Co-morbidities, i.e. diseases that have an increased frequency in patients with rheumatic disease as compared to the population, provide important challenges in diagnostics, therapeutics and prevention for all rheumatologists. Their occurrence depends on three different pathogenetic principles, and knowledge about these principles is important for all handling of these co-morbidities:
First, co-morbidities may occur as a result of shared risk factors for the musculoskeletal disease and its co-morbidity. A prototype case for this is the co-existence of type I diabetes and ACPA-positive RA, where genetic risk factors are shared, and where the “co-morbidity” in T1D most often begins before the onset of RA. In this and other cases of co-morbidity due to shared risk factors, we need knowledge about the risk for specific co-morbidities and appreciate the diagnosis and treatment of those in parallel to the treatment of the rheumatic condition.
Second, co-morbidities may occur as a result of the rheumatic condition (and not of its treatment). Prototype cases for this are cardiovascular disease and some lymphoid cancers, in particular lymphomas, which occur in increased frequency in several of the inflammatory rheumatic conditions. As these diseases depend on distinct manifestations of the rheumatic disease, increased knowledge of the relation between the rheumatic disease and its co-morbidity may allow efficient treatment as well as prevention of the co-morbidity.
Thirdly, the co-morbidity may depend on our treatment of the rheumatic condition. This is typically the case for some infections as well as some more rare manifestations of other autoimmune diseases such as neurological inflammatory diseases after treatment with different immunosuppressant including biologicals. Here, we need deep knowledge about the adverse event spectrum of drugs that we use.
For all these co-morbidities, there is a need for increased knowledge about who are at risk and what is the most efficient treatment of the combined morbidity. This lecture will also discuss how modern genetics and biomarker analysis, together with classical analysis of clinical signs and symptoms provide us with new means to handle these complex medical challenges.
Disclosure of Interest None Declared
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