Weiling Lian1,2,3,4,5, Cheng Liu1,2,3,4,5, Bingxin Gu1,2,3,4,5, Jianping Zhang1,2,3,4,5, Linjun Lu1,2,3,4,5, Herong Pan1,2,3,4,5, Zhifeng Yao1,2,3,4,5, Mingwei Wang1,2,3,4,5, Shaoli Song1,2,3,4,5, Yingjian Zhang1,2,3,4,5, Zhongyi Yang1,2,3,4,5. 1. Department of Nuclear Medicine, Fudan University Shanghai Cancer Center. 2. Department of Oncology, Shanghai Medical College, Fudan University. 3. Center for Biomedical Imaging, Fudan University. 4. Shanghai Engineering Research Center for Molecular Imaging Probes. 5. Key Laboratory of Nuclear Physics and Ion-beam Application (MOE), Fudan University, Shanghai, China.
Abstract
OBJECTIVE: To compare the predictive value of European Organization for Research and Treatment of Cancer (EORTC) criteria and PET Response Criteria in Solid Tumors (PERCIST), for the pathological response and prognosis of patients with breast cancer receiving neoadjuvant chemotherapy (NAC). METHODS: Consecutive PET/computed tomography scans in 128 operable female patients at baseline and after two courses of NAC were performed. Patients were categorized by complete metabolic response (CMR) and non-CMR groups using 2 PET criteria. CMR and non-CMR were used to predict pathological complete response (pCR) by diagnostic test evaluation, and to predict progression-free survival (PFS) using Kaplan-Meier plots and Cox proportional hazards regression. RESULTS: Ninety-two patients were finally analyzed. The sensitivity, specificity, and accuracy for pCR prediction were 69.7, 76.3, and 73.9% with EORTC criteria, and 69.7, 77.9, and 75.0% with PERCIST, respectively. Peak standardized uptake value normalized to lean body mass (SULpeak), maximum standardized uptake value (SUVmax), total lesion glycolysis (TLG), and metabolic tumor volume (MTV) were pCR response with accuracy of 70.7, 60.0, 75.0, and 71.4%, respectively. CMR by the EORTC (P = 0.021) and PERCIST (P = 0.007) was significantly related to a longer PFS. The univariate and multivariate analysis suggested that CMR by PERCIST was an independent predictor of recurrence (P = 0.008). CONCLUSION: EORTC criteria and PERCIST had early predictive value to long-term outcome, but moderate value for pCR. Furthermore, PERCIST might show more potential than the EORTC criteria and conventional PET-based parameters to predict prognosis in breast cancer patients following two cycles of neoadjuvant chemotherapy.Video abstract: see http://links.lww.com/NMC/A162.
OBJECTIVE: To compare the predictive value of European Organization for Research and Treatment of Cancer (EORTC) criteria and PET Response Criteria in Solid Tumors (PERCIST), for the pathological response and prognosis of patients with breast cancer receiving neoadjuvant chemotherapy (NAC). METHODS: Consecutive PET/computed tomography scans in 128 operable female patients at baseline and after two courses of NAC were performed. Patients were categorized by complete metabolic response (CMR) and non-CMR groups using 2 PET criteria. CMR and non-CMR were used to predict pathological complete response (pCR) by diagnostic test evaluation, and to predict progression-free survival (PFS) using Kaplan-Meier plots and Cox proportional hazards regression. RESULTS: Ninety-two patients were finally analyzed. The sensitivity, specificity, and accuracy for pCR prediction were 69.7, 76.3, and 73.9% with EORTC criteria, and 69.7, 77.9, and 75.0% with PERCIST, respectively. Peak standardized uptake value normalized to lean body mass (SULpeak), maximum standardized uptake value (SUVmax), total lesion glycolysis (TLG), and metabolic tumor volume (MTV) were pCR response with accuracy of 70.7, 60.0, 75.0, and 71.4%, respectively. CMR by the EORTC (P = 0.021) and PERCIST (P = 0.007) was significantly related to a longer PFS. The univariate and multivariate analysis suggested that CMR by PERCIST was an independent predictor of recurrence (P = 0.008). CONCLUSION: EORTC criteria and PERCIST had early predictive value to long-term outcome, but moderate value for pCR. Furthermore, PERCIST might show more potential than the EORTC criteria and conventional PET-based parameters to predict prognosis in breast cancerpatients following two cycles of neoadjuvant chemotherapy.Video abstract: see http://links.lww.com/NMC/A162.