HER2-positive breast cancer: ¹⁸F-FDG PET for early prediction of response to trastuzumab plus taxane-based neoadjuvant chemotherapy
- PMID: 24647576
- DOI: 10.1007/s00259-014-2739-1
HER2-positive breast cancer: ¹⁸F-FDG PET for early prediction of response to trastuzumab plus taxane-based neoadjuvant chemotherapy
Abstract
Purpose: To investigate the value of (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET/CT) to predict a pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in women with human epidermal growth factor receptor 2 (HER2)-positive breast cancer.
Material and methods: Fifty-seven consecutive women with HER2-positive breast cancer, treated with trastuzumab plus taxane-based NAC, were prospectively included. Maximum Standardized Uptake Value of the primary tumor and axillary nodes were measured at baseline (PET₁.SUVmax) and after the first course of NAC (PET₂.SUVmax). Tumor metabolic volumes were assessed to determine Total Lesion Glycolysis (TLG). The tumor metabolic response (ΔSUVmax and ΔTLG) was calculated.
Results: In univariate analysis, negative hormonal receptor status (p = 0.04), high tumor grade (p = 0.03), and low tumor PET₂.SUVmax (p = 0.001) were predictive of pCR. Tumor ΔSUVmax correlated with pCR (p = 0.03), provided that tumors with low metabolic activity at baseline were excluded. ΔTLG did not correlate with pCR. In multivariate analysis, tumor PET₂.SUVmax < 2.1 was the best independent predictive factor (Odds ratio =14.3; p = 0.004) with both negative and positive predictive values of 76 %. Although the metabolic features of the primary tumor did not depend on hormonal receptor status, both the baseline metabolism and early response of axillary nodes were higher if estrogen receptors were not expressed (p = 0.01 and p = 0.03, respectively).
Conclusion: In HER2-positive breast cancer, very low tumor residual metabolism after the first cycle of NAC (SUVmax < 2.1) was the main predictor of pCR. These results should be further explored in multicenter studies and incorporated into the design of clinical trials.
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