Rheumatoid arthritis (RA) is a heterogeneous disease that varies markedly in its severity. There is, therefore, a key research need to develop methods that can predict an individual's likely RA severity at disease onset, which would enable treatment to be tailored accordingly. A number of different prognostic factors for RA severity have been identified. These include environmental (such as smoking and alcohol consumption), genetic (such as the HLA-DRB1 alleles and polymorphisms in the IL1 locus), serological (rheumatoid factor and antibodies to citrullinated protein antigens) and biochemical (such as matrix metalloproteinases) factors. In this review, the authors discuss these prognostic factors in detail, outlining the evidence supporting them and focusing on how they have been combined in prognostic modeling to predict the likely severity of an individual's RA phenotype.
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Scott et al. (2013) studied this question.
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