title: Population Analysis of Adverse Events in Different Age Groups Using Big Clinical Trials Data.
abstract: BACKGROUND
  Understanding 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.
  
  
  OBJECTIVE
  The 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.
  
  
  METHODS
  Two 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.
  
  
  RESULTS
  In 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.
  
  
  CONCLUSIONS
  The 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.
authors.affiliation: Center 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.
authors.forename: Jake
authors.identifier: http://orcid.org/0000-0002-3900-643X
authors.initials: J
authors.lastname: Luo
authors.forename: Christina
authors.identifier: http://orcid.org/0000-0001-9963-959X
authors.initials: C
authors.lastname: Eldredge
authors.forename: Chi C
authors.identifier: http://orcid.org/0000-0002-3109-9707
authors.initials: CC
authors.lastname: Cho
authors.forename: Ron A
authors.identifier: http://orcid.org/0000-0002-7781-5203
authors.initials: RA
authors.lastname: Cisler
keywords: adverse events; big data analysis; clinical trial data; clinical trial safety; data processing and integration; population health