Research Article

Glucose Lowering Treatment Patterns in Type 2 Diabetes Mellitus (T2DM) Management: A Real World Study from the Rural-Urban Fringe Zone of Suzhou City, Jiangsu Province

by Xingfa Han1, Peng Xue1, Jin Yan2, Jingyu Yang1, Liping Wang1, Zheng Li1, Maoti Wei3*, Zhimin Ma1*

1Suzhou Research Center of Medical School, Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou, China

2Lhasa Detachment of Armed Police Crops Lhasa, Tibet Autonomous Region, 850000, China

3Center of Clinical Epidemiology, TEDA International Cardiovascular Hospital, Tianjin, China

*Corresponding author:Maoti Wei, Center of Clinical Epidemiology, TEDA International Cardiovascular Hospital, Tianjin, China

*Zhimin Ma, Suzhou Research Center of Medical School, Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou, China.

Received Date: 20 May, 2024

Accepted Date: 5 June, 2024

Published Date: 7 June, 2024

Citation:Han X, Xue P, Yan J, Yang J, Wang L, et al. (2024) Glucose Lowering Treatment Patterns in Type 2 Diabetes Mellitus (T2DM) Management: A Real World Study from the Rural-Urban Fringe Zone of Suzhou City, Jiangsu Province. Adv Prev Med Health Care 7: 1052. https://doi.org/10.29011/2688-996X.001052

Abstract

Objective: To manage type 2 diabetes mellitus (T2DM) using glucose lowering regents(GLRs) effectively, the patterns of treatment were studied based on real world data from a rural-urban fringe zone of Suzhou city, Jiangsu Province.

Methods: A cross-sectional study was carried out using data from T2DM management as basic public health service during August 2018 to January 2021 in the urban-rural fringe zone in Suzhou city, Jiangsu Province, China. HbA1c and detail information of the diabetic treating histories were collected when registered for T2DM management. HbA1c<7.0% was considered as T2DM controlled (i.e., HbA1c≥7.0% as the uncontrolled), and glucose lowering treatments patterns for medicine and insulin usages were described.

Results: Among GLRs in this rural-urban fringe zone, sulfonylurea (SU), metformin (MET) and alpha glucosidase inhibitor (AGI) were the most frequently used oral antidiabetic drugs(OADs), and 12% (150/1207) patients used short-term insulin(STI). More than 60% (764/1207) T2DM patients were managed with regent combinations. SU and MET were the most commonly observed combination for glucose lowering which accounted for 41%(489/1207) of patients under management and three quarters (371/489) were two-drug combinations. SU combined with AGI was observed as the second with proportion of 11% (127/1207).

More regent numbers with less control rates for T2DM management was observed. Single SU with control rate (95% CI) of 51.4% (108/210, 95% CI 44.5%-58.4%), nearly twenty percentage higher than that of then combination therapy (32.9%,189/386, 95% CI 29.0%-36.9%)(χ2=22.526, P<0.001). Among two-combinations of SU+MET, SU+AGI, AGI+MET and STI+MET, HbAc control rates were listed as 33% ( 95%CI 29%-37%), 35% (95%CI 26%-44%), 28% (95%CI 19%-38%) and 21%(95%CI 11%-33%), respectively.

Using SU as example, combinations had lower levels of HOMA-β scores which meant lower function of islets.

Conclusions: Antidiabetic drugs treatment patterns followed the national recommendation in the rural-urban fringe zone, however, the effects were not as expected, i.e., more glucose lowering regents would not raise the controlled rates and recently discovered regents should be included in the future managements.

Keywords: Glucose lowering regents(GLRs), oral antidiabetic drugs, T2DM management, rural-urban fringe zone

Abbreviations

T2DM: type 2 diabetes mellitus; FPG: fasting plasma glucose; 2hPG: 2h postprandial glucose; FPI: fasting plasma insulin; 2hPI: 2h postprandial insulin; HbA1c: glycosylated hemoglobin; HOMA-IR: homeostasis model assessment of insulin resistance;

HOMA-β: homeostasis model assessment of beta-cell function; SU: sulfonylurea; AGI: α-glucosidase inhibitor; DPP-4i: dipeptidyl peptidase-4 inhibitor; Non-SU: None sulfonylurea;

GLP-1RA: glucagon-like peptide-1 receptor agonist; SGLT2i: sodium-glucose cotransporter-2 inhibitor; TZD: thiazolidinedione; STI: short-term insulin; LTI: long-term insulin; MET,metformin; OADs: oral antidiabetic drugs; GLRs: glucose lowering regents

Introduction

Type 2 diabetes mellitus (T2DM) is a progressive disease, and controlling hyperglycemia is the goal of its management. Generally, medical nutrition therapies and exercises are the basic measures in T2DM management. However, as the course progresses, diet and exercise often fail to reach the glucose control target. The dependence on glucose lowering regents(GLRs) gradually increases, and timely treatment should be adopted, including hypoglycemic drugs and insulin injections alone or in combinations [1]. Chinese guidelines recommend metformin as the first-line medication for controlling hyperglycemia in T2DM and as the basic medication in drug combinations, while sulfonylurea(SU), none sulfonylurea (Non-SU), α-glycosidase inhibitors (AGI), thiazolidinedione (TZD), dipeptidyl peptidase-4 inhibitor (DPP4i), sodium-glucose cotransporter-2 inhibitor (SGLT2i), glucagonlike peptide-1 receptor agonist(GLP-1RA) and insulin are the main combination regents. Pharmacological regents alone or combination can be selected based on factors such as hypoglycemic risk, weight, economic conditions, and accessibility. In large urban communities in China, oral antidiabetic drugs(OADs) are the main ways for T2DM management. However, drug selection is different due to disease progress, clinical medication habits or other factors. For example, SUs are the most commonly used OAD among T2DM patients in Shanghai, with a usage rate of 62.4%, far higher than the levels in other cities (40-50%) [2]. In Italy, general practitioners, who play a major role in T2DM management, can only prescribe first-generation antidiabetic drugs, such as MET, SU, glinides, acarbose and glitazones, while the prescription of more recently marketed antidiabetic drugs, such as GLP-1RA, DPP-4i and SGLT2i, is restricted to diabetologist only, based on a therapeutic plan [3]. It can be seen that even under the same guidelines, there are differences in medication patterns.

The availability of new antidiabetic drugs has led to complex treatment patterns and to changes in drug utilization. A unique pattern of prescription is observed amongst Japanese patients with T2DM, i.e., DPP-4i, rather than MET, is predominantly used as the first-line treatments [4,5]. The growing number of people with T2DM has a great impact not only on clinical outcomes, but also on economic burden of the healthcare systems [3]. Therefore, the treatment approach should be substantially different from traditional methods. And, the introduction of new medications has led to inquiries regarding the role of older drugs in diabetes management [6]. Costs associated with diabetes-related complications represent the most relevant part of the national healthcare expenditure for diabetes and are higher than the costs of managing diabetes itself. Thus, an effective therapy with a good metabolic control can reduce the risk of complications and represents a valid strategy from an economic point of view [7].

From 2018, the local government initiated the project of chronic diseases management including T2DM in Suzhou, Jiangsu province. Each community health service center has set a team consisting of two trained-full-time physicians and a trainedfull-time nurse in charging the T2DM management. In the management, the first step was T2DM patient registration, then carried out basic information investigations, physical examinations and checkups, thus regularly following-ups were implemented for the management. It is recognized that to treat with a combination therapy from the time of initial diagnosis is the most effective way in T2DM management [6]. So, based on the baselines, especially pharmacological regimens in this area, the treatment patterns for T2DM management would be explored.

Material and Methods

Subjects

From August 2018 to January 2021, the local government initiated the project of chronic diseases management including T2DM. Three health service centers (urban-rural fringe zone) implemented in the T2DM management as the basic public health service, which covers about 20000 residents inhabited near a big lake (Taihu Lake) with the first class of government economy. These residents diagnosed or had the histories of T2DM were welcomed to participate in the project. After registration, basic information was investigated, physical examinations and checkups were recorded and regularly following-ups were carried out for T2DM management.

Registered T2DM patients met the inclusion criteria: (1) adults aged ≧30 years old diagnosed with diabetes based on fasting plasma glucose (FPG) ≥7.0mmol/L, or 2h plasma glucose (2hPG) during an oral glucose tolerance test ≥11.1mmol/L, or history of T2DM; (2) residents of Suzhou who visited the community health service center regularly; and (4) willing to participate in T2DM management.

Those with T1DM, or T3cDM or any other form of diabetes were excluded for T2DM management. Also data missing, without information of diabetes history or treating histories were excluded.

Biochemical tests

Glycosylated hemoglobin (HbA1c), plasma glucose (FPG and 2hPG) concentrations and insulin levels (FPI and 2hPI) were measured by biochemical tests. HbA1c was measured using high performance liquid chromatography and blood glucose concentrations were measured using the hexokinase method. And insulin levels were measured using chemiluminescent immunoassay method.

Data collection

This paper is a part job of a following-up studies, in this crosssectional study including T2DM patients registered during August 2018 to January 2021 and a medical staff team was trained for data collection. Self-report basic information and personal habits and individual disease histories and treatments were collected by face to face investigation, physical checkups and laboratory tests were carried out for body indexes, blood and urea results. Especial for the FPG, 2hPG, FPI and 2hPI levels were measured and the history of diabetes and the pharmacological regimens including medicines and insulins were investigated.

Using original data obtained from registration checkups, body mass index (BMI), homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis model assessment of beta-cell function (HOMA-β) were calculated. In brief, BMI was calculated as ratio of body weight(kg) and height(m)2. HOMA-IR index values were gotten as the FPG(mmol/L)×FPI(μU/mL)/22.5. HOMA‐β index values were calculated as 20 × FPI (μU/mL)/(FPG (mmol/L) –3.5).

All participants were informed that the data may be used for scientific researches and a signed consent form was obtained. The study was conducted in accordance with the declaration of Helsinki and approved by Clinical Research Ethics Committee of The Affiliated Suzhou Hospital of Nanjing University Medical School.

The controlled T2DM

All the criteria in this study referred to the guidelines for risk factors and control standards for prevention and treatment of T2DM in China (2020 Edition) [1]. In brief, the glycemic control of T2DM was plasma HbA1c < 7.0% and named as the controlled, on the contrary, plasma HbA1c ≥7.0% named as the uncontrolled.

Data processing and statistical methods

Data were first checked and then decrypted for the sake of personal confidentiality before analysis. After establishing the database, data were cleaned for unqualified data before analysis. The distribution of continuous data was checked first and then original data was used for calculation for normal distribution, and data were squared or logarithm transformed for skew distribution if condition permitted (Supplement. Fig. 1). In detail, disease duration of T2DM, HbA1c and C peptide were transformed using squared method. FPG, FPI, 2hPI, HOMA-IR and HOMA‐β were transformed using ln logarithm method. Quantitative data were presented using mean ± standard deviation or mean ± standard error or median with quartile percentiles. Student t-test (or t’-test) was used for the comparison between groups. Qualitative data (or counting data) were described as percentages or proportions, and comparisons between groups were carried out using chi-square test. P < 0.05 was considered as statistically significant of two sides.

Considering the fact that duration of T2DM may influence the HOMA-β, HOMA-IR and C-peptide, thus an analysis of covariance (ANCOVA) model with T2DM duration as covariates and leastsquares means were calculated for these indexes. The research data analysis and processing were completed by professional statistical analysts using SPSS software version 26.00 (Armonk, NY: IBM Corp).

The analysis process of the subjects was shown in Fig. 1.

 

Glucose lowering treatments patterns

According to self-reported information, 25 cases (2.1%, 25/1207) reported without glucose lowering treatments, 418 patients with only one antidiabetic regent. More than 60% (764/1207) patients managed with combination therapies and two-thirds (571/764) were two-drug combinations (Fig.1).

Among glucose lowering regents in this rural-urban fringe zone, SU, MET and AGI were the most frequently used OADs, especially for SU and MET, which accounted for 65% (785/1207) and 62% (749/1207) of the patients respectively. Also, 12% (150/1207) patients used short-term insulin (STI) as GLRs (Tab.1). For SU and STI, approximately one-third of them were single used for T2DM management, obvious higher than most of the regents except long-term insulin (LTI) (the most near percentage between SU and MET with χ2=26.850, P <0.001). AGI, TZD and DPP-4i were more used as combination therapies.

Usage frequency

Monotherapy (%)*

Combination therapy

2

3

4

5

Oral antidiabetic drugs(OADs)

SU

785

210(26.8)

449

114

11

1

MET

749

119(15.9)

459

154

16

1

AGI

194

11(5.7)

82

93

7

1

TZD

70

3(4.3)

25

36

6

0

Non-SU

68

10(14.7)

39

14

5

0

DPP-4i

51

2(3.9)

15

26

8

0

GLP-1RA

1

0(0.0)

0

0

1

0

Others

30

3(10.0)

3

17

7

0

Insulins

         

STI

151

46(30.5)

54

42

8

1

LTI

62

14(22.6)

16

20

11

1

*:Percentage in monotherapy means single usage of this regent accounted for all of its usage.

T2MD, type 2 diabetes mellitus; SU, sulfonylurea; MET, metformin; AGI, α‑glucosidase inhibitor; TZD, thiazolidinedione; Non-SU, None sulfonylurea; DPP-4i, dipeptidyl peptidase-4 inhibitor; GLP-1RA, glucagon-like peptide-1 receptor agonist; STI, short-term insulin; LTI, long-term insulin; Others including SGLT2i, sodium–glucose linked transporter 2 inhibitor and unspecific medicine in the investigation

Table 1: Treatment regimens for T2DM management in a rural-urban fringe zone in Suzhou city, Jiangsu Province, China.

T2DM, type 2 diabetes mellitus

*:Percentage in monotherapy means single usage of this regent accounted for all of its usage.

SU, sulfonylurea; AGI, alpha glucosidase inhibitor; DPP-4i, dipeptidyl peptidase-4 inhibitor; Non-SU, None sulfonylurea; GLP-1RA ,Glucagon-like peptide-1 receptor agonist; SGLT2i, sodium-glucose cotransporter-2 inhibitor; TZD, thiazolidinedione; STI, short-term insulin; LTI, long-term insulin; MET, metformin

SU and MET were the most commonly observed in combination usage for glucose lowering which accounted for 41%(489/1207) of patients under management (Tab.2). Among this combination, three quarters (371/489) were two-drug combination (Tab.3). SU combined with AGI was observed as the second with proportion of 11% (127/1207); however, more than a half (67/127) of this combination was in triple-drug combinations. And the AGI+MET combination accounted for more percentage (83%, 82/99) in the triple-drug combinations.

 

SU

MET

AGI

TZD

Non-SU

DPP-4i

GLP-1RA

Others

STI

LTI

SU

 

489

127

40

4

21

1

9

13

10

MET

489

 

99

38

45

33

1

20

63

31

AGI

127

99

 

3

10

5

0

5

35

9

TZD

40

38

3

10

4

0

3

12

5

Non-SU

4

45

10

10

4

0

2

6

1

DPP-4i

21

33

5

4

4

1

7

8

8

GLP-1RA

1

1

0

0

0

1

0

0

0

Others

9

20

5

3

2

7

0

6

6

STI

13

63

35

12

6

8

0

6

 

23

LTI

10

31

9

5

1

8

0

6

23

GLRs, glucose lowering regents; T2MD, type 2 diabetes mellitus; SU, sulfonylurea; MET, metformin; AGI, α‑glucosidase inhibitor; TZD, thiazolidinedione; Non-SU, None sulfonylurea; DPP-4i, dipeptidyl peptidase-4 inhibitor; GLP-1RA ,glucagon-like peptide-1 receptor agonist; STI, short-term insulin; LTI, long-term insulin; Others including SGLT2i, sodium–glucose linked transporter 2 inhibitor and unspecific medicine in the investigation

Table 2: Combination matrix of GLRs for T2MD management in a rural-urban fringe zone in Suzhou city, Jiangsu Province, China.

GLRs, glucose lowering regents;T2DM, type 2 diabetes mellitus

SU, sulfonylurea; AGI, alpha glucosidase inhibitor; DPP-4i, dipeptidyl peptidase-4 inhibitor;Non-SU, None sulfonylurea; GLP-1RA ,Glucagon-like peptide-1 receptor agonist; SGLT2i, sodium-glucose cotransporter-2 inhibitor; TZD, thiazolidinedione; STI, short-term insulin; LTI, long-term insulin; MET,metformin,

 

2

3

4

5

Total

SU+ MET

371

108

9

1

489

SU+AGI

56

67

3

1

127

AGI+ MET

13

82

3

1

99

STI+ MET

29

29

4

1

63

NonSU+ MET

29

12

4

 

45

SU+TZD

13

23

4

 

40

TZD+ MET

2

30

6

 

38

STI+AGI

11

17

6

1

35

DPP-4i +MET

6

20

7

 

33

LTI+ MET

9

13

8

1

31

STI+LTI

3

12

7

1

23

SU+DPP-4i

3

13

5

 

21

Met+others

0

14

6

 

20

STI+SU

2

7

3

1

13

STI+TZD

 

4

8

 

12

LTI+SU

1

3

5

1

10

LTI+AGI

 

3

5

1

9

SU+others

2

5

2

 

9

STI+ DPP-4i

2

5

1

 

8

LTI+ DPP-4i

1

5

2

 

8

Others+ DPP-4i

1

4

2

 

7

STI+NonSU

3

2

1

6

LTI+others

 

4

2

 

6

STI+others

 

2

4

 

6

GLRs, glucose lowering regents; T2MD, type 2 diabetes mellitus; SU, sulfonylurea; MET,metformin; AGI, α‑glucosidase inhibitor; STI, short-term insulin; Non-SU, None sulfonylurea; TZD, thiazolidinedione; DPP-4i, dipeptidyl peptidase-4 inhibitor; LTI, long-term insulin;

Others including GLP-1RA ,Glucagon-like peptide-1 receptor agonist and SGLT2i, sodium–glucose linked transporter 2 inhibitor

Table 3: Combination usages of GLRs for T2MD management in a rural-urban fringe zone in Suzhou city, Jiangsu Province, China

GLRs, glucose lowering regents;T2DM, type 2 diabetes mellitus

SU, sulfonylurea; AGI, alpha glucosidase inhibitor; DPP-4i, dipeptidyl peptidase-4 inhibitor; Non-SU, None sulfonylurea; GLP-1RA ,Glucagon-like peptide-1 receptor agonist; SGLT2i, sodium-glucose cotransporter-2 inhibitor; TZD, thiazolidinedione; STI, short-term insulin; LTI, long-term insulin; MET, metformin

Glucose lowering treatments and HbA1c control

Using HbA1c<7.0% as the T2DM control standard, the results showed that the control rate was 37.4% (451/1207, 95% CI 34.5% - 40.0%). Considering the therapy pattern of monotherapy or combination of regent numbers, it could be observed more regent numbers with less control rates for T2DM management. Single regent had control rate (95% CI) of 47.6% (199/418, 42.7%-52.5%), two-drug combination of 34.3%(196/571, 30.4%-38.4%), three-drug combination of 21.5%(37/172, 15.6%-28.4%) and four-drug combination of 15.0%(5/20,3.2%-37.9%). Specified for drug, for example, monotherapy of SU with control rate(95% CI) of 51.4% (108/210, 95% CI 44.5%-58.4%), nearly twenty percentage higher than that of combination therapy (32.9%,189/386, 95% CI 29.0%-36.9%)(χ2=22.526, P<0.001). This was also true for treatments with MET and STI (Tab. 4).

Monotherapy

Combination therapy

χ2

P

HbAc<7.0

HbAc≥7.0

Control rate(95% CI)

HbAc<7.0

HbAc≥7.0

Control rate(95% CI)

SU

108

102

51.4(44.5-58.4)

189

386

32.9(29.0-36.9)

22.526

<0.001

MET

58

61

48.7(39.5-58.1)

196

434

31.1(27.5-34.9)

13.878

<0.001

STI

18

28

39.1(25.1-54.6)

24

81

22.9(15.2-32.1)

4.218

0.040

LTI

1

13

7.1(0.2-33.9)

9

39

18.8(8.9-32.6)

0.391*

0.531

Non-SU

4

6

40.0(12.2-73.8)

15

43

25.9(15.3-39.0)

0.290*

0.590

AGI

6

5

54.5(23.4-83.3)

56

127

30.6(24.0-37.8)

1.745*

0.186

TZD

2

1

66.7(9.4-99.2)

15

52

22.4(13.1-34.2)

Fisher**

0.144

DPP-4i

0

2

0.0(0.0-84.2)

8

41

16.3(7.3-29.7)

Fisher**

1.000

* Yates corrected chi square; **:Fisher exact

SU, sulfonylurea; MET, metformin; STI, short-term insulin; LTI, long-term insulin; Non-SU, None sulfonylurea; AGI, α‑glucosidase inhibitor; TZD, thiazolidinedione;DPP-4i, dipeptidyl peptidase-4 inhibitor;

Table 4: Comparisons between monotherapy and combination therapy of the GLRs for T2DM management in a rural-urban fringe zone in Suzhou City, Jiangsu Province, China.

* Yates corrected chi square; **:Fisher exact

GLRs, glucose lowering regents;T2DM, type 2 diabetes mellitus

SU, sulfonylurea; AGI, alpha glucosidase inhibitor; DPP-4i, dipeptidyl peptidase-4 inhibitor; Non-SU, None sulfonylurea; GLP-1RA ,Glucagon-like peptide-1 receptor agonist; SGLT2i, sodium-glucose cotransporter-2 inhibitor; TZD, thiazolidinedione; STI, short-term insulin; LTI, long-term insulin; MET, metformin,

Among the most frequently combined used in combination therapies in T2DM management, two combinations of SU+MET and SU+AGI were with HbAc control rates of 33%( 95%CI 29%-37%) and 35% (95%CI 26%-44%). Two combinations of AGI+ MET and STI+ MET were lower control rates of 28% (95%CI 19%-38%) and 21%(95%CI 11%-33%) (Fig.2 & 3).

 

Figure 2: T2DM control rates for two-drug combinations in a rural-urban fringe zone in Suzhou City, Jiangsu Province, China.

SU, sulfonylurea; AGI, alpha glucosidase inhibitor; DPP-4i, dipeptidyl peptidase-4 inhibitor; Non-SU, None sulfonylurea; GLP-1RA ,Glucagon-like peptide-1 receptor agonist; SGLT2i, sodium-glucose cotransporter-2 inhibitor; TZD, thiazolidinedione; STI, short-term insulin; LTI, long-term insulin; MET,                metformin,

 

Figure 3: HOMA‐β scores, HOMA-IR scores and C-peptide levels in T2DM patients treated with glucose lowering regents in a rural-urban fringe zone in Suzhou city, Jiangsu Province, China

HOMA‐β means homeostasis model assessment of beta-cell function, HOMA-IR  means homeostasis model assessment of insulin resistance

Glucose lowering treatments and islet function

HOMA‐β scores, HOMA-IR scores and C-peptide levels were used to evaluate the function of islet in T2DM patients. The results showed that higher levels of HOMA-β and C-peptide in monotherapy of glucose lowering regents than the combinations, and HOMA-IR increased with number of combination regents. HOMA‐β scores was in the levels 40.9±2.3(range: 3.4-3749.4), HOMA-IR was 3.2± 2.1(range: 0.4-88.2) and C-peptide 1.24 ± 0.08(range: 0.2-5.4) (Fig. 4).

SU as one insulin secretion promote regents, could increase 20% more HOMA-β levels when monotherapy used (untreated patients with HOMA-β: 35.0±1.9), however, almost no increase of this score when compared with combination (Tab. 5)

Original Mean±SE

Least-squares Mean±SE*

Monotherapy

Combine therapy

F

P

Monotherapy

Combine therapy

F

P

HOMA-β

41.6±1.1

35.0±1.0

3.387

0.034

39.4±1.1

35.6±1.0

2.374

0.124

HOMA-IR

2.8±1.0

2.9±1.0

2.508

0.082

2.8±1.1

2.9±1.0

0.283

0.595

C-peptide

3.3±1.0

3.2±1.0

0.789

0.456

1.4±0.0

1.3±0.0

0.304

0.582

*Least-squares mean are means for groups that are adjusted for means of other factors in the model. In this paper, duration of T2DM was considered, and the process in SPSS as following (HOMA-β as example):

UNIANOVA LN_ HOMA-β BY monornotSU WITH SQDurationT2DM

  /METHOD=SSTYPE(3)

  /INTERCEPT=INCLUDE

  /EMMEANS=TABLES(monornotSU) WITH(SQDurationT2DM=MEAN) COMPARE ADJ(SIDAK)

  /CRITERIA=ALPHA(0.05)

  /DESIGN=SQDurationT2DM monornotSU.

Table 5: SU treatment and islet function evaluation in T2DM patients in a rural-urban fringe zone in Suzhou City, Jiangsu Province, China

Discussion

As an effective way to control blood glucose in patients with T2DM, antidiabetic regents play important roles in management. Studies show that strict control of blood glucose from the early stage can significantly reduce the risk of diabetic microangiopathy, which were confirmed by follow-up results with lower myocardial infarctions and deaths [1]. The Chinese guideline for the prevention and treatment of T2DM recommended metformin and life style intervention as the first-line measures [1]. However, in the ruralurban fringe zone in Suzhou city, about 62% (749/1207) of the patients followed the recommendation using metformin and the most frequently used antidiabetic regent was sulfonylurea with usage rate 65% (785/1207), which is near to neighbor Shanghai with a usage rate of 62.4%, far higher than the levels in other cities (40-50%) [3]. Also, the Chinese guideline suggested more GLRs combinations in T2DM managements for these with unsatisfactory control results, and results in this paper showed 64% (770/1207) of the patients used combinations, two-regent combination was 47% (571/1207) similar to that of its neighbor city Shanghai [3]. Thus, to implement better T2DM managements in this area, metformin and combination should be improved.

According to mechanisms, OADs are divided into drugs that mainly promote insulin secretion and drugs that lower blood sugar through other mechanisms. The former mainly includes SU, glinides, and DPP⁃4i, while drugs that lower blood sugar through other mechanisms mainly include MET, TZD, AGI and SGLT2i. The last decade experienced a surge in the number of GLRs that can be used to treat patients with T2DM. Accordingly, various medical associations have updated their guidelines for the treatment of diabetes in this new era. The most effective way to manage diabetes is to treat it with a combination therapy from the time of initial diagnosis and early combination therapy with diabetes/disease modifying drugs may improve the multiple pathophysiological abnormalities responsible for T2DM and its complications, thus resulting in the greatest long term benefits [6,9]. And the definition of diabetes/disease modifying drugs was proposed what makes T2DM treatment approaches simpler and therefore more useful in the primary care setting. Among DMDs, SGLT2i worked through their function in the kidney and GLP1RAs probably through reduction in body weight. Yet, the diabetes/ disease modifying drugs were seldom used in rural-urban fringe zone in Suzhou City, one case of GLP-1RA and none of SGLT2i. According to SIMPLE approach, for patient with T2DM not controlled on OADs, most patients should initiate SGLT2i and/or GLP-1RA [9]. Unique pattern that DPP-4i rather than metformin is predominantly used as the first-line treatment and SGLT2i use has increased consistently since their market entry, but remains low [4,5]. So, future management of T2DM in this area should increase the usage of novel regents issued recently, such as diabetes/disease modifying drugs including SGLT2i and/or GLP-1RA.

In this region, 37.4% (451/1207, 95% CI 34.5% - 40.0%) T2DM patients were with satisfactory control results (HbA1c<7.0%), far lower than the goal of management (55%). Usually, it is considered that combinations of antidiabetic regents would works more effectively, however, according to this study, single regent had higher control rate, than two-drug combination or triple- or tetrad- drug combinations. This phenomenon was also observed in a combination of insulin and antidiabetic drugs [10]. This can be explained in two ways: first, before 2018, a sequential therapy strategy was carried out for T2DM management and the influence would still play a role in some places, especially in rural-urban fringe zone. In this condition, if T2DM uncontrolled with more drugs would be added instead of the effect and mechanism. The failure of single target approaches is the major challenge faced in T2DM treatment. Multitargeting is a promising approach for the treatment of T2DM as it includes multiple pathways [11]. Second, the combination had less effect and almost no new drugs were introduced in the patients of this area.

Different combinations may be caused by different patterns and habits. For example, in Italy, general practitioners, who play a major role in T2DM management, can only prescribe firstgeneration antidiabetic drugs, such as MET, SU, Non-SU, AGI, while the prescription of more recently marketed antidiabetic drugs, such as GLP-1RA, DPP-4i and SGLT2i, is restricted to diabetologist only [7]. SU and MET combination is 30% in Italy and decrease slightly from 2011 to 2017 [3], and this combination was the most commonly observed for glucose lowering which accounted for 41%(489/1207) of patients under management in this area. Among the most frequently combined used in combination therapies in T2DM management, two-drug combinations of SU+MET and SU+AGI were with HbAc control rates of 33% and 35%, higher than such combinations of AGI+MET (28%) and STI+MET(21%). With the number of drugs and classes of GLAs increasing rapidly, multiple combinations of therapies are available. The level of evidence required today for the introduction of new GLAs differs from what was required in the past, and no such information will be available for some of the older drug groups. And the experience of health care providers as well as patient experience with the older GLAs should not be dismissed [12]. It is suggested that the patient’s pancreatic function should be evaluated before managements and the management plan should be formulated based on the HbA1c. [8] In this paper, though GLAs was used as monotherapy or combination, yet their effect should be considered carefully. For example, SU as one insulin secretion promote regents, could increase 20% more HOMA-β levels when monotherapy used (untreated patients with HOMA-β:35.0±1.9). So, in future management of T2DM, more suitable combinations should be developed depending on islet function evaluation.

In traditional Chinese medicine, T2DM is recognized as “marasmus and thirsty (in Chinses XiaoKe)” in traditional Chinese medical theory and the Chinese patent drugs ( in Chinese ZhongCheng Yao) are widely used for preventing and treating according to the traditional Chinese medical theories such as “elimination thirsty, anti-weight loss and improve diuresis (SanXiao theory) “, “discrimination of yin deficiency type, yang deficiency type, and yin and yang dual-deficiency type (SanXing discrimination) ” and “phased differentiation”. The Guideline for the prevention and treatment of T2DM in China (2020 edition) issued in 2021 suggested that the Chinese patent drugs should play important roles in reducing blood glucose, improving symptoms and signs, and preventing complications [1]. Phytoconstituents are promising as they interact with multiple pathways simultaneously [11]. However, the reluctance to rely on phytoconstituents as the main therapy still remains as a limiting factor for such drugs to serve as mainstream interventions.

A few limitations of this study should be noted when interpreting its results. The study was based on data from registration claims, with limited information on the patients’ clinical status. Furthermore, the reasons for combination therapies or adding other regents were not available. Although claims data provide accurate information on medication dispensation, the lack of these factors may have biased our assessment for the reasons. The paper based on prescription/dispensation data submitted by healthcare providers, so the patients’ actual administration behaviors were unknown. Also, the dosage of the regents were not included in the paper because of there may be mistakes reported by patients themselves.

In conclusion, the glucose lowering treatment for T2DM management in the rural-urban fringe zone was a pattern almost following the recommendation by the authority, however, the effect of them was not as expected, and more glucose lowering regents would not raise the controlled rate. Thus, attentions should be paid to factors other than only drugs, including improving the education of diabetic patients, strengthening lifestyle intervention and blood glucose monitoring, improving the compliance, increasing the level of T2DM management ability and reducing the drug adjustment inertia of community doctors. Also, recently discovered regents should be included in the future managements.

Acknowledgements

This study was supported by Special Project on diagnosis and treatment of key clinical diseases in Suzhou(LCZX202030), Health Science and Technology Program in new district of                Suzhou(2020Z010),           the          China     International        Medical Foundation(grant no. Z-2019-42-1908) and Tianjin Key Medical Discipline (Specialty) Construction Project(TJYXZDXK-020A). We thank all staff members for collecting the data. It would have been impossible to successfully complete this study without their valuable assistance.

Conflict of interest: No.

Disclosure: Xingfa Han, Peng Xue, Jin Yan and Jingyu Yang contributed equally to this work. Our research was conducted in accordance with the declaration of Helsinki and approved by Clinical Research Ethics Committee of The Affiliated Suzhou Hospital of Nanjing University Medical School. All the participants have signed informed consent.

Approval of the research protocol: Yes

Informed Consent: Informed consent was obtained from all subjects and/or their legal guardians.

Approval date of Registry and the Registration

No. of the study/trial: Animal Studies: N/A

Data availability:The raw data has been uploaded. All data generated or analysed during this study are included in this published article [and its supplementary information files].

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Supplement Figure 1 Data distribution for original data and transformed data Original distribution      Transformed distribution

 

C peptide(μU/mL)         SQRT(C peptide)

 

Disease duration(Years)     SQRT(Disease duration)

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