title: Effect of tumor subtype on survival and the graded prognostic assessment for patients with breast cancer and brain metastases.
abstract: OBJECTIVE
  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
  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.
authors.affiliation: University of Minnesota Gamma Knife, Minneapolis Radiation Oncology, Minneapolis, MN, USA. psperduto@mropa.com
authors.forename: Paul W
authors.initials: PW
authors.lastname: Sperduto
authors.forename: Norbert
authors.initials: N
authors.lastname: Kased
authors.forename: David
authors.initials: D
authors.lastname: Roberge
authors.forename: Zhiyuan
authors.initials: Z
authors.lastname: Xu
authors.forename: Ryan
authors.initials: R
authors.lastname: Shanley
authors.forename: Xianghua
authors.initials: X
authors.lastname: Luo
authors.forename: Penny K
authors.initials: PK
authors.lastname: Sneed
authors.forename: Samuel T
authors.initials: ST
authors.lastname: Chao
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Weil
authors.forename: John
authors.initials: J
authors.lastname: Suh
authors.forename: Amit
authors.initials: A
authors.lastname: Bhatt
authors.forename: Ashley W
authors.initials: AW
authors.lastname: Jensen
authors.forename: Paul D
authors.initials: PD
authors.lastname: Brown
authors.forename: Helen A
authors.initials: HA
authors.lastname: Shih
authors.forename: John
authors.initials: J
authors.lastname: Kirkpatrick
authors.forename: Laurie E
authors.initials: LE
authors.lastname: Gaspar
authors.forename: John B
authors.initials: JB
authors.lastname: Fiveash
authors.forename: Veronica
authors.initials: V
authors.lastname: Chiang
authors.forename: Jonathan P S
authors.initials: JP
authors.lastname: Knisely
authors.forename: Christina Maria
authors.initials: CM
authors.lastname: Sperduto
authors.forename: Nancy
authors.initials: N
authors.lastname: Lin
authors.forename: Minesh
authors.initials: M
authors.lastname: Mehta
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001932:Brain Neoplasms / Q000401:mortality* / Q000473:pathology / Q000556:secondary*; D001943:Breast Neoplasms / Q000378:metabolism / Q000401:mortality* / Q000473:pathology*; D018567:Breast Neoplasms, Male / Q000378:metabolism / Q000401:mortality / Q000473:pathology; D015331:Cohort Studies; D005260:Female; D006801:Humans; D017567:Karnofsky Performance Status; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011379:Prognosis; D016016:Proportional Hazards Models; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism; D011960:Receptors, Estrogen / Q000378:metabolism; D011980:Receptors, Progesterone / Q000378:metabolism; D012189:Retrospective Studies
chemical_list: D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone