Factors Affecting Sentinel Node Metastasis in Thin (T1) Cutaneous Melanomas: Development and External Validation of a Predictive Nomogram

• Published in: Journal of clinical oncology Vol. 38; no. 14; pp. 1591 - 1601
• Main Authors: Maurichi, Andrea, Miceli, Rosalba, Eriksson, Hanna, Newton-Bishop, Julia, Nsengimana, Jérémie, Chan, May, Hayes, Andrew J, Heelan, Kara, Adams, David, Patuzzo, Roberto, Barretta, Francesco, Gallino, Gianfranco, Harwood, Catherine, Bergamaschi, Daniele, Bennett, Dorothy, Lasithiotakis, Konstantinos, Ghiorzo, Paola, Dalmasso, Bruna, Manganoni, Ausilia, Consoli, Francesca, Mattavelli, Ilaria, Barbieri, Consuelo, Leva, Andrea, Cortinovis, Umberto, Espeli, Vittoria, Mangas, Cristina, Quaglino, Pietro, Ribero, Simone, Broganelli, Paolo, Pellacani, Giovanni, Longo, Caterina, Del Forno, Corrado, Borgognoni, Lorenzo, Sestini, Serena, Pimpinelli, Nicola, Fortunato, Sara, Chiarugi, Alessandra, Nardini, Paolo, Morittu, Elena, Florita, Antonio, Cossa, Mara, Valeri, Barbara, Milione, Massimo, Pruneri, Giancarlo, Zoras, Odysseas, Anichini, Andrea, Mortarini, Roberta, Santinami, Mario
• Format: Journal Article
• Language: English
• Published: United States American Society of Clinical Oncology 10.05.2020
• Subjects: Medicin och hälsovetenskap; Original Reports
• ISSN: 0732-183X; 1527-7755; 1527-7755
• DOI: 10.1200/JCO.19.01902

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. 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. 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. We propose the nomogram as a decision aid in all patients with T1 melanoma being considered for SNB.