Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.766154
Title: Improving prediction strategies in rheumatoid arthritis : additional predictive ability of synovial pathotype over clinical, laboratory and imaging findings
Author: Di Cicco, Maria
ISNI:       0000 0004 7653 7015
Awarding Body: Queen Mary University of London
Current Institution: Queen Mary, University of London
Date of Award: 2018
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Abstract:
Rheumatoid arthritis (RA) is a chronic inflammatory disease of autoimmune origin affecting approximately 1% of adult population worldwide. The clinical course of RA is highly variable, ranging from self-limiting to severe disease, with considerable individual and socio-economic implications. It is now well acknowledged that early diagnosis and treatment equates to better long-term outcomes. However, despite major therapeutic advances in recent decades, the management of RA remains challenging as a significant proportion of patients presents with active disease despite maximization of therapy. It is also difficult to predict which patients will respond adequately to various treatment regimens. The identification of biomarkers of clinical outcome capable of stratifying patients into accurate prognostic categories and guide pharmacological intervention is therefore urgently needed. Notably, along with clinical variability, RA is characterised by high biological heterogeneity at the tissue level. The cellular infiltrate of the RA synovium can be distinguished into at least three main patterns according to the degree and organisation of the immune cells: the 'Lymphoid' pattern characterised by predominant B and T lymphocytes which tend to cluster in discrete aggregates resembling ectopic lymphoid structures; the 'Myeloid' pattern characterised by absence of lymphocytic aggregates but significant expression of sublining macrophages; the 'Pauci-immune' pattern, that hardly shows any infiltrating immune cells. The hypothesis of this thesis was to determine whether these distinct synovial pathotypes may define specific disease subsets and predict response to therapy in patients with RA. Specifically, this work aims at: 1. evaluating whether the synovial pathotype associates with the presence of specific clinical, serological, radiological and ultrasonographic findings in an early RA cohort (< 1 year onset); 2. exploring the potential role of the synovial pathotype as a predictor of response to conventional synthetic disease-modifying antirheumatic drugs (csDMARD) after 6 months in an early RA cohort; 3. exploring the potential role of the synovial pathotype as a predictor of response to anti-TNFα treatment after 3 months in a csDMARD-failure established RA cohort.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.766154  DOI: Not available
Keywords: Rheumatoid Arthritis ; RA synovium ; synovial pathotypes
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