Free Article with CME: Postoperative Stereotactic Radiosurgery to the Resection Cavity for Large Brain Metastases

BACKGROUND: Postoperative stereotactic radiosurgery for brain metastases potentially offers similar local control rates and fewer long-term neurocognitive sequelae compared to whole brain radiation therapy, although patients remain at risk for distant brain failure (DBF).

OBJECTIVE: To describe clinical outcomes of adjuvant stereotactic radiosurgery for large brain metastases and identify predictors of intracranial failure and their implications on optimal patient selection criteria.

METHODS: We performed a retrospective review on 100 large (>3 cm) brain metastases in 99 patients managed by resection followed by postoperative stereotactic radiosurgery to a median dose of 22 Gy (range, 10-28) in 1 to 5 fractions (median, 3). Primary histology was nonsmall cell lung in 40%, breast cancer in 18%, and melanoma in 17%. Forty (40%) patients had uncontrolled systemic disease.

RESULTS: With a median follow-up of 12.2 months (range, 0.6-87.4), the 1-year Kaplan-Meier local control was 72%, DBF 64%, and overall survival 55%. Nine patients (9%) developed evidence of radiation injury, and 6 (6%) developed leptomeningeal disease. Uncontrolled systemic disease (P = .03), melanoma histology (P = .04), and increasing number of brain metastases (P < .001) were significant predictors of DBF on Cox multivariate analysis. Patients with <4 metastases, controlled systemic disease, and nonmelanoma primary (n = 47) had a 1-year DBF of 48.6% vs 80.1% for all others (P = .01).

CONCLUSION: Postoperative stereotactic radiosurgery to the resection cavity safely and effectively augments local control of large brain metastases. Patients with <4 metastases and controlled systemic disease have significantly lower rates of DBF and are ideal treatment candidates.

From: Postoperative Stereotactic Radiosurgery to the Resection Cavity for Large Brain Metastases: Clinical Outcomes, Predictors of Intracranial Failure, and Implications for Optimal Patient Selection by Ling et al.

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