title: CyberKnife radiosurgery for brainstem metastases: Management and outcomes and a review of the literature.
abstract: To our knowledge this paper is the first to use recursive partitioning analysis (RPA) for brainstem metastasis (BSM) patient outcomes, after CyberKnife radiosurgery (CKRS; Accuray, Sunnyvale, CA, USA); nine similar previous publications used mainly Gamma Knife radiosurgery (Elekta AB, Stockholm, Sweden). Retrospective chart reviews from 2006-2013 of 949 CKRS-treated brain metastasis patients showed 54 BSM patients (5.7%): 35 RPA Class II (65%) and 19 Class III (35%). There were 30 women (56%) and 24 men (44%). The median age was 59 years (range 36-80) and median follow-up was 5 months (range 1-52). Twenty-three patients (43%) had lung carcinoma BSM and 12 (22%) had breast cancer BSM. Fifty-four RPA Class II and III BSM patients had a median overall survival (OS) of 5 months, and for each Class 8 and 2 months, respectively. Of 36 RPA Class II and III patients with available symptoms (n=31) and findings (n=33), improvement/stability occurred in the majority for symptoms (86%) and findings (92%). Of 35 cases, 28 (80%) achieved BSM local control (LC); 13/14 with breast histology (93%) and 10/13 with lung histology (77%). All six RPA Class II and III patients with controlled extracranial systemic disease (ESD) experienced LC. Median tumor volume was 0.14 cm(3); of 34 RPA Class II and III cases, 26 LC patients had a 0,13 cm(3) median tumor volume while it was 0.27 cm(3) in the eight local failures. Of 35 cases, single session equivalent dosages less than the median (n=13), at the 17.9 Gy median (n=5) and greater than the median (n=17) had BSM LC in 10 (77%), four (80%) and 14 cases (82%), respectively. Univariate analysis showed Karnofsky Performance Score, RPA Class and ESD-control predicted OS. CKRS is useful for RPA Class II and III BSM patients with effective clinical and local BSM control.
authors.affiliation: Department of Neurosurgery, Stanford University School of Medicine, 300 Pasteur Drive, R225, Stanford, CA 94305-5327, USA.
authors.forename: Szu-Hao
authors.initials: SH
authors.lastname: Liu
authors.affiliation: Department of Neurosurgery, Stanford University School of Medicine, 300 Pasteur Drive, R225, Stanford, CA 94305-5327, USA.
authors.forename: Judith
authors.initials: J
authors.lastname: Murovic
authors.affiliation: Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, CA 94305-5327, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Wallach
authors.affiliation: Department of Neurosurgery, Stanford University School of Medicine, 300 Pasteur Drive, R225, Stanford, CA 94305-5327, USA.
authors.forename: Guosheng
authors.initials: G
authors.lastname: Cui
authors.affiliation: Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, CA 94305-5327, USA.
authors.forename: Scott G
authors.initials: SG
authors.lastname: Soltys
authors.affiliation: Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, CA 94305-5327, USA.
authors.forename: Iris C
authors.initials: IC
authors.lastname: Gibbs
authors.affiliation: Department of Neurosurgery, Stanford University School of Medicine, 300 Pasteur Drive, R225, Stanford, CA 94305-5327, USA. Electronic address: sdchang@stanford.edu.
authors.forename: Steven D
authors.initials: SD
authors.lastname: Chang
mesh_terms: D000328:Adult; D000368:Aged; D020295:Brain Stem Neoplasms / Q000401:mortality / Q000556:secondary* / Q000601:surgery*; D001943:Breast Neoplasms / Q000401:mortality / Q000556:secondary / Q000601:surgery; D019468:Disease Management; D005260:Female; D006801:Humans; D017567:Karnofsky Performance Status; D008175:Lung Neoplasms / Q000401:mortality / Q000556:secondary / Q000601:surgery; D008297:Male; D008875:Middle Aged; D016634:Radiosurgery / Q000379:methods*; D012189:Retrospective Studies; D016019:Survival Analysis
keywords: Brainstem metastases; CyberKnife radiosurgery; Overall survival; Recursive partitioning analysis