ArticleCancer medicine2023
Development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor.
Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Development and validation of a new nomogram for self-reported OA based on machine learning: a cross-sectional study.Scientific reports · 2025Article
- Development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor.Cancer medicine · 2023Article
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Authors and funding
3 authors.
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Abstract
backgroundMalignant myofibroblastic tumors are a rare group of soft tissue sarcomas, for which a prognosis prediction model is lacking. Based on the Surveillance, Epidemiology, and End Results (SEER) database and cases from Nanjing Drum Tower Hospital, the current study constructed and validated a nomogram to assess overall survival of patients with malignant myofibroblastic tumors.
methodsData of patients with myofibroblastic tumors diagnosed between 2000 and 2018 were extracted from the SEER database. Similarly, data of patients with myofibroblastic tumor in Nanjing Drum Tower Hospital between May 2016 and March 2022 were collected. Then, we conducted univariate and multivariate Cox analyses to identify independent prognostic parameters to develop the nomogram. The model was evaluated by concordance index (C-index), calibration curve, the area under the curve (AUC), decision curve analysis (DCA), Kaplan-Meier analysis, and subgroup analyses.
resultsSeven variables were selected to construct the nomogram. The results of the C-index (0.783), calibration curve, the AUCs, and subgroup analyses demonstrated the accurate predictive capacity and excellent discriminative ability of the nomogram. The DCA of the model indicated its better clinical net benefit than that of the traditional system.
conclusionEvaluation of the predictive performance of the nomogram revealed the superior sensitivity and specificity of the model and the higher prediction accuracy of the outcomes compared with those of the traditional system. The established nomogram may assist patients in consultation and help physicians in clinical decision-making.
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