Impact of Using Biomarkers in Eligibility Criteria in Acute Kidney Injury Randomized Controlled Trials: A Systematic Review and Methodological Meta-Analysis

ABSTRACT Rationale & Objective Many recent RCTs for AKI have incorporated biomarkers as part of their eligibility criteria. The sample size calculation of these trials is often based on prior studies that did not include such criteria. This meta-analysis evaluates the impact of a biomarker-based enrichment strategy on the rate of anticipated versus observed primary events and explores the effect of integrating such biomarkers on statistical power. Study Design We performed a PRISMA-guided systematic review and methodological meta-analysis of RCTs extracted from six databases. Setting & Study Population RCTs included patients at risk for or diagnosed with AKI. Selection Criteria for Studies Clinical trials with a biomarker-based eligibility criterion and either a renal or mortality primary outcome, published between 2010 and 2023. Data Extraction Data were extracted independently by two reviewers. Analytical Approach The absolute risk difference between anticipated and observed event rates was measured for all patients and stratified for control and intervention groups. Results Fourteen RCTs involving 3817 patients were included. Biomarkers of interest were NGAL, TIMP-2*IGFBP7, proteinuria, serum albumin, NT-pro-BNP, homocysteine and uric acid. The pooled absolute risk difference between anticipated and observed event rates was 0.12 (95%CI; 0.06-0.17). In the control and interventional groups, the absolute risk differences were 0.10 (95%CI 0.01-0.19) and 0.12 (95%CI; 0.06-0.18) respectively. For kidney damage biomarkers, the risk difference was 0.13 (95% CI; 0.06-0.20). The mean pre-planned and achieved statistical powers were 0.84 (±0.07) and 0.43 (±0.28), respectively, with no improvement when extrapolating the pre-planned sample size. Limitations Most RCTs were underpowered for their primary outcome. There was a high level of heterogeneity. Conclusions There is a difference between expected and observed incidence rates that may be partly attributed to biomarker-based enrichment methods. These findings highlight the need for rigorous validation of biomarkers before their incorporation into the eligibility criteria of RCTs.