Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
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alsfakia@gmail.com

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Παρασκευή 16 Δεκεμβρίου 2016

Pretreatment metabolic parameters measured by 18F-FDG-PET to predict the outcome of first-line chemotherapy in extensive-stage small-cell lung cancer.

Pretreatment metabolic parameters measured by 18F-FDG-PET to predict the outcome of first-line chemotherapy in extensive-stage small-cell lung cancer.

Nucl Med Commun. 2016 Dec 13;

Authors: Yu X, Zhu Y, Wang J, Song X, Zhu L, Men X, Li X, Dai D, Xu W

Abstract
OBJECTIVE: Patients' pretreatment metabolic burden, as measured by radiotracer fluorine-18 fluorodeoxyglucose (F-FDG) PET/computed tomography (CT), has been shown to predict treatment outcome in various malignancies. However, its predictive role in extensive-stage small cell lung cancer (SCLC) has not been definitively determined. This retrospective study investigated the viability of using common pretreatment metabolic parameters, obtained through F-FDG-PET/CT, to predict outcomes of first-line chemotherapy in extensive-stage SCLC.
PARTICIPANTS AND METHODS: The study population comprised 154 consecutive patients with extensive-stage SCLC who underwent a pretreatment F-FDG-PET/CT scan and received standard first-line chemotherapy between January 2011 and December 2015.
RESULTS: Ten (6.5%) and 66 (42.9%) patients achieved a complete or a partial response, respectively (considered an objective response); 35 (22.7%) and 43 (27.9%) experienced stable or progressive disease. The metabolic tumor volume (MTV) was a significant factor for predicting an objective response. For predicting disease control (objective response or stable disease), MTV and total lesion glycolysis (TLG) were nonindependent factors.
CONCLUSION: Greater MTV and TLG could indicate a poorer response to first-line chemotherapy for patients with extensive-stage SCLC, but the predictive efficiency was not high enough for routine reliance. For patients who are not suitable to receive first-line chemotherapy, MTV and TLG may help guide clinical decisions.

PMID: 27977537 [PubMed - as supplied by publisher]



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