Application of nomograms to predict overall and cancer-specific survival in patients with chordoma

• Published in: Journal of bone oncology 2019-10, Vol.18, p.100247, Article 100247
• Main Authors: Zheng, Weipeng, Huang, Yuanping, Guan, Tianwang, Lu, Songfang, Yao, Liquan, Wu, Senrui, Chen, Haoyi, Wang, Ning, Liang, YingJie, Xiao, Wende, Jiang, Xin, Wen, Shifeng
• Format: Article
• Language: English
• Subjects: Cancer-specific survival; Chordoma; Nomogram; Overall survival; SEER database
• ISSN: 2212-1374; 2212-1366; 2212-1374
• DOI: 10.1016/j.jbo.2019.100247

•Age of diagnosis, primary site, histology, tumor stage, use of surgery and tumor size were identified as independent prognostic factors for both overall and cancer-specific survival of chordoma patients.•The optimal age cutoff values of chordoma patients were 38, 54 and 66 years.•The optimal cutoff values of chordoma tumor size were identified as 2.9 and 10.0 cm.•The nomogram constructed in present study can serve as an effective and convenient evaluation tool to help surgeons to perform personalized survival evaluation and mortality risk identification in chordoma patients. The survival prediction of patients with chordoma is difficult to make due to the rarity of this oncologic disease. Our objective was to apply a nomogram to predict survival outcomes in individuals with chordoma of the skull base, vertebral column, and pelvis. A total of 558 patients with chordoma between 1973 and 2014 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors in patients with chordoma were identified via univariate and multivariate Cox analysis. Then these prognostic factors were incorporated into a nomogram to predict 3- and 5-year overall survival and cancer-specific survival rates. Internal and external data were used to validate the nomograms. Concordance indices (C-indices) were used to estimate the accuracy of this nomogram system. A total of 558 patients were randomly assigned into a training cohort (n = 372) and a validation cohort (n = 186). Age, surgical stage, tumor size, histology, primary site, and use of surgery were identified as independent prognostic factors via univariate and multivariate Cox analysis (all p