A multi-institutional study evaluating predictors of gross-total resection in skull-base chondrosarcoma and testing machine-learning models for preoperative prediction.

Zuluaga-García, Rubino, Ramirez Ferrer, Zenonos, Gardner, Fernandez-Miranda, Raza and colleagues analyzed 185 skull-base chondrosarcomas treated at four centers. The overall gross-total resection rate was 56%.

Among petroclival tumors, the endoscopic transpterygoid approach achieved a higher gross-total resection rate than open approaches in this cohort. Carotid encasement, lateral extension and cranial nerve involvement were among the variables associated with incomplete resection. The predictive model achieved an area under the curve of approximately 0.84.

Why it matters

This paper combines approach selection, tumor anatomy and predictive modeling in one of the most challenging skull-base pathologies. It is particularly useful for preoperative counseling and for discussing when an endoscopic corridor may offer an anatomical advantage in petroclival chondrosarcoma. Because the study is observational, the approach-related differences should not be interpreted as proof of causal superiority.

Reference

Zuluaga-García JP, Rubino F, Ramirez Ferrer E, Zenonos GA, Gardner PA, Fernandez-Miranda JC, Raza SM, et al.
Predicting gross-total resection in skull base chondrosarcoma: a multi-institutional machine learning study.
Journal of Neurosurgery. 2026;145(4):1105–1116. Published online July 24, 2026.
DOI: 10.3171/2026.2.JNS252854
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