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E-raamat: Methods in Comparative Effectiveness Research

Edited by , Edited by (Brown University, Providence, Rhode Island, USA)
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Comparative effectiveness research (CER) is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care (IOM 2009). CER is conducted to develop evidence that will aid patients, clinicians, purchasers, and health policy makers in making informed decisions at both the individual and population levels. CER encompasses a very broad range of types of studiesexperimental, observational, prospective, retrospective, and research synthesis.

This volume covers the main areas of quantitative methodology for the design and analysis of CER studies. The volume has four major sectionscausal inference; clinical trials; research synthesis; and specialized topics. The audience includes CER methodologists, quantitative-trained researchers interested in CER, and graduate students in statistics, epidemiology, and health services and outcomes research. The book assumes a masters-level course in regression analysis and familiarity with clinical research.

Arvustused

". . . the book edited by Gatsonis and Morton fills a gap and seems very valuable for applied statisticians interested in the field of comparative effectiveness research particularly due to the selection of relevant topics and the scientific quality of the individual chapters written by leaders in the field." ~Christian Stock, Biometrical Journal

"In summary, the book covers a wide range of topics in CER with a good balance of methodology and practical considerations. Given that CER is a fast-growing area and is relatively unfamiliar to pharmaceutical statisticians, this book will be useful either as a general reference for those working in medical affairs or health technology assessment, or for those looking for a short introduction to a specific method (e.g., NMA)... In general, the book is quite readable without much prerequisite for statistical knowledge and will be useful to applied statisticians who are working in relevant areas or have an interest in CER." ~Pharmaceutical Statistics

Contributors xi
Introduction xv
Section I Causal Inference Methods
1 An Overview of Statistical Approaches for Comparative Effectiveness Research
3(36)
Lauren M. Kunz
Sherri Rose
Donna Spiegelman
Sharon-Lise T. Normand
2 Instrumental Variables Methods
39(68)
Michael Baiocchi
Jing Cheng
Dylan S. Small
3 Observational Studies Analyzed Like Randomized Trials and Vice Versa
107(24)
Miguel A. Hernan
James M. Robins
Section II Clinical Trials: Design, Interpretation, and Generalizability
4 Cluster-Randomized Trials
131(26)
Ken Kleinman
5 Bayesian Adaptive Designs
157(20)
Jason T. Connor
6 Generalizability of Clinical Trials Results
177(26)
Elizabeth A. Stuart
7 Combining Information from Multiple Data Sources: An Introduction to Cross-Design Synthesis with a Case Study
203(24)
Joel B. Greenhouse
Heather D. Anderson
Jeffrey A. Bridge
Anne M. Libby
Robert Valuck
Kelly J. Kelleher
8 Heterogeneity of Treatment Effects
227(46)
Issa J. Dahabreh
Thomas A. Trikalinos
David M. Kent
Christopher H. Schmid
9 Challenges in Establishing a Hierarchy of Evidence
273(28)
Robert T. O'Neill
Section III Research Synthesis
10 Systematic Reviews with Study-Level and Individual Patient-Level Data
301(40)
Joseph Lau
Sally C. Morton
Thomas A. Trikalinos
Christopher H. Schmid
11 Network Meta-Analysis
341(44)
Orestis Efthimiou
Anna Chaimani
Dimitris Mavridis
Georgia Salanti
12 Bayesian Network Meta-Analysis for Multiple Endpoints
385(24)
Hwanhee Hong
Karen L. Price
Haoda Fu
Bradley P. Carlin
13 Mathematical Modeling
409(40)
Mark S. Roberts
Kenneth J. Smith
Jagpreet Chhatwal
Section IV Special Topics
14 On the Use of Electronic Health Records
449(34)
Sebastien J-P.A. Haneuse
Susan M. Shortreed
15 Evaluating Personalized Treatment Regimes
483(16)
Eric B. Laber
Min Qian
16 Early Detection of Diseases
499(20)
Sandra Lee
Marvin Zelen
17 Evaluating Tests for Diagnosis and Prediction
519(16)
Constantine Gatsonis
Index 535
Constantine Gatsonis is Henry Ledyard Goddard University Professor, Chair of the Department of Biostatistics, and founding Director of the Center for Statistical Sciences at the Brown University School of Public Health. Dr. Gatsonis is a Fellow of the American Statistical Association (ASA) and received a Long-Term Excellence Award from the Health Policy Statistics Section of ASA.

Sally C. Morton is Dean of the College of Science at Virginia Tech. Previously, she was Professor and Chair of the Department of Biostatistics in the Graduate School of Public Health, and Director of the Comparative Effectiveness Research Center in the Health Policy Institute, at the University of Pittsburgh. Dr. Morton is a Fellow and past president of the ASA and received the association's Founders Award.