Combination of Molecular Biomarkers and Functional Imaging in Predicting Pathologic Response and Clinical Outcomes in Squamous Esophageal Cancer Patients Who Undergo Trimodality Therapy
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 200
- 试验地点
- 1
- 主要终点
- Pathologic Response
研究概览
简要总结
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
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 70 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patient must have histologic documentation of squamous carcinoma of the esophagus at Xijing Hospital.
- •Newly diagnosed Patients with localized carcinoma of the esophagus who have undergone standard testing and been evaluated by the multidisciplinary team at Xijing Hospital and are considered appropriate candidates for and are willing to undergo chemoradiotherapy followed by surgery at Xijing Hospital.
- •Patient must have undergone a baseline esophageal-gastroduodenoscopy (EGD) with biopsy and endoscopic ultrasonography at Xijing, with tissue available for biomarker analysis.
- •Patient must be willing to undergo this research and must provide written informed consent.
排除标准
- •Patient is unable or unwilling to comply with the requirements of the protocol.
- •History of prior malignancy within the past 3 years.
- •Patients with second primary tumors.
- •Patients who received endoscopical therapy or induction chemotherapy prior to chemoradiation therapy are excluded.
- •Patient is not a candidate for chemoradiation followed by surgery.
结局指标
主要结局
Pathologic Response
时间窗: Approximately 12 months
Mandard tumor regression grade (TRG) was used for pathology analysis. Primary tumor and positive lymph node regression were classified into five histologic tumor regression grades. Grade 1 (complete regression) showed absence of histologically identifiable residual cancer and fibrosis extending through the different layers of the esophageal wall, with or without granuloma. Grade 2 was characterized by the presence of rare residual cancer cells scattered through the fibrosis. Grade 3 involved an increase in the number of residual cancer cells, but fibrosis still predominated. Grade 4 showed residual cancer outgrowing fibrosis. Grade 5 was characterized by the absence of regressive changes.
次要结局
- Overall Survival(Approximately 4 years)
研究者
Mei Shi
Professor
Air Force Military Medical University, China