ABSTRACT
Objective:To identify prognosis factors and construct a nomogram for the prediction of cancer-specific survival in surgically resected pediatric melanoma.Methods:A total of 912 patients aged 0-19 years were extracted from the Surveillance, Epidemiology, and SEER database and randomly divided into training cohort (n=640) and validation cohort (n=272) (A ratio of 70:30) . Univariable and multivariable cox analysis were used to determine prognostic factors, and these factors were used to construct a nomogram for predicting cancer-specific survival in patients with resected pediatric melanoma. Model performance was evaluated by Harrell’s concordance index (C-index) ,the area under the time-dependent receiver operating characteristic curve (AUC) and calibration plots.Results:As revealed by the multivariable cox analysis, age, tumor location, ulceration, and lymph node status were all associated with melanoma-specific survival in pediatric patients. On the basis of these factors, a nomogram was constructed. Both the training cohort and the validation cohort had a concordance index of 0.9, which validated the accuracy of our nomogram. The nomogram showed significant discriminative power in both training cohort (3-year AUC: 0.87, 5-year AUC: 0.88, 10-year AUC: 0.85) and validation cohort (3-year AUC: 0.87, 5-year AUC: 0.87, 10-year AUC: 0.89) . Also, the nomogram displayed a good calibration.Conclusions:These results suggest that the new model has superior predictive performance in predicting cancer-specific survival of pediatric melanoma. This individualized prediction model can provide reference for tailoring treatment and clinical counseling of pediatric melanoma.
ABSTRACT
Objective:To identify prognosis factors in patients with resected Merkel cell carcinoma and construct a nomogram for predicting 3- and 5-year overall survival.Methods:A total of 1271 patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. According to the ratio of 70:30, patients were randomly divided into training cohort ( n=891) and validation cohort ( n=380) . Cox regression model was fitted with R software, thus the prognostic factors for 3- and 5-year overall survival were confirmed and a nomogram to predict overall survival was established. C-index was used to evaluate model discrimination and the calibration plot was used to evaluate model accuracy.The predictive power of the model was compared with the eighth TNM staging system. Results:Multivariable cox analysis indicated age, sex, tumor size, N stage, M stage, marital status and radiation therapy were associated with overall survival. The above predictors were employed to build a new nomogram, and we found that the new predictive model was better at predicting 3- and 5- year overall survival than the latest TNM staging system. The C-index of the training cohort using the new model for survival prediction was 0.72, and the C-index of the training cohort using TNM staging system was only 0.64. The C-index of the validation cohort using the new model for survival prediction was 0.73, while the C-index of the validation cohort using TNM staging system was 0.63. The nomogram also displayed a good calibration.Conclusions:The new predictive model with comprehensive prognostic factors is superior to the 8th TNM staging system in predicting overall survival of patients with Merkel cell carcinoma. This new model can help doctors to predict the prognosis of each patient more accurately, and assist clinical decision-making and individualized treatment.