Abstract
Background18-Fluorodeoxyglucose-PET (18F-FDG-PET) can be used for early response assessment in patients with locally advanced adenocarcinomas of the oesophagogastric junction (AEG) undergoing neoadjuvant chemotherapy. It has been recently shown in the MUNICON trials that response-guided treatment algorithms based on early changes of the FDG tumor uptake detected by PET are feasible and that they can be implemented into clinical practice.Only 40%-50% of the patients respond metabolically to therapy. As metabolic non-response is known to be associated with a dismal prognosis, metabolic non-responders are increasingly treated with alternative neoadjuvant chemotherapies or chemoradiation in order to improve their clinical outcome. We plan to investigate whether PET can be used as response assessment during radiochemotherapy given as salvage treatment in early metabolic non-responders to standard chemotherapy.Methods/DesignThe HICON trial is a prospective, non-randomized, explorative imaging study evaluating the value of PET as a predictor of histopathological response in metabolic non-responders. Patients with resectable AEG type I and II according to Siewerts classification, staged cT3/4 and/or cN+ and cM0 by endoscopic ultrasound, spiral CT or MRI and FDG-PET are eligible. Tumors must be potentially R0 resectable and must have a sufficient FDG-baseline uptake. Only metabolic non-responders, showing a < 35% decrease of SUV two weeks after the start of neoadjuvant chemotherapy are eligible for the study and are taken to intensified taxane-based RCT (chemoradiotherapy (45 Gy) before surgery. 18FDG-PET scans will be performed before ( = Baseline) and after 14 days of standard neoadjuvant therapy as well as after the first cycle of salvage docetaxel/cisplatin chemotherapy (PET 1) and at the end of radiochemotherapy (PET2). Tracer uptake will be assessed semiquantitatively using standardized uptake values (SUV). The percentage difference ΔSUV = 100 (SUVBaseline - SUV PET1)/SUVBaseline will be calculated and assessed as an early predictor of histopathological response. In a secondary analysis, the association between the difference SUVPET1 - SUVPET2 and histopathological response will be evaluated.DiscussionThe aim of this study is to investigate the potential of sequential 18FDG-PET in predicting histopathological response in AEG tumors to salvage neoadjuvant radiochemotherapy in patients who do not show metabolic response to standard neoadjuvant chemotherapy.Trial RegistrationClinical trial identifier NCT01271322
Highlights
Oesophageal cancer is among the 10 most common malignancies worldwide and is associated with a high mortality [1,2]
The aim of this study is to investigate the potential of sequential 18FDG-PET in predicting histopathological response in adenocarcinomas of the oesophagogastric junction (AEG) tumors to salvage neoadjuvant radiochemotherapy in patients who do not show metabolic response to standard neoadjuvant chemotherapy
In cases of locally advanced tumors (T3/T4, N+), surgery remains the mainstay of therapy, but evidence is growing that preoperative chemotherapy or chemoradiotherapy improves survival in responding patients with locally advanced adenocarcinoma of the oesophagus and the oesophagogastric junction [3,4]
Summary
Oesophageal cancer is among the 10 most common malignancies worldwide and is associated with a high mortality [1,2]. For patients who do not respond, the prognosis after neoadjuvant therapy might be worse than that of a primarily surgical approach [5]. These metabolic non-responders have a low histopathological response rate of only 5% and a poor prognosis compared with responders [6]. Since about half of the patients treated with neoadjuvant chemotherapy will not respond [7], an early predictor of response would avoid futile therapy and allow patients to pursue other, potentially more efficacious treatments. Over the past few years, many attempts have been made to improve prognostication of the individual tumor biology in oesophageal carcinoma and to identify prognostic and predictive biomarkers
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