The objectives of this study were to determine if the baseline SUVmax measured by 18F-FDG PET/CT correlates with molecular subtype and to explore the impact of baseline SUVmax on the survival of patients with metastatic breast cancer (MBC).
Patients with MBC were screened with PET/CT from February 2007 until December 2010. Multivariate linear regression analysis was performed to identify independent variable correlation with SUVmax. Prognostic variables identified by univariate analysis, with P < 0.1, were analyzed in the multivariate Cox model.
A total of 244 MBC patients were eligible for this study. Multivariate linear regression analysis showed that molecular subtype, visceral metastasis, and number of metastatic organs could be used to predict the logarithmic values of SUVmax (lgSUVmax) for previous untreated MBC patients, whereas for those with 1 or more line previous treatment, the number of metastatic organs was identified as the only independent variable correlating with lgSUVmax. Cox regression analysis indicated that only in patients with previously untreated MBC did baseline SUVmax (continuous variable) act as an independent prognostic factor (hazard ratio = 1.049 for progression-free survival, 1.124 for overall survival).
Baseline SUVmax correlates with molecular subtypes only in previously untreated MBC patients. PET/CT imaging can be used as a potential prognostic tool for patients with newly diagnosed MBC.
From the *Department of Medical Oncology, Fudan University Shanghai Cancer Center; †Department of Oncology, Shanghai Medical College, Fudan University; and ‡Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai, China; and §Faculty of Medicine, School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada.
Received for publication July 15, 2012; revision accepted November 14, 2012.
Conflicts of interest and sources of funding: none declared.
Reprints: Xi-Chun Hu, MD, or Ying-Jian Zhang, MD, Fudan University Shanghai Cancer Center, No. 270 Dong’an Rd, Shanghai 200032, China. E-mail: email@example.com; firstname.lastname@example.org.
Drs J. Zhang and Z. Jia contributed equally to this work.