To aid in therapy selection for patients with spinal bone metastases (SBM), predictive models have been developed. These models consider SBM from breast cancer a positive predictive factor, but do not take phenotypes based on estrogen (ER), progesterone (PR) and human epidermal growth factor 2 (HER2) receptors into account. The aim of this study was to ascertain whether receptors are associated with survival, when the disease has progressed up to SBM. All patients who were treated for SBM from breast cancer between 2005 and 2012 were included in this international multi-center retrospective study (n = 111). Reports were reviewed for ER, PR and HER2 status and subsequently subdivided into one of four categories; luminal A, luminal B, HER2 and triple negative. Survival time was calculated as the difference between start of treatment for SBM and date of death. Analysis was performed using the Kaplan–Meier method and log-rank tests. Median follow-up was 3.7 years. Survival times in the luminal B and HER2 categories were not significantly different to the luminal A category and were joined into a single receptor positive category. Eighty-five patients (77 %) had a receptor positive phenotype and 25 (23 %) had a triple negative phenotype. Median survival time was 22.5 months (95 %CI 18.0–26.9) for the receptor positive category and 6.7 months (95 %CI 2.4–10.9) for the triple negative category (p < 0.001). Patients with SBM from breast cancer with a triple negative phenotype have a shorter survival time than patients with a receptor positive phenotype. Models estimating survival should be adjusted accordingly.
Spinal bone metastases Survival Breast cancer Molecular phenotype Receptor status
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The authors would like to thank V.T.H.B.M. Smit for his advice on pathology, breast cancer and molecular phenotypes.
Conflict of interest
The authors report no conflicts of interest and have no funding sources to disclose.
Bollen L, de Ruiter GCW, Pondaag W et al (2013) Risk factors for survival of 106 surgically treated patients with symptomatic spinal epidural metastases. Eur Spine J 22(6):1408–1416PubMedCentralPubMedCrossRefGoogle Scholar
Wibmer C, Leithner A, Hofmann G et al (2011) Survival analysis of 254 patients after manifestation of spinal metastases: evaluation of seven preoperative scoring systems. Spine 36(23):1977–1986PubMedCrossRefGoogle Scholar
Wang M, Bünger CE, Li H et al (2012) Predictive value of Tokuhashi scoring systems in spinal metastases, focusing on various primary tumor groups: evaluation of 448 patients in the Aarhus spinal metastases database. Spine 37(7):573–582PubMedCrossRefGoogle Scholar
Tomita K, Kawahara N, Kobayashi T, Yoshida A, Murakami H, Akamaru T (2001) Surgical strategy for spinal metastases. Spine 26(3):298–306PubMedCrossRefGoogle Scholar
Tokuhashi Y, Matsuzaki H, Oda H, Oshima M, Ryu J (2005) A revised scoring system for preoperative evaluation of metastatic spine tumor prognosis. Spine 30(19):2186–2191PubMedCrossRefGoogle Scholar
Linden Y, Dijkstra S, Vonk E, Marijnen C, Leer J (2005) Prediction of survival in patients with metastases in the spinal column: results based on a randomized trial of radiotherapy. Cancer 103(2):320–328PubMedCrossRefGoogle Scholar
Bauer HC, Wedin R (1995) Survival after surgery for spinal and extremity metastases. Prognostication in 241 patients. Acta Orthop Scand 66(2):143–146PubMedCrossRefGoogle Scholar
Bollen L, van der Linden YM, Pondaag W et al (2014) Prognostic factors associated with survival in patients with symptomatic spinal bone metastases: a retrospective cohort study of 1043 patients. Neuro-oncology (Epub ahead of print)Google Scholar
Sørlie T, Perou CM, Tibshirani R et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98(19):10869–10874PubMedCentralPubMedCrossRefGoogle Scholar
Dawood S, Hu R, Homes M et al (2011) Defining breast cancer prognosis based on molecular phenotypes: results from a large cohort study. Breast Cancer Res 126(1):185–192CrossRefGoogle Scholar
Vallejos C, Gómez H, Cruz W et al (2010) Breast cancer classification according to immunohistochemistry markers: subtypes and association with clinicopathologic variables in a Peruvian hospital database. Clin Breast Cancer 10(4):294–300PubMedCrossRefGoogle Scholar
Schemper M, Smith TL (1996) A note on quantifying follow-up in studies of failure time. Control Clin Trials 17(4):343–346PubMedCrossRefGoogle Scholar
Harrell FE Jr, Lee KL, Mark DB (1996) Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 15(4):361–387PubMedCrossRefGoogle Scholar
Carey LA, Perou CM, Livasy CA et al (2006) Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 295(21):2492–2502PubMedCrossRefGoogle Scholar
Fan C, Oh DS, Wessels L et al (2006) Concordance among gene-expression-based predictors for breast cancer. N Engl J Med 355(6):560–569PubMedCrossRefGoogle Scholar
Sciubba DM, Gokaslan ZL, Suk I et al (2007) Positive and negative prognostic variables for patients undergoing spine surgery for metastatic breast disease. Eur Spine J 16(10):1659–1667PubMedCentralPubMedCrossRefGoogle Scholar
Rades D, Douglas S, Schild SE (2013) A validated survival score for breast cancer patients with metastatic spinal cord compression. Strahlenther Onkol 189(1):41–46PubMedCrossRefGoogle Scholar