Active clinical trials for "Neoplasms"

Volatile organic compounds (VOCs) are low molecular weight (<1 kDa) compounds which represent the final products of cell metabolism. Their composition can be affected by several factors including diet, hormones, environment and the presence of diseases, in particular, cancer. Colorectal cancer (CRC) is one of the commonest tumours and is an important cause of cancer-related mortality. The expression of VOCs in breath that are linked to a patient's disease state could offers a powerful, non-invasive approach to identifying CRC patients.

This is a prospective, single-center, clinical study.This study is to evaluate the feasibility of genetic susceptibility screening based on the detection of tumor tissue mutations by a NGS panel.

Analyze the dynamics of incorporation of 5-fluorouracil into cancer cell ribosomes from liver metastases of patient with metastatic colon cancer.

This study evaluates the Dynamic Spectral Imaging (DSI) Colposcope (DySIS) in it's ability to diagnose cervical dysplasia. Half of participants with be examined by the DySIS colposcope, there the other half will be examined by standard colposcopy.

Incidence of digestive neuroendocrine tumors are increasing. Analysis of individual microbiota is a way to explore new neoplastic mechanisms, tumor identification and therapeutic orientations. This prospective pilot study aims to describe fecal bacterial phylogeny of patients with digestive neuroendocrine tumor. Bacterial genomic signature will be recorded at initiation of Lanreotide treatment in naive patient with digestive neuroendocrine tumor (pancreas or small intestine), metastatic or locally advanced, as well as after one year follow up.

Colorectal cancer is one of the most common cancer in Hong Kong. In 2018, CRC accounted for 17.4%, 5,780 cases, of the total new cancers. CRC claimed 2,279 lives (15.8%) making it the second most deadly killer in the population. Since 2010, the Cancer Expert Working Group (CEWG) has recommended that asymptomatic average-risk individuals aged 50 to 75 years should consider one of the screening methods: fecal occult blood test (FOBT) every one to two years; OR flexible sigmoidoscopy every 5 years; OR colonoscopy every 10 years. However, it poses great challenges for large scale CRC screening using colonoscopy, such as bowel preparation difficulties, complications of procedure and poor compliance. ColoClear® is intended for use as an adjunctive screening test for the detection of colorectal neoplasia associated DNA markers and for the presence of occult hemoglobin in human stool. It has the potential of increasing the sensitivity of detecting CRC as compared to FOBT or faecal immunochemical test (FIT), which detects the presence of hemoglobin in stool alone. A positive result may indicate the presence of colorectal cancer or pre-malignant colorectal neoplasia. ColoClear® is not intended as a replacement for diagnostic colonoscopy. A positive result in ColoClear®, as with any screening test, should be followed by colonoscopy. ColoClear® is intended for colorectal cancer screening in average risk individuals: adults of either sex, 40 years or older, who are at high risk for colorectal cancer.

Due to the inconclusive results on the benefits of 3D laparoscopic system present in literature, this prospective randomised pilot study aims to assess if the operative time of total laparoscopic hysterectomy (TLH) for benign indication performed by trainees could be reduced using 3D laparoscopy instead of standard laparoscopy.

It is now felt that the majority of ovarian cancers originate in the fallopian tubes. Opportunistic salpingectomy has been found to decrease ovarian cancer risk by approximately 65%, with additional removal of the ovaries decreasing risk up to 98%. Using data collected under IRB #21841 and a population based statistics model we found that performing opportunistic salpingectomy during non-gynecologic abdominal surgery could decrease the incidence of ovarian cancer by 28-38%.

This study will collect retrospective CT scan images and clinical data from participants with incidental lung nodules seen in hospitals across London. The investigators will research whether machine learning can be used to predict which participants will develop lung cancer, to improve early diagnosis.

In this study, investigators utilize a radiomics prediction model to predict the tumor response to neoadjuvant chemoradiotherapy (nCRT) before the nCRT is administered for patients with locally advanced rectal cancer (LARC). Previously, the radiomics prediction model has been constructed based on the radiomics features extracted from pretreatment Magnetic Resonance Imaging (MRI) in the training set, and optimized in the external validation set. The predictive power of this radiomics prediction model to discriminate the pathologic complete response (pCR) patients from non-pCR individuals, will be further verified in this prospective, multicenter clinical study.