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Clinical Trial Summary

The purpose of this study is to determine whether combination of molecular and biomarkers with functional imaging can predict pathologic response and clinical outcomes in squamous esophageal cancer patients who undergo trimodality therapy which includes neoadjuvant chemoradiotherapy and surgery


Clinical Trial Description

The recommended care for the management of locally advanced esophageal cancers is neoadjuvant chemoradiotherapy (nCRT) followed by esophagectomy based on the NCCN guideline. The rate of pathologic complete response (pCR) after nCRT was around 25-30%, reflecting potential cure of unresectable esophageal cancer receiving CRT. Since esophagectomy might have substantial morbidity and mortality rate, establishing the model for predicting nCRT response and survival will guide neoadjuvant treatment decisions and personalized treatment. Thus surgery might be spared in some patients with complete responses after nCRT, and surgery could be selectively reserved for those with only partial or no response to CRT. However, reported models yield unsatisfactory results due to small sample size and low accuracy, and most cases were adenocarcinoma and few models were used to predict survival. This study will prospectively collect the tissue and blood samples of locally advanced esophageal cancer patients, detect CRT resistance biomarkers, assess the SUV value and texture parameters of 18F-FDG PET-CT as well as ADC values DWI-MRI. The investigators will use advanced statistical tools to establish the model and further validate the model in another group of patients.The investigators will also establish a model for survival prediction. This model might possibly guide the personalized treatment for esophageal squamous cell carcinoma patients in China. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT03029793
Study type Observational
Source Fourth Military Medical University
Contact Li-Na Zhao, MD, Ph.D
Phone +86-29-84775425
Email zhaolinazln@outlook.com
Status Recruiting
Phase N/A
Start date May 2016
Completion date January 2020

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