P204: Using Historical RCT Controls Cohort to Contextualize Serious Adverse Events for ongoing RCTs
Poster Presenter
Chris Schneiderman
Director - Epidemiology
Abbvie United States
Objectives
Describe the ‘Adverse Events in placebo controls of Abbvie Clinical Trials’ database composed of historical RCT placebo controls across 52 countries, among 10 therapeutic areas, and its utility for estimating incidence of serious AEs in clinical trials and findings across demographic strata.
Method
RCT placebo control (PC) data was obtained and assessed for missing data. Qlik/R was used to visualize & calculate crude and person-year (PY) adjusted incidence rates of AEs & 95% CIs. High level outcomes were stratified according to MedDRA System Organ Class (SOC), severity & demographic measures
Results
A total of 3,361 subjects (53.4% female, median age 45) constituting 2,689 PY were included across 44 studies between 2015-2021. Therapeutic areas; Gastrointestinal (35% of subjects), Women’s health (12%), Oncology, Immunology, CNS (11%), Dermatology (10%) Infectious disease (8%), Respiratory & specialty/other (1%).
Subjects were located in the US (39%), China (9.6%), Canada (5.9%) Japan (5.1%) and S. Korea (4.2%), with the remaining 36.3% distributed among 48 countries.
By study phase, Phase 0/1 was 10% of the cohort, Phase 2 - 12%, Phase 2/3 - 17%, Phase 3 - 58% and Phase 4 – 3%, with some subjects overlapping between phases.
White subjects constituted 64.5% of the cohort, 23.7% Asian, 9.4% African American, 1.3% multiple races, and the remaining 0.8% Native American/Hawaiian/unspecified.
Data are near 100% complete, with <0.4% missing, with exception of AE severity, 8.4%, but overcome with the AE Serious variable, which was 100% captured.
AEs are observed for 2,365 subjects (70.4%), 9,538 events across 1,467 MedDRA PTs. SAEs are observed in 400 subjects (11.9%) constituting 631 events across 304 PTs. According to SOC, the most frequent AEs were ‘infections and infestations’ (32%), ‘gastrointestinal disorders’ (28%) & ‘musculoskeletal and connective tissue disorders’ (17%). The most frequent AEs reported were headache (243), nasopharyngitis (196), upper respiratory tract infection (193), nausea (182), fatigue (180), arthralgia (155), urinary tract infection (143), anaemia (137), diarrhoea (131) & cough (119).
Rates of AEs and SAEs were higher for those aged 65+ compared to <65 (AE: 82.7% vs 68.0%; SAE: 23.3% vs 9.65%). Rates of AEs and SAEs were slightly elevated for men (AE: 72.2% vs 68.8%; SAE: 13.2% vs 10.8%). By SOC, AE rates by age groups show older subjects having higher event rates, and seriousness. AE rates are generally balanced between men and women, though the ratio of SAE among all AEs show men having more serious outcomes among select SOCs.
Conclusion
The AEPACT database has proven to be a valuable resource for understanding the incidence of AEs and SAEs in AbbVie conducted clinical trials. The data collected from the database is globally representative and demographically diverse, providing a comprehensive understanding of the safety profiles of various populations.
A key advantage of the AEPACT database is the ability to provide accurate and reliable information compared to real world data (RWD). This is due to the strict standards followed in conducting RCTs, which ensure high-quality data and thorough subject follow-up. Consequently, the AEPACT database may more accurately predict the expected rates of AEs and SAEs in ongoing or planned trials, making it a valuable tool for researchers and safety clinicians.
The analysis of the placebo controls data from the studies included in the AEPACT database has allowed for the identification of the most frequent AEs and their distribution by SOC. This information is crucial for understanding the safety profile of investigational drugs and can greatly inform decision-making during the clinical trial process, such as issues around unblinding cases.
The AEPACT database has revealed interesting insights regarding incidence of AEs and SAEs based on demographic factors. For instance, it has shown expected higher rates of AEs and SAEs among individuals aged 65 and above. Additionally, the database has indicated slightly elevated rates of SAEs among men, particularly among cardiac and vascular disorders.
Moving forward, the development of use cases will enable a better quantification of the predictive utility of AEPACT. By comparing the database's predictions with the actual outcomes of completed RCTs, investigators and safety clinicians will have a more accurate understanding of the expected rate of AE incidence within the context of specific trials and population demographics. This knowledge will facilitate better decision-making and improve patient safety.
