In defining human disease unequivocally, physicians have traditionally relied on recognition of patterns of phenotypic expression of previously described diseases, as well as laboratory, radiological and other features. The spectrum of the rheumatic diseases, and the relative paucity of both diagnostic and prognostic biomarkers, remain a significant challenge in rheumatology research, and in the clinics. Classification criteria, and more rarely, diagnostic criteria, have been developed to assist physicians and researchers, however, these criteria frequently fail to successfully and usefully separate out the varying disease phenotypes that exist even within a given classification/diagnostic category, for example in rheumatoid arthritis. Stratifying disease accurately at diagnosis remains a challenge in 2017, and these difficulties hamper attempts to achieve true personalised or precision medicine. Nevertheless, there is great cause for optimism, as powerful, high-throughput, molecular analytical technologies become less expensive and more widely available, combined with advances in computational biology. Such tools will allow a more precise set of available diagnoses, each with meaningful clinical and prognostic relevance.
Developing meaningful outcome measures in rheumatic disease is also adversely affected by the lack of sensitive and specific biomarkers. Tremendous progress has been made over the last two decades in developing validated measures of disease activity, for example in the vasculitides and in rheumatoid arthritis. Nevertheless, common rheumatic conditions such as psoriatic arthritis, have proven challenging to empirically assess for disease activity, in part, once again, to the heterogeneity of the disease itself. Existing validated measures are subject to challenge too, as they are often seen as too complex to perform in routine clinics, and contain parameters that are themselves subjective. Longer term outcome measures frequently suffer similar failings.
We welcome innovative, high quality articles, addressing the key challenges the rheumatology community faces in the field of diagnostics and treatment outcomes.
In defining human disease unequivocally, physicians have traditionally relied on recognition of patterns of phenotypic expression of previously described diseases, as well as laboratory, radiological and other features. The spectrum of the rheumatic diseases, and the relative paucity of both diagnostic and prognostic biomarkers, remain a significant challenge in rheumatology research, and in the clinics. Classification criteria, and more rarely, diagnostic criteria, have been developed to assist physicians and researchers, however, these criteria frequently fail to successfully and usefully separate out the varying disease phenotypes that exist even within a given classification/diagnostic category, for example in rheumatoid arthritis. Stratifying disease accurately at diagnosis remains a challenge in 2017, and these difficulties hamper attempts to achieve true personalised or precision medicine. Nevertheless, there is great cause for optimism, as powerful, high-throughput, molecular analytical technologies become less expensive and more widely available, combined with advances in computational biology. Such tools will allow a more precise set of available diagnoses, each with meaningful clinical and prognostic relevance.
Developing meaningful outcome measures in rheumatic disease is also adversely affected by the lack of sensitive and specific biomarkers. Tremendous progress has been made over the last two decades in developing validated measures of disease activity, for example in the vasculitides and in rheumatoid arthritis. Nevertheless, common rheumatic conditions such as psoriatic arthritis, have proven challenging to empirically assess for disease activity, in part, once again, to the heterogeneity of the disease itself. Existing validated measures are subject to challenge too, as they are often seen as too complex to perform in routine clinics, and contain parameters that are themselves subjective. Longer term outcome measures frequently suffer similar failings.
We welcome innovative, high quality articles, addressing the key challenges the rheumatology community faces in the field of diagnostics and treatment outcomes.
