A Risk Classifier Model that Predicts Tumor Progression in Cranial Base Chondrosarcoma Patients. (16th November 2020)

• Record Type: Journal Article
• Authors: Venteicher, Andrew S; McDowell, Michael M; Goldschmidt, Ezequiel; Wang, Eric; Snyderman, Carl H; Gardner, Paul A
• Is Part Of: Neurosurgery. Volume 67(2010)Supplement 1
• Publication Date: 2020-11-16
• Subjects: Nervous system -- Surgery -- Periodicals; 617.48005
• DOI: 10.1093/neuros/nyaa447_888
• Languages: English
• ISSNs: 0148-396X

Abstract

Abstract: INTRODUCTION: Cranial base chondrosarcomas are challenging tumors to treat surgically due to their frequent involvement of critical neurovascular structures. Furthermore, patients with cranial base chondrosarcomas are characterized by a variable clinical course with few predictors that aid in management decisions. METHODS: A retrospective study at a tertiary care Cranial Base Center was performed. Sequential patients between 2004 and 2018 and their longitudinal followup was included. Univariate and multivariate models were generated to find factors that can predict progression-free survival (PFS). RESULTS: A total of 43 patients with chondrosarcoma were in the cohort. Of these, 41 patients had histologically proven "conventional" cranial base chondrosarcoma. The median progression-free survival (PFS) was 123 months. Both univariate and multivariate analysis was performed on clinical, anatomic, and radiographic parameters. Two independent predictors of PFS were discovered: patient age and encasement of 3 or more major arteries. Using these two predictors, a risk stratification model was generated that can be used to predict PFS in cranial base chondrosarcoma patients. Based on these two factors known preoperatively, we could stratify patients into high risk (10% of patients), intermediate risk (68% of patients), and low risk (22% of patients) subgroups corresponding to dramatically distinct median PFS (1.8 years, 10.2 years, and no progression, respectively). CONCLUSION: In patients with cranial base chondrosarcoma, age and artery encasement can powerfully predict tumor progression. Since these are known preoperatively, this model can define operative goals as well as assist in post-operative adjuvant therapy selection.