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Clinical Epidemiology: Principles, Methods, and Applications for Clinical Research

Author(s): Diederick E. Grobbee, MD, PhD, Professor of Clinical Epidemiology, Chair, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, UTRECHT, Netherlands
Arno W. Hoes, MD, PhD, Professor of Clinical Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
Details:
  • ISBN-13: 9780763753153
  • ISBN-10:0763753157
  • Paperback    413 pages      © 2009
Price: International Sales $103.95 US List
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Overview

In the current era of evidence-based medicine, clinical epidemiology is increasingly recognized as an essential tool in the critical appraisal of available evidence and the design of new studies. 

Clinical Epidemiology: Principles, Methods, and Applications for Clinical Research is a comprehensive resource that introduces the reader to the basics of clinical epidemiology and explores the principles and methods that can be used to obtain quantitative evidence on the effects of interventions and on the diagnosis, etiology, and prognosis of disease. 

The everyday challenges of clinical research and the quantitative knowledge required to practice medicine are also examined, making this book a valuable reference for both graduate and undergraduate students in medicine and related disciplines, as well as for professionals involved in the design and conduct of clinical research. 

Key Features:

  • Worked-out examples from daily clinical practice included in all sections.
  • Relevant clinical research that can be used as exercises.
  • Several chapters devoted to research assessing the main and adverse effects of interventions, including introductions to clinical trials.
  • Common study designs (such as meta-analyses, case-control studies and randomized trials), as well as elementary data-analytical issues.


ShowTable of Contents

Preface

The Julius Center

About the Authors

Contributors

Acknowledgements

CHAPTER 1 INTRODUCTION

Clinical epidemiology

Research relevant to patient care

Epidemiologic study design

Theoretical design

Design of data collection

Design of data analysis

Diagnostic, etiologic, prognostic and intervention research

Shared and disparate aspects of diagnostic and prognostic research

Shared and disparate aspects of etiologic and prognostic research

Moving from research to practice: relevance and generalizability

CHAPTER 2 Etiologic research

Theoretical design

Confounding

Handling of confounding

Causality

Modification and interaction

Measurement of modification

Modifiers and confounders

Design of data collection: cohorts, cases or experimentation

Design of data analysis: measures of association

Common etiologic questions in clinical epidemiology

Etiologic research: worked out example

CHAPTER 3 Diagnostic research

             Diagnosis in clinical practice

From diagnosis in clinical practice to diagnostic research

Diagnostic research versus test research

Rational diagnostic research

Theoretical design

Design of data collection

Bias in diagnostic research

Design of data analysis

Worked-out example

CHAPTER 4 Prognostic research

Prognosis in clinical practice

Motive and aim of prognosis

The format of prognoses

Approaches to prognostication

Prognostication is a multivariable process

Added prognostic value

From prognosis in clinical practice to prognostic research

The predictive nature of prognostic research

Appraisal of prevailing prognostic research

Rational prognostic research

Theoretical design

Design of data collection

Bias in prognostic research

Design of data analysis

Worked-out example

CHAPTER 5 Intervention research: Main effects

Learning about effects of intervention

Natural history

Extraneous effects

Observer effects

The treatment effect

Comparability of natural history

Randomization

Comparability of extraneous effects

Comparability of observations

Limits to trials

The randomized trial as a paradigm for etiologic research

CHAPTER 6 Intervention research: side effects

Research on side effects of interventions

Studies on side effects of interventions: causal research

Type A and type B side effects

Theoretical design

Design of data collection

Comparability of observations in observational research on side effects

Comparability of extraneous effects in observational research on side effects

Comparability of natural history effects in observational research on side effects

Methods to limit confounding in observational studies on side effects of interventions

Methods to limit confounding in the design of data collection

Methods to limit confounding in the design of data collection

Health care databases as framework for research on side effects of interventions

CHAPTER 7 Design of data collection

Time

Census or sampling

Experimental or observational

Taxonomy of epidemiologic data collection

CHAPTER 8 Cohort and cross-sectional studies

Timing of the association relative to the timing of data collection

Causal and descriptive cohort studies

Experimental cohort studies

Cross-sectional studies

Ecologic studies

Cohort studies using routine care data

Limitations to cohort studies

Worked out example (SMART)

CHAPTER 9 Case-control studies

Rationale and essence of case-control studies

A brief history of case-control studies in clinical research

Theoretical design

Design of data collection

Swimming-pool, a life-guard chair and a net

Identification of cases

Sampling of controls: the study base (or “swimming-pool”) principle

Specific types of control series

Multiple control series?

Matching of cases and controls?

Design of data-analysis in case-control studies

Case-cohort studies

Case-crossover studies

Case-control studies with no controls

Advantages and limitations of case-control studies

Worked-out example

CHAPTER 10 Randomized trials

‘Regular’ parallel, factorial, cross-over and cluster trials

Participants

Treatment allocation and randomization

Informed consent

Blinding

Outcome

Design of data analysis

CHAPTER 11 Meta-analyses

Rationale of meta-analysis

Principles of meta-analysis

Theoretical design and research question

Design of data collection

Critical appraisal

Design of data analysis

Reporting results from meta-analysis

Inferences from meta-analysis

CHAPTER 12 Clinical Epidemiologic Data Analysis

Measures of Disease Frequency: Incidence and Prevalence

Data-analytical strategies in clinical epidemiology research

The relationship between determinant and outcome

Adjustment for confounding

Regression analysis

Frequentists and Baysians

 

 

References

Index


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ShowAbout the Author(s)

Diederick E. Grobbee, MD, PhD-Professor of Clinical Epidemiology, Chair, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, UTRECHT, Netherlands

Diederick E. Grobbee, MD, PhD (1957) was trained in medicine in Utrecht and, after a residency in internal medicine, obtained a PhD in epidemiology at Erasmus University in Rotterdam. His education was continued at McGill University in Montreal and as a visiting associate professor at Harvard University School of Public Health. He spent about a decade at Erasmus were he headed the cardiovascular epidemiology group and was appointed professor of clinical epidemiology. He subsequently moved to the University Medical Center Utrecht, to become professor of clinical epidemiology and chairman of the Julius Center for Health Sciences and Primary Care. He is program director of the international MSc Epidemiology program at Utrecht University and board member of the Netherlands Institute for Health Sciences. Diederick Grobbee is on the board of the Academic Alliance for Clinical Trials and is a board member of the Medical Advisory Council of the Royal Netherlands Academy for Arts and Sciences. He is editor of the European Journal of Epidemiology. His teaching experience includes courses on clinical epidemiology and clinical research methods to various audiences in several countries.

Arno W. Hoes, MD, PhD-Professor of Clinical Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands

Arno W. Hoes, MD, PhD (1958) studied medicine at the Catholic University Nijmegen. He obtained his PhD degree in clinical epidemiology at the Erasmus Medical Center in Rotterdam. He was futher trained in clinical epidemiology at the London School of Hygiene and Tropical Medicine. In 1991 he was appointed assistant professor of clinical epidemiology and general practice at both the Department of Epidemiology & Biostatistics and the Department of General Practice at the Erasmus Medical Center. At the latter department he headed the research line “Cardiovascular disease in primary care”. In 1996, he moved to the Julius Center for Health Sciences and Primary Care of the University Medical Center in Utrecht, where he was appointed professor of Clinical Epidemiology and Primary Care in 1998. He is currently director of research of the Julius Center. His teaching experience includes courses on study design, clinical epidemiology, diagnostic research, drug risk assessment and cardiovascular disease. Since 1998 he is a member of the Dutch Medicines Evaluation Board.

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