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Prediction of Non-sentinel Node Status in Patients with Melanoma and Positive Sentinel Node Biopsy: An Italian Melanoma Intergroup (IMI) Study

  • Autori: Rossi, Carlo Riccardo; Mocellin, Simone; Campana, Luca Giovanni; Borgognoni, Lorenzo; Sestini, Serena; Giudice, Giuseppe; Caracò, Corrado; Cordova, Adriana; Solari, Nicola; Piazzalunga, Dario; Carcoforo, Paolo; Quaglino, Pietro; Caliendo, Virginia; Ribero, Simone
  • Anno di pubblicazione: 2018
  • Tipologia: Articolo in rivista (Articolo in rivista)
  • OA Link: http://hdl.handle.net/10447/298931

Abstract

Background and Purpose: Approximately 20% of melanoma patients harbor metastases in non-sentinel nodes (NSNs) after a positive sentinel node biopsy (SNB), and recent evidence questions the therapeutic benefit of completion lymph node dissection (CLND). We built a nomogram for prediction of NSN status in melanoma patients with positive SNB. Methods: Data on anthropometric and clinicopathological features of patients with cutaneous melanoma who underwent CLND after a positive SNB were collected from nine Italian centers. Multivariate logistic regression was utilized to identify predictors of NSN status in a training set, while model efficiency was validated in a validation set. Results: Data were available for 1220 patients treated from 2000 through 2016. In the training set (n = 810), the risk of NSN involvement was higher when (1) the primary melanoma is thicker or (2) sited in the trunk/head and neck; (3) fewer nodes are excised and (4) more nodes are involved; and (5) the lymph node metastasis is larger or (6) is deeply located. The model showed high discrimination (area under the receiver operating characteristic curve 0.74, 95% confidence interval [CI] 0.70–0.79) and calibration (Brier score 0.16, 95% CI 0.15–0.17) performance in the validation set (n = 410). The nomogram including these six clinicopathological variables performed significantly better than five other previously published models in terms of both discrimination and calibration. Conclusions: Our nomogram could be useful for follow-up personalization in clinical practice, and for patient risk stratification while conducting clinical trials or analyzing their results.