View clinical trials related to Esophageal Neoplasm.
Filter by:Analyze the correlation between the conformity of the anatomy (based on endoscopic examination) and postoperative anastomotic fistula and anastomotic stenosis; establish an anastomotic classification; and construct a predictive model combined with perioperative-related test indicators to provide more accurate risk assessment for clinical practice. Analyze the natural recovery process of postoperative recurrent laryngeal nerve injury in esophageal cancer by tracking vocal cord movement (based on endoscopic examination) and hoarseness symptoms; combined with perioperative related surgical and laboratory indicators, identify the relevant risk factors associated with delayed recovery of recurrent laryngeal nerve injury.
The objective of this study is to prospectively document the efficacy and clinical outcomes of Endoscopic Submucosal Dissection procedure that utilize either a novel Bipolar-Current ESD device or the standard monopolar electrocautery knife.
The perioperative management of esophageal cancer has evolved considerably in recent years. Over the last 30 years, postoperative mortality has been steadily decreasing. However, respiratory morbidity remains high (30-40%). This is due to the procedure itself requiring a thoracic approach and intraoperative unipulmonary ventilation. The postoperative pulmonary complications (PPCs) are multiple: bronchial congestion, atelectasis, pneumopathy, acute respiratory distress syndrome (ARDS), liquid pleural effusion, pneumothorax. In general, prevention and early treatment are aimed at limiting the evolution towards acute respiratory failure requiring ventilatory assistance. Chest radiography is essential for the presumptive diagnosis of pneumopathy in particular, but the interpretation of the images may be difficult. Thoracic computed tomography (CT) is the gold standard because it is sensitive and can discriminate among differential diagnoses. This is difficult to perform: it requires intra-hospital transport of patient, who is often in acute respiratory failure, and the availability of an examination area. Lung ultrasound is used at the bedside for diagnosis of lung infection in intensive care unit. This has a sensitivity close to thoracic CT and has the advantage of being feasible at any time, does not require transport of the patient and is not irradiating. Lung ultrasound allows early detection of the need for ventilatory support in postoperative major abdominal surgery . In addition, the sensitivity of lung ultrasound is close to that of CT, allowing this examination to be relied upon. The main objective of the study is to determine the role of lung ultrasound in the prediction of postoperative pulmonary complications within one hour after extubation.
The incidence of cancer in France has increased by +135% to reach nearly 400,000 new cases in 2018. The ten-year cancer control strategy 2021-2030 and the health innovation plan have defined strategic axes. Almost all of these axes are addressed in our project. Firstly, the main objective of our study is to improve the quality of life of patients. Secondly, pharyngolaryngeal and oesophageal cancers are among the cancers with a poor prognosis in adults. Thirdly, the project provides access to personalised supportive care for all patients at all times. Finally, the secondary objectives of this study are the prevention of post-operative complications (infectious, thrombo-embolic, pain...).
This is an exploratory phase II clinical study designed to evaluate the safety and efficacy of Camrelizumab in combination with standard radiotherapy as preoperative neoadjuvant therapy for patients with resectable esophageal squamous cell carcinoma. In the study, all subjects who met the enrollment criteria are enrolled after giving full informed consent and signing the enrollment informed consent form, and received radical surgery within 4-8 weeks after completion of neoadjuvant Camrelizumab in combination with standard radiotherapy. The safety evaluation indicators for the study were so adverse events and the number and proportion of subjects who discontinued treatment due to adverse events. The main efficacy indicators of the study were the rate of major pathological remission and the rate of complete pathological remission. A total of 26 cases had to be enrolled in the study. Phase I enrollment was 12 cases, with at least 5 cases achieving efficacy to proceed to Phase II. The trial was considered successful when 14 cases were enrolled in the second phase and the total number of effective cases was greater than 13. The need for postoperative adjuvant treatment and the adjuvant treatment plan were determined by the investigator, and all subjects were required to complete the study's follow-up plan after surgery.
An Expanded Access Protocol for use of DKN-01 for the treatment of advanced solid tumors.
In esophageal carcinoma, neoadjuvant concurrent chemo-radiotherapy (NA-CCRT) followed by surgery is the current standard of care and ample evidence has accumulated supporting the view that complete pathological response (pCR) is a positive prognostic marker for improved outcomes. Predicting the probability of achieving pCR prior to neoadjuvant treatment could permit modification of treatment protocols for those patients unlikely to achieve pCR. Radiomics is a new entrant in the field of imaging where specific features are derived from the intensity and distribution pattern of pixels based on a region-of-interest (ROI). The features thus extracted can then be used for prediction modelling similar to other -omics datasets. Preliminary investigations examining its utility have been performed and its applications have thus far focused on screening and survival prediction after treatment. Due to the multi-dimensional nature of data extracted using radiomics, Artificial Intelligence (AI) methods are ideally suited for analysing and modelling radiomic features. Machine Learning (ML) and Deep Learning (DL)[utilising Convolutional Neural Networks (CNN)] are both part of the AI framework. In contrast to ML, DL is a new entrant and has been utilised by some medical researchers for modelling using prediction-type algorithms. Besides significantly reducing the workflow associated with Radiomics-based research, feature engineering and modelling using DL are immune to the effects of incorrect ROI delineation. However, the main limitation of DL is the 'blackbox' effect, in which the underlying basis of a CNN is not known. This has been mitigated in part by the visualisation of activation maps directly on the image dataset to prove biological plausibility of predictions. The comparative performance of both types of modelling is also not known. Our objective is to investigate pCR probability in our study population using radiomics-based ML and AI-based modelling. We will also investigate the comparative performance of both modelling techniques. For DL based prediction modelling, we will attempt to provide biological plausibility on the basis of activation maps.
The objective of this study is to evaluate the efficacy and safety of concurrent chemoradiotherapy combined with Itraconazole in patients with locally adcvanced esophageal squamous cancer
The Multi-OutcoMe EvaluatioN of radiation Therapy Using the Unity MR-Linac Study (MOMENTUM) is a multi-institutional, international registry facilitating evidenced based implementation of the Unity MR-Linac technology and further technical development of the MR-Linac system with the ultimate purpose to improve patients' survival, local, and regional tumor control and quality of life.
To prospectively collect blood and tumor tissue from esophageal cancer patients to identify specific esophageal cancer mutations that can be measured in the blood (cell free DNA) during the course of treatment as a marker of response and recurrence.