Evidence map›Paper›PMID 27751983›Full record

ArticleJMIR medical informatics2016

Population Analysis of Adverse Events in Different Age Groups Using Big Clinical Trials Data.

Jake Luo, Christina Eldredge, Chi C Cho, Ron A Cisler

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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  15. 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 · 2022
    Article
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  18. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jake LuoCenter for Biomedical Data and Language Processing, College of Health Sciences, Department of Health Informatics and Administration, University of Wisconsin-Milwaukee, Milwaukee, WI, United States. jakeluo@uwm.edu.ORCID http://orcid.org/0000-0002-3900-643X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

adverse eventsbig data analysisclinical trial dataclinical trial safetydata processing and integrationpopulation health

Identifiers

PMID27751983
PMCPMC5088342

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Registered trials

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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.