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Table 1 Key features and limitations of different approaches to assessing adverse effects of healthcare interventions

From: Drug safety assessment in clinical trials: methodological challenges and opportunities

Study design

Key features


Spontaneous or voluntary reporting systems, including journal-published case reports

Captures very wide range of events

No denominator or control group, difficult to quantify risk


Particularly useful for detecting signals of rare (low background incidence in treated population) and/or unexpected events (e.g., new unrecognized pathology)

Format and type of information differs substantially among regulators and journals


Sophisticated statistical techniques have been developed for signal detection

Clinical details may be incomplete, causality uncertain


Selective reporting or under-reporting of cases

Randomized clinical trials

Randomization reduces possibility of confounding at baseline

Rigid recruitment criteria may lead to exclusion of patients who are at risk of adverse effects


Certain adverse effects can be prospectively specified for detailed monitoring

Powered for detection of significant difference between groups for beneficial effect, estimates for adverse effects may lack precisions


Intervention is typically well defined


Non-randomized studies

‘Real-world’ use with more generalizable data and longer follow-up

Monitoring for rare or unexpected events may be less rigorous, and the trials may not be of sufficient duration to detect long-term problems


Potentially able to specify and assess rare events as primary outcomes in case control designs

Non-randomized nature is susceptible to confounding


May be able to explore relationship to dose, duration and patient susceptibility factors

Drug exposures are often based on computerized records rather than dispensing or actual use

Meta-analysis of controlled observational studies and/or trials

Pooled analysis has greater power to detect significant differences, even with rare events

Reliant on quality of primary data


Missing or unreported data on adverse events is a major problem, as are the statistical techniques of pooling sparse data


Aims to summarize complete data set and can evaluate consistency of findings among studies

Susceptible to selective outcome reporting of primary studies

Heterogeneity within the pooled analysis