ArticleEpidemiology (Cambridge, Mass.)2018
Data Mining for Adverse Drug Events With a Propensity Score-matched Tree-based Scan Statistic.
Article in Epidemiology (Cambridge, Mass.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
What it found
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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
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods for drug safety signal detection using routinely collected observational electronic health care data: A systematic review.Pharmacoepidemiology and drug safety · 2023Pooled it
- Antiemetic Combination Use During the First Trimester and Adverse Circulatory Outcomes in Newborn Infants: A Data-Mining Analysis.Drug safety · 2026Article
- Adverse drug-event detection using the tree-based scan statistics (TreeScan) and comparison with common mining methods: new user, propensity score-matched cohorts.European journal of clinical pharmacology · 2026Article
- Generative Transformers for Pharmacovigilance Signal Detection using Electronic Health Records.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026Article
- Association Discovery Approach in Healthcare Big Data to Identify Drug Safety and Drug Repurposing Signals.Clinical pharmacology and therapeutics · 2026Article
- Mapping the applications and methodological characteristics of the TreeScan method in pharmacovigilance and beyond: a scoping review of 44 studies.Frontiers in pharmacology · 2026Article
- High-Throughput Screening Using the Self-Controlled Tree-Based Scan Statistic to Identify Medications Associated With Hospitalization for Severe Acute Liver Injury.Pharmacoepidemiology and drug safety · 2025Article
- Large-scale Empirical Identification of Candidate Comparators for Pharmacoepidemiological Studies.Drug safety · 2025Article
- Hierarchical clustering analysis to inform classification of congenital malformations for surveillance of medication safety in pregnancy.American journal of epidemiology · 2025Article
- Article
- Tree-based scan statistics to generate drug repurposing hypotheses: a test case using sodium-glucose cotransporter-2 inhibitors.American journal of epidemiology · 2024Article
- An open-source implementation of tree-based scan statistics.Pharmacoepidemiology and drug safety · 2024Article
- Assessing the incidence and severity of drug adverse events: a Bayesian hierarchical cumulative logit model.Journal of biopharmaceutical statistics · 2024Article
- Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study.Drug safety · 2023Article
- A machine learning-based phenotype for long COVID in children: An EHR-based study from the RECOVER program.PloS one · 2023Article
- A machine learning-based phenotype for long COVID in children: an EHR-based study from the RECOVER program.medRxiv : the preprint server for health sciences · 2022Article
- The US Food and Drug Administration Sentinel System: a national resource for a learning health system.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- A tree-based scan statistic for zero-inflated count data in post-market drug safety surveillance.Scientific reports · 2022Article
- Signal Detection of Adverse Events Associated with Trastuzumab in a Cohort of Elderly Patients with Breast Cancer.The oncologist · 2022Article
- Applying Machine Learning in Distributed Data Networks for Pharmacoepidemiologic and Pharmacovigilance Studies: Opportunities, Challenges, and Considerations.Drug safety · 2022Review
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
The tree-based scan statistic is a statistical data mining tool that has been used for signal detection with a self-controlled design in vaccine safety studies. This disproportionality statistic adjusts for multiple testing in evaluation of thousands of potential adverse events. However, many drug safety questions are not well suited for self-controlled analysis. We propose a method that combines tree-based scan statistics with propensity score-matched analysis of new initiator cohorts, a robust design for investigations of drug safety. We conducted plasmode simulations to evaluate performance. In multiple realistic scenarios, tree-based scan statistics in cohorts that were propensity score matched to adjust for confounding outperformed tree-based scan statistics in unmatched cohorts. In scenarios where confounding moved point estimates away from the null, adjusted analyses recovered the prespecified type 1 error while unadjusted analyses inflated type 1 error. In scenarios where confounding moved point estimates toward the null, adjusted analyses preserved power, whereas unadjusted analyses greatly reduced power. Although complete adjustment of true confounders had the best performance, matching on a moderately mis-specified propensity score substantially improved type 1 error and power compared with no adjustment. When there was true elevation in risk of an adverse event, there were often co-occurring signals for clinically related concepts. TreeScan with propensity score matching shows promise as a method for screening and prioritization of potential adverse events. It should be followed by clinical review and safety studies specifically designed to quantify the magnitude of effect, with confounding control targeted to the outcome of interest.
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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.