ArticleStatistical methods in medical research2013
Shrinkage observed-to-expected ratios for robust and transparent large-scale pattern discovery.
Article in Statistical methods in medical research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 184 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
184 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Risk of Death and Adverse Effects in Patients on Liothyronine: A Multisource Systematic Review and Meta-analysis.The Journal of clinical endocrinology and metabolism · 2025Pooled it
- Methods for drug safety signal detection using routinely collected observational electronic health care data: A systematic review.Pharmacoepidemiology and drug safety · 2023Pooled it
- Linezolid-related Optic Nerve Disorders: Insight From a Pharmacovigilance Analysis of the US FDA Adverse Event Reporting System.Open forum infectious diseases · 2025Trial
- Safety Signals of GLP-1 Receptor Agonists: A Multi-Method Pharmacovigilance Analysis of FAERS (2018-2025) With Sensitivity-Stratified Prioritisation, Notoriety-Bias Assessment, and Cross-Database Validation.Diabetes, obesity & metabolism · 2026Article
- Male Reproductive Disorders Associated with Antiseizure Medications: Evidence from Meta-Analysis and FAERS Pharmacovigilance Study.Journal of clinical medicine · 2026Article
- Masking effect in the Spanish spontaneous reporting database FEDRA.European journal of clinical pharmacology · 2026Article
- Multimodal investigation of the association between bevacizumab and pulmonary arterial hypertension.ERJ open research · 2026Article
- Drug Safety and Polypharmacy Signals in Ibrutinib-Treated Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma: Age- and Sex-Specific FAERS Analysis of CYP3A Modifier and Antithrombotic Co-Exposure.Journal of clinical medicine · 2026Article
- The safety profile of lenalidomide, dexamethasone, daratumumab, and bortezomib combinations in multiple myeloma: a retrospective analysis of the FAERS database.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- VigiBase: Resource Profile Update with a Summary of Global Patterns and Trends in Adverse Event Reports for Medicines and Vaccines.Drug safety · 2026Review
- Dysesthesia associated with GLP-1 agonist therapies: data-mining analysis and literature review.European journal of clinical pharmacology · 2026Review
- An updated pharmacovigilance evidence from U.S. tobacco problem reports following the FDA safety communication on e-cigarettes and seizures.BMC public health · 2026Article
- Posterior Reversible Encephalopathy Syndrome with Angiogenesis Inhibitors for Solid Tumours: Clues from a Disproportionality Analysis of the FDA Adverse Event Reporting System and Pharmacodynamics.Targeted oncology · 2026Article
- Neutropenia and infectious events during off-label treatment with venetoclax in children with malignant disease: a pharmacovigilance analysis of FDA adverse event reporting system reports.Annals of hematology · 2026Article
- Drug-Induced Raynaud's Phenomenon and Underlying Mechanism: A Disproportionality Analysis From the World Health Organization Pharmacovigilance Database.Arthritis & rheumatology (Hoboken, N.J.) · 2026Article
- Causal Inference Tools for Pharmacovigilance: Using Causal Graphs to Identify and Address Biases in Disproportionality Analysis.Drug safety · 2026Article
- A pharmacovigilance data-driven approach to reveal high fatal adverse events following checkpoint immunotherapy.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Global insights into [Scientific reports · 2026Article
- Charting and Sidestepping the Pitfalls of Disproportionality Analysis.Drug safety · 2026Review
- Mapping adverse events and monitoring priorities for trastuzumab deruxtecan use in metastatic breast cancer.International journal of surgery (London, England) · 2026Article
124 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large observational data sets are a great asset to better understand the effects of medicines in clinical practice and, ultimately, improve patient care. For an empirical pattern in observational data to be of practical relevance, it should represent a substantial deviation from the null model. For the purpose of identifying such deviations, statistical significance tests are inadequate, as they do not on their own distinguish the magnitude of an effect from its data support. The observed-to-expected (OE) ratio on the other hand directly measures strength of association and is an intuitive basis to identify a range of patterns related to event rates, including pairwise associations, higher order interactions and temporal associations between events over time. It is sensitive to random fluctuations for rare events with low expected counts but statistical shrinkage can protect against spurious associations. Shrinkage OE ratios provide a simple but powerful framework for large-scale pattern discovery. In this article, we outline a range of patterns that are naturally viewed in terms of OE ratios and propose a straightforward and effective statistical shrinkage transformation that can be applied to any such ratio. The proposed approach retains emphasis on the practical relevance and transparency of highlighted patterns, while protecting against spurious associations.
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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.