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

Maurichi, A; Miceli, R; Eriksson, H; Newton-Bishop, J; Nsengimana, J; Chan, M; Hayes, AJ; Heelan, K; Adams, D; Patuzzo, R; et al. Maurichi, A; Miceli, R; Eriksson, H; Newton-Bishop, J; Nsengimana, J; Chan, M; Hayes, AJ; Heelan, K; Adams, D; Patuzzo, R; Barretta, F; Gallino, G; Harwood, C; Bergamaschi, D; Bennett, D; Lasithiotakis, K; Ghiorzo, P; Dalmasso, B; Manganoni, A; Consoli, F; Mattavelli, I; Barbieri, C; Leva, A; Cortinovis, U; Espeli, V; Mangas, C; Quaglino, P; Ribero, S; Broganelli, P; Pellacani, G; Longo, C; Del Forno, C; Borgognoni, L; Sestini, S; Pimpinelli, N; Fortunato, S; Chiarugi, A; Nardini, P; Morittu, E; Florita, A; Cossa, M; Valeri, B; Milione, M; Pruneri, G; Zoras, O; Anichini, A; Mortarini, R; Santinami, M (2020) Factors Affecting Sentinel Node Metastasis in Thin (T1) Cutaneous Melanomas: Development and External Validation of a Predictive Nomogram. Journal of Clinical Oncology, 38 (14). pp. 1591-1601. ISSN 0732-183X https://doi.org/10.1200/jco.19.01902
SGUL Authors: Bennett, Dorothy Catherine

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Abstract

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.

Item Type: Article
Additional Information: © 2020 by American Society of Clinical Oncology
Keywords: 1112 Oncology and Carcinogenesis, Oncology & Carcinogenesis
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: Journal of Clinical Oncology
ISSN: 0732-183X
Language: en
Dates:
DateEvent
10 May 2020Published
13 March 2020Published Online
1 January 2020Accepted
Publisher License: Publisher's own licence
Projects:
Project IDFunderFunder ID
C588/A19167Cancer Research UKhttp://dx.doi.org/10.13039/501100000289
C8216/A6129Cancer Research UKhttp://dx.doi.org/10.13039/501100000289
C588/A10721Cancer Research UKhttp://dx.doi.org/10.13039/501100000289
CA83115National Institutes of Healthhttp://dx.doi.org/10.13039/100000002
URI: http://openaccess.sgul.ac.uk/id/eprint/111809
Publisher's version: https://doi.org/10.1200/jco.19.01902

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