Classification and management of allergic rhinitis patients in general practice during pollen season

Background: Allergic rhinitis (AR) represents a major challenge in primary care. The Allergic Rhinitis and its Impact on Asthma (ARIA) group proposed a new classification for AR and developed evidence-based guidelines for the management of this disease. We conducted this study to further characterize the classes of AR described by ARIA, and to evaluate whether the management of AR in general practice is in accordance with the ARIA guidelines. Methods: During the pollen season of 2003, 95 Belgian general practitioners (GPs) enrolled 804 patients who presented with symptoms of AR. For each patient, a questionnaire comprising the clinical presentation and management was completed. Results: In 64% of the patients, AR was classified as intermittent and in 36% as persistent. Persistent rhinitis caused more discomfort than intermittent rhinitis. Only 50% of the patients had ever undergone allergy testing. Among them, 51% were allergic to both seasonal and perennial allergens. Eighty-two per cent of the persistent rhinitics were allergic to at least one seasonal allergen and 72% of the intermittent rhinitics to at least one perennial allergen. When compared strictly with the ARIA recommendations, 49% of the patients with mild and/or intermittent AR were overtreated, whereas about 30% of those with moderate/severe persistent rhinitis were undertreated. Conclusion: This study confirms that the previous classification of AR into 'seasonal' and 'perennial' is not satisfactory and that intermittent and persistent AR are not equivalent to seasonal and perennial AR respectively. Furthermore, persistent rhinitis has been shown to be a distinct disease entity. Further efforts are required to disseminate and implement evidence-based diagnostic and treatment guidelines for AR in primary care practice

Predicting the outcome of ankylosing spondylitis therapy

Objectives To create a model that provides a potential basis for candidate selection for anti-tumour necrosis factor (TNF) treatment by predicting future outcomes relative to the current disease profile of individual patients with ankylosing spondylitis (AS). Methods ASSERT and GO-RAISE trial data (n=635) were analysed to identify baseline predictors for various disease-state and disease-activity outcome instruments in AS. Univariate, multivariate, receiver operator characteristic and correlation analyses were performed to select final predictors. Their associations with outcomes were explored. Matrix and algorithm-based prediction models were created using logistic and linear regression, and their accuracies were compared. Numbers needed to treat were calculated to compare the effect size of anti-TNF therapy between the AS matrix subpopulations. Data from registry populations were applied to study how a daily practice AS population is distributed over the prediction model. Results Age, Bath ankylosing spondylitis functional index (BASFI) score, enthesitis, therapy, C-reactive protein (CRP) and HLA-B27 genotype were identified as predictors. Their associations with each outcome instrument varied. However, the combination of these factors enabled adequate prediction of each outcome studied. The matrix model predicted outcomes as well as algorithm-based models and enabled direct comparison of the effect size of anti-TNF treatment outcome in various subpopulations. The trial populations reflected the daily practice AS population. Conclusion Age, BASFI, enthesitis, therapy, CRP and HLA-B27 were associated with outcomes in AS. Their combined use enables adequate prediction of outcome resulting from anti-TNF and conventional therapy in various AS subpopulations. This may help guide clinicians in making treatment decisions in daily practice.Pathophysiology and treatment of rheumatic disease

Four-year follow-up of infliximab therapy in rheumatoid arthritis patients with long-standing refractory disease: attrition and long-term evolution of disease activity

Although there is strong evidence supporting the short-term efficacy and safety of anti-tumour necrosis factor-α agents, few studies have examined the long-term effects. We evaluated 511 patients with long-standing refractory rheumatoid arthritis treated with intravenous infusions of infliximab 3 mg/kg at weeks 0, 2, 6, and 14 and every 8 weeks thereafter for 4 years. Among the initial 511 patients included in the study, 479 could be evaluated; of these, 295 (61.6%) were still receiving infliximab treatment at year 4 of follow-up. The most common reasons for treatment discontinuation were lack of efficacy (65 patients, 13.6%), safety (81 patients, 16.9%), and elective change (38 patients, 7.9%). Analysis of disease activity scores (DAS28 [disease activity score based on the 28-joint count]) over time showed that, after the initial rapid improvement during the first 6 to 22 weeks of therapy, a further decrease in disease activity of 0.2 units in the DAS28 score per year was observed. DAS28 scores, measured at week 14 or 22, were found to predict subsequent discontinuation due to lack of efficacy. In conclusion, long-term maintenance therapy with infliximab 3 mg/kg is effective in producing further reductions in disease activity. Disease activity measured by the DAS28 at week 14 or 22 of infliximab therapy was the best predictor of long-term attrition

Prediction of remission and low disease activity in disease-modifying anti-rheumatic drug-refractory patients with rheumatoid arthritis treated with golimumab

OBJECTIVE: To create a tool to predict probability of remission and low disease activity (LDA) in patients with RA being considered for anti-TNF treatment in clinical practice. METHODS: We analysed data from GO-MORE, an open-label, multinational, prospective study in biologic-naïve patients with active RA (DAS28-ESR ⩾3.2) despite DMARD therapy. Patients received 50 mg s.c. golimumab (GLM) once monthly for 6 months. In secondary analyses, regression models were used to determine the best set of baseline factors to predict remission (DAS28-ESR <2.6) at month 6 and LDA (DAS28-ESR ⩽3.2) at month 1. RESULTS: In 3280 efficacy-evaluable patients, of 12 factors included in initial regression models predicting remission or LDA, six were retained in final multivariable models. Greater likelihood of LDA and remission was associated with being male; younger age; lower HAQ, ESR (or CRP) and tender joint count (or swollen joint count) scores; and absence of comorbidities. In models predicting 1-, 3- and 6-month LDA or remission, area under the receiver operating curve was 0.648-0.809 (R(2) = 0.0397-0.1078). The models also predicted 6-month HAQ and EuroQoL-5-dimension scores. A series of matrices were developed to easily show predicted rates of remission and LDA. CONCLUSION: A matrix tool was developed to show predicted GLM treatment outcomes in patients with RA, based on a combination of six baseline characteristics. The tool could help provide practical guidance in selection of candidates for anti-TNF therapy