ArticleJMIR medical informatics2016
Population Analysis of Adverse Events in Different Age Groups Using Big Clinical Trials Data.
Article in JMIR medical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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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
18 citing papers in PubMed.
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- Nitrous oxide for late-life depression with inadequate antidepressant response: a randomised controlled trial.EClinicalMedicine · 2026Article
- Quantification of Age and Sex Ratio Differences between Trial and Target Population for New Drugs.Clinical pharmacology and therapeutics · 2026Article
- Patient Safety Events and Additional Hospital Stay and Direct Cost among Pediatric Patients in a Philippine Tertiary Government Hospital.Acta medica Philippina · 2026Article
- Exploring scalable assessment methods for terminated trials in ClinicalTrials.gov: A cohort analysis of German and Californian trials.PloS one · 2026Article
- Unwanted or negative treatment reactions in digital psychological interventions for adolescents with chronic pain.Journal of pediatric psychology · 2025Article
- Evaluating the Real-World Use of Topical Diclofenac Sodium Gel 1% Using US Longitudinal Electronic Health Records Database: A study supporting OTC switch.Pain and therapy · 2025Article
- Patients Safety Events at Philippine General Hospital.Acta medica Philippina · 2025Article
- Article
- Response to Comment on "Exercise Snacks and Other Forms of Intermittent Physical Activity for Improving Health in Adults and Older Adults: A Scoping Review of Epidemiological, Experimental and Qualitative Studies".Sports medicine (Auckland, N.Z.) · 2024Article
- Out-of-hours emergent surgery for degenerative spinal disease in Canada: a retrospective cohort study from a national registry.Lancet regional health. Americas · 2024Article
- The effect of age and resilience on the dose-response function between the number of adversity factors and subjective well-being.Frontiers in psychology · 2024Article
- Safety and effectiveness of vortioxetine for major depressive disorder: Real-world evidence from a population-based study in South Korea.Frontiers in psychiatry · 2023Article
- Assessing the quality of evidence on safety: specifications for application and suggestions for adaptions of the GRADE-criteria in the context of preparing a list of potentially inappropriate medications for older adults.BMC medical research methodology · 2022Article
- A Computational Framework for Identifying Age Risks in Drug-Adverse Event Pairs.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2022Article
- Observed and expected serious adverse event rates in randomised clinical trials for hypertension: an observational study comparing trials that do and do not focus on older people.The lancet. Healthy longevity · 2021Observational
- Article
- Making Sense of Big Textual Data for Health Care: Findings from the Section on Clinical Natural Language Processing.Yearbook of medical informatics · 2017Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUnderstanding adverse event patterns in clinical studies across populations is important for patient safety and protection in clinical trials as well as for developing appropriate drug therapies, procedures, and treatment plans.
objectivesThe objective of our study was to conduct a data-driven population-based analysis to estimate the incidence, diversity, and association patterns of adverse events by age of the clinical trials patients and participants.
methodsTwo aspects of adverse event patterns were measured: (1) the adverse event incidence rate in each of the patient age groups and (2) the diversity of adverse events defined as distinct types of adverse events categorized by organ system. Statistical analysis was done on the summarized clinical trial data. The incident rate and diversity level in each of the age groups were compared with the lowest group (reference group) using t tests. Cohort data was obtained from ClinicalTrials.gov, and 186,339 clinical studies were analyzed; data were extracted from the 17,853 clinical trials that reported clinical outcomes. The total number of clinical trial participants was 6,808,619, and total number of participants affected by adverse events in these trials was 1,840,432. The trial participants were divided into eight different age groups to support cross-age group comparison.
resultsIn general, children and older patients are more susceptible to adverse events in clinical trial studies. Using the lowest incidence age group as the reference group (20-29 years), the incidence rate of the 0-9 years-old group was 31.41%, approximately 1.51 times higher (P=.04) than the young adult group (20-29 years) at 20.76%. The second-highest group is the 50-59 years-old group with an incidence rate of 30.09%, significantly higher (P<.001) when compared with the lowest incidence in the 20-29 years-old group. The adverse event diversity also increased with increase in patient age. Clinical studies that recruited older patients (older than 40 years) were more likely to observe a diverse range of adverse events (P<.001). Adverse event diversity increased at an average rate of 77% for each age group (older than 30 years) until reaching the 60-69 years-old group, which had a diversity level of 54.7 different types of adverse events per trial arm. The 70-100 years-old group showed the highest diversity level of 55.5 events per trial arm, which is approximately 3.44 times more than the 20-29 years-old group (P<.001). We also observe that adverse events display strong age-related patterns among different categories.
conclusionThe results show that there is a significant adverse event variance at the population level between different age groups in clinical trials. The data suggest that age-associated adverse events should be considered in planning, monitoring, and regulating clinical trials.
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