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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and Validation of a Prognostic Nomogram for Postoperative Recurrence-Free Survival of Ameloblastoma
Yao-Cheng Yang1,2, Jun-Jie Wang3,4, Yun Huang1,2
1Department of Oral and Maxillofacial Surgery, Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, 510055, People's Republic of China.
Purpose:
Ameloblastoma is a benign odontogenic neoplasm with a high local recurrence rate if the operation is not thorough. However, a useful clinical tool for the quantitative assessment of the prognosis and risk of postoperative recurrence of ameloblastoma has not yet been constructed. This study aims to develop a prognostic nomogram model for ameloblastoma of the jaw to assist surgeons in surgical decision-making.
Patients And Methods:
Patients who underwent initial surgery for ameloblastoma in our department from October 2004 to March 2020 were enrolled and randomly divided into training and validation sets. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify the independent prognostic factors, from which a nomogram for predicting 3-, 5- and 10-year recurrence-free survival (RFS) of ameloblastoma was constructed using the training set and internally validated using the validation set. The model performance was assessed by Harrell's concordance index (C-index) and calibration curves.
Results:
A total of 302 eligible patients with ameloblastoma were enrolled, 54 of whom were confirmed to relapse during the follow-up period of 6 to 191 months. Four independent predictors, including cortical bone perforation, root(s) resorption, WHO classification, and treatment pattern, were identified and included in the construction of a nomogram for recurrence-free survival (RFS), which showed promising calibration performance and discrimination in the training set (C-index 0.790, 95% confidence interval [CI] 0.735-0.845) and the validation set (C-index 0.734, 95% CI 0.599-0.869).
Conclusion:
A favorable nomogram was developed that accurately predicted the RFS of patients with ameloblastoma based on individual characteristics. Risk stratification using the nomogram could optimize tailored therapy and follow-up.
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