Novel Prognostic Models Predicting the Cancer-Specific Survival in Patients with Cutaneous Melanoma Based on Metastatic Lymph Node Status.

Abstract

In cutaneous melanoma (CM), the present methods of lymph node (LN) staging have not sufficiently utilized the prognostic information of metastatic LNs. In this study, we aimed to construct prognostic nomograms based on the number of positive LNs (PLNs) and other clinicopathologic characteristics of CM patients. Two prognostic models were constructed in the none/single PLN (PLNnone/single) and multiple PLN (PLNmultiple) cohorts, respectively. Independent prognostic predictors associated with cancer-specific survival (CSS) in the above two cohorts were integrated to construct two nomograms for predicting the probability of 2-, 4-, and 6-year CSS in the PLNnone/single and PLNmultiple cohorts. The nomograms were evaluated by the area under the receiver operating characteristic curves (AUC), the calibration plots, and the decision curve analyses (DCAs). A total of 31,065 CM cases were included in this study. Factors included in the prognostic nomogram for patients in the PLNnone/single cohort were age, sex, race, marital status, insurance, primary tumor site, T stage, and number of PLNs, while factors included in the nomogram for cases in the PLNmultiple cohort included age, sex, marital status, insurance, primary tumor site, T stage, and number of PLNs. The AUC values for 2-, 4-, and 6-year CSS in the validation group of the PLNnone/single cohort were 0.833, 0.811, and 0.818, respectively, while in the validation group of the PLNmultiple cohort, the AUC values for 2-, 4,- and 6-year CSS were 0.720, 0.723, and 0.745, respectively. Compared with the American Joint Committee on Cancer 7th edition staging system, our two nomograms showed better predictive values. Additionally, the calibration plots and DCA curves for 2-, 4-, and 6-year CSS prediction demonstrated good coordination and net benefit in both the PLNnone/single and PLNmultiple cohorts. Our nomograms, based on the number of PLNs and other clinicopathologic characteristics, showed good predictive ability for predicting the survival of CM patients.