The outlook for women with breast cancer has improved in recent years. Due to the combination of improved treatments and the benefits of mammography screening, breast cancer mortality has decreased steadily since 1989. Yet breast cancer remains a major problem, second only to lung cancer as a leading cause of death from cancer for women. To date, no means to prevent breast cancer has been discovered and experience has shown that treatments are most effective when a cancer is detected early, before it has spread to other tissues. These two facts suggest that the most effective way to continue reducing the death toll from breast cancer is improved early detection and diagnosis. Building on the 2001 report Mammography and Beyond, this new book not only examines ways to improve implementation and use of new and current breast cancer detection technologies but also evaluates the need to develop tools that identify women who would benefit most from early detection screening. Saving Women's Lives: Strategies for Improving Breast Cancer Detection and Diagnosis encourages more research that integrates the development, validation, and analysis of the types of technologies in clinical practice that promote improved risk identification techniques. In this way, methods and technologies that improve detection and diagnosis can be more effectively developed and implemented. Table of Contents Front Matter Executive Summary 1 Introduction 2 Benefits and Limitations of Mammography 3 Improving Breast Cancer Screening Services 4 Understanding Breast Cancer Risk 5 Biologically-Based Technologies 6 The Necessary Environment for Research and Development 7 Translating New Technologies into Improved Patient Outcomes 8 Recommendations Appendix A: Breast Cancer Technology Overview Appendix B: Workshop Agendas Appendix C: ROC Analysis: Key Statistical Tool for Evaluating Detection Technologies Appendix D: Common Weaknesses in Study Designs Glossary Index

Interpreting the Volume-Outcome Relationship in the Context of Cancer Care is a summary of a workshop held on May 11, 2000, which brought together experts to review evidence of the relationship between volume of services and health-related outcomes for cancer and other conditions, discuss methodological issues related to the interpretation of the association between volume and outcome, assess the applicability of volume as an indicator of quality of care; and identify research needed to better understand the volume--outcome relationship and its application to quality improvement.

This text focuses on areas of public health practice in which the systematic application of epidemiologic methods can have a large and positive impact. It describes how best to apply traditional epidemiologic methods for determining disease etiology to "real-life" problems in public health and health services research. Brownson and Petitti's much-needed book bridges the gap between theoretical epidemiology and public health practice, and covers a number of topics not addressed by other epidemiology texts with a focus on methods. This second edition contains a new chapter on the development and use of systematic reviews and one on epidemiology and the law. Each chapter includes one or more case studies intended to illustrate major points from the chapter and to provide a basis for teaching exercises. All of the chapters are authored by leading experts in the fields of epidemiology and public health, and all are fully revised and updated.
The book is intended for practitioners in epidemiology as well as for students in epidemiology and related disciplines that rely on epidemiologic methods and reasoning. It is a practical and informative book for use in academic institutions, federal agencies which have significant educational missions, state and local public health agencies, and health care organizations. By providing a resource of immense accessibility to several key audiences, this edition of Applied Epidemiology: Theory to Practice further extends the fields ability to make a real difference on behalf of better health for all.

Meta-analysis, decision analysis, and cost-effectiveness analysis are the cornerstones of evidence-based medicine. These related quantitative methods have become essential tools in the formulation of clinical and public policy based on the synthesis of evidence. All three methods are taught with increasing frequency in medical schools and schools of public health and in health policy courses at the undergraduate and graduate level. This book is a lucid introduction, and will serve the needs of students taking introductory courses that cover these topics. It will also be useful to clinicians and policymakers who need to understand the quantitative underpinnings of the methods in order to best apply the information that derives from them. The second edition of this popular book adds new material on cumulative meta-analysis as a method to explore heterogeneity. The coverage of cost-effectiveness analysis has been brought into close alignment with recommendations of the U.S. Public Health Panel on Cost-Effectiveness Analysis in Health and Medicine. Many of the examples have been replaced with more current examples, and all of the material has been updated to reflect recent advances in the methods and the emergence of consensus about some previously controversial issues. analysis. These three closely related methods have become even more important for synthesizing research since the first edition was published in 1994. And they have gained legitimacy as tools for guiding health policy. In the Second Edition, Petitti has added new material on cumlative meta-analysis and the exploration of heterogeneity, incorporated recommendations for standardizing the conduct of cost-effectiveness analysis, and updated the rest of the text.