View clinical trials related to Melanoma (Skin).
Filter by:The purpose of this study is to collect data from various sources (PROM / PREM, sensors, journal data) to train AI based models in the LifeChamps digital platform in a pre-pilot, as well as partly implement a pilot/feasibility study to examine the applicability of the digital technology developed in LifeChamps, as well as the usability for patients (cancer survivors) and health care professionals
This clinical study is designed as a randomized, double-blind trial. Subjects with unresectable, metastatic, or recurrent skin melanoma will be randomized to one of the two study groups (BCD-201 group and Keytruda group) at a 1:1 ratio. The goal of this study is to compare the efficacy and safety of BCD-201 and Keytruda as first-line therapy in subjects with unresectable, metastatic, or recurrent skin melanoma.
This Phase 1 study will evaluate the safety and tolerability of [Ga-68]-PNT6555 and [Lu-177]-PNT6555 in subjects with select solid tumors that have FAP over-expression, in order to determine a recommended Phase 2 dose.
Serious medical diagnosis frequently induce fear focused on specific anticipations or generalized anxiety, along with uncertainty, insecurity, and disorientation. Other emotions such as anger, depression, hopelessness, shame, or grief may also become involved following a serious diagnosis. The adverse impact of stress on health and immune function is well-established, as well as its link to depression and anxiety. Emotional Freedom Techniques (EFT) has demonstrated efficacy in treating anxiety, depression, and PTSD. This study tests its effectiveness in reducing negative emotional symptoms in general, and fear of recurrence in particular, among individuals previously diagnosed with melanoma and currently in remission.
Melanoma (skin cancer) frequently develops from existing moles on the skin. Current practice relies on expert dermatologists being able to successfully identify new/changing moles in individuals with multiple moles. Total body photography (TBP-high-quality images of the entire skin) can track and monitor moles over time to detect melanoma. However, TBP is currently used as a visual guide when diagnosing melanoma, requiring visual inspection of each mole sequentially. This process is challenging, time-consuming and inefficient. Artificial intelligence (AI) is ideally suited to automate this process. Comparing baseline TBP images to newly acquired photographs, AI techniques can be used to accurately identify and highlight changing moles, and potentially distinguish harmless moles from cancerous changes. Astrophysicists face a similar problem when they map the night sky to detect new events, such as exploding stars. Using AI, based on two or more images, astrophysicists detect new events and accurately predict how they will appear subsequently. This project, called MoleGazer, is a collaboration with astrophysicists aiming to apply AI methods that are currently used for astronomical sky surveys, to TBP images. The MoleGazer algorithm, developed at Oxford University Hospitals NHS Foundation Trust, will automatically identify the appearance of new moles and characterise changes in existing ones, when new TBP images are taken. To optimise this MoleGazer algorithm TBP images will be taken at multiple time-points, as there are no existing datasets of TBP images that are publicly available. The investigators invite a) high-risk patients attending skin cancer screening clinics to attend sequential three-monthly TBP imaging and clinical assessment and b) any patient who undergoes TBP as standard care to share images so that the investigators can develop the MoleGazer algorithm. The ultimate goal is for the MoleGazer algorithm to 'map moles' over a patient's lifetime to detect changes, with the eventual aim to detect melanoma as early as possible.
From Protocol v3.0 dated 16Jun2022. This is an international, multicenter, open-label, multiple cohort, First in Human, phase 1b clinical study, designed to evaluate safety, tolerability, and immunogenicity, and to detect any preliminary evidence of anti-tumor activity of a personalized vaccine (PEV) based on GAd-PEV priming and MVA-PEV boosting, combined with SoC first-line immunotherapy using an anti-PD-1 checkpoint inhibitor in patients with unresectable stage III/IV cutaneous melanoma or with stage IV NSCLC (PDL1 ≥ 50%). The PEV vaccines will be prepared on an individual basis, following a tumor biopsy performed at the time of screening and subsequent NGS analysis, to identify patient-specific tumor mutations. Both neoantigen-encoding genetic vaccines are administered intramuscularly using 1 prime with GAd-PEV and 3 boosts with MVA-PEV in combination with the licensed programmed death receptor-1 (PD-1)-blocking antibody pembrolizumab in adult patients in patients with unresectable stage III/IV cutaneous melanoma (Cohort a) or with stage IV NSCLC (PDL1 ≥ 50%) (Cohort b).
This is a trial of prospective collection of serial blood samples after administration of COVID-19 vaccine in patients with cancer who are receiving active cancer treatment, planned to start therapy with 14 days of consent, or have had stem cell transplant. Cancer treatments and administration of vaccine are not controlled by the study.
This phase II trial studies how well nivolumab works in treating patients with stage IIB-IIC melanoma that can be removed by surgery. Monoclonal antibodies, such as nivolumab, may interfere with the ability of tumor cells to grow and spread.
This study evaluates intratumoral administration of CV8102 in patients with advanced melanoma, squamous cell carcinoma of the skin, squamous cell carcinoma of the head and neck, or adenoid cystic carcinoma. Patients will receive CV8102 as single agent or in combination with SoC anti-PD-1 therapy.
The aim of this study is to determine whether adjuvant treatment with nDC vaccination, after complete radical lymph node dissection or sentinel node procedure in stage IIIB and IIIC melanoma patients, improves recurrence-free survival (RFS) as compared to treatment with matching placebo.