Annals of the rheumatic diseases
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To evaluate the available evidence on the efficacy and feasibility of the new concept of tight control in randomised trials in patients with rheumatoid arthritis (RA). Tight control is a treatment strategy tailored to the individual patient with RA, which aims to achieve a predefined level of low disease activity or remission within a certain period of time. ⋯ Tight control aiming for low disease activity or even better still, remission, seems a promising option in treating patients with RA in clinical trials and probably also in daily practice.
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An increasing focus has over recent years been directed to the use of categorical endpoints to define response, i.e. to define cut-points for important improvement and/or acceptable clinical state. The levels of Minimal Clinically Important Improvement (MCII) are typically defined according to the patients perception of what is an important improvement. It can be defined as the smallest change in measurement that signifies an important improvement. ⋯ The 75th percentage approach identifies the cut-point corresponding to the 75 percentile of the scores for improvement in patients who report an important improvement by the anchoring question. Applying receiver operating characteristic (ROC) curves allows for choosing the threshold that is the best compromise between sensitivity and specificity for each outcome criterion. The identified cut-points for MCII and PASS may easily be incorporated as endpoints in clinical trials, and will provide information about the proportion of patients that achieve an improvement exceeding the level accepted as MCII and achieve a state accepted as PASS.
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In this manuscript we discuss the reasons why and how health economics is important, the type of economic studies that are relevant in healthcare to different stakeholders in general, and what analyses can and have been performed in the field of rheumatoid arthritis (RA). We will thus specifically address costs and outcome measurements in RA, as well as the need for modelling in chronic progressive diseases.