Dataset Information

Metformin Treatment Is Associated with a Decreased Risk of Nonproliferative Diabetic Retinopathy in Patients with Type 2 Diabetes Mellitus: A Population-Based Cohort Study.

ABSTRACT: Purpose:To assess the relationship between metformin use and the severity of diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM) and to investigate the effect of metformin dosage on reducing the incidence of DR. Methods:The study population included patients with newly diagnosed T2DM, who were aged ?20 years and prescribed with antidiabetic drug therapy lasting ?90 days, as identified using the National Health Insurance Research Database between 2000 and 2012. We matched metformin users and nonusers by a propensity score. Cox proportional hazard regression analyses were used to compute and compare the risk of developing nonproliferative diabetic retinopathy (NPDR) in metformin users and nonusers. Results:Overall, 10,044 T2DM patients were enrolled. Metformin treatment was associated with a lower risk of NPDR (aHR 0.76, 95% CI 0.68-0.87) and sight-threatening diabetic retinopathy (STDR, aHR 0.29, 95% CI 0.19-0.45); however, the reduction in risk was borderline significant for STDR progression among NPDR patients (aHR 0.54, 95% CI 0.28-1.01). Combination therapy of metformin and DPP-4i exhibited a stronger but inverse relationship with NPDR development (aHR 0.32, 95% CI 0.25-0.41), especially at early (<3 months) stages of metformin prescription. These inverse relationships were also evident at different metformin doses and in adapted Diabetes Complications Severity Index scores (aDCSI). Moreover, combination therapy of metformin with sulfonylureas was associated with an increased risk of NPDR. Conclusion:Metformin treatment in patients with T2DM was associated with a reduced risk of NPDR, and a potential trend was found for a reduced STDR risk in patients who had previously been diagnosed with NPDR. Combining metformin with DPP-4i seemingly had a significantly beneficial effect against NPDR risk, particularly when aDCSI scores were low, and when metformin was prescribed early after T2DM diagnosis. These results may recommend metformin for early treatment of T2DM.

SUBMITTER: Fan YP

PROVIDER: S-EPMC7189314 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Metformin Treatment Is Associated with a Decreased Risk of Nonproliferative Diabetic Retinopathy in Patients with Type 2 Diabetes Mellitus: A Population-Based Cohort Study.

Fan Yu-Pei YP Wu Chien-Tung CT Lin Jiun-Lu JL Hsiung Chao A CA Liu Hsiao Yu HY Lai Jung-Nien JN Yang Chen-Chang CC

Journal of diabetes research 20200419

<h4>Purpose</h4>To assess the relationship between metformin use and the severity of diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM) and to investigate the effect of metformin dosage on reducing the incidence of DR.<h4>Methods</h4>The study population included patients with newly diagnosed T2DM, who were aged ≥20 years and prescribed with antidiabetic drug therapy lasting ≥90 days, as identified using the National Health Insurance Research Database between 2000 and 201 ...[more]

PMID: 32377525

Similar Datasets

Project description:BackgroundThe proportion of patients with diabetic retinopathy (DR) has grown with increasing number of diabetes mellitus patients in the world. It is among the major causes of blindness worldwide. The main objective of this study was to identify contributing risk factors of DR among people with type II diabetes mellitus.MethodA sample of 191 people with type II diabetes mellitus was selected from the Black Lion Specialized Hospital diabetic unit from 1 March 2018 to 1 April 2018. A multivariate stochastic regression imputation technique was applied to impute the missing values. The response variable, DR is a categorical variable with two outcomes. Based on the relationship derived from the exploratory analysis, the odds of having DR were not necessarily linearly related to the continuous predictors for this sample of patients. Therefore, a semiparametric model was proposed to identify the risk factors of DR.ResultFrom the sample of 191 people with type II diabetes mellitus, 98 (51.3%) of them had DR. The results of semiparametric regression model revealed that being male, hypertension, insulin treatment, and frequency of clinical visits had a significant linear relationships with the odds of having DR. In addition, the log- odds of having DR has a significant nonlinear relation with the interaction of age by gender (for female patients), duration of diabetes, interaction of cholesterol level by gender (for female patients), haemoglobin A1c, and interaction of haemoglobin A1c by fasting blood glucose with degrees of freedom [Formula: see text], respectively. The interaction of age by gender and cholesterol level by gender appear non significant for male patients. The result from the interaction of haemoglobin A1c (HbA1c) by fasting blood glucose (FBG) showed that the risk of DR is high when the level of HbA1c and FBG were simultaneously high.ConclusionClinical variables related to people with type II diabetes mellitus were strong predictive factors of DR. Hence, health professionals should be cautious about the possible nonlinear effects of clinical variables, interaction of clinical variables, and interaction of clinical variables with sociodemographic variables on the log odds of having DR. Furthermore, to improve intervention strategies similar studies should be conducted across the country.

Project description:BackgroundDiabetic retinopathy (DR) is the primary oculopathy causing blindness in diabetic patients. Currently, there is increasing interest in the role of lipids in the development of diabetic retinopathy, but it remains controversial. Remnant cholesterol (RC) is an inexpensive and easily measurable lipid parameter; however, the relationship between RC and DR in type 2 diabetes mellitus (T2DM) has not been elucidated. This research investigates the relevance between RC levels and DR severity while building a risk prediction model about DR.MethodsIn this single-centre retrospective cross-sectional study. Each hospitalised T2DM patient had no oral lipid-lowering drugs in the past three months, and coronary angiography showed epicardial coronary artery stenosis of less than 50% and completed seven-field stereo photographs, fluorescein fundus angiography, and optical coherence tomography detection. The RC value is calculated according to the internationally recognised formula. Binary logistic regression was used to correct confounding factors, and the receiver operating characteristic (ROC) analysis was used to identify risk factors and assess the nomogram's diagnostic efficiency.ResultsA total of 456 T2DM patients were included in the study. The RC levels in the DR team was higher [0.74 (0.60-1.12) mmo/l vs 0.54 (0.31-0.83) mmol/l P < 0.001] in the non-DR team. After adjusting for confounding elements, RC levels are still associated with DR risk (OR = 5.623 95%CI: 2.996-10.556 P < 0.001). The ratio of DR in every stage (except mild non-proliferative diabetic retinopathy) and DME in the high RC level team were further increased compared to the low-level team (all P < 0.001). After ROC analysis, the overall risk of DR was predicted by a nomogram constructed for RC, diabetes duration, and the neutrophil-lymphocyte ratio as 0.758 (95%CI 0.714-0.802 P < 0.001).ConclusionsHigh RC levels may be a potential risk factor for diabetic retinopathy, and the nomogram does better predict DR. Despite these essential findings, the limitation of this study is that it is single-centred and small sample size analysis.

Dataset Information

Metformin Treatment Is Associated with a Decreased Risk of Nonproliferative Diabetic Retinopathy in Patients with Type 2 Diabetes Mellitus: A Population-Based Cohort Study.

Publications

Metformin Treatment Is Associated with a Decreased Risk of Nonproliferative Diabetic Retinopathy in Patients with Type 2 Diabetes Mellitus: A Population-Based Cohort Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets