Effects of sodium-glucose cotransporter-2 (SGLT-2) inhibitors on serum uric acid levels in patients with chronic kidney disease: a systematic review and network meta-analysis

Abstract

Elevated serum uric acid levels are an independent predictor of occurrence and development of chronic kidney disease (CKD) and are strongly associated with prognosis. Several clinical trials have demonstrated the benefits of sodium-glucose cotransporter-2 (SGLT-2) inhibitors. To evaluate and rank the effects and safety of various SGLT-2 for serum uric acid levels in patients with CKD. We performed a systematic PubMed, Embase, Scopus, and Web of Science search, including studies published before July 1, 2023. Two researchers independently extracted data on study characteristics and outcomes and assessed study quality using the Cochrane Collaboration’s risk of bias tool 2. The gemtc package of R software was used to perform network meta-analysis within a Bayesian framework. The primary outcome was serum uric acid levels, and the secondary outcome was adverse events. Effect sizes are reported as standardized mean differences (SMDs), risk ratio (RR), and 95% CI, respectively. The certainty of evidence was evaluated using Grading of Recommendations, Assessment, Development and Evaluations (GRADE) criteria. Eight RCTs (9367 participants) were included in this meta-analysis. The results of the paired meta-analysis showed that SGLT-2 inhibitors significantly reduced serum uric acid levels in patients with CKD compared with the placebo group (SMD −0.22; 95% CI −0.42 to –0.03; GRADE: low). Pooled analysis of any adverse events reported in the included studies showed similar incidence rates in the SGLT-2 inhibitor and placebo groups (RR: 0.99; 95% CI 0.97 to 1.00; p=0.147; GRADE: high). Subgroup analysis showed a statistically significant difference only for tofogliflozin. Further network meta-analysis showed that dapagliflozin 10 mg and ipragliflozin 50 mg may be the most effective in reducing uric acid levels. SGLT-2 inhibitors significantly reduced serum uric acid levels in patients with CKD, and dapagliflozin 10 mg and ipragliflozin 50 mg may be the optimal dosages. SGLT-2 inhibitors hold great promise as an antidiabetic therapeutic option for patients with CKD who have elevated serum uric acid levels. PROSPERO registration number: CRD42023456581.

WHAT IS ALREADY KNOWN ON THIS TOPIC

• Serum uric acid levels are elevated in patients with chronic kidney disease (CKD), and it remains unknown how effective sodium-dependent glucose transporters 2 (SGLT-2) inhibitors are in reducing serum uric acid levels in this population.

WHAT THIS STUDY ADDS

• We provide a comprehensive overview of the effects of SGLT-2 inhibitors on serum uric acid levels in CKD patients. By employing a systematic review and network meta-analysis, we have an innovative findings that SGLT-2 inhibitors have an additive effect of lowering serum uric acid in CKD patients and that Dapagliflozin 1 0 mg may be the optimal dose. In addition, there are differences in the uric acid-lowering effects of SGLT-2 inhibitors in patients with different stages of CKD, which may be related to renal function.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• These findings suggest that SGLT-2 applied to treatment of patients with CKD may have an additional benefit of lowering serum uric acid levels.

Introduction

Previous studies have shown that serum uric acid levels in patients with chronic kidney disease (CKD) gradually increase as renal function declines,^{1 2} progressing gradually to hyperuricemia with associated symptoms.^{3 4} It has been reported that 60% of patients with CKD have combined asymptomatic hyperuricemia.⁵ Hyperuricemia is an independent predictor of the development and progression of CKD,^{6 7} and in addition, elevated serum uric acid levels are associated with an increased risk of cardiovascular disease in patients with CKD.^{8 9} Also, serum uric acid levels are U-shapedly related to the risk of all-cause mortality in CKD, including hemodialysis population.^{10 11} Recently, Johnson et al⁵ stated that even asymptomatic hyperuricemia may be detrimental for patients with CKD and should be treated with uric acid-lowering therapy.

Sodium-glucose cotransporter-2 (SGLT-2) inhibitors are a novel class of antidiabetic agents¹² that reduce plasma glucose levels by decreasing renal reabsorption and increasing urinary glucose excretion.¹³ In addition, several recent publications have reported additional benefits of SGLT-2 inhibitors, such as weight loss, blood pressure control, lipid-lowering, and reduction of cardiovascular risk factors.^14–17 Notably, there is growing evidence of the potential benefits of SGLT-2 inhibitors for lowering serum uric acid levels.^{18 19} A recent meta-analysis showed that in patients with diabetes mellitus, the risk of gout was reduced in those using SGLT-2 inhibitors compared with those not using SGLT-2 inhibitors (HR 0.66, 95% CI 0.57 to 0.76).²⁰ However, there is no comparison of the effects of different SGLT-2 inhibitors on serum uric acid levels in patients with CKD.

To add further evidence, we systematically review the evidence on various SGLT-2 inhibitors (including dapagliflozin, canagliflozin, empagliflozin, ertugliflozin, lpragliflozin, tofogliflozin, luseogliflozin, remogliflozin, and sotagliflozin) for patients with CKD to answer the following specific research questions:

1. Do SGLT-2 inhibitors reduce serum uric acid levels in patients with CKD?

2. Which SGLT-2 inhibitor has the most excellent effect on serum uric acid levels in patients with CKD?

3. Explore the optimal dose of SGLT-2 inhibitors for lowering serum uric acid levels in patients with CKD.

4. Does SGLT-2 inhibitors cause adverse events?

Method

This systematic review and meta-analysis followed the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines²¹ (online supplemental table S1). The protocol has been registered in the International Prospective Register of Systematic Reviews (PROSPERO: CRD42023456581). The current study methodology is similar to the previously described protocol with a few modifications (online supplemental table S2).

Data sources and search strategies

We systematically searched Embase, PubMed, Scopus, and Web of Science using a combination of medical subject terms and keywords related to SGLT-2 inhibitors and CKD. The timeline was from the inception to July 1, 2023. The search strategies for each database are shown in online supplemental table S3–S6. In addition, we also manually searched for records in the reference lists of previous systematic reviews.^{16 19} Literature downloaded from the databases was imported into EndNote V.20 software for management. A weekly national library of the USA reminder was set up for the primary search strategy by September 1, 2023, but no new articles were generated.

Eligibility criteria

Eligibility criteria were based on Population, Intervention, Comparator, Outcome, Study design elements developed by potential randomized controlled trials (RCTs) should include (1) adult patients (aged ≥18 years) diagnosed with CKD, including predialysis, peritoneal dialysis, hemodialysis, and kidney transplant recipients, (2) participants in the intervention group receiving SGLT-2 inhibitor monotherapy or in combination with other antidiabetes therapy, (3) participants in the control or placebo group receiving usual care or sham drug or placebo, (4) outcomes of interest included serum uric acid level and adverse events.

Selection process

Two authors (FZ and YB) independently conducted the selection. We first screen the titles/abstracts for relevance based on eligibility criteria and then potential full-text articles. A third author adjudicated disagreements. Reasons for full-text exclusion were documented (online supplemental table S7) and summarized in a PRISMA flow chart.

Risk of bias assessment

Two independent authors (LH and LZ) assessed the risk of bias for each included RCT according to the Cochrane Collaboration’s risk of bias tool 2 (RoB-2) as having a low risk of bias, some concerns or a high risk of bias: bias arising from the randomization process, bias due to deviations from intended interventions, bias due to missing outcome data, bias in measuring the outcome and bias in the selection of the reported result.²² Any discrepancies were resolved through a third author (YZ).

Data extraction

Two independent reviewers (YB and LZ) extracted data using an established form. The information is shown in table 1. We attempted to contact the corresponding author for any incomplete or missing data. If no response was received within 2 weeks, it was considered as no response, and the data available in the articles were extracted. Any discrepancies were resolved through a third author (YZ).

Table 1.

Data extraction elements

Topic	Items
Articles	First authors and publication year.
Study details	Study designs, registration numbers, and study locations (countries).
Subjects	Sample size, mean age, gender, body mass index, estimated glomerular filtration rate.
Methods	Dose and type of SGLT-2 inhibitors, and treatment duration.
Results	Pre-treatment (baseline) and post-treatment (end point) serum uric acid levels, or change from baseline.

SGLT-2, sodium-glucose cotransporter-2.

The last data item was extracted if assessment results were reported for multiple time points. If data were presented in figures, the mean and SD were extracted using GetData software (getdata-graph-digitizer.com). For studies that included different doses of SGLT-2 inhibitors (eg, dapagliflozin 5 mg vs dapagliflozin 10 mg vs placebo), all were included. However, according to the Cochrane guidelines,²³ the number of participants in the control group was split equally to avoid double counting.

When mean with SE were reported, SE was converted to SD using the following formula, where n is the number of subjects: SD=SE error×${\displaystyle \sqrt{n}}$ .

If the study did not report baseline and end point change values, calculate according to formula A and formula B.

Formula A: mean_change=mean_{end point}−mean_baseline

Formula B: SD_change=${\displaystyle \sqrt{S{D}_{baseline}^2+S{D}_{endpoint}^2-\left(2\times R\times S{D}_{baseline}\times S{D}_{endpoint}\right)}}$

Any disagreements regarding data extraction were resolved by consulting a third author (YZ).

Data synthesis and analysis

Pairwise meta-analysis

We used the meta²⁴ packages in R software to include studies with continuous or dichotomous data for outcomes in the meta-analysis. Because of the relevant differences in SGLT-2 inhibitors, region and sample size across studies, a restricted maximum likelihood meta-analysis was used to estimate the mean effect size of the included studies. The primary measure of effect was the mean change from baseline. Change value and SDs were used in all cases.²³ In all meta-analyses, negative values indicated a benefit of SGLT-2 inhibitor intervention if not otherwise stated. Continuous data (ie, serum uric acid) analysis selects the standardized mean difference (SMD) with 95% CI to explain the effect size. In addition, we calculated 95% prediction intervals (95% PI) to predict the range of actual effects.²⁵

For the adverse event, a risk ratio (RR) and 95% CI for the dichotomous outcome were measured using the inverse variance method. A continuity correction of 0.5 was used in case of zero events in one group.

The I² and Cochrane Q tests assessed heterogeneity across studies, and the criteria are as follows: ≥25% (low heterogeneity), ≥50% (moderate heterogeneity), and ≥75% (high heterogeneity).²⁶ Random effects models were used when I² was >50%, and otherwise, a fixed effects model. We performed a subgroup analysis to determine the effects of different SGLT-2 inhibitors. Contour-enhanced funnel plot was used to assess publication bias for outcomes with ≥10 studies.²⁷ Further exploratory analysis was performed using Egger’s regression test to assess asymmetry statistically. In addition, a leave-one-out sensitivity analysis was conducted.

Network meta-analysis

To determine the most effective SGLT-2 inhibitor and its dosage for reducing serum uric acid levels, we conduct a network meta-analysis within a Bayesian framework using the R package gemtc consistency model.²⁸ In this analysis, we calculate SMDs and 95% CI to measure the effect of different SGLT-2 inhibitors on serum uric acid levels in patients with CKD.

The rankings of the interventions are summarized and reported based on the cumulative sorting under the curve (SUCRA), ranging from 1 (indicating that SGLT-2 inhibitors are likely to be least effective in reducing serum uric acid) to 0 (indicating that SGLT-2 inhibitors are likely to be most effective in lowering serum uric acid).²⁹

Grading of evidence assessment

We assessed the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) methodology to determine the certainty of evidence (online supplemental table S8).³⁰ The certainty of evidence was rated as high, medium, low, and very low by the GRADE tool. High means that further research is unlikely to change confidence in effect estimates; medium implies that further research is likely to have a significant impact on confidence in effect estimates; low means that further research is very likely to have an impact on confidence in effect estimates; and very low means that estimates of effects are very uncertain.

Results

A total of 5041 records were retrieved, of which 8 RCTs^31–38 with 22 study arms (9367 adult participants) met the eligibility criteria and were included in the meta-analysis (figure 1) and had 6 SGLT-2 inhibitors: dapagliflozin, empagliflozin, sotagliflozin, ipragliflozin, tofogliflozin, and canagliflozin (figure 2). The duration of trials ranged from 12 weeks to 206 weeks. The primary characteristics of included studies are detailed in table 2.

Figure 1.

Literature screening flow chart. CKD, chronic kidney disease; RCT, randomised controlled trial; SGLT-2, sodium-glucose cotransporter 2.

Figure 2.

Network diagram of comparisons for the effects of different sodium-glucose cotransporter-2 (SGLT-2) inhibitors and placebo on serum uric acid in patients with chronic kidney disease. The nodes represent different SGLT-2 inhibitors, and size is proportional to sample size. Lines represent the available direct comparisons between various medicines, and width is proportional to the number of trials comparing each pair.

Table 2.

Characteristics of included studies

Study	Registration number	Country	Study design	Sample size (treatment/control)	Age (years) (mean±SD)	Sex (male/female)	BMI (kg/m2)	eGFR (mL/min/1.73 m2)	Duration (weeks)
Dapagliflozin
Kohan et al33	NCT00663260	Multicenter	RCT	Placebo: 84	67±8.6	53/31	Reported as number	Reported as number	104
				5 mg: 83	66±8.9	55/28
				10 mg: 85	68±7.7	56/29
Satirapoj et al34	TCTR20180424002	Thailand	RCT	Placebo: 29	59.9±1.6	8/21	27.9±0.9	87.3±2.9	12
				Dapagliflozin: 28	55.9±1.4	17/11	28.4±0.8	88.7±3.1
Empagliflozin
Zinman et al38	NCT01131676	Multicenter	RCT	Placebo: 2333	63.2±8.8	1680/653	30.7±5.2	73.8±21.1	206
				10 mg: 2345	63.0±8.6	1653/692	30.6±5.2	74.3±21.8
				25 mg: 2342	63.2±8.6	1683/659	30.6±5.3	74.0±21.4
Barnett et al31	NCT01164501	Multicenter	RCT (stage 2 CKD)	Placebo: 95	62.6±8.1	56/39	30.8±5.6	71.8±10.2	52
				10 mg: 98	63.2±8.5	60/38	32.4±5.4	70.8±10.3
				25 mg: 97	62.0±8.4	61/36	31.3±5.8	72.3±11.2
			RCT (stage 3 CKD)	Placebo: 187	65.1±8.2	106/81	30.3±5.3	44.3±10.3	52
				25 mg: 187	64.6±8.9	107/80	30.2±5.3	45.4±10.2
Canagliflozin
Yale et al53	NCT01064414	Multicenter	RCT	Placebo: 90	68.2±8.4	57/33	33.1±6.5	40.1±6.8	52
				100 mg: 90	69.5±8.2	58/32	32.4±5.5	39.7±6.9
				300 mg: 89	67.9±8.2	48/41	33.4±6.5	38.5±6.9
Sotagliflozin
Cherney et al32	NCT03242252	Multicenter	RCT	Placebo: 260	69.3±8.1	149/111	32.5±5.2	44.8±8.4	26
				200 mg: 263	69.6±7.5	143/120	32.3±5.7	45.2±8.1
				400 mg: 264	69.5±8.2	152/112	32.4±5.2	45.1±7.9
Ipragliflozin
Tanaka et al35	UMIN000016563	Japan	RCT	Control: 15	62.5±13.5	7/8	31.4±5.1	67.9±16.9	12
				Ipragliflozin: 15	59.1±11.2	8/7	30.5±7.0	67.3±18.2
Tofogliflozin
Terauchi et al36	NCT02201004	Japan	RCT	Control: 70	56.4±10.0	48/22	26.9±3.9	79.5±17.0	16
				Tofogliflozin: 141	59.1±10.8	59/82	25.8±3.5	79.7±19.8

BMI, body mass index; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; RCT, randomized controlled trial.

Quantitative evidence synthesis through network meta-analysis was considered appropriate given the comparability of study designs, outcome measures, participating patients, and inclusion and exclusion criteria. The assumptions of homogeneity and consistency were confirmed.

Role of SGLT-2 inhibitors on serum uric acid level in patients with CKD

Pairwise meta-analysis showed that SGLT-2 inhibitors significantly reduced serum uric acid levels in patients with CKD compared with placebo, and the difference was significant but with higher heterogeneity (SMD −0.22; 95% CI −0.42 to –0.03; I²=71%) (figure 3). Subgroup analyses showed that only tofogliflozin led statistically significant: dapagliflozin: SMD −0.72; 95% CI −1.83 to 0.39; empagliflozin: SMD −0.17; 95% CI −0.34 to 0.00; sotagliflozin: SMD −0.09; 95% CI −0.24 to 0.06; ipragliflozin: SMD −0.68; 95% CI −1.46 to 0.10; tofogliflozin: SMD −0.34; 95% CI −0.64 to –0.04; canagliflozin: SMD, −0.14; 95% CI −0.16 to 0.44 (table 3 and online supplemental figure S1).

Figure 3.

Forest plot and pooled estimates of the impact of sodium-glucose cotransporter-2 (SGLT-2) inhibitors on serum uric acid levels compared with placebo. SMD, standard mean difference.

Table 3.

Subgroup analyses of different SGLT-2 inhibitors regarding serum uric acid levels of patients with CKD

Groups	Included trials (study arm)	Sample size (final)	SMD (95% CI)	Heterogeneity (I2)	Publication bias (Egger’s regression test)	GRADE
Total	8 (22)	2836	−0.22 (−0.42 to 0.03)	71%	0.181	⨁⨁◯◯ (low level of evidence)*
Dapagliflozin	2 (5)	309	−0.72 (−1.83 to 0.39)	92%
Empagliflozin	2 (7)	1314	−0.17 (−0.34 to 0.00)	54%
Sotagliflozin	1 (3)	787	−0.09 (−0.24 to 0.06)	0%
Ipragliflozin	1 (2)	27	−0.68 (−1.46 to 0.10)	–
Tofogliflozin	1 (2)	201	−0.34 (−0.64 to 0.04)	–
Canagliflozin	1 (3)	198	0.14 (−0.16 to 0.44)	0%

*See online supplemental table S8 for details.

GRADE, Grading of Recommendations, Assessment, Development and Evaluations; SGLT-2, sodium-glucose cotransporter-2; SMD, standard mean difference.

To observe the effect of SGLT-2 inhibitors on serum uric acid in different stages of CKD, we developed further subgroup analyses based on participants’ estimated glomerular filtration rate (eGFR) at baseline. The results of paired meta-analysis showed that SGLT-2 inhibitors were able to significantly reduce serum uric acid in participants with CKD stage 1–2 but had no significant effect on CKD stage 3–4 (online supplemental figure S2); then, we categorized the SGLT-2 inhibitors and empagliflozin and tofogliflozin in stage 2 participants were significant, and dapagliflozin may have a role in lowering serum uric acid in patients with CKD stage 1 (online supplemental table S9).

The 95% PI values ranged from −0.97 to 0.53, suggesting that SGLT-2 inhibitors may not significantly reduce serum uric acid levels compared with placebo in future studies conducted under similar conditions (figure 3). The quality of this evidence was deemed low (online supplemental table S10). Although the contour-enhanced funnel plot indicated possible small-study effects (online supplemental figure S3), Egger’s test for small-study effects was not significant (p=0.181). The sensitivity analyses were consistent with the primary analysis results (online supplemental figure S4). In addition, Cochrane’s risk of bias assessment showed that all included RCTs had ‘some concern’ or ‘low risk’, which proves that our study is more credible (online supplemental figure S5).

Determination of the most effective SGLT-2 inhibitors in reducing serum uric acid levels in patients with CKD

We performed a network meta-analysis to compare further the efficacy of different SGLT-2 inhibitors in lowering serum uric acid levels. As shown in figure 4, dapagliflozin 10 mg ranked first in terms of effectiveness in reducing serum uric acid in patients with CKD compared with placebo, but the difference was not statistically significant, followed by ipragliflozin 50 mg, dapagliflozin 5 mg, tofogliflozin 20 mg, and empagliflozin 10 mg. In a pairwise comparison of the included trials, dapagliflozin 10 mg had an advantage in lowering uric acid compared with other SGLT-2 inhibitors (online supplemental table S11).

Figure 4.

Effect sizes of different SGLT-2 inhibitors relative to placebo. SMD, standard mean difference; SGLT-2, sodium-glucose cotransporter-2.

Online supplemental table S12 shows the ranking probability of each class of SGLT-2 inhibitors. The results showed that dapagliflozin 10 mg had the highest probability of being the best uric acid-lowering regimen for CKD (29.3%), followed by ipragliflozin 50 mg (26.6%). In contrast, placebo and empagliflozin 25 mg ranked relatively low. Similarly, SGLT-2 inhibitors used to reduce serum uric acid levels in patients with CKD were rated as follows based on SUCRA values (top five): dapagliflozin 10 mg (SUCRA: 18.11%), dapagliflozin 5 mg (SUCRA: 31.29%), ipragliflozin 50 mg (SUCRA: 31.54%), tofogliflozin 20 mg (SUCRA: 44.56%), and empagliflozin 10 mg (52.30%) (online supplemental figure S6).

Adverse events

Six studies reported adverse events and two studies had no adverse events. With a 0.5 correction for ‘double-zero events’, there was no statistically significant difference in the incidence of adverse events between the two groups; 87.6% (5337/6093) of participants in the SGLT-2 inhibitors group had an adverse effect compared with 87.6% (2862/3268) in the placebo group (RR: 0.99; 95% CI 0.97 to 1.00; p=0.147; GRADE: high) (figure 5 and online supplemental table S10).

Figure 5.

Meta-analysis of the incidence of adverse events in the two groups of participants. RR, risk ratio; SGLT-2, sodium-glucose cotransporter-2.

Discussion

This systematic review and meta-analysis assessed the effects of six classes of SGLT-2 inhibitors on serum uric acid levels in patients with CKD, and paired meta-analysis demonstrated that SGLT-2 significantly lowered serum uric acid (GRADE: low), with sensitivity analyses and subgroup analyses (in addition to canagliflozin) supporting this conclusion. Further network meta-analysis indicated that dapagliflozin 10 mg may have the best effect (29.3% probability) and that there was no significant difference in the incidence of adverse events between participants in the SGLT-2 inhibitor group and the placebo group.

These results are consistent with previous meta-analyses. Zhao et al¹⁹ evaluated the effect of SGLT-2 inhibitors on serum uric acid in 34 941 individuals from 60 studies and showed that any of the SGLT-2 inhibitors significantly lowered uric acid levels; however, in subgroup analyses, the researchers noted that eGFR <60 mL/min/1.73 m² in patients with CKD, the uric acid-lowering reduction effect was lost. Similarly, Akbari et al³⁹ reported 55 trials (122 arms) which showed that all SGLT-2 inhibitors significantly reduced uric acid levels compared with the placebo group (mean difference (MD) −34.07 μmol/L, 95% CI –37.00 to –31.14); a subgroup analysis of 13 294 individuals reported that uric acid-lowering effect of canagliflozin (MD −36.27 µmol/L, 95% CI –41.62 to –30.93). Another network meta-analysis¹⁸ of 19 included studies (4218 participants) also demonstrated that SGLT-2 inhibitors significantly reduced serum uric acid levels in patients with type 2 diabetes mellitus (MD −0.965 mg/dL, 95% CI −1.029 to –0.901), but there were some issues with the heterogeneity of this study (I²=98.7%).

Regarding clinical guidance on using SGLT-2 inhibitors in patients with CKD, the 2023 Kidney Disease: Improving Global Outcomes (KDIGO) guideline⁴⁰ states that SGLT-2 inhibitors are recommended for treating adult patients with CKD in combination with heart failure or with an eGFR ≥20 mL/min/1.73 m², and a urinary albumin/creatinine ratio ≥200 mg/g (1A). This landmark result also signaled the emergence of SGLT-2 inhibitors as first-line agents in treating CKD. Nonetheless, the current meta-analysis found no advantage of canagliflozin over placebo in lowering uric acid, which may be a bias caused by the small sample size. Another result reported in the same population³⁷ showed that at 26 weeks, canagliflozin was superior to placebo for lowering serum uric acid in CKD (placebo (per cent change): 2.5±18.6; canagliflozin 100 mg: −0.3±16.9; canagliflozin 300 mg; canagliflozin 300 mg: −2.0±20.0). For dapagliflozin use, a small non-randomized trial by Mori et al⁴¹ demonstrated differences in uric acid values and fractional excretion of uric acid after 3 weeks and 3 months of administration, showing a significant decrease in uric acid values and an increase in fractional excretion of uric acid. The study by Chino et al⁴² also reported the effect mechanism by which SGLT-2 inhibitors can reduce serum uric acid by accelerating the rate of uric acid excretion. It has been estimated that SGLT-2 inhibitors typically reduce serum uric acid by approximately 35–45 µmol/L (0.60–0.75 mg/dL) in individuals with baseline uric acid values within a normal range of roughly 200–400 µmol/L (about 3.3–6.7 mg/dL).⁴³

On a molecular level, Nokikov et al⁴⁴ reported that urate transporter 1 (URAT1) and glucose transporter 9 (GLUT9) are required for increased uric acid excretion. URAT1 is a uric acid transporter known to be expressed in the proximal renal tubule,⁴⁵ whereas GLUT9, a hexose/urate transporter, is located on the basolateral membrane of proximal renal tubular cells.⁴³ Chino et al⁴² found that SGLT-2 inhibitors suppress GLUT9 activity and may inhibit renal tubular collecting duct GLUT9 isoform 2-mediated uric acid reabsorption, increasing urinary uric acid. Thus, increasing uric acid excretion by SGLT-2 inhibitors depends on renal function, which may explain a decrease in the uric acid-lowering effects of SGLT-2 inhibitors as renal function declines.

Given that different doses of SGLT-2 inhibitors may produce different uric acid-lowering effects, we conducted a network meta-analysis of doses across SGLT-2 inhibitors, which suggested that dapagliflozin 10 mg and ipragliflozin 50 mg may have better efficacy in reducing serum uric acid levels in patients with CKD. Caution should be taken in interpreting this finding due to the small number of participants included and the lack of statistical significance. In addition, the limited number of included studies also limited our ability to perform meta-regression to determine the optimal duration of treatment for uric acid reduction by SGLT-2 inhibitors in patients with CKD, and therefore, more research is needed in this area.

Regarding safety, the incidence was almost similar between the SGLT-2 inhibitor and placebo groups. Given that the primary objective of this study was to assess the effect of SGLT-2 inhibitors on serum uric acid in patients with CKD, we only performed a pooled analysis of any adverse events reported in the included studies and lacked more nuanced safety results (eg, cardiovascular events). Nevertheless, several recent studies have reported that SGLT-2 inhibitors show a favorable safety profile.^{16 46–48}

Several factors strengthened the results of this systematic review and meta-analysis. We used strict eligibility criteria limited to RCTs and performed a risk of bias assessment using the RoB-2 tool. We also performed pairwise and network meta-analyses to determine the role of SGLT-2 inhibitors on serum uric acid in patients with CKD. However, we recognize some limitations. First, changes in serum uric acid levels were not a primary outcome of the included studies, which may undermine confidence in the effects measured. In addition, it was not easy to identify available studies because titles/abstracts of an article did not necessarily describe the uric acid results. Despite our rigorous screening, we cannot completely exclude the possibility that a few studies were not identified. Second, due to the limited number of included studies, we could not further define the moderators that influence the reduction of uric acid by SGLT-2 inhibitors in patients with CKD. Third, hyperuricemia and antigout treatments were not included in the inclusion or exclusion criteria to obtain information on combination medications that affect uric acid levels.⁴⁹ Fourth, only eight RCTs were included in this meta-analysis, which means that relatively small pooled data are available, and results must be interpreted cautiously. Fortunately, increasing numbers of ongoing trials^50–52 have been conducted, and the consequences of these studies may contribute to our understanding of the reduction of serum uric acid by SGLT-2 inhibitors in patients with CKD.

Conclusion

In conclusion, SGLT-2 inhibitors decreased serum uric acid levels in patients with CKD and are considered a promising therapeutic option for this population. Dapagliflozin was even more effective with a recommended dose of 10 mg. These findings may be considered in future guidelines and clinical medications, and SGLT-2 inhibitors may be used to treat patients with CKD with high serum uric acid levels. However, given the limitations of the included studies, this evidence requires further validation.

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information. Not applicable.

Ethics statements

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Ethics approval

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