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Home > Standards & Guidances > Methodological Guide

ENCePP Guide on Methodological Standards in Pharmacoepidemiology

 

10.1.1. Introduction

Comparative effectiveness research (CER) is designed to inform health-care decisions at the level of both policy and the individual by comparing the benefits and harms of therapeutic strategies available in routine practice, for the prevention, the diagnosis or the treatment of a given health condition. The interventions under comparison may be related to similar treatments, such as competing drugs, or different approaches, such as surgical procedures and drug therapy. The comparison may focus only on the relative medical benefits and risks of the different options or it may weigh both their costs and their benefits. The methods of comparative effectiveness research (Annu Rev Public Health 2012;33:425-45) defines the key elements of CER as (a) head-to-head comparison of active treatments, (b) study populations typical of day-to-day clinical practice, and (c) a focus on evidence to inform health care tailored to the characteristics of individual patients. In What is Comparative Effectiveness Research, the AHRQ highlights that CER requires the development, expansion and use of a variety of data sources and methods to conduct timely and relevant research and disseminate the results in a form that is quickly usable. The evidence may come from a review and synthesis of available evidence from existing clinical trials or observational studies or from the conduct of studies that generate new evidence. In Developing a Protocol for Observational Comparative Effectiveness Research: A User’s Guide, AHRQ also highlights that CER is still a relatively new field of enquiry that has its origin across multiple disciplines and is likely to evolve and be refined over time.

 

Among resources for keeping up with the evolution in this field, the US National Library of Medicine provides a web site for queries on CER.

 

The terminology ‘Relative effectiveness assessment (REA)’ is also used when comparing multiple technologies or a new technology against standard of care, while ‘rapid’ REA refers to performing an assessment within a limited timeframe in the case of a new marketing authorisation or a new indication granted for an approved medicine (What is a rapid review? A methodological exploration of rapid reviews in Health Technology Assessments. Int J Evid Based Healthc. 2012;10(4):397-410).

 

 

Individual Chapters:

 

1. Introduction

2. Formulating the research question

3. Development of the study protocol

4. Approaches to data collection

4.1. Primary data collection

4.1.1. Surveys

4.1.2. Randomised clinical trials

4.2. Secondary data collection

4.3. Patient registries

4.3.1. Definition

4.3.2. Conceptual differences between a registry and a study

4.3.3. Methodological guidance

4.3.4. Registries which capture special populations

4.3.5. Disease registries in regulatory practice and health technology assessment

4.4. Spontaneous report database

4.5. Social media and electronic devices

4.6. Research networks

4.6.1. General considerations

4.6.2. Models of studies using multiple data sources

4.6.3. Challenges of different models

5. Study design and methods

5.1. Definition and validation of drug exposure, outcomes and covariates

5.1.1. Assessment of exposure

5.1.2. Assessment of outcomes

5.1.3. Assessment of covariates

5.1.4. Validation

5.2. Bias and confounding

5.2.1. Selection bias

5.2.2. Information bias

5.2.3. Confounding

5.3. Methods to handle bias and confounding

5.3.1. New-user designs

5.3.2. Case-only designs

5.3.3. Disease risk scores

5.3.4. Propensity scores

5.3.5. Instrumental variables

5.3.6. Prior event rate ratios

5.3.7. Handling time-dependent confounding in the analysis

5.4. Effect measure modification and interaction

5.5. Ecological analyses and case-population studies

5.6. Pragmatic trials and large simple trials

5.6.1. Pragmatic trials

5.6.2. Large simple trials

5.6.3. Randomised database studies

5.7. Systematic reviews and meta-analysis

5.8. Signal detection methodology and application

6. The statistical analysis plan

6.1. General considerations

6.2. Statistical analysis plan structure

6.3. Handling of missing data

7. Quality management

8. Dissemination and reporting

8.1. Principles of communication

8.2. Communication of study results

9. Data protection and ethical aspects

9.1. Patient and data protection

9.2. Scientific integrity and ethical conduct

10. Specific topics

10.1. Comparative effectiveness research

10.1.1. Introduction

10.1.2. General aspects

10.1.3. Prominent issues in CER

10.2. Vaccine safety and effectiveness

10.2.1. Vaccine safety

10.2.2. Vaccine effectiveness

10.3. Design and analysis of pharmacogenetic studies

10.3.1. Introduction

10.3.2. Identification of generic variants

10.3.3. Study designs

10.3.4. Data collection

10.3.5. Data analysis

10.3.6. Reporting

10.3.7. Clinical practice guidelines

10.3.8. Resources

Annex 1. Guidance on conducting systematic revies and meta-analyses of completed comparative pharmacoepidemiological studies of safety outcomes