ReviewPharmacoepidemiology and drug safety2026
A Methodological Review of Simulation Studies Published in Pharmacoepidemiology and Drug Safety.
Review in Pharmacoepidemiology and drug safety, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A Methodological Review of Simulation Studies Published in Pharmacoepidemiology and Drug Safety.Pharmacoepidemiology and drug safety · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
purposeSimulation studies are used in pharmacoepidemiology for evaluating statistical methods in a controlled setting, whereby a known data-generating mechanism allows evaluation of the performance of different approaches and assumptions. This study aimed to review simulation studies performed in pharmacoepidemiology.
methodsWe conducted a review of all papers published in the journal of Pharmacoepidemiology and Drug Safety (PDS) over the period 2017-2024. We extracted data on study characteristics and key simulation choices such as the type of data-generating mechanism used, inferential methods tested and simulation size.
resultsAmong 42 simulation studies included, 34 (81%) were informing comparative effectiveness/safety studies. Twenty-two studies (52%) used simulation in the context of a clinical condition, and 36 (86%) used Monte-Carlo simulation. Inputs not derived from empirical data alone (n = 22, 52%) or in combination with real-world data sources (n = 19, 45%) were most often used for data generation. The complexity of simulations was often relatively low: although 31 studies (74%) generated data based on other covariates, time-dependent covariates (n = 3) and effects (n = 4) were rarely implemented. Bias was the most often used performance measure (n = 26, 62%), although notably 18 studies (43%) did not report uncertainty in the method.
conclusionSimulations contributed a relatively small number of articles (3.2% of 1320) to PDS over 2017-2024. Greater focus on evaluating methods and inferential approaches, using simulation studies that are appropriately complex given clinical realities, may be beneficial to the pharmacoepidemiology field.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.