Sodium-Glucose Cotransporter 2 Inhibitors and Risk of Retinopathy in Patients With Type 2 Diabetes

Original Investigation | Diabetes and Endocrinology
Sodium-Glucose Cotransporter 2 Inhibitors and Risk of Retinopathy in Patients

With Type 2 Diabetes
Fu-Shun Yen, MD; James Cheng-Chung Wei, PhD; Teng-Shun Yu, MS; Yu-Tung Hung, MS; Chih-Cheng Hsu, DrPH; Chii-Min Hwu, MD
Abstract Key Points

Question Could sodium-glucose
IMPORTANCE Diabetic nephropathy and diabetic retinopathy share many similarities in
cotransporter 2 inhibitors (SGLT2is)
pathophysiological processes. Preclinical studies have shown that sodium-glucose cotransporter 2
protect against the risk of sight-
inhibitors (SGLT2is) have a protective role in the risk of diabetic retinopathy.
threatening diabetic retinopathy?
OBJECTIVE To compare the risk of sight-threatening retinopathy associated with SGLT2is and other Findings In this cohort study of
second-line glucose-lowering medications (including pioglitazone, sulfonylureas, and dipeptidyl 3 544 383 patients with type 2 diabetes
peptidase-4 inhibitors [DPP-4is]) in patients with type 2 diabetes (T2D). in Taiwan, SGLT2is were associated with
a significantly lower risk and lower
DESIGN, SETTING, AND PARTICIPANTS This cohort study in Taiwan applied a new-user and active- cumulative incidence of sight-
comparator design. Patient demographic and clinical data were obtained from the National Health threatening retinopathy than dipeptidyl
Insurance Research Database. Adult patients with newly diagnosed T2D from January 1, 2009, to peptidase-4 inhibitors, pioglitazone,
December 31, 2019, were recruited and followed up until December 31, 2020. Propensity score and sulfonylureas.
matching was used to identify pairs of patients treated with SGLT2i vs DPP-4i, SGLT2i vs
Meaning Findings from this study
pioglitazone, and SGLT2i vs sulfonylurea from January 1, 2016, to December 31, 2019. Data were
suggest that SGLT2is may have an
analyzed between August 18, 2022, and May 5, 2023.
association not only with reduced risk of
diabetic nephropathy but also with the
EXPOSURES Treatment with SGLT2i, DPP-4i, pioglitazone, and sulfonylureas starting on January
slow progression of diabetic retinopathy
1, 2016.
in patients with type 2 diabetes.
MAIN OUTCOMES AND MEASURES The main outcome was sight-threatening retinopathy in
participants. Cox proportional hazards regression models were used to assess relative hazards of + Supplemental content
sight-threatening retinopathy between the matched case and control groups. Author affiliations and article information are
listed at the end of this article.
RESULTS A total of 3 544 383 patients with newly diagnosed T2D were identified. After 1:1
propensity score matching, 65 930 pairs of patients treated with SGLT2i vs DPP-4i, 93 760 pairs
treated with SGLT2i vs pioglitazone, and 42 121 pairs treated with SGLT2i vs sulfonylurea were
identified. These matched patients included 236 574 males (58.6%), with a mean (SD) age of 56.9
(11.8) years. In the matched cohorts, SGLT2i had a significantly lower risk of sight-threatening
retinopathy than DPP-4i (adjusted hazard ratio [AHR], 0.57; 95% CI, 0.51-0.63), pioglitazone (AHR,
0.75; 95% CI, 0.69-0.81), and sulfonylureas (AHR, 0.62; 95% CI, 0.53-0.71). The Kaplan-Meier curves
showed that SGLT2i was associated with a significantly lower cumulative incidence of sight-
threatening retinopathy than DPP-4i (3.52 vs 6.13; P < .001), pioglitazone (4.32 vs 5.76; P < .001),
and sulfonylureas (2.94 vs 4.67; P < .001).
CONCLUSIONS AND RELEVANCE This cohort study found that SGLT2i was associated with a lower
risk of sight-threatening retinopathy compared with DPP-4i, pioglitazone, and sulfonylureas. This
finding suggests that SGLT2i may play a role not only in reduced risk of diabetic nephropathy but also
in the slow progression of diabetic retinopathy in patients with T2D.
JAMA Network Open. 2023;6(12):e2348431. doi:10.1001/jamanetworkopen.2023.48431
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JAMA Network Open | Diabetes and Endocrinology Sodium-Glucose Cotransporter 2 Inhibitors and Risk of Retinopathy in Type 2 Diabetes
Introduction
Sodium-glucose cotransporter 2 inhibitors (SGLT2is) can lower blood glucose levels, reduce body
weight, and lower blood pressure by inhibiting proximal tubule glucose reabsorption and promoting
urinary glucose excretion.1 A meta-analysis found that SGLT2is can effectively slow the progression
of chronic kidney disease (CKD) by reducing renal hyperfiltration in patients with type 2 diabetes
(T2D).2 However, there are associations and similarities between diabetic nephropathy and
retinopathy.3,4 One study found that proteinuria and CKD are associated with the risk of diabetic
retinopathy, and there is an association between diabetic retinopathy and the development or
worsening of CKD.3 Chronic kidney disease and diabetic retinopathy share common risk factors, such
as obesity, diabetes, and hypertension.3 Hyperglycemia can activate several biochemical pathways
and promote oxidative stress accumulation in glomerular and retinal cells, resulting in chronic
inflammation, cellular damage, endothelial dysfunction, and basement membrane thickening.1,3,4
Blood flow and circulation in the glomerulus and retina are regulated by microvasculature. Increased
blood flow increases shear stress in glomerular and retinal capillaries, promoting inflammation and
leakage.3,4 Studies have found that the embryogenetic stages in kidney and eye development occur
concurrently, and renal and ocular organogenesis share several genes.3,5 Additionally, SGLT2is
expressed in kidney mesangial cells and retinal pericytes may act as a glucose sensor to control
cellular tone and regulation of blood flow.4,6 As CKD and retinopathy have several similarities in
pathophysiological processes and SGLT2is can attenuate the development and progression of CKD,
SGLT2is may also play a role in reducing the risk of diabetic retinopathy.3,4
Preclinical studies have found that dapagliflozin can decrease glucose uptake in human retinal
endothelial cells, leading to less oxidative stress (retinal hydrogen peroxide as a marker) and
inflammation (interleukin 6 as a marker).4,7 A study found that tofogliflozin in db/db mice can
prevent the activation of glial fibrillary acidic protein and vascular endothelial growth factor (VEGF)
production in the retina.8 Empagliflozin in Akimba mice can reduce vascular leakage and expression
of VEGF in the retina.9 Phlorizin can attenuate pericyte swelling and normalize glucose uptake and
type IV collagen overproduction in cultured bovine retinal pericytes.6,10 Dapagliflozin can reduce
apoptosis in the diabetic retina and human retinal microvascular endothelial cells independent of
hypoglycemic effects.11 Therefore, we hypothesized that SGLT2is play a protective role in the risk of
diabetic retinopathy. We conducted a nationwide cohort study to compare the risk of sight-
threatening retinopathy (including severe diabetic retinopathy and macular edema) associated with
SGLT2is and other second-line glucose-lowering medications (including pioglitazone, sulfonylureas,
and dipeptidyl peptidase-4 inhibitors [DPP-4is]) in patients with T2D.
Methods
Data Source
The Taiwan government established the National Health Insurance (NHI) program in 1995. Under the
NHI, the government is the sole purchaser and, along with employers, pays most of the insurance
premium while the public pays only a small premium. Thus, by 2000, 99% of the 23 million residents
in Taiwan were enrolled in the NHI. Patient data, such as sex, age, address, premium payments,
examinations, diagnoses, prescriptions, and surgical procedures, are recorded in the NHI Research
Database (NHIRD). Disease diagnoses are defined using International Classification of Diseases, Ninth
Revision (ICD-9) and International Statistical Classification of Diseases and Related Health Problems,
Tenth Revision (ICD-10) diagnostic codes. All clinicians caring for patients with diabetes, including
general practitioners and ophthalmologists in private practice, report ICD codes to the NHIRD. The
NHI administration conducts random and periodic inspections of medical records at clinics and
hospitals throughout the country to improve the adequacy of disease management and the accuracy
of diagnoses. This cohort study used the full population dataset of the NHIRD for patient
identification and data analysis.12 All procedures were performed according to the Declaration of

Helsinki.13 The China Medical University and Hospital Research Ethics Committee approved this
study and waived the informed consent requirement because all identifiable clinician and patient
data were scrambled and encrypted before database release. We followed the Strengthening the
Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
Study Cohorts
We recruited patients with newly diagnosed T2D from January 1, 2009, to December 31, 2019, and
followed up until December 31, 2020 (eFigure in Supplement 1). A diagnosis of T2D was defined as 1
hospitalization or at least 2 outpatient visits within 1 year using ICD-9-CM (Clinical Modification) code
250.xx, except 250.1x, and ICD-10-CM code E11 (eTable 1 in Supplement 1). The algorithm for the use
of ICD diagnostic codes for the definition of T2D was validated by a previous Taiwanese study14 with
acceptable accuracy.
We applied the new-user and active-comparator model for this cohort study. Generally, the
model involves watching what happens when people try a drug for the first time and comparing the
results with those of a well-established drug. This approach allowed us to ascertain whether the new
drug was better, worse, or about the same as the usual drug. Patients treated with SGLT2i, DPP-4i,
pioglitazone, or sulfonylureas for the first time after T2D diagnosis were defined as new users of
those medications. For the SGLT2i, the index date was defined as the first date of SGLT2i use. Next,
we calculated the duration (elapsed time) between the date of T2D diagnosis and the index date of
SGLT2i. For pioglitazone, sulfonylureas, and DPP-4i, we identified the index date and elapsed time of
use in the same way we defined those for SGLT2i. As SGLT2i has been marketed in Taiwan since May
2016, the index date for all drugs was set after January 1, 2016.
By observation, most patients were Han Taiwanese. Race and ethnicity were not available in the
NHIRD or collected and analyzed for this study. Exclusion criteria were as follows: (1) age younger
than 20 years or older than 80 years at first diagnosis of T2D, (2) missing information on sex or age,
(3) diagnosis of type 1 diabetes or dialysis treatment before the index date, (4) study medication used
within 1 year before the index date, and (5) diagnosis of sight-threatening retinopathy before the
index date or death within 180 days after the index date to exclude potential mortality or morbidity
due to other unrelated causes.
The clinically relevant variables used in the propensity score matching process were as follows
(Table 1)15: age, sex, smoking status, comorbidities (obesity [composite of severely obese, obese,
and overweight diagnoses], hypertension, coronary artery disease, stroke, heart failure, atrial
fibrillation, peripheral artery disease, dyslipidemia, liver cirrhosis, chronic obstructive pulmonary
disease, CKD, and diabetic retinopathy), Charlson Comorbidity Index (score range: 0 to ⱖ2, with the
highest score indicating a greater burden of comorbid conditions and a higher risk of mortality),16
Diabetes Complications Severity Index (DCSI; score range: 0 to ⱖ2, with the highest score indicating
a greater burden of diabetes complications),17 T2D diagnosis within 1 year prior to the index date,
medications (sulfonylureas, metformin, α-glucosidase inhibitors, thiazolidinediones, and DPP-4i;
number of oral antidiabetic agents; glucagon-like peptide-1 receptor agonists [GLP-1 RA]; insulin;
aspirin; and statins), and duration of T2D.
Main Outcome
The main outcome of this study was sight-threatening retinopathy in participants with at least 2
outpatient visits or 1 hospitalization for diabetic retinopathy and requiring surgery (NHI codes
86206B, 86207B, 86407B, and 86408B; ICD-10-Procedure Coding System [PCS] codes 08943ZZ,
08BE3ZZ, 08BF3ZZ, 08QE, and 08QF), laser photocoagulation (NHI codes 60001C, 60002C,
60005C, 60006C, 60003C, and 60004C; ICD-10-PCS codes 085E3ZZ and 08QE3ZZ), or anti-
VEGF injections (ranibizumab, bevacizumab, or aflibercept) within 90 days of retinopathy diagnosis
or vision loss (ICD-9-CM code 369; ICD-10-CM code H54).15,18 We followed up participants until
sight-threatening retinopathy occurred or until the study ended on December 31, 2020, whichever
occurred first.

Table 1. Baseline Characteristics of Matched Patients With Type 2 Diabetes Treated With Dipeptidyl Peptidase-4 Inhibitor (DPP-4i), Pioglitazone, Sulfonylurea, or
Sodium-Glucose Cotransporter 2 Inhibitor (SGLT2i) Since 2016
Patient treatment, No. (%) Patient treatment, No. (%) Patient treatment, No. (%)
DPP-4i SGLT2i Pioglitazone SGLT2i Sulfonylurea SGLT2i
Variable (n = 65 930) (n = 65 930) SMDa (n = 93 760) (n = 93 760) SMDa (n = 42 121) (n = 42 121) SMDa
Sex
Female 25 027 (38.0) 24 915 (37.8) 40 773 (43.5) 40 941 (43.7) 17 795 (42.2) 17 597 (41.8)
0.004 0.004 0.010
Male 40 903 (62.0) 41 015 (62.2) 52 987 (56.5) 52 819 (56.3) 24 326 (57.8) 24 524 (58.2)
Age, y
20-40 7405 (11.2) 7916 (12.0) 0.024 5593 (6.0) 5858 (6.3) 0.012 5198 (12.3) 5342 (12.7) 0.010
41-60 33 406 (50.7) 33 256 (50.4) 0.005 41 659 (44.4) 41 663 (44.4) <0.001 20 812 (49.4) 21 014 (49.9) 0.010
61-80 25 119 (38.1) 24 758 (37.6) 0.011 46 508 (49.6) 46 239 (49.3) 0.006 16 111 (38.3) 15 765 (37.4) 0.017
Mean (SD) ageb 55.9 (11.7) 55.6 (11.9) 0.019 59.5 (11.2) 59.3 (11.3) 0.011 55.8 (12.2) 55.5 (12.2) 0.020
Comorbidities
Obesity 3748 (5.7) 4116 (6.2) 0.024 2416 (2.6) 2669 (2.9) 0.017 2783 (6.6) 3039 (7.2) 0.024
Smoking 3848 (5.8) 3792 (5.8) 0.004 4758 (5.1) 4731 (5.1) 0.001 2218 (5.3) 2210 (5.3) 0.001
Hypertension 45 019 (68.3) 45 154 (68.5) 0.004 67 173 (71.6) 67 036 (71.5) 0.003 28 927 (68.7) 28 763 (68.3) 0.008
Dyslipidemia 51 723 (78.5) 51 694 (78.4) 0.001 75 203 (80.2) 75 299 (80.3) 0.003 32 112 (76.2) 31 841 (75.6) 0.015
CAD 16 424 (24.9) 16 601 (25.2) 0.006 22 495 (24.0) 22 498 (24.0) <0.001 11 543 (27.4) 11 702 (27.8) 0.008
Stroke 6069 (9.2) 6137 (9.3) 0.004 12 838 (13.7) 12 765 (13.6) 0.002 4478 (10.6) 4230 (10.0) 0.019
Heart failure 3264 (5.0) 3371 (5.1) 0.007 4375 (4.7) 4420 (4.7) 0.002 2502 (5.9) 2573 (6.1) 0.007
Atrial fibrillation 6197 (9.4) 6280 (9.5) 0.004 8910 (9.5) 8956 (9.6) 0.002 4785 (11.4) 4749 (11.3) 0.003
PAD 581 (0.9) 613 (0.9) 0.005 1193 (1.3) 1197 (1.3) <0.001 385 (0.9) 374 (0.9) 0.003
COPD 15 552 (23.6) 15 558 (23.6) <0.001 23 310 (24.9) 23 354 (24.9) 0.001 10 866 (25.8) 10 757 (25.5) 0.006
Liver cirrhosis 1158 (1.8) 1137 (1.7) 0.002 2443 (2.6) 2431 (2.6) 0.001 705 (1.7) 711 (1.7) 0.001
CKD 4739 (7.2) 4796 (7.3) 0.003 10 718 (11.4) 10 666 (11.4) 0.002 3251 (7.7) 3190 (7.6) 0.005
Diabetic retinopathy 5187 (7.9) 5156 (7.8) 0.002 10 052 (10.7) 9993 (10.7) 0.002 2477 (5.9) 2579 (6.1) 0.010
CCI score
0 41 376 (62.8) 41 226 (62.5) 0.005 53 185 (56.7) 53 179 (56.7) <0.001 26 873 (63.8) 26 746 (63.5) 0.006
1 12 718 (19.3) 12 576 (19.1) 0.005 18 222 (19.4) 18 290 (19.5) 0.002 7285 (17.3) 7440 (17.7) 0.010
≥2 11 836 (18.0) 12 128 (18.4) 0.011 22 353 (23.8) 22 291 (23.8) 0.002 7963 (18.9) 7935 (18.8) 0.002
DCSI score
0 21 232 (32.2) 21 057 (31.9) 0.006 25 989 (27.7) 26 082 (27.8) 0.002 13 832 (32.8) 13 707 (32.5) 0.006
1 13 446 (20.4) 13 281 (20.1) 0.006 18 201 (19.4) 18 220 (19.4) 0.001 8206 (19.5) 8285 (19.7) 0.005
≥2 31 252 (47.4) 31 592 (47.9) 0.010 49 570 (52.9) 49 458 (52.8) 0.002 20 083 (47.7) 20 129 (47.8) 0.002
Medications
Metformin 59 573 (90.4) 59 549 (90.3) 0.001 87 504 (93.3) 87 483 (93.3) 0.001 36 577 (86.8) 36 187 (85.9) 0.027
Sulfonylureas 39 722 (60.3) 39 652 (60.1) 0.002 71 578 (76.3) 71 574 (76.3) <0.001 4042 (9.6) 4289 (10.2) 0.020
DPP-4i 13 205 (20.0) 13 101 (19.9) 0.004 51 526 (55.0) 51 434 (54.9) 0.002 15 889 (37.7) 16 188 (38.4) 0.015
α-Glucosidase inhibitors 10 955 (16.6) 10 991 (16.7) 0.001 24 787 (26.4) 24 716 (26.4) 0.002 5376 (12.8) 5472 (13.0) 0.007
No. of oral antidiabetic
drugs
0-1 23 637 (35.9) 23 684 (35.9) 0.001 15 011 (16.0) 14 897 (15.9) 0.003 23 410 (55.6) 23 216 (55.1) 0.009
2-3 38 328 (58.1) 38 289 (58.1) 0.001 62 057 (66.2) 62 251 (66.4) 0.004 17 968 (42.7) 18 058 (42.9) 0.004
>3 3965 (6.0) 3957 (6.0) 0.001 16 692 (17.8) 16 612 (17.7) 0.002 743 (1.8) 847 (2.0) 0.018
GLP-1 RA 5445 (8.3) 5495 (8.3) 0.003 23 266 (24.8) 23 274 (24.8) <0.001 5359 (12.7) 5405 (12.8) 0.003
Insulin 23 904 (36.3) 23 914 (36.3) <0.001 40 214 (42.9) 40 340 (43.0) 0.003 14 193 (33.7) 14 232 (33.8) 0.002
Statin 44 422 (67.4) 44 368 (67.3) 0.002 66 150 (70.6) 66 043 (70.4) 0.003 27 496 (65.3) 27 370 (65.0) 0.006
Aspirin 25 505 (38.7) 25 632 (38.9) 0.004 38 902 (41.5) 38 849 (41.4) 0.001 16 357 (38.8) 16 389 (38.9) 0.002
Duration of diabetes, mean 5.03 (3.6) 5.00 (3.6) 0.032 5.82 (3.3) 5.83 (3.3) 0.011 4.07 (3.4) 4.08 (3.4) 0.020
(SD), yb
Abbreviations: CAD, coronary artery disease; CCI, Charlson Comorbidity Index; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; DCSI, Diabetes
Complications Severity Index (score range: 0 to ⱖ2, with the highest score indicating a greater burden of diabetes complications); GLP-1 RA, glucagon-like peptide-1 receptor agonist;
PAD, peripheral artery disease; SMD, standardized mean difference.
a
An SMD of 0.10 or lower indicated a negligible difference between SGLT2i, DPP-4i, pioglitazone, and sulfonylurea use.
b
Calculated with an unpaired, 2-tailed t test.

Statistical Analysis
To increase their comparability, we used 1:1 propensity score matching to balance the variables
among participants treated with SGLT2i, DPP-4i, pioglitazone, and sulfonylurea.19 Considered as the
case group in each comparison cohort, SGLT2i was selected repeatedly for matching with other
non-SGLT2i treatments. Nonparsimonious multivariable logistic regression, with SGLT2i as the
dependent variable, was used to estimate propensity scores for each patient. Twenty-nine clinically
relevant variables, including baseline characteristics, comorbidities, medications, and duration of
T2D, were used as independent variables, as listed in Table 1. We adopted the nearest-neighbor
algorithm to construct matched pairs and assumed that the standardized mean difference (SMD) of
0.10 or lower between the matched case group and control group in each comparison cohort was
negligible.
Conditional Cox proportional hazards regression models with robust sandwich SE estimates
were used to compare the hazards of sight-threatening retinopathy between the matched case
group and each control group. We used Schoenfeld residuals to test for the assumption of
proportional hazards in the Cox proportional hazards regression models. Results were shown as
hazard ratios and 95% CIs for SGLT2i vs DPP-4i, SGLT2i vs pioglitazone, or SGLT2i vs sulfonylurea. We
used the Kaplan-Meier method to identify the cumulative incidence of sight-threatening retinopathy
over time across the SGLT2i, DPP-4i, pioglitazone, and sulfonylurea treatments.
Subgroup analyses were performed to assess the risk of sight-threatening retinopathy in the
age, sex, comorbidities, and medications variables between the matched SGLT2i cohort and DPP-4i,
pioglitazone, or sulfonylurea cohorts. We conducted interaction tests to find the differential
associations between subgroups of variables. For the subgroup analyses, we adjusted the
significance threshold to a lower value (P < .005) to reduce the potential for type I error due to
multiple comparisons.
We conducted a supplementary analysis to assess the risk of sight-threatening retinopathy
associated with different SGLT2i treatments (empagliflozin, dapagliflozin, and canagliflozin) vs
non-SGLT2i treatments to understand whether different SGLT2i treatments were associated with
deviated outcomes. For secondary outcomes, we compared the hazards of dialysis, hospitalization
for heart failure, and severe hypoglycemia (ie, patients who were referred to the emergency
department or hospitalized for hypoglycemia) between the matched SGLT2i cohort and DPP-4i,
pioglitazone, or sulfonylurea cohorts.
Statistical significance was defined as a 2-tailed P < .05 for the main analyses. Data were
analyzed between August 18, 2022, and May 5, 2023, using SAS 9.4 (SAS Institute Inc).
Results
The study identified from the NHIRD a total of 3 544 383 patients with newly diagnosed T2D from
January 1, 2009, to December 31, 2019. After excluding ineligible patients, we identified 159 965
patients treated with SGLT2i, 304 383 treated with DPP-4i, 108 420 treated with pioglitazone, and
189 618 treated with sulfonylurea during the study period (eFigure in Supplement 1). We included the
clinically related variables, such as age, sex, obesity, smoking, comorbidities, and medications, to
match the 3 groups of patients with an SMD of 0.10 or lower, which was considered to be a negligible
difference (Table 1). After 1:1 propensity score matching, we identified 65 930 pairs of patients
treated with SGLT2i vs DPP-4i, 93 760 pairs treated with SGLT2i vs pioglitazone, and 42 121 pairs
treated with SGLT2i vs sulfonylurea (eFigure in Supplement 1; Table 1). Of the overall matched
patients, 167 048 were females (41.4%) and 236 574 were males (58.6%), with a mean (SD) age of
56.9 (11.8) years. The median (IQR) follow-up time in this study was 2.19 (1.53-3.16) years.
In the matched cohorts, the absolute numbers of sight-threatening retinopathy were 541 in the
SGLT2i vs 928 in the DPP-4i groups, 1048 in the SGLT2i vs 1392 in the pioglitazone groups, and 284
in the SGLT2i vs 446 in the sulfonylurea groups. The multivariable-adjusted hazard ratios (AHRs) for
sight-threatening retinopathy were 0.57 (95% CI, 0.51-0.63) for the SGLT2i vs DPP-4i, 0.75 (95% CI,

0.69-0.81) for the SGLT2i vs pioglitazone, and 0.62 (95% CI, 0.53-0.71) for the SGLT2i vs sulfonylurea
groups (Table 2). The SGLT2i cohort had a significantly lower risk of the cumulative incidence of
sight-threatening retinopathy than the DPP-4i (3.52 vs 6.13; P < .001), pioglitazone (4.32 vs 5.76;
P < .001), and sulfonylureas cohorts (2.94 vs 4.67; P < .001) (Figure).
Subgroup and Additional Analyses

We found that SGLT2i was associated with a lower risk of sight-threatening retinopathy than DPP-4i
in all subgroups of variables, with no significant interaction in the subgroup analyses (eTable 2 in
Table 2. Risks of Sight-Threatening Retinopathy in Matched Patients With Type 2 Diabetes
Patient treatment
Risks of sight-threatening retinopathy SGLT2i DPP-4i SGLT2i Pioglitazone SGLT2i Sulfonylureas
No. of events 541 928 1048 1392 284 446
Person-years 153 585 151 416 242 663 241 470 96 444 95 570
IR per 1000 person-years 3.52 6.13 4.32 5.76 2.94 4.67
Crude HR (95% CI) 0.58 (0.52-0.64) 1 [Reference] 0.75 (0.69-0.81) 1 [Reference] 0.63 (0.54-0.73) 1 [Reference]
AHR (95% CI)a 0.57 (0.51-0.63) 1 [Reference] 0.75 (0.69-0.81) 1 [Reference] 0.62 (0.53-0.71) 1 [Reference]
P value <.001 NA <.001 NA <.001 NA
Abbreviations: AHR, adjusted hazard ratio; DPP-4i, dipeptidyl peptidase-4 inhibitor; HR, hazard ratio; IR, incidence rate; NA, not applicable; SGLT2i, sodium-glucose cotransporter 2
inhibitor.
a
Adjusted for age, sex, obesity, smoking, Charlson Comorbidity Index, Diabetes Complications Severity Index, comorbidities, medications, and duration of type 2 diabetes with the
Cox proportional hazards regression model.
Figure. Cumulative Incidence of Sight-Threatening Retinopathy Between Medications
A DPP-4i and SGLT2i cohorts B Pioglitazone and SGLT2i cohorts

0.030 0.030
sight-threatening retinopathy
DPP-4i cohort Pioglitazone cohort

0.025 0.025
Cumulative incidence of
SGLT2i cohort SGLT2i cohort
0.020 0.020
0.015 0.015
0.010 0.010
0.005 0.005
0 0
0 1 2 3 4 5 0 1 2 3 4 5
Follow-up, y Follow-up, y
No. of patients at risk No. of patients at risk
DPP-4i cohort 65 930 63 855 33 666 16 069 5825 0 Pioglitazone cohort 93 760 90 957 58 660 32 606 13 749 0
SGLT2i cohort 65 930 65 004 36 026 17 522 5370 0 SGLT2i cohort 93 760 92 001 59 938 35 263 13 320 0
C Sulfonylureas and SGLT2i cohorts

0.030
Sulfonylureas cohort
0.025
SGLT2i cohort
0.020
0.015
0.010
0.005
0
0 1 2 3 4 5
Follow-up, y
No. of patients at risk
Sulfonylureas cohort 42 121 40 946 21 532 9425 2992 0
SGLT2i cohort 42 121 41 584 22 043 10 637 3515 0
DPP-4i indicates dipeptidyl peptidase-4 inhibitor; SGLT2i, sodium-glucose cotransporter 2 inhibitor.

Supplement 1). Additionally, SGLT2i was associated with a lower risk of sight-threatening retinopathy
than pioglitazone in all subgroups of variables, and the interactions were significant in the metformin
(AHR, 0.72; 95% CI, 0.67-0.79; P = .007), sulfonylurea (AHR, 0.71; 95% CI, 0.65-0.77; P = .009),
and DPP-4i (AHR, 0.68; 95% CI, 0.61-0.75; P < .001) variable subgroups (eTable 3 in Supplement 1).
Similarly, SGLT2i was associated with a lower risk of sight-threatening retinopathy than sulfonylureas
in all subgroups of variables, and the interaction was significant in the insulin subgroup (AHR, 0.76;
95% CI, 0.61-0.94; P = .001) (eTable 4 in Supplement 1).
In matched patients, empagliflozin, dapagliflozin, and canagliflozin were associated with a
significantly lower risk of sight-threatening retinopathy than DPP-4i, pioglitazone, and sulfonylureas
(eg, vs DPP-4i: AHR, 0.53 [95% CI, 0.40-0.72]; 0.54 [95% CI, 0.48-0.62]; and 0.65 [95% CI, 0.57-
0.74], respectively; P < .001) (eTable 5 in Supplement 1). Also in the matched cohorts, SGLT2i
compared with DPP-4I, pioglitazone, and sulfonylurea was associated with a significantly lower risk
of dialysis (eg, vs DPP-4i: AHR, 0.05; 95% CI, 0.03-0.08; P < .001), hospitalizations for heart failure
(eg, vs DPP-4i: AHR, 0.47; 95% CI, 0.41-0.52; P < .001), and severe hypoglycemia (eg, vs DPP-4i:
AHR, 0.44; 95% CI, 0.38-0.51; P < .001) (eTable 6 in Supplement 1).
Discussion
This nationwide population-based cohort study found that SGLT2i was associated with a significantly
lower risk of sight-threatening retinopathy than DPP-4i, pioglitazone, and sulfonylureas in patients
with T2D. The results were consistent across the subgroups of age, sex, comorbidities, and
medications.
The post hoc analysis of the EMPA-REG OUTCOME (Empagliflozin Cardiovascular Outcome
Event Trial in Type 2 Diabetes Mellitus Patients–Removing Excess Glucose) trial found that
empagliflozin was not associated with a significant difference in the risk of vision-threatening
retinopathy compared with placebo.20 Three meta-analyses of randomized clinical trials also found
that SGLT2i treatment was not associated with ocular events compared with no SGLT2i
treatment.21-23 However, a meta-analysis found that SGLT2i was associated with a reduced risk of
diabetic retinopathy in patients with diabetes for less than 10 years.22 Another meta-analysis
reported that ertugliflozin and empagliflozin could reduce the risk of retinal disease, whereas
canagliflozin could increase the risk of vitreous disease.23 The association of SGLT2i with decreased
central retinal thickness and improved diabetic macular edema has been reported in several case
reports.8 Su et al24 found that SGLT2i was associated with a significantly lower risk of diabetic
macular edema compared with GLP-1 RA. The retrospective cohort by Lin et al25 found that SGLT2i
compared with GLP-1 RA was associated with a lower risk of sight-threatening retinopathy but not
the development of diabetic retinopathy. Dziuba et al26 used the Archimedes model to estimate
20-year cardiovascular and microvascular complications in patients with T2D. These investigators
found that adding dapagliflozin to current treatment was associated with a 9.8% decrease in incident
diabetic retinopathy compared with standard care.26 Findings from these clinical studies suggest
that SGLT2i treatments are associated with a lower risk of diabetic retinopathy. The present study
found that SGLT2i was associated with a significantly lower risk of sight-threatening retinopathy than
DPP-4i, pioglitazone, and sulfonylureas in patients with T2D.
A small retrospective study of 82 patients with T2D found that DPP-4i treatment was
associated with a significantly lower risk of diabetic retinopathy progression than non–DPP-4i
treatment.27 However, a cohort study involving adults aged 65 years or older suggested that DPP-4i
treatment lasting approximately 1 year was not associated with increased risk of diabetic
retinopathy.28 A nationwide cohort study reported that DPP-4i add-on therapy was associated with
a significantly higher risk of diabetic retinopathy progression than non–DPP-4i add-on therapy.29 A
network meta-analysis found that DPP-4i was associated with a significantly higher risk of diabetic
retinopathy events.30 A clinical cohort study revealed that SGLT2i was associated with a significantly
lower risk of incident diabetic retinopathy but no significant difference in the risk of diabetic

retinopathy progression compared with DPP-4i.31 These studies suggest that the association
between DPP-4i and diabetic retinopathy is uncertain. In this study, we found that SGLT2i was
associated with a significantly lower risk of sight-threatening retinopathy than DPP-4i in patients
with T2D, and this result was consistent across different subgroups of patients.
A large cohort study involving 103 368 patients with T2D and without diabetic macular edema
found that thiazolidinediones were associated with an increased risk of incident diabetic macular
edema.32 A case-control study of 996 new cases of diabetic macular edema suggested that
thiazolidinediones could play a role in diabetic macular edema development.33 A longitudinal study
found an association between rosiglitazone and reduced risk of progression of diabetic retinopathy
but without an association with diabetic macular edema.34 Subsequently, in a post hoc analysis of
the ACCORD (Action to Control Cardiovascular Risk in Diabetes) eye study, 695 patients (20.0%)
were treated with thiazolidinediones and 217 (6.2%) were diagnosed with macular edema.35
Thiazolidinediones could improve visual acuity and were not associated with an increased risk of
diabetic macular edema.35 Results regarding the association of thiazolidinediones with diabetic
retinopathy complications are conflicting. Sulfonylureas were associated with an increased risk of
complications of diabetic retinopathy in a network meta-analysis of 36 clinical trials.30 A
retrospective cohort study reported that SGLT2i treatment in patients with T2D could slow the
progression of diabetic retinopathy compared with sulfonylureas.36 The present study found that
SGLT2i was associated with a significantly lower risk of sight-threatening retinopathy than
pioglitazone and sulfonylureas in patients with T2D.
There are several potential mechanisms by which SGLT2i was associated with a decreased risk
of sight-threatening retinopathy. First, SGLT2i can lower blood glucose, blood pressure, uric acid, and
body weight by increasing kidney excretion of glucose, sodium, and uric acid, thereby playing a role
in reducing the risk of diabetic retinopathy, intracellular oxidative stress, visceral fat, and
proinflammatory cytokines.1,3,4 Second, SGLT2i can reduce diabetic retinal and human microvascular
endothelial cell apoptosis regardless of hypoglycemic effects.11 Third, SGLT2i can reduce pericyte
swelling, increase microcirculation control, and normalize glucose uptake and type IV collagen
overproduction in retinal pericytes.6,10 Fourth, SGLT2i can repair impaired retinal neurovascular
coupling (including retinal blood flow dysregulation and neural retinal dysfunction) and inhibit retinal
glial activation in mice with T2D.8 Fifth, animal studies have found that SGLT2i can reduce retinal
vascular leakage and VEGF expression.9 Sixth, SGLT2i may downregulate the sympathetic nervous
system and exert neuroprotection in the retina.3,9,23 In brief, SGLT2i has been associated with
improved metabolism and microcirculation of the retinal neurovascular coupling and decreased
apoptosis of retinal and microvascular endothelial cells to lower the risk of sight-threatening
retinopathy.
Strengths and Limitations

This study has some strengths. First, more than 95% of the population in Taiwan was enrolled in the
NHI program, minimizing the possibility of selection bias. The number of patients with sight-
threatening retinopathy was also higher, providing adequate power for performing subgroup
analyses. Second, a period of 5 years (2016 to 2020) was covered, which was long enough for
diabetic retinopathy to develop.1,15 Third, the new-user and active-comparator design was applied,
which could restrict the potential for confounding by indication, reduce prevalent user bias, and
allow a head-to-head comparison. Fourth, the clinical implication of this study was that SGLT2i
treatments were as safe and effective in slowing the progression of diabetic retinopathy as in
lowering the risk for diabetic nephropathy in patients with T2D.
This study also has several limitations. First, the NHIRD lacked information on participants’
family history, smoking status, alcohol consumption, and physical activity, which could have affected
the results. Patients with suboptimal glycemic control or CKD were more prone to incident
retinopathy and sight-threatening retinopathy. However, results of biochemical, blood glucose,
hemoglobin A1C, and kidney function tests were unavailable in the NHIRD, preventing the assessment

of participants’ diabetes management status and T2D severity. However, we matched CKD, diabetic
retinopathy, and DCSI scores to balance the diabetes complications; we also matched the number of
oral antidiabetic drugs, use of insulin, and duration of diabetes to balance the severity of T2D
between the matched case and control groups. Second, the NHIRD lacked complete information on
retinal fundoscopy, fluorescein angiography, and ocular computer tomography, which prevented the
accurate identification of macular edema and diabetic retinopathy. However, we used ICD codes to
identify baseline diabetic retinopathy and calculated DCSI scores to compare diabetes complications
between the matched case and control groups. The algorithm of using ICD-10-PCS codes to define
surgery for sight-threatening retinopathy has not been validated in previous studies, but because it is
a clinical procedure performed by trained ophthalmologists, this algorithm might be more accurate
than ICD-9-CM and ICD-10-CM codes. Third, the results may not apply to other races and ethnicities
because the study participants were mainly Han Taiwanese in ethnicity. Fourth, a retrospective
cohort study has residual confounding factors; therefore, the results can be interpreted only in terms
of associations but not causation. Randomized clinical trials are warranted to confirm these results.
Conclusions
This cohort study demonstrated that SGLT2i treatment was associated with a significantly lower risk
of sight-threatening retinopathy than DPP-4i, pioglitazone, and sulfonylureas treatments in patients
with T2D. The potential protective role of SGLT2i in sight-threatening retinopathy was observed in
different subgroups of patients. In addition to playing a role in reducing the risk of diabetic
nephropathy, SGLT2i may be associated with the slow progression of diabetic retinopathy.
ARTICLE INFORMATION
Accepted for Publication: October 25, 2023.
Published: December 20, 2023. doi:10.1001/jamanetworkopen.2023.48431
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2023 Yen FS et al.
JAMA Network Open.
Corresponding Author: Chii-Min Hwu, MD, Section of Endocrinology and Metabolism, Department of Medicine,
Taipei Veterans General Hospital, No. 201, Sec. 2 Shi-Pai Rd, Chung-Cheng Building, 11F Room 522, Taipei 112,
Taiwan (chhwu@vghtpe.gov.tw); Chih-Cheng Hsu, DrPH, Institute of Population Health Sciences, National Health
Research Institutes, 5 Keyan Rd, Zhunan, Miaoli County 35053, Taiwan (cch@nhri.edu.tw).
Author Affiliations: Private practice, Taoyuan, Taiwan (Yen); Department of Allergy, Immunology and
Rheumatology, Chung Shan Medical University Hospital, Taichung City, Taiwan (Wei); Institute of Medicine, Chung
Shan Medical University, Taichung City, Taiwan (Wei); Graduate Institute of Integrated Medicine, China Medical
University, Taichung, Taiwan (Wei); Management Office for Health Data, China Medical University Hospital,
Taichung, Taiwan (Yu, Hung); College of Medicine, China Medical University, Taichung, Taiwan (Yu, Hung); Institute
of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan (Hsu);
Department of Health Services Administration, China Medical University, Taichung, Taiwan (Hsu); Department of
Family Medicine, Min-Sheng General Hospital, Taoyuan, Taiwan (Hsu); National Center for Geriatrics and Welfare
Research, National Health Research Institutes, Yunlin County, Taiwan (Hsu); Section of Endocrinology and
Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan (Hwu); Faculty of Medicine,
National Yang-Ming Chiao Tung University School of Medicine, Taipei, Taiwan (Hwu).
Author Contributions: Drs Hwu and Hsu had full access to all of the data in the study and take responsibility for
the integrity of the data and the accuracy of the data analysis.
Concept and design: Yen, Hsu, Hwu.
Acquisition, analysis, or interpretation of data: Wei, Yu, Hung, Hsu.
Drafting of the manuscript: Yen, Hung.
Critical review of the manuscript for important intellectual content: Wei, Yu, Hsu, Hwu.
Statistical analysis: Yu, Hung, Hsu.
Obtained funding: Hwu.

Administrative, technical, or material support: Yen, Wei, Hsu, Hwu.

Supervision: Wei, Hsu.
Conflict of Interest Disclosures: None reported.
Funding/Support: This study was supported in part by grant MOHW109-TDU-B-212-114004 from the Taiwan
Ministry of Health and Welfare Clinical Trial Center, grant MOST 109-2321-B-039-002 from MOST Clinical Trial
Consortium for Stroke, grant DMR-110-222 from China Medical University Hospital, Tseng-Lien Lin Foundation,
grants V105C-204 and V110C-175 from Taipei Veterans General Hospital, and grant MOST 110-2314-B-075-
027-MY3 from the Taiwan Ministry of Science and Technology.
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection,
management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and
decision to submit the manuscript for publication.
Data Sharing Statement: See Supplement 2.
Additional Contributions: Wordvice and Wallace Academic Editing were paid to edit this manuscript.
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SUPPLEMENT 1.
eTable 1. Diseases and Associated ICD-9 and ICD-10 Codes
eTable 2. Risk of Sight-Threatening Retinopathy in Patients With Type 2 Diabetes Treated With DPP-4i or SGLT2i
Stratified by Variables
eTable 3. Risk of Sight-Threatening Retinopathy in Patients With Type 2 Diabetes Treated With Pioglitazone or
SGLT2i Stratified by Variables
eTable 4. Risk of Sight-Threatening Retinopathy in Patients With Type 2 Diabetes Treated With Sulfonylureas or
SGLT2i Stratified by Variables
eTable 5. Risk of Sight-Threatening Retinopathy Associated With SGLT2i, DPP4i, Pioglitazone and Sulfonylureas
Use
eTable 6. Risk of Outcomes Between SGLT2i, DPP-4i, Pioglitazone and Sulfonylureas Use
eFigure. Flowchart for the Selection of Matched Patients for SGLT2i, DPP-4i, Pioglitazone, and Sulfonylureas
SUPPLEMENT 2.
Data Sharing Statement

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Original Investigation | Diabetes and Endocrinology

Sodium-Glucose Cotransporter 2 Inhibitors and Risk of Retinopathy in Patients

Abstract Key Points

JAMA Network Open. 2023;6(12):e2348431. doi:10.1001/jamanetworkopen.2023.48431

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Subgroup and Additional Analyses

Table 2. Risks of Sight-Threatening Retinopathy in Matched Patients With Type 2 Diabetes

Figure. Cumulative Incidence of Sight-Threatening Retinopathy Between Medications

A DPP-4i and SGLT2i cohorts B Pioglitazone and SGLT2i cohorts

DPP-4i cohort Pioglitazone cohort

SGLT2i cohort SGLT2i cohort

C Sulfonylureas and SGLT2i cohorts

DPP-4i indicates dipeptidyl peptidase-4 inhibitor; SGLT2i, sodium-glucose cotransporter 2 inhibitor.

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Strengths and Limitations

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Administrative, technical, or material support: Yen, Wei, Hsu, Hwu.

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