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The Prognostic Role of Pretreatment 18F-FDG (PET/CT) Maximum Standardized Uptake Value in Multiple or Oligometastatic Breast Cancer Patients

Abstract

Hala A El-Lathy, Ahlam A Dohal, Yasser Alassiri, Yasser Al Malki and Ehab Ibrahim

Purpose: To determine the prognostic role of pretreatment F-18FDG PET/CT maximum standardized uptake value (SUVmax) in metastatic breast cancer (MBC) patients and its correlation with clinicopathological parameters.
Materials and Methods: The pretreatment 18FDG-PET-CT SUVmax in MBC patients was compared with clinicopathological parameters. The prognostic value of pretreatment SUVmax for progression free survival (PFS) and overall survival (OS) were assessed using log rank test and cox regression analysis.
Results: Overall, 100 patients (77%) had evidence of visceral metastases while 30 patients (23%) had oligometastatic disease confined to bones only. The receiver operator curve (ROC) demonstrated that SUVmax of 4.4 and 7.7 to be the cutoff value for predicting PFS in patients with oligometastasis to bones and multiple metastatic disease respectively. Patients with bone oligometastasis SUVmax of >4.4 had a significantly shorter OS [Hazard ratio (HR 3.2)] <4.4 (P<0.0001),whereas patients with SUV max of ≤4.4 had significantly longer PFS compared with those with SUVmax >4.4 (P<0.001). Consequently, multiple metastatic patients with SUVmax ≤ 7.7 had significant improvement in OS compared to those with SUV max >7.7.On Cox regression analysis, the SUVmax category was the only factor correlated with both PFS (HR=4.5, 95% C I 3-6.8, P<0. 0001) and OS (HR=3.2, 95% C I 2.2-4.9, P<0. 0001) in patients with multiple metastasis.
Conclusions: The pretreatment 18FDG-PET-CT SUVmax showed a statistically significant association with different clinicopathological prognostic factors. In addition, it may be considered as a potential independent prognostic indicator of clinical outcomes in metastatic breast cancer.

Keywords

18FDG PET/CT SUVmax; Metastatic breast cancer

Haftungsausschluss: Dieser Abstract wurde mit Hilfe von Künstlicher Intelligenz übersetzt und wurde noch nicht überprüft oder verifiziert

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