Current evidence for the management of rheumatoid arthritis with glucocorticoids: a systematic literature review informing the EULAR recommendations for the management of rheumatoid arthritis.
ABSTRACT Glucocorticoids (GCs) rapidly reduce disease activity in early and advanced rheumatoid arthritis (RA). This systematic review on behalf of the task force on recommendations for the management of RA addresses the efficacy of GCs in RA. A literature search was performed in Medline, Embase, the Cochrane database, and the ACR/EULAR abstracts 2007 and 2008 on a set of questions relating to the use of GCs in RA. Eleven publications (including three Cochrane reviews comprising 33 trials) that met the criteria for detailed assessment were found. Robust evidence that GCs are effective as bridging therapy was obtained. The addition of GCs, to either standard synthetic disease-modifying antirheumatic drug (DMARD) monotherapy or combinations of synthetic DMARDs, yields clinical benefits and inhibition of radiographic progression that may extend over many years. In early RA, the addition of low-dose GCs (<7.5 mg/day) to DMARDs leads to a reduction in radiographic progression; in longstanding RA, GCs (up to 15 mg/day) improve disease activity. There is some evidence that appropriate timing of GC administration may result in less morning stiffness. Only indirect information was found on the best tapering strategy, supporting the general view that GCs should be tapered slowly in order to avoid clinical relapses. GCs are effective in relieving signs and symptoms and inhibiting radiographic progression, either as monotherapy or in combination with synthetic DMARD monotherapy or combination therapy.
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ABSTRACT: Forty-one patients with rheumatoid arthritis (RA) maintained on low dose prednisolone (mean 5.8 mg) participated in a double-blind cross-over study to determine the effect of timing (morning or night) of prednisolone dosage on morning stiffness. Prednisolone given at night resulted in a significantly shorter duration of morning stiffness (p = 0.0001) than did an equivalent dose given in the morning.Annals of the Rheumatic Diseases 01/1985; 43(6):790-3. · 9.11 Impact Factor
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ABSTRACT: Null hypothesis significance testing (NHST) is the dominant statistical approach in biology, although it has many, frequently unappreciated, problems. Most importantly, NHST does not provide us with two crucial pieces of information: (1) the magnitude of an effect of interest, and (2) the precision of the estimate of the magnitude of that effect. All biologists should be ultimately interested in biological importance, which may be assessed using the magnitude of an effect, but not its statistical significance. Therefore, we advocate presentation of measures of the magnitude of effects (i.e. effect size statistics) and their confidence intervals (CIs) in all biological journals. Combined use of an effect size and its CIs enables one to assess the relationships within data more effectively than the use of p values, regardless of statistical significance. In addition, routine presentation of effect sizes will encourage researchers to view their results in the context of previous research and facilitate the incorporation of results into future meta-analysis, which has been increasingly used as the standard method of quantitative review in biology. In this article, we extensively discuss two dimensionless (and thus standardised) classes of effect size statistics: d statistics (standardised mean difference) and r statistics (correlation coefficient), because these can be calculated from almost all study designs and also because their calculations are essential for meta-analysis. However, our focus on these standardised effect size statistics does not mean unstandardised effect size statistics (e.g. mean difference and regression coefficient) are less important. We provide potential solutions for four main technical problems researchers may encounter when calculating effect size and CIs: (1) when covariates exist, (2) when bias in estimating effect size is possible, (3) when data have non-normal error structure and/or variances, and (4) when data are non-independent. Although interpretations of effect sizes are often difficult, we provide some pointers to help researchers. This paper serves both as a beginner's instruction manual and a stimulus for changing statistical practice for the better in the biological sciences.Biological Reviews 12/2007; 82(4):591-605. · 10.26 Impact Factor
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ABSTRACT: The efficacy of oral prednisone as bridge therapy in rheumatoid arthritis (RA) was studied. Forty patients starting aurothioglucose were randomized to receive either prednisone or placebo for 18 weeks. The dose was 10 mg/day in the first 12 weeks, 7.5 mg/day in weeks 13 and 14, 5 mg/day in weeks 15 and 16, and 2.5 mg/day in weeks 17 and 18. Patients were followed for 44 weeks. We found that disease activity was significantly lower in the prednisone group as early as week 1 and continued up to week 12. Response to prednisone was noticed in 60% of the patients. After tapering prednisone, a rebound deterioration was noticed at weeks 20 and 24 in 58% of the responders. No significant differences in X-ray progression were found between the two groups. We concluded that oral prednisone (10 mg/day) significantly reduces short-term disease activity in 60% of patients with active RA. The rebound deterioration after tapering the dose means that bridge therapy with prednisone using this dose-reduction scheme is not recommended.British journal of rheumatology 05/1995; 34(4):347-51.