Effect of tumor subtype on survival and the graded prognostic assessment for patients with breast cancer and brain metastases
- PMID: 21497451
- PMCID: PMC3172400
- DOI: 10.1016/j.ijrobp.2011.02.027
Effect of tumor subtype on survival and the graded prognostic assessment for patients with breast cancer and brain metastases
Abstract
Purpose: The diagnosis-specific Graded Prognostic Assessment (GPA) was published to clarify prognosis for patients with brain metastases. This study refines the existing Breast-GPA by analyzing a larger cohort and tumor subtype.
Methods and materials: A multi-institutional retrospective database of 400 breast cancer patients treated for newly diagnosed brain metastases was generated. Prognostic factors significant for survival were analyzed by multivariate Cox regression and recursive partitioning analysis (RPA). Factors were weighted by the magnitude of their regression coefficients to define the GPA index.
Results: Significant prognostic factors by multivariate Cox regression and RPA were Karnofsky performance status (KPS), HER2, ER/PR status, and the interaction between ER/PR and HER2. RPA showed age was significant for patients with KPS 60 to 80. The median survival time (MST) overall was 13.8 months, and for GPA scores of 0 to 1.0, 1.5 to 2.0, 2.5 to 3.0, and 3.5 to 4.0 were 3.4 (n = 23), 7.7 (n = 104), 15.1 (n = 140), and 25.3 (n = 133) months, respectively (p < 0.0001). Among HER2-negative patients, being ER/PR positive improved MST from 6.4 to 9.7 months, whereas in HER2-positive patients, being ER/PR positive improved MST from 17.9 to 20.7 months. The log-rank statistic (predictive power) was 110 for the Breast-GPA vs. 55 for tumor subtype.
Conclusions: The Breast-GPA documents wide variation in prognosis and shows clear separation between subgroups of patients with breast cancer and brain metastases. This tool will aid clinical decision making and stratification in clinical trials. These data confirm the effect of tumor subtype on survival and show the Breast-GPA offers significantly more predictive power than the tumor subtype alone.
Copyright © 2012 Elsevier Inc. All rights reserved.
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