Recursive partitioning analysis (RPA) classification predicts survival in patients with brain metastases from sarcoma

Rachel Grossman*, Zvi Ram

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review


Objective Sarcoma rarely metastasizes to the brain, and there are no specific treatment guidelines for these tumors. The recursive partitioning analysis (RPA) classification is a well-established prognostic scale used in many malignancies.

Methods We retrospectively analyzed the medical, radiological, surgical, pathological, and follow-up clinical records of 21 patients who were operated for metastatic sarcoma to the brain between 1996 and 2012. Gliosarcomas, sarcomas of the head and neck with local extension into the brain, and metastatic sarcomas to the spine were excluded from this reported series.

Results The patients' mean age was 49.6 ± 14.2 years (range, 25-75 years) at the time of diagnosis. Sixteen patients had a known history of systemic sarcoma, mostly in the extremities, and had previously received systemic chemotherapy and radiation therapy for their primary tumor. The mean maximal tumor diameter in the brain was 4.9 ± 1.7 cm (range 1.7-7.2 cm). The group's median preoperative Karnofsky Performance Scale was 80, with 14 patients presenting with Karnofsky Performance Scale of 70 or greater. The median overall survival was 7 months (range 0.2-204 months). The median survival time stratified by the Radiation Therapy Oncology Group RPA classes were 31, 7, and 2 months for RPA class I, II, and III, respectively (P = 0.0001).

Conclusions This analysis is the first to support the prognostic utility of the Radiation Therapy Oncology Group RPA classification for sarcoma brain metastases and may be used as a treatment guideline tool in this rare disease.

Original languageEnglish
Pages (from-to)1291-1294
Number of pages4
JournalWorld Neurosurgery
Issue number6
StatePublished - 1 Dec 2014


  • Brain metastases
  • Recursive partitioning analysis (RPA)
  • Sarcoma
  • Surgery


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