ROUTINE EXCLUSIONS IN NEPHROLOGY CLINICAL TRIALS FROM 2010 TO 2023: A META EPIDEMIOLOGICAL STUDY
Dr Shiva Raj Mishra1, Dr Karen Waller1, Prof Angela Webster1
1University Of Sydney, Australia
Aim: We aimed to determine which groups are mostly excluded in RCTs in adults with chronic kidney disease, dialysis, and transplantation from 2010 to 2023.
Background: Randomized clinical trials (RCTs) may not accurately reflect the characteristics of the general population due to the presence of unreasonable exclusion criteria.
Methods and Results: We counted the number of trials excluding patients of the prespecified exclusion groups (e.g., demographic, geographic, reproductive, medical comorbidities, disease severity, health services) and calculated the prevalence of exclusion for each group. A total of 1024 clinical trials were examined. The median sample size at recruitment was 79 (IQR: 42 to 159). Nearly, 11.8% of the trial excluded patients with physical comorbidities; 14.6% of trials excluded people with mental illness. 36.5% and 22.7% of trials excluded pregnant and breastfeeding women. 38.8 of the trials excluded patients with cardiovascular complications, cancer 29.1%, and infectious diseases (25.0%). Further, 1.1% and 8.7% of the trials excluded participants who were either “too trail” or reported having “low life expectancy” by trialists.
Conclusions: Majority of the trials excluded patients with common diseases, 11.8% with at least one physical condition and 14.6% with mental health conditions. Excluding certain population groups might lead to lower generalisability of trial evidence, further limiting understanding on the possible side effects and efficacy of interventions in these population groups. Future studies are needed to explore discretionary exclusionary practices in clinical trials, as well as exploring framework/guidelines for promoting diversity in participant’s recruitment strategies.
Biography:
Dr Shiva Raj Mishra is a research fellow at the NHMRC Clinical Trials Center, University of Sydney. He is involved in designing meta-epidemiological studies looking at health equity, diversity and inclusion in clinical trials and exploring health disparities in cardiovascular outcomes and services. Shiva has several years of training and experience in epidemiology and health data science. He collaborates in studies to improve understanding of health disparities, individual and population-level determinants of risk factors and public health interventions on cardiometabolic diseases with a focus on low-income setting.