Letter to the Editor regarding the article “SGLT2 inhibitors and cardiovascular and renal outcomes: a meta‑analysis and trial sequential analysis”

Abstract

Barbarawi and colleagues [1] carried out a study of meta‐analysis and trial sequential analysis regarding the effects of sodium‐ glucose cotransporter 2 (SGLT2) inhibitors on cardiovascular and renal endpoints. This study [1] by Barbarawi et al. is an up‐to‐date meta‐analysis of assessing SGLT2 inhibitors because the authors incorporated the data from all the relevant large randomized trials including the latest two trials of SOLOIST‐ WHF [2] and SCORED [3]. However, what concerns me is that the authors failed to perform any quantitative analysis in the subgroup of patients with type 2 diabetes (T2D) and athero‐ sclerotic cardiovascular disease (ASCVD) but came to the main conclusion of their study that SGLT2 inhibitors in patients with T2D and ASCVD lower the risk of heart failure hospitalization (HFH), cardiovascular mortality (CVM), all‐cause mortality (ACM), major adverse cardiovascular events (MACE), and chronic kidney disease (CKD) progression without increasing the risk of total serious adverse events and amputation. To verify the correctness of that conclusion and to further identify which patients SGLT2 inhibitors are suitable for, we implemented a fur‐ ther meta‐analysis based on the 10 randomized trials included in Barbarawi et al.’s meta‐analysis [1]. In the present meta‐analysis, we evaluated the effects of SGLT2 inhibitors on five cardiorenal outcomes (i.e., HFH, CVM, ACM, MACE, and CKD progression) in different T2D subgroups defined by with/without ASCVD, with/without CKD, and with/without heart failure (HF). We defined the above 5 outcomes in the same way as Barbarawi et al. [1] did. CKD was defined as estimated glomerular filtration rate < 60 mL/min/1.73 m2 [4]. Two authors extracted the out‐ come data in relevant subgroups from the subgroup analysis articles based on the 10 trials included in Barbarawi et al.’s study [1]. The outcome data were extracted via hazard ratio (HR) and 95% confidence interval (CI) of gliflozins versus placebo. All the data extracted are provided in Appendix 1. A third author with rich experience in meta‐analysis solved the divergences between them. Meta‐analysis was performed using the random‐effects model with the method of DerSimonian and Laird [5], while subgroup analysis was conducted strati‐ fied by with/without ASCVD, with/without CKD, and with/ without HF. We evaluated heterogeneity using I2 and exam‐ ine subgroup differences using meta‐regression analysis with P‐value < 0.05 denoting statistical significance. By performing meta‐analysis on the five outcomes of interest, respectively, stratified by the baseline status of ASCVD, CKD, and HF, we produced the following find‐ ings. Compared with placebo, among T2D patients SGLT2 inhibitors lowered the incidence of HFH by 32% (HR 0.68, 95% CI 0.62–0.76, P for effect size < 0.001) independent of the ASCVD status (Psubgroup = 0.504), the CKD status (Psubgroup = 0.119), and the HF status (Psubgroup = 0.846) (Figure S1); lowered the incidence of CVM by 15% (HR 0.85, 95% CI 0.75–0.96, P for effect size = 0.008) independ‐ ent of the ASCVD status (Psubgroup = 0.434), the CKD sta‐ tus (Psubgroup = 0.816), and the HF status (Psubgroup = 0.553) (Figure S2); lowered the incidence of ACM by 14% (HR 0.86, 95% CI 0.79–0.94, P for effect size < 0.001) independ‐ ent of the ASCVD status (Psubgroup = 0.669), the CKD sta‐ tus (Psubgroup = 0.851), and the HF status (Psubgroup = 0.767) (Figure S3); lowered the incidence of MACE by 11% (HR 0.89, 95% CI 0.84–0.96, P for effect size = 0.001) independent of the ASCVD status (Psubgroup = 0.533), the CKD status (Psubgroup = 0.088), and the HF status (Psubgroup = 0.459) (Figure S4); and lowered the incidence of CKD progression by 37% (HR 0.63, 95% CI 0.57–0.68, P for effect size < 0.001) independent of the ASCVD status * Mei Qiu [email protected]