Prognostic nomograms for predicting long‐term overall survival in spindle cell melanoma: a population‐based study - Lau, Wai Chi; Huang, Liying; Zheng, Xinkai; Ming, Wai-kit; Leong, Nga Cheng; Tak Wong, Yu; Yin, Zhinan; Yu, Hai; Lyu, Jun; Deng, Liehua (Frontiers in Endocrinology, 2024)
Background There are few research findings on the survival prognosis of spindle cell melanoma (SCM), which is an unusual kind of melanoma. The purpose of this study was to develop a thorough nomogram for predicting the overall survival (OS) of patients with SCM and to assess its validity by comparing it with the conventional American Joint Committee on Cancer (AJCC) staging system. Methods The Surveillance, Epidemiology, and End Results database was searched, and 2,015 patients with SCM were selected for the analysis. The patients were randomly divided into training (n = 1,410) and validation (n = 605) cohorts by using R software. Multivariate Cox regression was performed to identify predictive factors. A nomogram was established based on these characteristics to predict OS in SCM. The calibration curve, concordance index (C-index), area under the receiver operating characteristic curve, and decision-curve analysis were utilized to assess the accuracy and reliability of the model. The net reclassification improvement and integrated discrimination improvement were also applied in this model to evaluate its differences with the AJCC model. Results The developed nomogram suggests that race, AJCC stage, chemotherapy status, regional node examination status, marital status, and sex have the greatest effects on OS in SCM. The nomogram had a higher C-index than the AJCC staging system (0.751 versus 0.633 in the training cohort and 0.747 versus 0.650 in the validation cohort). Calibration plots illustrated that the model was capable of being calibrated. These criteria demonstrated that the nomogram outperforms the AJCC staging system alone. Conclusion The nomogram developed in this study is sufficiently reliable for forecasting the risk and prognosis of SCM, which may facilitate personalized treatment recommendations in upcoming clinical trials.