• Andrea Maurichi, Rosalba Miceli, Hanna Eriksson, Julia Newton-Bishop, Jérémie Nsengimana, May Chan, Andrew J Hayes, Kara Heelan, David Adams, Roberto Patuzzo, Francesco Barretta, Gianfranco Gallino, Catherine Harwood, Daniele Bergamaschi, Dorothy Bennett, Konstantinos Lasithiotakis, Paola Ghiorzo, Bruna Dalmasso, Ausilia Manganoni, Francesca Consoli, Ilaria Mattavelli, Consuelo Barbieri, Andrea Leva, Umberto Cortinovis, Vittoria Espeli, Cristina Mangas, Pietro Quaglino, Simone Ribero, Paolo Broganelli, Giovanni Pellacani, Caterina Longo, Corrado Del Forno, Lorenzo Borgognoni, Serena Sestini, Nicola Pimpinelli, Sara Fortunato, Alessandra Chiarugi, Paolo Nardini, Elena Morittu, Antonio Florita, Mara Cossa, Barbara Valeri, Massimo Milione, Giancarlo Pruneri, Odysseas Zoras, Andrea Anichini, Roberta Mortarini, and Mario Santinami.
• Melanoma and Sarcoma Unit, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori di Milano, Milan, Italy.
• J. Clin. Oncol. 2020 May 10; 38 (14): 1591-1601.

PurposeThin 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 MethodsThe 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.ResultsOf 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.ConclusionWe propose the nomogram as a decision aid in all patients with T1 melanoma being considered for SNB.

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