View clinical trials related to Lung Cancer.
Filter by:In radiotherapy, tumour tracking allows us to ensure the radiation beam is accurately targeting the tumour while it moves in a complex and unpredictable way. Most tumour tracking techniques require the implantation of fiducial markers around the tumour. Markerless Tumour Tracking negates the need for implanted markers, enabling accurate and optimal cancer radiotherapy in a non-invasive way.
Lung cancer is the leading cause of cancer-related death worldwide. Thoracoscopic pulmonary resection is a prevalent management for early stage of lung cancer. Placement of traditional chest tube is the standard procedure after surgery, which causes pain that cannot be ignored. We aimed to determine whether a modified thoracic drainage strategy based on pigtail catheter associated with better clinical results compared with traditional methods after thoracoscopic surgery for lung cancer.
The objective of the study aims to collect tumor tissue at the moment of progression under Immune checkpoint inhibitors (ICI) in biological resources center in Ambroise Paré hospital, in order to insure later study on molecular mechanism involving the progression of NSCLC and SCLC under ICI. The further analysis of research will be performed in the EA 4340 unity, Biomarkers and Clinical Trials in cancerology and onco-hematology, UVSQ, University of Paris-Saclay.
This research study is evaluating Lorlatinib in combination with Crizotinib, Binimetinib, or TNO155 as a possible treatment for either anaplastic lymphoma kinase (ALK)-positive lung cancer or ROS1-positive lung cancer. - This research study involves four study drugs. - Lorlatinib - Binimetinib - Crizotinib - TNO155
Several published clinical trials have shown the superiority of immunotherapy in neoadjuvant setting. Here we conducted this real world study to see whether neoadjuvant immunotherapy would bring MPR and survival benefits in NSCLC, for example, single agent immunotherapy or immunotherapy combination with chemotherapy. Furthermore biomarker analysis would be also performed to achieve personalized neoadjuvant immunotherapy.
The purpose of this study is to investigate the use of Magnetic Resonance Imaging (MRI) in the diagnostic and planning phase of radiotherapy for lung cancer and then introduce it into on-treatment imaging to improve the accuracy of radiotherapy. The study compromises of two phases, a technical phase followed by a clinical phase. The aim of the technical phase is to develop and test MR sequences using a diagnostic scanner for use in the chest. This will be carried out on a humanoid phantom and subsequently healthy volunteers. The second phase will be a clinical phase to assess the accuracy of visualising all thoracic structures and the tumour in lung cancer patients using the defined MR sequences. It will compromise of 2 parts; the first part will involve 3 lung cancer patients as a pilot to enable the fine tuning of the sequences. The 2nd part will involve the evaluation of MRI in relation to planning CT in 12 lung cancer patients. The hypothesis is that the use of 4D MRI will be more accurate in defining the tumour and intrathoracic structures thanachieved with the current standard of 4DCT to improve the accuracy and potentially the outcome of radical radiotherapy for non-small cell lung cancer.
This study will investigate the effects of atezolizumab on select cancer types in people whose analysis of tumour DNA and RNA indicates they may be sensitive to atezolizumab. This study aims to determine if the information from the cancer genome analysis corresponds with the effects of atezolizumab on individuals and their cancer. This is a Phase 2 study, which is undertaken after preliminary safety testing on a drug is completed, and will involve approximately 200 participants. Participants are assigned to one of 8 cohorts based on their primary tumour type: breast, lung, gastrointestinal (GI), primary unknown, genitourinary (GU), sarcoma, gynecological, and 'other' cancer types. Participants in all cohorts will receive the same dose of atezolizumab (1200 mg every 3 weeks). In the first stage for each cohort, 8 participants will be enrolled and if no participants respond to treatment, enrollment to that cohort will be closed. If 1 or more participants respond to treatment, up to 16 additional participants will be enrolled to that cohort. Participants continue on treatment until they no longer may benefit from the treatment or they decide to stop treatment.
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.
The recent introduction of anti-PD-1 (nivolumab and pembrolizumab) and anti- PD-L1 (atezolizumab, durvalumab, avelumab) immune checkpoint inhibitors revolutionized oncological guidelines. Durable responses and prolongation of survival with these agents come at the price of the development of immune related adverse events (irAEs). Innovative tools are required in order to manage irAEs and to prevent their potential relapse, with the goal to improve the outcome of patients. In this regard, the Investigators aim to develop a multidisciplinary clinical pathway for cancer patients that are treated with immune checkpoint inhibitors.
Lung cancer is the malignant tumor with the highest incidence, accounting for the first cause of tumor death. At present, smoking, occupational and environmental exposure, air pollution and genetic factors are considered to be related to the incidence of lung cancer. However, the occurrence of cancer is related to many factors. In recent years, researches have found that microorganisms are closely related to various human cancers. It is reported that 20% of cancers are related to multiple microorganisms, such as EB virus and nasopharyngeal cancer, HBV and liver cancer. Understanding the correlation between pathogenic microorganisms and cancer is of great significance for the pathogenesis, prevention and treatment of cancer. Basic researches have found that mycotoxins are related to animal models of lung cancer, but have not been confirmed in clinical and human. With the help of microbial metagenome Next Generation Sequencing (mNGS) and bioinformatics analysis, the investigators initially found in clinical practice that some patients had fungal infections such as fungi in lung cancer tissues. This study intends to collect clinical cases (cross-sectional studies) to explore the correlation between the pathogenic microbiome and lung cancer, in order to confirm that the occurrence of lung cancer is closely related to microorganisms such as fungi.