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Home > Standards & Guidances > Methodological Guide

ENCePP Guide on Methodological Standards inPharmacoepidemiology

 

Section 7.2. Guidelines on communication of studies

The ISPE GPP contain a section on communication (section V) which includes a statement that there is an ethical obligation to disseminate findings of potential scientific or public health importance and that research sponsors (government agencies, private sector, etc.) shall be informed of study results in a manner that complies with local regulatory requirements. The Guidance on the format and content of the final study report of non-interventional post-authorisation safety studies (PASS) provides a template for final study reports that may be applied to all non-interventional PASS, including meta-analyses and systematic reviews. The FDA’s Best Practices for Conducting and Reporting Pharmacoepidemiologic Safety Studies Using Electronic Health Care Data Sets includes a description of all the elements that should be addressed and included in the final study report of such studies.

 

The Enhancing the Quality and Transparency of Health Research (EQUATOR) network is an international initiative that aims to enhance the reliability and value of the published health research literature. A catalogue of reporting guidelines for health research (Eur J Clin Invest 2010;40(1):35-53) presents a collection of tools and guidelines available on the EQUATOR website relating to resources, education and training to facilitate good research reporting and the development, dissemination and implementation of robust reporting guidelines to increase the accuracy and transparency of health research reporting.

 

The Strengthening the Reporting of Observational studies in Epidemiology (STROBE) Statement Guidelines for reporting observational studies has established recommendations for improving the quality of reporting of observational studies and seeks to ensure a clear presentation of what was planned, done, and found. Of note, the aim of these guidelines was not to prescribe the reporting of observational research in a rigid format, but to address what should be the critical information that a publication on an observational study should contain. In this regard, the guidance provided is complete, with practical examples that facilitate interpretation and understanding of the recommendations, though it is of limited usefulness for the design and conduct of epidemiological research projects.

 

The STROBE statement is designed to apply to all observational studies.  The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement (PLoS Med. 2015;12(10):e1001885) was created as an extension to the STROBE statement to address reporting items specific to observational studies using routinely collected health data. RECORD makes additional recommendations on the reporting of methods of selection for study populations, exposures, outcomes and covariates (including codes or algorithms used), whether validation has been conducted, the level of access to databases used, and data linkages that were required to conduct the study.

 

The Meta-analysis of Observational Studies in Epidemiology (MOOSE) group has developed a consensus statement and recommendations for reporting meta-analyses of observational studies in epidemiology. It is equivalent to the STROBE Statement Guidelines for reporting observational studies and the Consolidated Standards of Reporting Trials Consolidated Standards for Reporting Trials (CONSORT) 2010 Statement for RCTs, in that they have communication as their primary objective and take the form of a list of minimum requirements for adequate reporting. The authors recommend a broad inclusion of studies and to conduct post-hoc sensitivity on the dependence of the results on factors, such as quality of underlying papers, design, accounting for confounders etc. The authors comment on the particular problems in merging observational studies with highly variable sets of confounders that were or were not controlled for, but they do not suggest any solution or give any references to possible ways to address it.

 

The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) Statement is an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses consisting of a 27-item checklist and a flow diagram. While focused on randomised trials, PRISMA can also be used as a basis for reporting systematic reviews of other types of research, particularly evaluations of interventions. PRISMA may also be useful for critical appraisal of published systematic reviews, although it is not a quality assessment instrument to gauge the quality of a systematic review.

 

Additional guidance is provided in the ENCePP Checklist for Study Protocols and Code of Conduct and the IEA GEP guideline that have been reviewed elsewhere in this Guide.

Some of the points that are emphasised by the cited guidelines are:

  • Sources of research funding should always be disclosed whether in oral or written presentation.

  • A dissemination and communication strategy should be pre-defined as part of the funding contract.

  • All results with a scientific or public health impact must be made publicly available without undue delay.

  • Quantitative measures of association should be reported rather than just results of testing.

Authorship should conform to the guidelines established by the International Committee of Medical Journal Editors (ICJME)Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly work in Medical Journals’.

 

Individual Chapters:

 

1. General aspects of study protocol

2. Research question

3. Approaches to data collection

3.1. Primary data collection

3.2. Secondary use of data

3.3. Research networks

3.4. Spontaneous report database

3.5. Using data from social media and electronic devices as a data source

3.5.1. General considerations

4. Study design and methods

4.1. General considerations

4.2. Challenges and lessons learned

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

4.2.1.1. Assessment of exposure

4.2.1.2. Assessment of outcomes

4.2.1.3. Assessment of covariates

4.2.1.4. Validation

4.2.2. Bias and confounding

4.2.2.1. Choice of exposure risk windows

4.2.2.2. Time-related bias

4.2.2.2.1. Immortal time bias

4.2.2.2.2. Other forms of time-related bias

4.2.2.3. Confounding by indication

4.2.2.4. Protopathic bias

4.2.2.5. Surveillance bias

4.2.2.6. Unmeasured confounding

4.2.3. Methods to handle bias and confounding

4.2.3.1. New-user designs

4.2.3.2. Case-only designs

4.2.3.3. Disease risk scores

4.2.3.4. Propensity scores

4.2.3.5. Instrumental variables

4.2.3.6. Prior event rate ratios

4.2.3.7. Handling time-dependent confounding in the analysis

4.2.4. Effect modification

4.3. Ecological analyses and case-population studies

4.4. Hybrid studies

4.4.1. Pragmatic trials

4.4.2. Large simple trials

4.4.3. Randomised database studies

4.5. Systematic review and meta-analysis

4.6. Signal detection methodology and application

5. The statistical analysis plan

5.1. General considerations

5.2. Statistical plan

5.3. Handling of missing data

6. Quality management

7. Communication

7.1. Principles of communication

7.2. Guidelines on communication of studies

8. Legal context

8.1. Ethical conduct, patient and data protection

8.2. Pharmacovigilance legislation

8.3. Reporting of adverse events/reactions

9. Specific topics

9.1. Comparative effectiveness research

9.1.1. Introduction

9.1.2. General aspects

9.1.3. Prominent issues in CER

9.1.3.1. Randomised clinical trials vs. observational studies

9.1.3.2. Use of electronic healthcare databases

9.1.3.3. Bias and confounding in observational CER

9.2. Vaccine safety and effectiveness

9.2.1. Vaccine safety

9.2.1.1. General aspects

9.2.1.2. Signal detection

9.2.1.3. Signal refinement

9.2.1.4. Hypothesis testing studies

9.2.1.5. Meta-analyses

9.2.1.6. Studies on vaccine safety in special populations

9.2.2. Vaccine effectiveness

9.2.2.1. Definitions

9.2.2.2. Traditional cohort and case-control studies

9.2.2.3. Screening method

9.2.2.4. Indirect cohort (Broome) method

9.2.2.5. Density case-control design

9.2.2.6. Test negative design

9.2.2.7. Case coverage design

9.2.2.8. Impact assessment

9.2.2.9. Methods to study waning immunity

9.3. Design and analysis of pharmacogenetic studies

9.3.1. Introduction

9.3.2. Identification of genetic variants

9.3.3. Study designs

9.3.4. Data collection

9.3.5. Data analysis

9.3.6. Reporting

9.3.7. Clinical practice guidelines

9.3.8. Resources

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