SECTION I -- 1. Introduction to Clinical Diagnosis -- 2. The Evidence Hierarchy -- 3. Peculiarities of Diagnostic Test Accuracy Studies -- 4. Meta-analyses of Clinical Trials vs Diagnostic Test Accuracy Studies -- SECTION II -- 5. Designing the Review -- 6. Registering the review -- 7. Searching for Diagnostic Test Accuracy Studies -- 8. Abstracting Evidence -- 9. Appraising Evidence -- 10. Synthesizing Evidence -- 11. Appraising Heterogeneity -- 12. Statistical Packages and Diagnostic Meta-analysis and Their Application -- 13. Network Meta-analysis of Diagnostic Test Accuracy Studies -- 14. Transition to Intervention Meta-analysis -- 15. Updating Diagnostic Test Accuracy Systematic Reviews: Which, When and How Should They be Updated? -- SECTION III -- 16. Diagnostic Meta-Analysis: Case Study in Endocrinology -- 17. Diagnostic Meta-Analysis: Case Study in Gastroenterology -- 18. Diagnostic Meta-Analysis: Case Study in Oncology -- 19. Diagnostic Meta-analysis: Case Study in Surgery -- SECTION IV -- 20. Avenues for Further Research -- 21. Conclusion.

This book is the first exclusively devoted to the systematic synthesis of diagnostic test accuracy studies. It builds upon the major recent developments in reporting standards, search methods, and, in particular, statistical tools specifically devoted to diagnostic studies. In addition, it borrows extensively from the latest advances in systematic reviews and meta-analyses of intervention studies. After a section dedicated to methods for designing reviews, synthesizing evidence and appraising inconsistency in research, the application of these approaches is demonstrated in the context of case studies from various clinical disciplines. Diagnosis is central in medical decision-making, and in many other fields of human endeavor, such as education and psychology. The plurality of sources of evidence on diagnostic test accuracy poses a huge challenge for practitioners and researchers, as do the multiple dimensions of evidence validity, which include sensitivity, specificity, predictive values, and likelihood ratios. This book offers an invaluable resource for anyone aiming to improve decision-making processes in diagnosis, classification or risk prognostication, from epidemiologists to biostatisticians, radiologists, laboratory physicians and graduate students, as any physician interested in refining his methodological skills in clinical diagnosis.