Journal of investigative surgery : the official journal of the Academy of Surgical Research · 2024
Establishment and Validation of Prognostic Nomograms for Nonmetastatic Melanoma of the Limbs-A SEER-Based Study.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Shi Yutong, Mo Ran, Chen Yutong, Ma Zhouji, Wen Bo, Tan Qian
Аннотация
BACKGROUND: Malignant melanoma, a highly aggressive skin cancer, has remarkable incidence and mortality nowadays. This study aims to explore prognostic factors associated with nonmetastatic cutaneous melanoma of the limbs and to develop nomograms for predicting overall survival (OS) and cancer-specific survival (CSS).
METHODS: The study cohort was derived from the Surveillance, Epidemiology, and End Results database. Univariate Cox regression, Lasso regression, and multivariate Cox regression analyses were conducted to identify prognostic factors and construct nomograms. The receiver operating characteristic (ROC) curve, time-dependent C-index, calibration curve, decision curve analysis (DCA) and Kaplan-Meier method were used to evaluate the accuracy and clinical applicability of the nomograms.
RESULTS: A total of 15,606 patients were enrolled. Multivariate analysis identified several prognostic factors for OS and CSS including age, sex, histologic type, N stage, tumor thickness, depth of invasion, mitotic rate, ulceration, surgery of primary site, systemic therapy, race, and number of lymph nodes examined. A nomogram incorporating 12 independent predictors for OS was developed, with a C-index of 0.866 (95% confidence interval [CI]: 0.858-0.874) in the training cohort and 0.853 (95% CI: 0.839-0.867) in validation. For CSS, 10 independent predictors and one related factor were included, yielding a C-index of 0.913 (95% CI: 0.903-0.923) in the training cohort and 0.922 (95% CI: 0.908-0.936) in validation. The ROC curve, time-dependent C-index, calibration curve, DCA, and K-M plot demonstrated favorable discrimination, calibration, and clinical utility.
CONCLUSION: The developed nomograms provide a precise and personalized predictive tool for risk management of patients with nonmetastatic limb melanoma.
METHODS: The study cohort was derived from the Surveillance, Epidemiology, and End Results database. Univariate Cox regression, Lasso regression, and multivariate Cox regression analyses were conducted to identify prognostic factors and construct nomograms. The receiver operating characteristic (ROC) curve, time-dependent C-index, calibration curve, decision curve analysis (DCA) and Kaplan-Meier method were used to evaluate the accuracy and clinical applicability of the nomograms.
RESULTS: A total of 15,606 patients were enrolled. Multivariate analysis identified several prognostic factors for OS and CSS including age, sex, histologic type, N stage, tumor thickness, depth of invasion, mitotic rate, ulceration, surgery of primary site, systemic therapy, race, and number of lymph nodes examined. A nomogram incorporating 12 independent predictors for OS was developed, with a C-index of 0.866 (95% confidence interval [CI]: 0.858-0.874) in the training cohort and 0.853 (95% CI: 0.839-0.867) in validation. For CSS, 10 independent predictors and one related factor were included, yielding a C-index of 0.913 (95% CI: 0.903-0.923) in the training cohort and 0.922 (95% CI: 0.908-0.936) in validation. The ROC curve, time-dependent C-index, calibration curve, DCA, and K-M plot demonstrated favorable discrimination, calibration, and clinical utility.
CONCLUSION: The developed nomograms provide a precise and personalized predictive tool for risk management of patients with nonmetastatic limb melanoma.