Writing the Data in Summary Tabulations Section in a PBRER

Summary tabulations convert large volumes of individual safety information into a structured view that can be reviewed across the reporting interval and cumulatively. Their role is descriptive: they show what has been reported and how the data are distributed, while later sections determine what those observations mean scientifically.

Purpose and Regulatory Framework

The PBRER structure is defined by ICH E2C(R2) and, for EU PSURs, implemented through Commission Implementing Regulation (EU) No 520/2012 and GVP Module VII — Periodic safety update report (Rev. 1).

ICH E2C(R2) includes summary tabulations so that the assessor can view important aggregate safety data in a consistent form. The tables support subsequent interpretation but do not replace signal detection, case review, risk evaluation or epidemiological analysis.

What Summary Tabulations Can and Cannot Show

Summary tabulations can help a reviewer see:

• the volume and distribution of reported reactions or events;
• interval versus cumulative patterns;
• serious or fatal report distributions where the applicable table provides them;
• coded patterns by MedDRA terms; and
• changes that may justify further review.

They generally cannot, by themselves, establish:

• incidence or absolute risk;
• a causal relationship;
• a change in true event frequency;
• the existence of a validated safety signal; or
• the effectiveness of a risk-minimisation measure.

Spontaneous-report counts are influenced by exposure, reporting behaviour, geography, stimulated reporting, coding, duplicate management and data-processing changes. A numerical difference is therefore an observation requiring context.

Start With the Dataset, Not the Table

Before medical interpretation begins, the author should understand what data generated the table.

Important dataset questions include:

• What is the data lock point?
• Is the table interval, cumulative or both?
• Which products, formulations and routes are included?
• Which reporting sources contribute data?
• How are clinical-trial and post-marketing data separated where required?
• How are duplicates and follow-up reports handled?
• Which MedDRA version was used?
• Were partner, affiliate or acquired data incorporated?
• Did any database migration or major reconciliation occur?

A perfectly formatted table can still be misleading if the dataset is misunderstood.

Counting Rules Must Be Explicitly Understood

The author should know what each number represents. Depending on the table, a count may refer to:

• cases;
• patients;
• reports;
• reactions/events;
• MedDRA Preferred Terms; or
• another defined unit.

These are not interchangeable. One case can contain several reactions, and multiple follow-up transmissions can relate to one underlying case.

The report does not need to reproduce an entire database specification, but the writing and medical review team must understand the counting logic well enough to avoid false comparisons.

MedDRA and Coding Context

MedDRA provides the standard terminology used to organise many tabulations. Coding changes can alter apparent patterns even when the underlying clinical information has not changed.

Relevant considerations may include:

• MedDRA version changes;
• recoding of historical cases;
• movement between Preferred Terms;
• changes in coding conventions; and
• use of Standardised MedDRA Queries in separate analyses.

A table should therefore be interpreted as coded representation of clinical reports, not as a direct map of disease incidence.

Medical Review of the Tabulations

Review should move from the dataset to the pattern, and only then to individual terms or cases.

A useful sequence is:

1. confirm the dataset and counting rules;
2. compare overall interval and cumulative patterns;
3. identify medically meaningful changes rather than every numerical fluctuation;
4. consider exposure and changes in product use;
5. consider reporting stimulation, coding or database effects;
6. review relevant cases or analyses when a pattern remains important; and
7. carry the scientific conclusion into the appropriate signal or risk section.

Exposure Provides Context, Not a Perfect Denominator

A higher number of reports may simply reflect wider use of the medicine. Conversely, a stable report count during rapidly increasing exposure can mean something different from the same count during declining use.

Exposure estimates should therefore be considered alongside the tabulations. However, spontaneous-report counts and broad exposure estimates often cannot be combined reliably into incidence calculations because the numerator and denominator arise from different data-generation processes.

The author should avoid converting crude reporting counts into apparently precise risk estimates unless the underlying data source supports that analysis.

Stimulated Reporting and Regulatory Events

Reporting can rise after:

• product-information changes;
• a DHPC or public safety communication;
• media attention;
• new literature;
• litigation or public controversy;
• introduction into a new market; or
• increased surveillance.

Such changes can be clinically important because they affect the observed dataset, but they do not automatically indicate a change in intrinsic product risk.

Product Lifecycle and Population Change

The composition of the exposed population can change over time. New indications, formulations, age groups or countries may produce a different event distribution even if the medicine's underlying pharmacology is unchanged.

The reviewer should therefore consider whether apparent changes correspond to:

• a new indication;
• increased use in patients with comorbidities;
• longer treatment duration;
• a new formulation or route;
• wider geographic use; or
• other material changes in clinical practice.

Database and Reconciliation Effects

Apparent increases or decreases may result from changes in data management rather than safety.

Examples include:

• migration of historical cases;
• duplicate clean-up;
• bulk receipt of partner cases;
• MedDRA recoding;
• correction of seriousness or outcome fields;
• delayed literature processing; or
• changes in case-import logic.

When these effects materially alter interpretation, the relevant context should be documented or explained.

When a Pattern Warrants Further Evaluation

A pattern may deserve additional review when it involves, for example:

• a previously unrecognised serious event;
• an unusual cluster of similar clinical presentations;
• a change affecting a known important risk;
• unexpected fatal outcomes;
• a new patient subgroup;
• a medically plausible temporal pattern; or
• a finding consistent with independent evidence from another source.

The next step should be scientific evaluation, not automatic declaration of a signal.

Relationship With Signal Management

Summary tabulations and formal signal management are connected but distinct.

A table can prompt questions that lead to signal detection, but a signal-management system may also identify important issues that are not visually obvious in the PBRER tables.

The PSUR/PBRER should therefore reconcile with the signal system. If a clinically important pattern is discussed in the report, the author should understand whether it has been evaluated as a signal, known risk, coding artefact, exposure effect or other phenomenon.

Relationship With Risk Evaluation

Where tabulations contribute to understanding an important identified or potential risk, the scientific interpretation belongs in the later risk-evaluation sections.

For example, a rise in reports of severe cutaneous reactions may be noted in the tabulation review, but the risk section should integrate case quality, exposure, literature, trials, mechanism and any other relevant evidence before reaching a conclusion.

This prevents the descriptive table section from becoming an unstructured second signal-assessment chapter.

Practical Quality Review

A final review should reconcile the tables to their source logic and to the rest of the PBRER.

Recommended checks include:

1. confirm the DLP and reporting interval;
2. confirm whether counts are interval or cumulative;
3. confirm the unit being counted;
4. verify the applicable MedDRA version and any important recoding effects;
5. check major changes against exposure and utilisation;
6. identify known data migrations or reconciliations that affect comparability;
7. reconcile important observations with the signal-management system;
8. confirm that later risk discussions reflect clinically meaningful findings; and
9. ensure that no descriptive count is presented as incidence or causal proof.

Illustrative Example

Suppose reports coded to a renal-failure Preferred Term increase substantially during the interval.

The table itself supports the statement that more reports were recorded. It does not establish that renal-failure incidence increased.

A competent review would ask whether exposure increased, whether a new high-risk indication was authorised, whether case coding changed, whether a safety communication stimulated reporting, whether the cases share a clinically coherent phenotype and whether independent evidence supports an association. Only after that evaluation should a signal or risk conclusion be reached.

Potential Writing and Review Failure Modes

The following are illustrative failure modes, not inspection findings.

Inspection and Governance Considerations

An inspector or assessor may ask how the organisation knows that the tabulations are complete, reproducible and consistent with the safety database. Relevant evidence may include controlled extraction logic, data-quality checks, reconciliation records, documented counting rules and traceability to the final report.

There is no universal regulatory requirement for one particular spreadsheet, table-production committee or QPPV sign-off step. The quality system should nevertheless ensure that important discrepancies are detected and resolved before submission.

Practical Authoring Checklist

1. Is the dataset scope understood?
2. Is the counting unit clear?
3. Are interval and cumulative data distinguished correctly?
4. Is the MedDRA context known?
5. Are duplicate/follow-up effects understood?
6. Are major database migrations or reconciliation events considered?
7. Are exposure and utilisation changes considered before interpreting trends?
8. Are stimulated-reporting effects considered?
9. Are clinically meaningful findings evaluated outside the table section where appropriate?
10. Does the signal inventory reconcile with important tabulation observations?
11. Are risk conclusions consistent with the observed data?
12. Has the author avoided causal or incidence claims unsupported by the dataset?

Relationship With Other QPPV.com PBRER Articles

For overall report architecture see [[understanding-the-structure-of-a-pbrer]]. For the broader PSUR/PBRER framework see [[pbrer-guide]]. Detailed authoring guidance is available in [[how-to-write-a-pbrer]], [[writing-the-evaluation-of-risks-and-new-information-section-in-a-pbrer]] and [[writing-the-signal-evaluation-section-in-a-pbrer]].

Key Takeaways

Summary tabulations organise safety-report data; they do not independently establish causality, incidence or a safety signal.

The author should understand the dataset, counting rules, coding conventions and important data-management changes before interpreting patterns.

Numerical changes require clinical context, including exposure, utilisation, stimulated reporting and independent evidence.

The table section should remain descriptive. Scientific conclusions should be carried into signal and risk evaluation, where all relevant evidence can be integrated.

References

1. International Council for Harmonisation. ICH E2C(R2): Periodic Benefit-Risk Evaluation Report (PBRER). Step 4, 15 November 2012.
2. International Council for Harmonisation. ICH E2C(R2) Questions and Answers. Last update 31 March 2014.
3. European Medicines Agency. Guideline on good pharmacovigilance practices (GVP) Module VII — Periodic safety update report (Rev. 1). EMA/816292/2011 Rev. 1.
4. European Medicines Agency. Periodic safety update reports (PSURs). Current procedural guidance.
5. MedDRA Maintenance and Support Services Organization. MedDRA terminology and versioning documentation. Current applicable release information.
6. European Union. Commission Implementing Regulation (EU) No 520/2012, as amended.
7. European Union. Directive 2001/83/EC, as amended.
8. European Union. Regulation (EC) No 726/2004, as amended.

Regulatory Note

This article describes authoring and review of the PBRER/PSUR summary-tabulation section. It distinguishes required aggregate presentation from subsequent scientific interpretation. As of 9 September 2026, GVP Module VII Rev. 1 remains the published EMA module. Current MedDRA and EMA procedural requirements should be confirmed for each live report.