View clinical trials related to Melanoma (Skin).
Filter by:Among the mechanisms responsible for resistance to immunotherapy, metabolism seems to play a major role. A better understanding of tumor metabolism appears to be absolutely necessary in order to propose efficient therapeutic alternatives to target tumor cells without exerting a deleterious effect on the cells responsible for the anti-tumor immune response. The main objective is to evaluate metabolism modulations in melanoma cells extracted from metastases of patients sensitive and resistant to immunotherapies (anti-PD1 or anti-PD1+anti-CTLA4).
Study of Zirconium Zr 89 Crefmirlimab Berdoxa PET/CT as an imaging biomarker for assessing an early response to therapy in patients with advanced melanoma on immunotherapy and hydroxychloroquine. This study is a companion study to the "LIMIT Melanoma Trial." Patients with melanoma who are potentially eligible for the LIMIT Melanoma Trial and have at least one site of measurable disease based on RECIST 1.1 are potentially eligible. Associations with progression-free survival (PFS) and overall survival (OS) will be tested.
The purpose of this study is to obtain archived tumor tissue or pre-existing antigen expression data from patients with Head and Neck, Cervical, Melanoma and Non-Small Cell Lung Cancers to assess antigen expression and patient suitability for a Repertoire Immune Medicines Treatment Protocol.
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 study examines melanoma and nonmelanoma skin cancer in people diagnosed with vitiligo compared to matched controls.
1. Background The purpose of this study is to describe the profile of patients with BRAF-mutated melanoma treated with BRAF/MEK inhibitors combination and using the Tavie Skin application. TavieSkin app, a digital solution developped by Pierre Fabre, is dedicated to all BRAF-mutant unresectable or metastatic melanoma patients who are treated with "any" targeted therapies. 2. Study objectives The primary objective of the survey is to describe the demographics and clinical characteristics of patients with unresectable or metastatic BRAF-mutated melanoma treated with targeted therapy (BRAFi/MEKi) and using the TavieSkin application The secondary objectives include: - To assess the use of TavieSkin app in patients with unresectable or metastatic BRAF-mutated melanoma treated with BRAFi/MEKi combination; - To assess the treatment adherence of patients using TavieSkin app including treatment interruption or permanent discontinuation; - To assess the health-related quality of life of patients using TavieSkin app (FACT-M); - To assess work productivity and activity impairment over the treatment duration - To assess the patient satisfaction toward the TavieSkin application; - To assess the patient satisfaction toward the treatment. 3. Research methods 3.1 Study design This prospective, longitudinal, survey will be conducted in Europe to characterize BRAF-mutant unresectable or metastatic melanoma patients using TavieSkin app designed for accompanying patients treated with targeted therapies. To date, there are three combinations of BRAFi/MEKi available in routine practice for the treatment of BRAF-mutant unresectable or metastatic melanoma. The survey does not provide or recommend any treatment or procedure; all decisions regarding treatment are made at the sole discretion of the treating physicians in accordance with their usual practices. The patients initiating any BRAFi/MEKi combination will be invited to use the TavieSkin app by their healthcare provider (HCP) (i.e. oncologist, dermatologist, nurse…). Once the patient has installed and started to use the application, an e-survey will be proposed to the patient via the app. A detailed information letter about the data collection, data privacy and analysis will be displayed to the patient via the app along with an e-consent for data collection. The patient will be able then to provide an e-signature, if he/she accepts to take part of this survey. The survey will collect anonymized data about health status, QoL data and satisfaction. These data will be collected by the patient only. The physician will not be involved in this e-survey (including e-consent), nor in data collection. Only patients having given consent (e-consent) to data collection and analysis will be included. Data will be collected at baseline and at different subsequent timepoints during the BRAFi/MEKi treatment duration only. Only data reported by the patients in the application will be collected and analyzed. The patient will discontinue the study in case of definitive withdrawal of BRAFi/MEKi treatment, or if he/she decides to withdraw the study and to stop data collection. The target countries for patient enrollment will include Germany, Belgium, Portugal, France, Spain, Italy and Sweden with the additional possibility of including patients from other EU countries. At least, 400 adult patients (≥18 years) will be enrolled. 3.2 Population (see section: Eligibility) 3.3 Study outcomes (see section: Outcome measures) 3.4 Statistical considerations Statistical analyses will be fully described in a written statistical analysis plan (SAP). The study endpoints will be analysed overall and by country. Analyses will be descriptive in nature, as no hypothesis will be tested. The treatment patterns of patients, baseline demographics and clinical characteristics, and reasons for treatment discontinuation will be described using summary statistics. Categorical variables will be summarized by frequencies and percentages. Continuous variables will be summarized by descriptive statistics (mean, and standard deviation, median, 25th and 75th percentiles, minimum and maximum). The number of missing observations for each variable will also be reported. Change in health-related quality-of-life scores (i.e. (FACT-M) will be summarised at baseline and at each timepoints. The change from baseline will be assessed using a mixed model for repeated measures (MMRM). Time to event data (i.e. time to treatment discontinuation, time QoL deterioration) will be evaluated using Kaplan-Meier survival curves. Median survival estimates will be reported along with the 25th and 75th percentiles and corresponding 95% confidence intervals (CIs). Cox regression analysis may be performed to adjust for predefined (baseline) covariates. If the sample size is adequate, subgroup analyses using variables at baseline might be conducted.
The study hypothesis is that new imaging agents [203Pb]VMT01 and [68Ga]VMT02 can be safely used in humans without independent biological effect and can be used to image melanoma tumors expressing the melanocortin sub-type 1 receptor (MC1R) by SPECT/CT and PET/CT imaging modalities respectively.
The trial is looking for new and better ways to treat melanoma, an aggressive type of skin cancer. Having surgery to remove the melanoma will cure the majority of patients with early stage disease. However, a small percentage of these patients will go on to develop further disease, which may spread to other places in their body. Currently, patients who have been cured of melanoma will have appointments in clinic to check that further disease has not developed or returned and some may also receive regular scans. The trial team has developed a blood test that tells us whether cancer cells are still present or is becoming active after a patient has been 'cured' of melanoma, even if a scan looks normal. The test looks for pieces of DNA in the blood that are known to have come from the cancer, which we call 'circulating tumour DNA', or ctDNA. Patients who have ctDNA in their blood have an extremely high chance of the cancer returning. By using the blood test that we have developed we think that we can identify patients earlier than normal. We think that some of the treatments that are used when melanoma cancer has spread may benefit patients at this earlier stage. We want to see if these patients with ctDNA in their blood, who have a higher risk of their cancer returning or spreading, and receive treatment early have a better response to their cancer compared to those patients who receive treatment when their cancer has returned and it can be seen on a scan. This could mean we would be able to offer patients earlier treatment in the future using just a blood test rather than a scan, while also providing reassurance to those patients that do not have ctDNA in their blood that they do not need treatment and their cancer is not returning.
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