It is imperative that health professionals caring for patients with rheumatic diseases understand how to correctly interpret evidence in their field, taking into account the merits and shortcomings of available data. Understanding Evidence-Based Rheumatology offers a practical assessment of criteria, drugs, trials, and registries and provides useful tools for successfully interpreting this data. The book introduces readers to basic analysis of trial design, statistics and application of data through no-nonsense, easy-to-follow insights. Using numerous examples, chapters outline the difficulties physicians encounter when measuring disease activity in rheumatology and offer strategies for systematically approaching these situations. Ethical issues in study design and reporting are examined and the book closes with a summary of future directions for scientific and clinical studies in rheumatology.
Understanding Evidence-Based Rheumatology is an invaluable resource for trainees, clinicians and scientists, preparing them with the necessary tools to correctly gather evidence and shed light on the difficult practice of rheumatology.
Tabella dei contenuti
1. Evidence in Rheumatology: How Does It Differ from Other Diseases?.- 2. A Review of Statistical Approaches for the Analysis of Data in Rheumatology.- 3. Disease Classification/Diagnosis Criteria.- 4. Biomarkers, Genetic Association and Genomic Studies.- 5. Outcome Measures in Rheumatoid Arthritis.- 6. Issues in Setting Up a Study and Data Collection.- 7. The Randomized Controlled Trial: Methodological Perspectives.- 8. Limitations of Traditional Randomized Controlled Clinical Trials in Rheumatology.- 9. Methodological Issues Relevant to Observational Studies, Registries and Administrative Health Databases in Rheumatology.- 10. Systematic Reviews and Meta-analyses in Rheumatology.- 11. Ethical Issues in Study Design and Reporting.- 12. Future Directions.
Circa l’autore
Hasan Yazici, MD, Professor of Medicine
Istanbul University, Istanbul, Turkey
Yusuf Yazici, MD, Assistant Professor of Medicine
New York University School of Medicine, New York, NY, USA
Emmanuel Lesaffre, Ph D
Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands
and
L-Biostat, K.U.Leuven
Leuven, Belgium.
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