Evidence based medicine is at the core of modern medicine. It involves the integration of individual clinical expertise with the best available clinical evidence from systematic research and patient's values and expectations. Systematic reviews offer a summary of the best available evidence. They are the most reliable and comprehensive statement about what works. 

Written by clinical academics from Australia, UK, USA, and Switzerland, this contributed volume introduces the readers to the principles and practice of systematic reviews and meta-analysis. It covers the various steps involved in systematic reviews including development of a focused question and the strategy for conducting a comprehensive literature search, identifying studies addressing the underlying question, assessment of heterogeneity and the risk of bias in the included studies, data extraction, and the approach to meta-analysis. Crucial issues such as selecting the model for meta-analysis, generating and interpreting forest plots, assessing the risk of publication bias, cautions in the interpretation of subgroup and sensitivity analyses, rating certainty of the evidence using GRADE guideline, and standardized reporting of meta-analysis (PRISMA) are covered in detail. Every attempt is made to keep the narrative simple and clear. Mathematical formulae are avoided as much as possible. 

While the focus of this book is on systematic reviews and meta-analyses of randomised controlled trials (RCTs), the gold standard of clinical research, the essentials of systematic reviews of non-RCTs, diagnostic test accuracy studies, animal studies, individual participant data meta-analysis, and network meta-analysis are also covered. 

Readers from all faculties of medicine will enjoy this comprehensive and reader friendly book to understand the principles and practice of systematic reviews and meta-analysis for guiding their clinical practice and research.

Chapter 1. Systematic reviews, meta-analysis, and evidence-based medicine

Chapter 2. Literature search for systematic reviews
Chapter 3. Assessing and exploringheterogeneity
Chapter 4. Assessment of the risk of bias
Chapter 5. Assessment of publication bias
Chapter 6. Data extraction from included studies
Chapter 7. Fixed effect versus random effects model for meta-analysis
Chapter 8. Forest plots in a meta-analysis
Chapter 9. Subgroup and sensitivity analyses
Chapter 10. Rating certainty of the evidence using GRADE guidelines
Chapter 11. Reporting of meta-analysis (PRISMA)
Chapter 12. Critical appraisal of systematic reviews and meta-analysis
Chapter 13. Systematic reviews of non-randomised studies
Chapter 14. Individual participant data (IPD) meta-analysis
Chapter 15. Systematic reviews of diagnostic test accuracy
Chapter 16. Network meta-analysis
Chapter 17. Systematic reviews of animal studies.