View clinical trials related to Colorectal Cancer.
Filter by:Colorectal neoplastic lesion endoscopic characterization is a key element for histological predictive diagnostic value in conducting best appropriate resection choice. Six classifications are necessary for fully correct characterization of different colorectal lesions. Nonetheless, it can be tricky to use so many diagnostic tools with so many subcategories in the 6 existing classifications. That's why we decided to integrate all 6 existing classification validated factors in one single chart (CONECCT chart) allowing to both predict histological diagnostic value and to propose the best appropriate resection strategy. A previous prospective and multicentre study with all French medical residents in gastroenterology was conducted in order to prove pedagogic interest of this diagnostic tool. Each student was asked to review 20 files with lesion pictures before and after lecture about CONECCT chart. This allowed us to prove that this diagnostic tool could significantly improve both histological predictive diagnostic value and therapeutic choice by French medical residents and gastroenterologists. Our hypothesis is that CONECCT's classification can improve predictive diagnostic value of colorectal lesions in over 80% of cases. Now that pedagogic interest of this diagnostic tool has been proven, we would like to carry out a larger prospective assessment in term of performance (value) of this instrument in order to both facilitate endoscopic characterization and allow a most appropriate diagnostic and therapeutic management of each colorectal lesion category.
The standard way of screening for colorectal cancer is to have a series of fecal blood tests, where a sample is taken from a participant's stool, or an endoscopic procedure performed by a doctor, where a camera is used to look inside the bowel. This research study will use a test performed by the participant. This test will look for changes in the stool that can identify if participants are at higher risk for cancer. Another aim of this study is to better understand what firefighters and retired firefighters think about colorectal cancer and other health issues. This information will help us develop programs that may improve colorectal cancer outcomes in the firefighter community.
This study assesses the sensitivity and added benefits of computer-aided detection compared to standard care (white-light) in detecting colon polyps in patients undergoing colonoscopy.
Design: Prospective, randomized controlled trial Setting: Clinical Oncology and Nuclear Medicine, Ain Shams University Condition: Colorectal cancer Patients will be randomized into one of two groups: Group A: Patients will receive standard therapy FOLFOX PROTOCOL Group B: Patients will receive metformin (500 mg twice daily or 1000 mg once daily) on top of standard therapy Assessment: Baseline Assessment: - Patient Full History: Age, sex, smoking history, occupational history, medical history, concurrent diseases and medications. - Laboratory data: - Complete blood test - Liver functional test - Renal function test - Inflammatory Markers: Interleukin (IL)-6 EVERY 3 MONTH: CT/MRI /PET scan to detect the response to chemotherapy and progression , Quality of life by European Organization for Research and Treatment of Cancer Quality-of-life Questionnaire Core 30. (EORTC QLQC30), Assessment of chemotherapy toxicity using CTACE 4.0 . Every 2 CYCLE: Lab examination (CBC, Liver function, Kidney function),CTACE SIDE EFFECTS EXAMINATION AFTER 6 MONTH : iL-6 LEVELS AFTER 1 YEAR : PFS AND OS
To investigate and analyze the status of preoperative frailty and its influencing factors in elderly patients with colorectal cancer using FRALL scale and other related scales, and to explore the correlation between preoperative frailty and early prognosis in elderly patients with colorectal cancer, so as to attract the attention of medical staff to preoperative frailty in this population and provide a preliminary research basis for the study of frailty intervention in these patients.
Exploration of a novel rbcDNA liquid biopsy technique for early detection of colorectal cancer is a promising development in the field of disease diagnosis and screening. This technique has the potential to establish an efficient and sensitive system for the early detection of colorectal cancer, which can provide a new perspective for individual health monitoring.
Colorectal cancer is the 4th most common cancer in the world among all cancer types. Chemotherapy-induced peripheral neuropathy is a common and serious side effect caused by chemotherapeutic agents, especially platinum analogues, taxanes, vinca alkaloids and bortezomib. The most commonly used chemotherapeutic agents in the treatment of colorectal cancers are platinum analogues It is known that oxaliplatin, one of the platinum analogues, causes 85-96% of chemotherapy-induced peripheral neuropathy. The most common symptoms of chemotherapy-induced peripheral neuropathy are; numbness, paresthesia, dysesthesia, pain, hypersensitivity to cold or heat, tingling, muscle cramps, distal weakness, gait disturbances, balance disorders, and impaired movement. Oxaliplatin, which is frequently used in the treatment of colorectal cancer, causes symptoms of both acute and chronic chemotherapy-induced peripheral neuropathy. There is no proven method in the treatment of chemotherapy-induced peripheral neuropathy. However, various pharmacological and non-pharmacological approaches are applied in its preventive and symptomatic treatment. Exercise and physical therapy interventions; It is stated that it improves strength, balance and other functional disorders in patients, reduces symptoms, and reduces the risk of falling by affecting gross motor dysfunctions such as balance and gait abnormalities. However, the limitations of studies on this subject in the literature draw attention. This situation suggests that new methods that can be applied in the care of cancer patients who develop peripheral neuropathy due to chemotherapy should be developed in the field of nursing. This research is the first study to evaluate the effect of hand-foot exercises on colorectal cancer patients who developed peripheral neuropathy due to platinum-based therapy. Research results; Alleviation of KBPN-induced pain and prevention of falls are important in terms of increasing the quality of life of patients and providing evidence for nursing practices by using it as a new method that can be applied in the care of cancer patients with chemotherapy-induced peripheral neuropathy. The aim of this research was to determine the effect of hand-foot exercises on the severity of pain, falls and quality of life associated with platinum-based therapy-related peripheral neuropathy in patients with colorectal cancer.
CCIS is a novel score, created specifically to evaluate the completeness of caecal visualized. It can be applied to a single or multiple images. To create the CCIS, the caecum was divided into eight parts: the appendiceal orifice (AO), the tri-radiate fold part 1 (TF-1), 2 (TF-2), 3 (TF-3) and four outer quadrants (OQ 1-4). The ileo-caecal valve (ICV) is a reference point but is not part of the score. The quadrant adjacent to the ICV is labelled OQ1. The three other quadrants are labelled clockwise from this quadrant. The tri-radiate folds are also labelled clockwise with TF1 representing the triangle side that is majority-contained within OQ1. TF2 and TF3 are then labelled clockwise from TF1.
The study explored the effects of short-term structured psychological care on the level of postoperative psychological resilience, stigma, anxiety and depression in patients with colorectal cancer colostomy.
Background: To assist clinicians with diagnosis and optimal treatment decision-making, we attempted to develop and validate an artificial intelligence prediction model for lung metastasis (LM) in colorectal cancer (CRC) patients. Method: The clinicopathological characteristics of 46037 CRC patients from the Surveillance, Epidemiology, and End Results (SEER) database and 2779 CRC patients from a multi-center external validation set were collected retrospectively. After feature selection by univariate and multivariate analyses, six machine learning (ML) models, including logistic regression, K-nearest neighbor, support vector machine, decision tree, random forest, and balanced random forest (BRF), were developed and validated for the LM prediction. The optimization model with best performance was compared to the clinical predictor. In addition, stratified LM patients by risk score were utilized for survival analysis.