Summarising the Evidence for Drug Safety: A Methodological Discussion of Different Meta-Analysis Approaches

Clinical Imaging Research: Higher Evidence, Global Collaboration, Improved Reporting, and Data Sharing Are the Grand Challenges

The four grand challenges of imaging research—increasing evidence levels, enhancing global collaboration, improving research reporting quality, and sharing trial data—can be addressed, utilizing the tail wind of digital transformation, by consolidating actions of all stakeholders, with the ultimate goal of evidence-based, reproducible, generalizable, and broadly accepted results that will improve the quality and consistency of patient care.

Bias in pharmacoepidemiologic studies using secondary health care databases: a scoping review

BACKGROUND

The availability of clinical and therapeutic data drawn from medical records and administrative databases has entailed new opportunities for clinical and epidemiologic research. However, these databases present inherent limitations which may render them prone to new biases. We aimed to conduct a structured review of biases specific to observational clinical studies based on secondary databases, and to propose strategies for the mitigation of those biases.

METHODS

Scoping review of the scientific literature published during the period 2000-2018 through an automated search of MEDLINE, EMBASE and Web of Science, supplemented with manually cross-checking of reference lists. We included opinion essays, methodological reviews, analyses or simulation studies, as well as letters to the editor or retractions, the principal objective of which was to highlight the existence of some type of bias in pharmacoepidemiologic studies using secondary databases.

RESULTS

A total of 117 articles were included. An increasing trend in the number of publications concerning the potential limitations of secondary databases was observed over time and across medical research disciplines. Confounding was the most reported category of bias (63.2% of articles), followed by selection and measurement biases (47.0% and 46.2% respectively). Confounding by indication (32.5%), unmeasured/residual confounding (28.2%), outcome misclassification (28.2%) and "immortal time" bias (25.6%) were the subcategories most frequently mentioned.

CONCLUSIONS

Suboptimal use of secondary databases in pharmacoepidemiologic studies has introduced biases in the studies, which may have led to erroneous conclusions. Methods to mitigate biases are available and must be considered in the design, analysis and interpretation phases of studies using these data sources.

Primary versus secondary source of data in observational studies and heterogeneity in meta-analyses of drug effects: a survey of major medical journals

Background

The data from individual observational studies included in meta-analyses of drug effects are collected either from ad hoc methods (i.e. “primary data”) or databases that were established for non-research purposes (i.e. “secondary data”). The use of secondary sources may be prone to measurement bias and confounding due to over-the-counter and out-of-pocket drug consumption, or non-adherence to treatment. In fact, it has been noted that failing to consider the origin of the data as a potential cause of heterogeneity may change the conclusions of a meta-analysis. We aimed to assess to what extent the origin of data is explored as a source of heterogeneity in meta-analyses of observational studies.

Methods

We searched for meta-analyses of drugs effects published between 2012 and 2018 in general and internal medicine journals with an impact factor > 15. We evaluated, when reported, the type of data source (primary vs secondary) used in the individual observational studies included in each meta-analysis, and the exposure- and outcome-related variables included in sensitivity, subgroup or meta-regression analyses.

Results

We found 217 articles, 23 of which fulfilled our eligibility criteria. Eight meta-analyses (8/23, 34.8%) reported the source of data. Three meta-analyses (3/23, 13.0%) included the method of outcome assessment as a variable in the analysis of heterogeneity, and only one compared and discussed the results considering the different sources of data (primary vs secondary).

Conclusions

In meta-analyses of drug effects published in seven high impact general medicine journals, the origin of the data, either primary or secondary, is underexplored as a source of heterogeneity.

Electronic supplementary material

The online version of this article (10.1186/s12874-018-0561-3) contains supplementary material, which is available to authorized users.