Background: Sodium-glucose cotransporter 2 (SGLT2) inhibitors have emerged as promising agents for slowing chronic kidney disease (CKD) progression. While individual trials demonstrate renal and survival benefits, questions remain regarding the consistency, generalizability, and magnitude of these effects, particularly across populations with and without diabetes, and amid heterogeneous outcome definitions. Methods: We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) evaluating the effect of SGLT2 inhibitors on CKD progression and all-cause mortality. Eligible studies reported hazard ratios (HRs) for these outcomes in adult populations with or at risk for CKD. Data were pooled using random-effects models; heterogeneity was assessed via tau², I², and Cochran's Q. Meta-regression explored study-level moderators, including baseline estimated glomerular filtration rate (eGFR), diabetes prevalence, follow-up duration, outcome definition, and risk of bias. Cumulative meta-analysis and sensitivity analyses evaluated robustness, while absolute risk reductions (ARRs) and numbers needed to treat (NNTs) enhanced clinical interpretability. Results: Seven trials (n = 69, 827) were included for CKD progression and eight for all-cause mortality. The pooled HRs were 0. 71 (95% CI: 0. 66-0. 76) for CKD and 0. 87 (95% CI: 0. 82-0. 92) for mortality. Heterogeneity was negligible (I² = 0%). Standardized CKD definitions (e. g. , >=40% eGFR decline) yielded significantly stronger treatment effects than alternative definitions (p = 0. 017). Subgroup analysis suggested greater renal benefit in non-diabetic patients (HR = 0. 64), though interaction p = 0. 76. Sensitivity analyses confirmed robustness. Translating HRs to absolute terms, NNTs were 17 (CKD) and 77 (mortality). Egger's test suggested potential small-study effects for mortality (p = 0. 053). Conclusions: SGLT2 inhibitors robustly reduce CKD progression and mortality risks, with consistent effects across trial settings. However, treatment effects depend partly on outcome definitions, and statistical power to assess effect modifiers remains limited. Future trials should prioritize outcome harmonization and include underrepresented non-diabetic CKD populations to refine precision and generalizability.
Hassanein et al. (Mon,) studied this question.