A practical nomogram and risk stratification system predicting the cancer-specific survival for patients aged >50 with advanced melanoma - Xi, Qiufen; Lu, Xiaoou; Zhang, Jiali; Wang, Da; Sun, Yu; Chen, Hongquan (Frontiers in Oncology, 2023)
Objective: To investigate risk factors for advanced melanoma over 50 years of age and to develop and validate a new line chart and classification system. Methods: The seer database was screened for patients diagnosed with advanced melanoma from 2010 to 2019 and COX regression analysis was applied to select variables affecting patient prognosis. The area under curve (AUC), relative operating characteristic curve (ROC), Consistency index (C-index), decision curve analysis (DCA), and survival calibration curves were used to verify the accuracy and utility of the model and to compare it with conventional AJCC tumour staging. The Kaplan-Meier curve was applied to compare the risk stratification between the model and traditional AJCC tumour staging. Results: A total of 5166 patients were included in the study. Surgery， age, gender, tumor thickness, ulceration, the number of primary melanomas, M stage and N stage were the independent prognostic factors of CSS in patients with advanced melanoma (P<0.05). The predictive nomogram model was constructed and validated. The C-index values obtained from the training and validation cohorts were 0.732 (95%CI: 0.717-0.742) and 0.741 (95%CI: 0.732-0.751). Based on the observation and analysis results of the ROC curve, survival calibration curve, NRI, and IDI, the constructed prognosis model can accurately predict the prognosis of advanced melanoma and performs well in internal verification. The DCA curve verifies the practicability of the model. Compared with the traditional AJCC staging, the risk stratification in the model has a better identification ability for patients in different risk groups. Conclusion: The nomogram of advanced melanoma and the new classification system were successfully established and verified, which can provide a practical tool for individualised clinical management of patients.