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Factors Affecting Sentinel Node Metastasis in Thin (T1) Cutaneous Melanomas: Development and External Validation of a Predictive Nomogram
Journal of Clinical Oncology ( IF 42.1 ) Pub Date : 2020-05-10 , DOI: 10.1200/jco.19.01902
Andrea Maurichi 1 , Rosalba Miceli 2 , Hanna Eriksson 3, 4 , Julia Newton-Bishop 5 , Jérémie Nsengimana 5 , May Chan 5 , Andrew J Hayes 6, 7 , Kara Heelan 6, 7 , David Adams 8 , Roberto Patuzzo 1 , Francesco Barretta 2 , Gianfranco Gallino 1 , Catherine Harwood 9 , Daniele Bergamaschi 9 , Dorothy Bennett 10 , Konstantinos Lasithiotakis 11, 12 , Paola Ghiorzo 13 , Bruna Dalmasso 13 , Ausilia Manganoni 14 , Francesca Consoli 14 , Ilaria Mattavelli 1 , Consuelo Barbieri 1 , Andrea Leva 1 , Umberto Cortinovis 15 , Vittoria Espeli 16 , Cristina Mangas 16 , Pietro Quaglino 17 , Simone Ribero 17 , Paolo Broganelli 17 , Giovanni Pellacani 18 , Caterina Longo 19, 20 , Corrado Del Forno 21 , Lorenzo Borgognoni 22 , Serena Sestini 22 , Nicola Pimpinelli 23 , Sara Fortunato 23 , Alessandra Chiarugi 24 , Paolo Nardini 24 , Elena Morittu 25 , Antonio Florita 25 , Mara Cossa 12 , Barbara Valeri 12 , Massimo Milione 12 , Giancarlo Pruneri 12 , Odysseas Zoras 26 , Andrea Anichini 27 , Roberta Mortarini 27 , Mario Santinami 1
Affiliation  

PURPOSE Thin melanomas (T1; ≤ 1 mm) constitute 70% of newly diagnosed cutaneous melanomas. Regional node metastasis determined by sentinel node biopsy (SNB) is an important prognostic factor for T1 melanoma. However, current melanoma guidelines do not provide clear indications on when to perform SNB in T1 disease and stress an individualized approach to SNB that considers all clinicopathologic risk factors. We aimed to identify determinants of sentinel node (SN) status for incorporation into an externally validated nomogram to better select patients with T1 disease for SNB. PATIENTS AND METHODS The development cohort comprised 3,666 patients with T1 disease consecutively treated at the Istituto Nazionale Tumori (Milan, Italy) between 2001 and 2018; 4,227 patients with T1 disease treated at 13 other European centers over the same period formed the validation cohort. A random forest procedure was applied to the development data set to select characteristics associated with SN status for inclusion in a multiple binary logistic model from which a nomogram was elaborated. Decision curve analyses assessed the clinical utility of the nomogram. RESULTS Of patients in the development cohort, 1,635 underwent SNB; 108 patients (6.6%) were SN positive. By univariable analysis, age, growth phase, Breslow thickness, ulceration, mitotic rate, regression, and lymphovascular invasion were significantly associated with SN status. The random forest procedure selected 6 variables (not growth phase) for inclusion in the logistic model and nomogram. The nomogram proved well calibrated and had good discriminative ability in both cohorts. Decision curve analyses revealed the superior net benefit of the nomogram compared with each individual variable included in it as well as with variables suggested by current guidelines. CONCLUSION We propose the nomogram as a decision aid in all patients with T1 melanoma being considered for SNB.

中文翻译:


影响薄 (T1) 皮肤黑色素瘤前哨淋巴结转移的因素:预测列线图的开发和外部验证



目的 薄黑色素瘤(T1;≤ 1 毫米)占新诊断皮肤黑色素瘤的 70%。前哨淋巴结活检(SNB)确定的区域淋巴结转移是T1黑色素瘤的重要预后因素。然而,目前的黑色素瘤指南并未明确说明何时对 T1 期疾病进行 SNB,并强调采用考虑所有临床病理危险因素的个体化 SNB 方法。我们的目的是确定前哨淋巴结 (SN) 状态的决定因素,并将其纳入外部验证的列线图,以更好地选择 T1 疾病患者进行 SNB。患者和方法 开发队列由 2001 年至 2018 年间在国家肿瘤研究所(意大利米兰)连续接受治疗的 3,666 名 T1 期患者组成;同期在其他 13 个欧洲中心接受治疗的 4,227 名 T1 疾病患者组成了验证队列。将随机森林程序应用于开发数据集,以选择与 SN 状态相关的特征,以包含在多重二元逻辑模型中,并从中详细阐述列线图。决策曲线分析评估了列线图的临床效用。结果 在开发队列中,1,635 名患者接受了 SNB; 108 名患者(6.6%)SN 阳性。通过单变量分析,年龄、生长期、Breslow 厚度、溃疡、有丝分裂率、消退和淋巴管侵犯与 SN 状态显着相关。随机森林程序选择了 6 个变量(非生长阶段)包含在逻辑模型和列线图中。事实证明,列线图经过了良好的校准,并且在两个队列中都具有良好的区分能力。 决策曲线分析显示,与其中包含的每个单独变量以及当前指南建议的变量相比,列线图具有卓越的净效益。结论 我们建议列线图作为所有考虑接受 SNB 的 T1 黑色素瘤患者的决策辅助工具。
更新日期:2020-05-10
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