Novel Nomograms as Aids for Predicting Recurrence and Survival in Chordoma Patients A Retrospective Multicenter Study in mainland China

摘要

Study Design. A retrospective data analysis was performed. Objective. The aim of this study is to explore the significant prognostic factors and propose new nomograms to facilitate clinical decision-making. Summary of Background Data. Chordoma is a rare bone tumor. The clinical features and optimal therapeutic strategies are still uncertain. Methods. Chordoma patients treated in four medical centers of mainland China before January 2015 were included. The predictors for local relapse-free survival (LRFS) and overall survival (OS) were identified by the Lasso regression and Cox proportional hazards regression model. Then the nomograms were developed. Their discrimination, calibration, and accuracy were evaluated by the C-index, calibration curve, and receiver operating characteristic curve (ROC), respectively. Results. A total of 341 patients were identified and full prognostic variable data were available for 276 patients. A total of 179 patients (64.9%) experienced recurrence and 122 patients (44.2%) died of all causes with a median follow-up time of 57.5 (range, 1-325) months. We identified recurrence-relevant factors of tumor size, tumor location, histology subtype and resection method, and death-relevant factors of tumor size, tumor location, resection method, complication, and postoperative recurrence. The constructed LRFS and OS nomograms showed good calibration and discriminative ability (C index 0.79 and 0.76, respectively). The ROCs suggested decent prediction ability with the 5-year area under curve (AUC) value of 0.868 and 0.786, respectively. Conclusion. Based on the multicenter case series of chordoma with a relative long follow-up, we proposed two nomograms to predict the prognosis on the basis of recurrence- and death-relevant factors. These findings could be referenced in the clinical decision-making process and provide additional prognostic information for risk stratification.