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Additional file 1: Table S1. Mean duration between visits in years and standard deviation. Figure S1. Patient examples of exposure evaluation for time-varying analyses. bDMARD: biologic disease modifying anti-rheumatic drug. csDMARD: conventional synthetic disease modifying anti-rheumatic drug. Table S2. Missingness per variable throughout follow-up. Table S3. Missingness pattern of variables with missingness only of Cohort 1 throughout follow-up (6136 observations). Table S4. Missingness pattern of variables with missingness only of Cohort 2 throughout follow-up (4511 observations). Table S5. Crude data table. Table S6. Data table for time-invariant Cox proportional hazard regression. Table S7. Data table for time-invariant Cox proportional hazard regression. Table S8. Patient characteristics of patients before exclusion versus patients with one or ≥2 radiographs. Table S9. Median duration between radiographs in years and interquartile range. Table S10. Results of Cox regression analyses of progression of DIP OA crude, fully adjusted, and when adjusting for fewer variables. Table S11. Patient characteristics of patient without osteoarthritis at cohort entry. Table S12. Hazard ratios of incident hand OA per treatment group following Cox time varying regression analyses in subgroups of age, rheumatoid factor, osteoporosis (treatment), and prednisone use. Table S13. Hazard ratios of hand OA progression per treatment group following time-varying Cox proportional hazard regression analyses when not adjusting for DAS28-esr. Table S14. Hazard ratios of hand OA progression per treatment group following time-varying Cox proportional hazard regression analyses when leading the outcome hand OA progression by 6 months. Table 15. Hazard ratios of hand OA incidence per treatment group following Cox time-varying proportional hazard regression analyses without adjusting for DAS28-esr. Table 16. Hazard ratios of hand OA incidence per treatment group following Cox time-varying regression analyses when leading the outcome hand OA progression by 6 months.

Background: Giant Cell Arteritis (GCA) is the most frequent large vessel vasculitis (LVV) in Western countries, affecting predominantly women over 50 years of age. Intense inflammation in all layers of the medium- to large-sized arteries and formation of granulomas might lead to vascular obliteration,[for full text, please go to the a.m. URL], 46. Kongress der Deutschen Gesellschaft für Rheumatologie (DGRh), 32. Jahrestagung der Deutschen Gesellschaft für Orthopädische Rheumatologie (DGORh), Wissenschaftliche Herbsttagung der Gesellschaft für Kinder- und Jugendrheumatologie (GKJR)

BACKGROUND Decision makers often need to assess the real-world effectiveness of new drugs prelaunch, when phase II/III randomized controlled trials (RCTs) but no other data are available. OBJECTIVE To develop a method to predict drug effectiveness prelaunch and to apply it in a case study in rheumatoid arthritis (RA). METHODS The approach 1) identifies a market-approved treatment ( S) currently used in a target population similar to that of the new drug ( N); 2) quantifies the impact of treatment, prognostic factors, and effect modifiers on clinical outcome; 3) determines the characteristics of patients likely to receive N in routine care; and 4) predicts treatment outcome in simulated patients with these characteristics. Sources of evidence include expert opinion, RCTs, and observational studies. The framework relies on generalized linear models. RESULTS The case study assessed the effectiveness of tocilizumab (TCZ), a biologic disease-modifying antirheumatic drug (DMARD), combined with conventional DMARDs, compared to conventional DMARDs alone. Rituximab (RTX) combined with conventional DMARDs was identified as treatment S. Individual participant data from 2 RCTs and 2 national registries were analyzed. The model predicted the 6-month changes in the Disease Activity Score 28 (DAS28) accurately: the mean change was -2.101 (standard deviation [SD] = 1.494) in the simulated patients receiving TCZ and conventional DMARDs compared to -1.873 (SD = 1.220) in retrospectively assessed observational data. It was -0.792 (SD = 1.499) in registry patients treated with conventional DMARDs. CONCLUSION The approach performed well in the RA case study, but further work is required to better define its strengths and limitations.

Fragestellung: Hat die therapeutische Arthroskopie im Vergleich zu einer Scheinbehandlung oder einer anderen Behandlung bei Patienten mit Gonarthrose einen Nutzen? Methodik: Im Rahmen einer systematischen Übersicht wurden Literaturrecherchen in MEDLINE, EMBASE und Cochrane durchgeführt[zum vollständigen Text gelangen Sie über die oben angegebene URL], Deutscher Kongress für Orthopädie und Unfallchirurgie (DKOU 2016)

Objective: To examine whether exclusions of patients from the analysis of randomized trials are associated with biased estimates of treatment effects and higher heterogeneity between trials. Design: Meta-epidemiological study based on a collection of meta-analyses of randomised trials. Data sources: 14 meta-analyses including 167 trials that compared therapeutic interventions with placebo or non-intervention control in patients with osteoarthritis of the hip or knee and used patient reported pain as an outcome. Methods: Effect sizes were calculated from differences in means of pain intensity between groups at the end of follow-up, divided by the pooled standard deviation. Trials were combined by using random effects meta-analysis. Estimates of treatment effects were compared between trials with and trials without exclusions from the analysis, and the impact of restricting meta-analyses to trials without exclusions was assessed. Results: 39 trials (23 %) had included all patients in the analysis. In 128 trials (77 %) some patients were excluded from the analysis. Effect sizes from trials with exclusions tended to be more beneficial than those from trials without exclusions (difference -0.13, 95 %-confidence interval -0.29 to 0.04). However, estimates of bias between individual meta-analyses varied considerably (2=0.07). Tests of interaction between exclusions from the analysis and estimates of treatment effects were positive in five meta-analyses. Stratified analyses indicated that differences in effect sizes between trials with and trials without exclusions were more pronounced in meta-analyses with high between trial heterogeneity, in meta-analyses with large estimated treatment benefits, and in meta-analyses of complementary medicine. Restriction of meta-analyses to trials without exclusions resulted in smaller estimated treatment benefits, larger P values, and considerable decreases in between trial heterogeneity. Conclusion: Exclusions of patients from the analysis in randomised trials often result in biased estimates of treatment effects, but the extent and direction of bias is unpredictable. Results from intention to treat analyses should always be described in reports of randomised trials. In systematic reviews, the influence of exclusions from the analysis on estimated treatment effects should routinely be assessed.

Hintergrund: Metamizol wird in vielen Ländern der Welt zur Schmerztherapie (z.B. bei Kolik- oder postoperativem Schmerz) eingesetzt. Die Agranulozytose ist als seltene, aber schwerwiegende unerwünschte Arzneimittelwirkung (UAW) seit langem bekannt. Informationen zu Art und Häufigkeit [for full text, please go to the a.m. URL], 48. Kongress für Allgemeinmedizin und Familienmedizin