Prognosis following CLND was more closely related to number of positive NSNs than total number of positive nodes. Classification tree analysis defined distinctly different survival groups more accurately than use of single-factor analysis.
对于黑色素瘤患者,在前哨淋巴结活检(SNB)阳性后进行完全淋巴结清扫(CLND),大约 20%的病例中可检测到额外的非前哨淋巴结(NSN)转移。本研究旨在确定是否可以预测 NSN 状态,以确定其对生存的影响,并为 SN 阳性人群开发生存树模型。
从单位数据库中确定了 1992 年 10 月至 2005 年 6 月期间至少有 1 个阳性 SN 且符合纳入标准的悉尼黑色素瘤单位(SMU)患者。使用 Kaplan-Meier 方法、Cox 回归模型和逻辑回归分析分别评估生存特征、潜在生存预测因子和 NSN 状态。进行分类树分析以确定具有明显不同生存特征的组。
共有 323 例 SN 阳性黑色素瘤患者符合纳入标准。多变量分析显示,年龄、性别、原发肿瘤厚度、有丝分裂率、阳性 NSN 数量或阳性淋巴结总数是生存的统计学显著预测因子。在 19%的患者中,CLND 发现的 NSN 转移仅在统计学上与溃疡显著相关。多变量分析表明,生存与阳性 NSN 数量的关系比总阳性淋巴结数量更为密切。分类树分析显示出 4 个具有不同预后的生存组。
在 CLND 之前无法可靠地识别出 NSN 转移的患者。CLND 后的预后与阳性 NSN 数量的关系比总阳性淋巴结数量更为密切。分类树分析比使用单因素分析更准确地定义了明显不同的生存组。