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Introduction: There is a need to optimise the management of atopic dermatitis (AD), improving the efficacy of treatments and reducing the toxicity associated with them. Although the efficacy of ciclosporine (CsA) in the treatment of AD has been thoroughly documented in the literature, the optimal dose has not been yet established. The use of multiomic predictive models of treatment response could optimise CsA therapy in AD.
Methods And Analysis: The study is a low-intervention phase 4 trial to optimise the treatment of patients with moderate-severe AD requiring systemic treatment. The primary objectives are to identify biomarkers that could allow for the selection of responders and non-responders to first-line treatment with CsA and to develop a response prediction model to optimise the CsA dose and treatment regimen in responding patients based on these biomarkers. The study is divided into two cohorts: the first comprised of patients starting treatment with CsA (cohort 1), and the second, of patients already receiving or who have received CsA therapy (cohort 2).
Ethics And Dissemination: The study activities began following authorisation by the Spanish Regulatory Agency (AEMPS) and the Clinical Research Ethics Committee of La Paz University Hospital approval. Trial results will be submitted for publication in an open access peer-reviewed medical speciality-specific publication.Trial registration of this study can be located at the EU Clinical Trials Register, available from https://euclinicaltrials.eu/search-for-clinical-trials/?lang=en. Our clinical trial was registered in the website before the enrolment of the first patient complying with European regulations. EU Clinical Trials Register is a primary registry according the WHO. Once our trial was included in a primary and official registry, in order to extend the accessibility to our research, we also registered it retrospectively in clinicaltrials.gov; however, this is not mandatory as per our regulation.
Trial Registration Number: NCT05692843.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10335428 | PMC |
http://dx.doi.org/10.1136/bmjopen-2023-072350 | DOI Listing |
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