This edited volume showcases the recent research on diagnostic meta-analysis and related methods for the systematic synthesis of diagnostic test accuracy studies in a host of applications. Meta-analysis has been around for many decades in statistical and related literatures and it has applications in a wide area of biostatistics, medical science and related research. This volume provides a good blend of applications and methodological work.
The book divided into four parts, although Part 4 has only two chapters regarding future research and concluding remarks, respectively. Interestingly, Part 3, which has four chapters based on four separate case studies makes this volume attractive to practitioners. In total, there are 21 chapters in the book. Below is a biased selection of titles of the respective chapters in the book:
Chapter 2. The Evidence Hierarchy
Chapter 3. Peculiarities of Diagnostic Test Accuracy Studies
Chapter 7. Searching for Diagnostic Test Accuracy Studies
Chapter 9. Appraising Evidence
Chapter 10. Synthesizing Evidence
Chapter 11. Appraising Heterogeneity
Chapter 12. Statistical Packages for Diagnostic Meta-Analysis and Their Application
Chapter 13. Network Meta-Analysis of Diagnostic Test Accuracy Studies
Chapter 16. Diagnostic Meta-Analysis: Case Study in Endocrinology
Chapter 17. Diagnostic Meta-Analysis: Case Study in Gastroenterology
Chapter 18. Diagnostic Meta-Analysis: Case Study in Oncology
Chapter 19. Diagnostic Meta-Analysis: Case Study in Surgery
The book is well organized and structured, and topics are presented in a logical manner. Most of the chapters are self-contained. It includes many useful topics and methodologies for practitioners, graduate students and researchers alike in the broad arena of diagnostic meta-analysis. The contributions are presented in a manner that makes it accessible to readers with moderate to strong knowledge of biostatistics and epidemiology. One of the main strengths of the volume is that it provides methodology and concepts which are illustrated with data examples and case studies. The content is useful for practitioners who want to improve decision-making processes in diagnosis and classifications, among others.
In summary, I am happy to conclude that this is a good collection of work in one place. I think this volume will attract a broader audience. I enjoyed reading some of the chapters, especially on Appraising Heterogeneity and Transition to Intervention Meta-Analysis, respectively.
Brock University