https://orcid.org/0000-0002-4876-446X
Figures
Abstract
Background
Western guidelines often recommend biguanides as the first-line treatment for diabetes. However, dipeptidyl peptidase-4 (DPP-4) inhibitors, alongside biguanides, are increasingly used as the first-line therapy for type 2 diabetes (T2DM) in Japan. However, there have been few studies comparing the effectiveness of biguanides and DPP-4 inhibitors with respect to diabetes-related complications and cardio-cerebrovascular events over the long term, as well as the costs associated.
Objective
We aimed to compare the outcomes of patients with T2DM who initiate treatment with a biguanide versus a DPP-4 inhibitor and the long-term costs associated.
Methods
We performed a cohort study between 2012 and 2021 using a new-user design and the Shizuoka Kokuho database. Patients were included if they were diagnosed with T2DM. The primary outcome was the incidence of cardio-cerebrovascular events or mortality from the initial month of treatment; and the secondary outcomes were the incidences of related complications (nephropathy, renal failure, retinopathy, and peripheral neuropathy) and the daily cost of the drugs used. Individuals who had experienced prior events during the preceding year were excluded, and events within 6 months of the start of the study period were censored. Propensity score matching was performed to compare between two groups.
Results
The matched 1:5 cohort comprised 529 and 2,116 patients who were initially treated with a biguanide or a DPP-4 inhibitor, respectively. Although there were no significant differences in the incidence of cardio-cerebrovascular events or mortality and T2DM-related complications between the two groups (p = 0.139 and p = 0.595), daily biguanide administration was significantly cheaper (mean daily cost for biguanides, 61.1 JPY; for DPP-4 inhibitors, 122.7 JPY; p<0.001).
Citation: Nakatani E, Ohno H, Satoh T, Funaki D, Ueki C, Matsunaga T, et al. (2024) Comparing the effects of biguanides and dipeptidyl peptidase-4 inhibitors on cardio-cerebrovascular outcomes, nephropathy, retinopathy, neuropathy, and treatment costs in diabetic patients. PLoS ONE 19(8): e0308734. https://doi.org/10.1371/journal.pone.0308734
Editor: Yasunori Sato, Keio University School of Medicine, JAPAN
Received: April 5, 2024; Accepted: July 30, 2024; Published: August 9, 2024
Copyright: © 2024 Nakatani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: According to the terms of Shizuoka Prefecture’s data use agreement with local insurers, the analyzed data cannot be provided to readers by the authors. Researchers interested in accessing this dataset may apply to Shizuoka Prefecture to request access. Please contact the staff of Shizuoka Graduate University of Public Health (e-mail: info@s-sph.ac.jp).
Funding: The funding for this work was provided by Shizuoka Prefecture. The Shizuoka Graduate University of Public Health conducts contract research projects regarding public health in Shizuoka Prefecture, including the current study.The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Type 2 diabetes mellitus (T2DM) is a significant global public health challenge, affecting millions and associated with various complications, particularly cardiovascular and cerebrovascular events [1, 2]. Initial pharmacological interventions for T2DM commonly include biguanides and dipeptidyl peptidase-4 (DPP-4) inhibitors, each with specific mechanisms and potential effects on patient outcomes [3–5]. While Western guidelines often recommend biguanides as the first-line treatment, in Japan, DPP-4 inhibitors alongside biguanides are increasingly used as first-line therapy.
Despite the widespread use of biguanide drugs and DPP-4 inhibitors in the management of diabetes, there is a notable absence of direct comparative studies evaluating their cost-effectiveness in Japan. This gap in the literature underscores the necessity for comprehensive research to assess and compare the economic implications of biguanide drugs and DPP-4 inhibitors within the Japanese healthcare context.
In this study, we compared the long-term effects of initiating treatment with a biguanide or a DPP-4 inhibitor on the incidences of cardiac and cerebrovascular events, diabetic complications, and the associated daily treatment costs in Japanese T2DM patients.
Materials and methods
Data source, design, and sample
A retrospective cohort study was performed using a new-user design analysis [6] and the Shizuoka Kokuho Database (SKDB), version 2023 [7], between 1 April 2012 and 30 September 2021. The SKDB contains detailed medical and long-term care insurance data for over 2.3 million individuals, representing a diverse population [7]. Previous studies have leveraged this database to assess the effectiveness and safety of various drugs [8–10]. We accessed the SKDB for research purposes between January 18 and 27, 2024.
The study cohort comprised individuals who were covered by National Health Insurance (aged <75 years) and the Latter-Stage Elderly Medical Care System (aged ≥75 years) in Shizuoka Prefecture, and who had been diagnosed with T2DM. The eligible participants had received a prescription for a first-line diabetes drug following a 1-year baseline health evaluation and a health checkup conducted within the 6 months prior to the initiation of the medication. Patients who had been hospitalized because of acute diabetes mellitus; who had a relevant genetic disease; who had experienced a prior cerebrovascular or cardiac event, cancer, dialysis, glucagon or insulin therapy; or who had undergone home self-injection training during the baseline period were excluded from the analysis.
First-line treatments
We compared the effects of an initial prescription of a biguanide alone (metformin hydrochloride or buformin hydrochloride) and a DPP-4 inhibitor alone. In the SKDB, the list of codes used to identify the appropriate patients is shown in S1 Table. The index date for each patient was the date when the initial treatment was prescribed (Fig 1). The patients were analytically allocated to two groups on the basis of the initial treatment administered, which was used as the primary exposure variable. Patients were excluded from the analysis if they did not visit a clinic for a consultation regarding their antidiabetic medication over a period of >6 months within the first year following the index date.
DPP-4: dipeptidyl peptidase-4, SKDB: Shizuoka Kokuho Database. Cohort entry was defined as the later of the date of registration with the health insurance provider or April 1, 2012. The index data were collected on the day that the participants were first prescribed a DPP-4 inhibitor or a biguanide. The follow-up period was defined as the interval between the index date and the end date of the study (September 30, 2021), the date of withdrawal from the health insurance system, or the date of occurrence of an outcome.
Potential confounders and other covariates
We made comprehensive adjustments for a range of variables to control for their potential confounding effects on the outcomes. These variables comprised demographic factors, comorbidities, the use of medication, physical activity level, lifestyle habits, and a variety of clinical parameters. Specifically, adjustments were made for sex, age, and comorbid conditions, including hypertension, dementia, cerebrovascular disease, renal disease, rheumatic disease, liver disease, and chronic pulmonary disease. The types of medication that were considered were anti-hypertensive and lipid-lowering agents. Furthermore, the analysis involved adjustment for body mass index (BMI), glycated hemoglobin (HbA1c) level, and lifestyle factors, including the frequency of walking or engaging in physical exercise for more than 1 hour per week, an increase in body mass of >10 kg since the age of 20 years, current smoking status, and heavy alcohol consumption. Heavy alcohol drinking was defined as daily alcohol drinking exceeding 360 mL. Current smokers were defined as those who had smoked over 100 cigarettes or for a minimum of 6 months and were actively smoking for at least the past month. The clinical parameters that were adjusted for comprised gamma-glutamyl transferase (GGT), systolic blood pressure, estimated glomerular filtration rate (eGFR), aspartate aminotransferase (AST), alanine aminotransferase (ALT), low-density lipoprotein (LDL)-cholesterol, triglycerides, and uric acid. The anatomical therapeutic chemical (ATC) codes for the other antidiabetic drugs used for sample selection are listed in S2 Table.
Outcomes
The primary outcome was the interval between the index date and the earliest of a cerebrovascular event, cardiac event, or mortality, as a composite outcome, defined using the corresponding codes listed in S3 Table. The secondary outcomes were the intervals from the index date to the onset of any diabetes-related event, including diabetic nephropathy, renal failure, diabetic retinopathy, and diabetic peripheral neuropathy, defined using the corresponding codes listed in S4 Table. Participants who were hospitalized or experienced a cerebrovascular event, a cardiac event, cancer, dialysis, or mortality within 6 months of the index date were censored (no event recorded) at that time, such that there was a grace period before the comparison of the effects of the two target drugs.
Cardiac events were defined as hospitalization because of (International Classification of Diseases, 10th Revision) ICD-10 codes I20, I21, I22, I24, I25, and I50, encompassing a range of acute and chronic coronary artery conditions and heart failure, along with the performance of significant interventions, such as percutaneous coronary interventions or coronary artery bypass grafting. This definition aligns with standard clinical and epidemiologic practices in diabetes research and captures the spectrum of cardiovascular complications that are associated with diabetes.
We used the internationally recognized ICD-10 codes (I60, I61, I62, I63, I64) to define stroke and the Japanese health care codes (8838736, 8838748, 8838750) for the identification of other cerebrovascular events. In this way, we aimed to comprehensively and accurately identify cerebrovascular events, while reflecting both international standards and the specific context of Japan.
Cost per day associated with the use of the antidiabetic drugs
To assess the cost of the medication used by the two treatment groups, the mean daily cost in Japanese Yen (JPY) throughout the observation period was calculated. The advantage of this approach lies in its ability to permit a fair comparison of the costs of treatment over specific periods of time. This method mitigates the effect of differing lengths of observation period by focusing on the mean daily cost, rather than the total cost. Consequently, it enables a more accurate evaluation of the cost-effectiveness of types of medication.
Statistical analysis
The covariates are summarized using means and standard deviations for continuous data, and frequencies and the corresponding percentages for categorical data. The propensity score for each participant was estimated using a multivariate logistic regression model that incorporated the aforementioned potential confounders. Certain covariates were excluded from the modeling, owing to the difficulty associated with the estimation of their magnitude. We created the cohorts for the analysis by one-to-k matching, based on the propensity scores, with a caliper width set to 0.2. The value of k was determined to be an integer not exceeding 10 following the propensity score matching. Consequently, the size of each study group was maintained at ≥90% of its pre-matching size. The balance of the groups was assessed using standardized mean differences (SMDs), with thresholds set at <10%. For survival time analysis, cumulative incidence curves were plotted. Differences between groups were evaluated using the log-rank test for survival or the composite outcome and Gray’s test [11] for other outcomes, during which mortality was treated as a competing risk. Point estimates and 95% confidence intervals (CIs) for each cumulative incidence were calculated, and hazard ratios (HRs) and the corresponding CIs were also calculated using a cause-specific Cox regression model. To compare the cost per day of the use of the antidiabetic drugs, we used Wilcoxon’s rank-sum test. The mean difference and the 95% CI were estimated using a univariable regression model. As sensitivity analyses for each outcome, the p-values obtained using Gray’s test and the HR (95% CI) for the inter-group comparisons for each outcome in participants who attended the clinic for at least 9 months and for the entire 12 months were calculated. Furthermore, subgroup analyses with respect to sex [male, female], age [<70 years, 70–79.9 years, ≥80 years], BMI [<25 kg/m2, ≥25 kg/m2], hypertension [present, absent], liver disease [present, absent], and the administration of lipid-lowering agents [present, absent], were performed similarly. Simple imputation for missing data was not performed. P < 0.05 was interpreted as indicating statistical significance. Statistical analyses were performed using EZR Version 1.61 (Saitama Medical Center, Jichi Medical University, Tochigi, Japan) [12] or SAS Version 9.4 (SAS Institute Inc., Cary, NC, USA).
Ethics
Our research, which is a retrospective study on data from the SKDB, involved comprehensive anonymization processes before analysis to ensure the privacy and confidentiality of participants [7]. Ethical approval for the study plan (SGUPH_2021_001_078) was granted by the Ethics Committee of Shizuoka Graduate University of Public Health, confirming compliance with all pertinent ethical standards and regulations. Given its retrospective nature and adherence to Japanese medical ethics guidelines, the necessity for informed consent was waived.
Results
Characteristics of the participants
A flow chart describing the sample selection is shown in Fig 2. Comparisons of the characteristics of the participants before and after propensity matching are shown in S5 Table and Table 1, respectively. Before propensity score matching, there were differences in the ages of the participants when the drug was first prescribed, the prevalence of dementia, BMI during a medical checkup, and HbA1c between the biguanide and DPP-4 inhibitor groups (SMD > 0.15, S5 Table). However, matching was conducted based on the characteristics of the biguanide group, such that the initial distributions of all these variables were aligned, making the two groups comparable (SMD < 0.1, Table 1).
Prescriptions of antidiabetic medication and clinic visits following propensity score matching
The antidiabetic medication being used and the number of clinic visits made prior to matching are shown in S6 Table. Table 2 shows the antidiabetic medication prescriptions and the number of healthcare visits within the year following the index date and propensity score matching for participants who were treated with a biguanide (n = 514) or a DPP-4 inhibitor (n = 2,570). After matching, 100% of the participants remained on their respective initial treatments (a biguanide or a DPP-4 inhibitor), and none were administering insulin. Very few participants were being prescribed a GLP-1 receptor agonist (0.2% in the biguanide group and 0.1% in the DPP-4 inhibitor group). SGLT2 inhibitors were more commonly prescribed in the biguanide group (9.3%) than in the DPP-4 inhibitor group (4.6%). The prevalences of alpha-glucosidase inhibitor and thiazolidinedione administration also slightly differed between the two groups. Rapid-acting secretagogues were equally frequently prescribed in the two groups (2.5%), but sulfonylureas were slightly more frequently prescribed to the DPP-4 inhibitor group (12.1% vs. 10.3% for the biguanide group). The mean number of healthcare visits was similar for the two groups, with the biguanide group averaging 10.68 visits per year and the DPP-4 inhibitor group averaging 10.80 visits, indicating comparable levels of healthcare engagement following matching.
Cardiac and cerebrovascular outcomes
The matched cohort consisted of 514 participants who were prescribed biguanides and 2,570 who were prescribed DPP-4 inhibitors during the observation period (1:5 matching ratio; median 4.0 years, maximum 8.5 years). Cardiac events occurred in 23 participants (4.5%) in the biguanide group and 149 participants (5.8%) in the DPP-4 inhibitor group. Cerebrovascular events occurred in 17 participants (3.3%) in the biguanide group and 84 participants (3.3%) in the DPP-4 inhibitor group. There were 16 deaths (3.1%) in the biguanide group and 91 (3.5%) in the DPP-4 inhibitor group. Therefore, the composite outcome occurred in 49 participants (9.5%) in the biguanide group and 267 participants (10.4%) in the DPP-4 inhibitor group (Table 3). The incidence of the cardio-cerebrovascular composite outcome did not significantly differ between the groups (p = 0.544; Table 3 and Fig 3A). The HR for the biguanide vs. DPP-4 inhibitor group was 1.06 (95% CI: 0.79–1.44), indicating no significant difference.
DPP-4i: dipeptidyl peptidase-4 inhibitor. Cumulative incidences of (a) the composite outcome of cardiac or cerebrovascular outcomes or mortality and (a) diabetic complications, including diabetic retinopathy, nephropathy, neuropathy, and other conditions, in the propensity score-matched cohort.
With respect to the sensitivity analyses, there were no differences in the incidences of the composite outcome based on population with visits of 9- and 12-months made during the 12 months following the index date (p = 0.395 and p = 0.835, respectively; S7 and S8 Tables). Furthermore, the subgroup analyses also showed no significant differences (Fig 4).
HR: hazard ratio, CI: confidence interval.
Diabetic complications
During the observation period, diabetic complications occurred in 79 participants (15.4%) in the biguanide group and 439 participants (17.1%) in the DPP-4 inhibitor group (p = 0.290; Table 3 and Fig 3B). The cumulative incidence of diabetic retinopathy, nephropathy, neuropathy, and other conditions between the two groups also indicated no significant difference (p = 0.579, p = 0.894, p = 0.491, and p = 0.891; Table 3).
The HR of biguanide use vs. DPP-4 inhibitor use for diabetic complications was 0.88 (95% CI: 0.70–1.13), indicating no significant difference. The HRs of biguanide use vs. DPP-4 inhibitor use for diabetic retinopathy, nephropathy, neuropathy, and other conditions were 0.93 (0.71–1.22), 0.97 (0.61–1.54), 0.76 (0.34–1.67), and 1.04 (0.59–1.84), indicating no significant difference.
The sensitivity analyses indicated that the incidences of the composite outcomes for diabetic complications did not differ after 9 or 12 months, based on population with visits of 9- and 12-months made during the 12 months following the index date (p = 0.722 and p = 0.348, respectively; S7 and S8 Tables). Furthermore, the results of the subgroup analyses, as shown in Fig 5, showed no significant differences.
HR: hazard ratio, CI: confidence interval.
Discussion
In our study comparing the effectiveness and cost of DPP-4 inhibitors and biguanides in Japanese T2DM patients, we found no significant differences in long-term incidences of cardio-cerebrovascular events and complications between the two groups, but the daily cost for antidiabetic agents of biguanide use was lower.
Metformin is celebrated for its effectiveness, safety, and financial benefits; it primarily reduces hepatic glucose production and enhances insulin sensitivity, lowering both fasting and postprandial blood glucose levels [13]. Unlike many antidiabetic agents, metformin does not promote weight gain or significantly increase the risk of hypoglycemia, making it the preferred first-line therapy in Japan [14]. Additionally, metformin may have cardiovascular benefits, reduce cancer risk [15, 16], and lower the risk of cognitive decline with long-term use [17]. These findings underscore the importance of considering cost alongside clinical effectiveness when selecting initial treatments for T2DM, particularly in light of rising healthcare costs. Opting for less expensive treatments with similar effectiveness can reduce the financial burden on patients without compromising care. Previous studies, including a systematic review [18], have focused on the general effectiveness and safety of biguanides and DDP-4 inhibitors in T2DM management. We add to this knowledge by evaluating their cost-effectiveness, an often-overlooked aspect crucial for healthcare decision-making. Demonstrating the economic benefits of biguanides, our study provides a comprehensive assessment of potential treatment strategies and enriches the dialogue surrounding diabetes management.
DPP-4 inhibitors are important for T2DM treatment and have a favorable safety profile for many patients [19]. They are crucial in diabetes management by preventing incretin hormone degradation and enhancing insulin secretion, effectively managing postprandial hyperglycemia [20, 21]. Their widespread use in Japan to improve glycemic control in T2DM patients, along with their mild side effects, demonstrates their high regard [22]. We found no significant differences in cardiovascular events or diabetes complications between patients treated with DPP-4 inhibitors and biguanides. This aligns with findings that DPP-4 inhibitors reduce hypoglycemia risk when combined with sulfonylureas [23] and are as effective as GLP-1 analogs. Their safety is demonstrated in patients with high cardiovascular risk and renal impairment [5]. DPP-4 inhibitors improve glycemic control without causing weight gain, maintaining a benign adverse event profile [24]. They balance safety and effectiveness in T2DM treatment and are preferred by Japanese patients for treatment satisfaction [25]. However, they may be associated with higher risks of adverse events such as asthenia, cardiac, and vascular disorders [26], and heart failure [27]. Moreover, geographic differences exist in adverse outcomes, with studies in Taiwan, Hong Kong, and the United States showing higher incidences of heart failure, hyperlipidemia, and renal failure with DPP-4 inhibitors compared to biguanides [28]. Additionally, DPP-4 inhibitors are associated with a higher risk of infections, especially upper respiratory tract infections [29]. Despite these risks, DPP-4 inhibitors have advantages like lower hypoglycemia risk and weight management benefits [30, 31]. Specific DPP-4 inhibitors, such as vildagliptin and sitagliptin, are beneficial for older patients due to their tolerability and low incidence of gastrointestinal side effects, and they are effective and safe for patients with renal impairment [32, 33]. However, given the significant cost advantage of biguanides, prescribing behaviors should be reevaluated considering the higher unit costs of DPP-4 inhibitors and the long-term safety, effectiveness, and lower cost of metformin.
Previous research also found the annual cost of DPP-4 inhibitors significantly higher [34]. Despite this, DPP-4 inhibitors can be cost-effective for patients whose glycemia cannot be controlled with metformin alone [35]. For T2DM patients who do not achieve glycemic targets with metformin alone, our findings suggest that a DPP-4 inhibitor is a viable alternative, reducing HbA1c similarly to sulfonylurea or pioglitazone without affecting body mass [18]. Therefore, the financial implications of choosing a DPP-4 inhibitor over a biguanide must be carefully considered in Japanese T2DM patients.
The study had several limitations. First, the SKDB-based methodology affects the generalizability of the results. Second, the geographic specificity of the database limits its applicability to other regions or demographics. Third, retrospective cohort studies carry risks of bias, especially from unmeasured confounders, making causal links difficult to establish. Fourth, selection bias from the exclusion criteria may limit applicability to patients with severe conditions or specific comorbidities. Fifth, despite using propensity score matching, unmeasured variables like dietary habits and physical activity might have influenced the outcomes. Future studies should evaluate these factors through detailed patient surveys or longitudinal monitoring. Sixth, conclusions based on Japanese patient data may not generalize to other ethnicities due to genetic and physiological differences affecting drug metabolism and effectiveness. Although we did not analyze ethnicity effects, such differences could lead to significant variations. Seventh, we did not include changes in HbA1c as an outcome due to inconsistent data availability in the SKDB. HbA1c data was only available for patients who underwent health check-ups in subsequent years, which limited our ability to accurately track post-baseline HbA1c levels. Last, using ICD-10 codes to determine outcomes may not capture all early diabetic complications such as microalbuminuria or unmedicated diabetic neuropathy, potentially underestimating their true incidence.
Conclusions
In patients with T2DM who commence pharmacotherapy, biguanides are associated with similar incidences of long-term cardio-cerebrovascular events and complications to DPP-4 inhibitors, but are cheaper. These findings underscore the therapeutic effectiveness and financial benefits of administering biguanides as the initial treatment for T2DM.
Supporting information
S1 Table. Search codes for DPP-4 inhibitors and biguanides.
DPP-4: dipeptidyl peptidase-4.
https://doi.org/10.1371/journal.pone.0308734.s001
(DOCX)
S2 Table. ATC codes for other antidiabetic medication.
ATC: anatomical therapeutic chemical, DPP-4: dipeptidyl peptidase-4, GLP-1: glucagon-like peptide-1, SGLT2: Sodium–glucose cotransporter 2.
https://doi.org/10.1371/journal.pone.0308734.s002
(DOCX)
S3 Table. Definitions of outcomes.
ICD-10: International Classification of Diseases, 10th Revision.
https://doi.org/10.1371/journal.pone.0308734.s003
(DOCX)
S4 Table. Diagnostic codes for diabetes in Japan.
ICD-10: International Classification of Diseases, 10th Revision.
https://doi.org/10.1371/journal.pone.0308734.s004
(DOCX)
S5 Table. Characteristics of the participants prior to propensity score matching.
ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; DPP-4, dipeptidyl peptidase 4; GFR, glomerular filtration rate; GGT, gamma-glutamyl transpeptidase; HbA1c, hemoglobin A1c; LDL, low-density lipoprotein; SMD: standardized mean difference.
https://doi.org/10.1371/journal.pone.0308734.s005
(DOCX)
S6 Table. Antidiabetic medication prescribed and the number of health care visits within the year following the index date, before propensity score matching.
DPP-4: dipeptidyl peptidase-4; GLP-1: glucagon-like peptide-1; SGLT2: sodium–glucose cotransporter 2.
https://doi.org/10.1371/journal.pone.0308734.s006
(DOCX)
S7 Table. Outcomes of the participants who were prescribed biguanide or a DPP-4 inhibitor in the matched cohort and who attended the clinic for ≥9 months, as a sensitivity analysis (n = 2,634).
*Gray’s test was performed. †The log-rank test was performed. DPP-4: dipeptidyl peptidase 4 inhibitor.
https://doi.org/10.1371/journal.pone.0308734.s007
(DOCX)
S8 Table. Outcomes of participants who were prescribed biguanide or a DPP-4 inhibitor in the matched cohort and who had attended the clinic for 12 months, as a sensitivity analysis (n = 1,602).
*Gray’s test was performed. †The log-rank test was performed. DPP-4: dipeptidyl peptidase 4 inhibitor.
https://doi.org/10.1371/journal.pone.0308734.s008
(DOCX)
Acknowledgments
We thank Mark Cleasby, PhD from Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript.
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