Literature DB >> 27413017

Risk of hypoglycaemia in users of sulphonylureas compared with metformin in relation to renal function and sulphonylurea metabolite group: population based cohort study.

Judith van Dalem1, Martijn C G J Brouwers2, Coen D A Stehouwer3, André Krings4, Hubert G M Leufkens5, Johanna H M Driessen6, Frank de Vries7, Andrea M Burden6.   

Abstract

OBJECTIVE: To determine the association between use of sulphonylureas and risk of hypoglycaemia in relation to renal function and sulphonylurea metabolic group compared with use of metformin.
DESIGN: Population based cohort study using routinely collected data from general practices in England.
SETTING: Clinical Practice Research Datalink (CPRD) database, 2004-12. PARTICIPANTS: 120 803 new users of a non-insulin antidiabetic agent with at least one prescription and aged 18 years or more. The first prescription defined start of follow-up. Patients were followed until the end of data collection, a record for hypoglycaemia, or a blood glucose level of less than 3.0 mmol/L. MAIN OUTCOME MEASURES: Associations between sulphonylurea dose, renal impairment, type of sulphonylurea used, and risk of hypoglycaemia, were determined using Cox proportional hazard models. Adjustments were made for age, sex, lifestyle, comorbidity, and drug use.
RESULTS: The risk of hypoglycaemia in current users of sulphonylureas only was significantly increased compared with current users of metformin only (adjusted hazard ratio 2.50, 95% confidence interval 2.23 to 2.82). The higher risk in current users of sulphonylureas only was further increased in patients with an estimated glomerular filtration rate of less than 30 mL/min/1.73 m(2) (4.96, 3.76 to 6.55). The risk of hypoglycaemia was also significantly higher in patients with a high sulphonylurea dose (3.12, 2.68 to 3.62) and in current users of glibenclamide (7.48, 4.89 to 11.44). Gliclazide, the sulphonylurea of first choice, showed a similar risk of hypoglycaemia compared with other sulphonylureas.
CONCLUSIONS: Sulphonylurea treatment in patients with a renal function of less than 30 mL/min/1.73 m(2) should be considered with caution. Moreover, an increased risk of hypoglycaemic events was observed among all users of sulphonylureas. This contrasts with several guidelines that recommend gliclazide as first choice sulphonylurea, and therefore requires further investigation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

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Year:  2016        PMID: 27413017      PMCID: PMC4948031          DOI: 10.1136/bmj.i3625

Source DB:  PubMed          Journal:  BMJ        ISSN: 0959-8138


Introduction

In the 21st century, type 2 diabetes has reached epidemic proportions globally.1 It currently affects over 310 million people worldwide, and in 2014, 4.9 million deaths were attributable to diabetes related complications.1 2 Strict glycaemic control is critically important in people with type 2 diabetes. Sulphonylureas play a pivotal role in glycaemic control by stimulating insulin secretion, thereby suppressing glucose production and stimulating the utilisation of glucose.3 As a direct extension of their mechanism of action, however, the risk of hypoglycaemia is increased, and this risk may be further increased in patients with renal impairment, which is a common comorbidity associated with type 2 diabetes. It is well established that metabolites can accumulate as the glomerular filtration rate falls. In people with type 2 diabetes, hypoglycaemia is more common among those who use long acting sulphonylureas with renally excreted active metabolites (eg, glibenclamide and glimepiride).4 5 6 7 Use of these sulphonylureas might therefore further increase the risk of hypoglycaemia in patients with renal impairment. In contrast, tolbutamide, glipizide, and gliclazide are mainly excreted as unchanged drug or inactive metabolites with minimal hypoglycaemic effect.7 As gliclazide is associated with a low risk of hypoglycaemia, it is the first choice sulphonylurea in many countries.8 9 Studies have shown that incidence rates of hypoglycaemia in sulphonylurea users without renal impairment range from 0.2 to 1.8 events per 100 person years.10 11 12 13 For patients with renal impairment, however, the literature is sparse and conflicting. Although one study14 did not find an association in glibenclamide users, three others15 16 17 suggested an increased risk of hypoglycaemia among sulphonylurea users with renal impairment. No study has compared the risk of hypoglycaemia between the two groups of sulphonylureas—those with active metabolites and those with inactive metabolites—in patients with renal impairment. Therefore, we evaluated the association between current use of sulphonylureas only and the risk of hypoglycaemia according to renal function and sulphonylurea metabolite group, compared with current use of metformin only.

Methods

Data sources

Data for this study were derived from the Clinical Practice Research Datalink (CPRD), which contains computerised medical records for more than 11 million patients from 674 practices in the United Kingdom. CPRD currently holds data on 7% of the UK population and is generalisable to the UK population.18 Data since 1987 include patients’ personal characteristics, medical history, laboratory test results, details of prescriptions, specialist referrals, hospital admissions, and major outcomes, with ongoing data collection. Read codes, a hierarchical coding system, are used to define symptoms, diagnoses, referrals, and laboratory or diagnostic tests and results. Read codes are entered by the general practitioner and undergo quality checks before entry into CPRD. Diagnoses in CPRD have been validated in a wide range of diseases, including diabetes and hypoglycaemia, showing a high validity.19 20

Study population

We included all patients aged 18 years or more with at least one prescription for a non-insulin antidiabetic agent during the period of valid CPRD data collection. For this study, data collection began in April 2004, the introduction of the Quality and Outcomes Framework, and ended in August 2012. We defined the index date as the date of the first prescription, after the start of valid data collection. In the CPRD, the date that a practice became “up to research standard” (ie, practice has medical, laboratory, and drug recording of sufficient quality for at minimum one year) largely determines the valid data collection. Therefore, all patients had a minimum of one year of high quality data collection before the index date. We applied a new user design by excluding all patients with a history of non-insulin antidiabetic agent or insulin prescriptions, or the outcome of interest, before the index date.

Use of non-insulin antidiabetic agents

Use of non-insulin antidiabetic agents was assessed in a time dependent manner. We divided follow-up in 90 day intervals, starting on the first date of an eligible prescription (ie, the index date). Use of non-insulin antidiabetic agents was assessed at the start of each 90 day time interval, and classified according to the time since the most recent prescription: current use (1-90 days), recent use (91-180 days), or past use (>180 days). As a result, participants can move between these groups during follow-up. We further stratified current users of sulphonylureas only according to their most recent prescribed defined daily dose (low, medium, and high), most recent renal function (≥60, 30-59, and <30 mL/min/1.73 m2 or receiving dialysis), and sulphonylurea metabolite group (active versus inactive). Dosage equivalents were calculated using the World Health Organization’s defined daily dosages.21 When written instructions on dosage were missing, we assigned the median value of all prescriptions. Most recent renal function was evaluated using laboratory test data (estimated glomerular filtration rate (eGFR) (modification of diet in renal disease, MDRD) where possible) and CPRD Read codes (stages of chronic kidney disease). To obtain renal function, we considered data up to one year before the start of a 90 day interval. When multiple eGFR values were reported on one day, we used the mean value. In the event of a CPRD Read code and laboratory test result being recorded on the same day, we prioritised CPRD Read codes.

Outcomes

We followed patients from the index date to the end of data collection, date of transfer out of the practice area, date the practice stopped delivering data, date of death, or a first ever hypoglycaemic event; whichever occurred first. According to the methods of Bruderer et al,22 we defined a first ever hypoglycaemic event as the first Read code recording for hypoglycaemia or a laboratory test result indicating a blood glucose level of less than 3.0 mmol/L. When multiple blood glucose levels were recorded on the same day, we used the lowest value. Patients were excluded if they had a history of a hypoglycaemic event before their index date.

Potential confounders

We assessed the presence of risk factors for hypoglycaemia during follow-up by reviewing computerised medical records for any record of a risk factor before the start of an interval. Several potential confounders were determined at baseline: sex, smoking status (non-smoker, current smoker, former smoker, or unknown), and body mass index (<25.0, 25.0–29.9, ≥30 kg/m2, or unknown). Other confounders considered in this study were determined time dependently at the start of each new interval; alcohol use, the most recent haemoglobin A1c record in the past year, chronic liver disease, cardiovascular disease, congestive heart failure, or cognitive impairment or dementia. In addition, we considered use of any of the following drugs in the previous six months of an interval as a potential confounder: oral anticoagulants, statins, antipsychotics or antidepressants, corticosteroids, antihypertensives (including loop diuretics, thiazide diuretics, renin-angiotensin-aldosterone system inhibitors (angiotensin converting enzyme inhibitors or angiotensin receptor blockers), calcium channel blockers, and β blockers23), and non-steroidal anti-inflammatory drugs. Confounders are factors associated with hypoglycaemia and the exposure of interest (sulphonylurea use or renal function) and we selected them based on the literature. We entered confounders into the final model if they independently changed the β coefficient for current sulphonylurea use by at least 5% or when inclusion was supported by clinical evidence, or both.

Data analysis

We identified and summarised incidence rates as events per 1000 person years. The primary analysis was to estimate the risk of hypoglycaemia in current users of sulphonylureas only compared with current users of metformin only in relation to renal function. This analysis was further stratified by prescribed daily dose, sulphonylurea metabolite (active versus inactive), and specific sulphonylurea. We used Cox regression analysis (SAS 9.2. PHREG procedure) in all analyses.

Sensitivity analyses

Additional sensitivity analyses were requested during peer review, and the following post hoc analyses were completed: stratification of current users of metformin only by renal function, and stratification of current users of sulphonylureas only by daily dose and haemoglobin A1c level: low (<7%) versus high (≥7%).

Patient involvement

Patients were not involved in the development of the research question, outcome measures, design, or implementation of the study. Patients were not asked to advise, interpret, or disseminate results. However, we plan on sharing our findings with the European Diabetes Association.

Results

Table 1 shows the baseline characteristics of all 120 803 patients (see supplementary appendix for stratification by drugs at the index date). The mean duration of follow-up was 3.7 years. The mean age of all users was 67.4 years, and 47.2% (n=57 065) were women. No substantial differences were observed in age and sex distribution across drug use groups (see supplementary appendix A). However, the proportion of patients with a high body mass index (≥30) was considerably lower in sulphonylurea users (26.8%; n=3544) compared with metformin users (57.1%; n=52 496) or other non-insulin antidiabetic agents (57.9%; n=3628). More sulphonylurea users had lower renal function than metformin users or users of other non-insulin antidiabetic agents. Similarly, cardiovascular diseases were more prevalent in sulphonylurea users compared with the other groups.
Table 1

Baseline characteristics of users of non-insulin antidiabetic agents. Values are numbers (percentages) unless stated otherwise

CharacteristicsUsers of non-insulin antidiabetes agents (n=120 803)
Mean (SD) follow-up time3.65 (2.4)
Women57 065 (47.2)
Mean (SD) age (years)67.4 (16.0)
Age group (years):
 18-292127 (1.8)
 30-394014 (3.3)
 40-4910 157 (8.4)
 50-5919 319 (16.0)
 60-6927 815 (23.0)
 70-7929 042 (24.0)
 ≥8028 329 (23.5)
Most recent renal function in past year (mL/min/1.73 m2):
 <30734 (0.6)
 30-5919 070 (15.8)
 ≥6060 025 (49.7)
 Unknown40 974 (33.9)
Mean (SD) haemoglobin A1c (%)8.32 (1.86)
Unknown57 850 (47.9)
Smoking status:
 Current smoker22 007 (18.2)
 Former smoker49 598 (41.1)
 Never smoker48 328 (40.0)
 Unknown870 (0.7)
Alcohol use:
 Yes77 880 (64.5)
 No35 427 (29.3)
 Unknown7496 (6.2)
Body mass index:
 <20.01670 (1.4)
 20.0-24.914 759 (12.2)
 25.0-29.936 907 (30.6)
 ≥30.063 770 (52.8)
 Unknown3697 (3.1)
History of disease:
 Asthma or COPD18 698 (15.5)
 Cardiovascular disease18 863 (15.6)
 Chronic liver disease321 (0.3)
 Cognitive impairment or dementia1767 (1.5)
Drug use in past six months:
 Thiazide diuretics20 689 (17.1)
 RAAS inhibitors43 611 (36.1)
 Loop diuretics10 918 (9.0)
 β blockers20 843 (17.3)
 Calcium channel blockers23 963 (19.8)
 Typical antipsychotics1079 (0.9)
 Atypical antipsychotics1693 (1.4)
 SSRIs9159 (7.6)
 SNRIs1491 (1.2)
 Tricyclic antidepressants7276 (6.0)
 Monoamine oxidase inhibitors22 (0.02)
 NSAIDs15 471 (12.8)
 Statins50 925 (42.2)
 Corticosteroids (systemic)6185 (5.1)
 Oral anticoagulants4620 (3.8)
 Trimethoprim4838 (4.0)

COPD=chronic obstructive pulmonary disease; NSAIDs=non-steroidal anti-inflammatory drugs; RAAS=renin-angiotensin-aldosterone system; SSRIs=selective serotonin reuptake inhibitors; SNRIs=serotonin-norepinephrine reuptake inhibitors.

Baseline characteristics of users of non-insulin antidiabetic agents. Values are numbers (percentages) unless stated otherwise COPD=chronic obstructive pulmonary disease; NSAIDs=non-steroidal anti-inflammatory drugs; RAAS=renin-angiotensin-aldosterone system; SSRIs=selective serotonin reuptake inhibitors; SNRIs=serotonin-norepinephrine reuptake inhibitors. We identified a 2.5-fold increased risk of a hypoglycaemic event among current users of sulphonylureas only compared with current users of metformin only (adjusted hazard ratio 2.50, 95% confidence interval 2.23 to 2.82), adjusted for use of other non-insulin antidiabetic agents (table 2). The risk was further increased among patients who used sulphonylureas and metformin concomitantly. When current sulphonylurea use was stratified by prescribed daily dose, a more than threefold increased risk of hypoglycaemic events was found among users of the highest daily dose (3.12, 2.68 to 3.62) compared with users of metformin only.
Table 2

Risk of hypoglycaemia in participants with diabetic using non-insulin antidiabetic agents (NIAAs), sulphonylurea only users stratified by most recent prescribed daily dose

Drug useRisk of hypoglycaemia
No of eventsPerson yearsIncident rateAdjusted hazard ratio (95% CI)*Fully adjusted hazard ratio (95% CI)†
Metformin only use
Current836205 3514.1ReferenceReference
Recent2021 5840.90.37 (0.24 to 0.57)0.36 (0.23 to 0.55)
Past47673 0090.10.18 (0.14 to 0.24)0.18 (0.14 to 0.25)
Sulphonylurea only use
Current‡:45733 82913.53.30 (2.94 to 3.69)2.50 (2.23 to 2.82)
 Low dose14615 2369.62.68 (2.35 to 3.06)2.03 (1.77 to 2.32)
 Medium dose109898812.12.81 (2.43 to 3.24)2.16 (1.86 to 2.50)
 High dose102438623.34.18 (3.61 to 4.84)3.12 (2.68 to 3.62)
 Unknown§100380826.35.88 (5.02 to 6.87)4.60 (3.92 to 5.40)
Recent1737344.61.53 (0.95 to 2.48)1.09 (0.67 to 1.76)
Past4378 3830.60.74 (0.55 to 1.01)0.56 (0.41 to 0.76)
Metformin and sulphonylurea use
Current104374 84713.93.24 (2.95 to 3.56)3.06 (2.79 to 3.37)
Recent1661872.61.15 (0.68 to 1.97)1.05 (0.62 to 1.78)
Past58447 7230.10.44 (0.34 to 0.58)0.40 (0.30 to 0.52)
Metformin and other NIAA use
Current12419 6526.31.26 (1.00 to 1.59)1.28 (1.02 to 1.61)
Recent<65946.70.80 (0.23 to 2.84)0.83 (0.23 to 2.92)
Past<638500.10.17 (0.06 to 0.45)0.17 (0.06 to 0.47)
Sulphonylurea and other NIAA use
Current82483017.03.69 (2.83 to 4.80)3.12 (2.39 to 4.06)
Recent<64254.71.25 (0.25 to 6.18)1.05 (0.21 to 5.20)
Past<678220.40.52 (0.17 to 1.62)0.41 (0.13 to 1.30)
Other NIAA use¶
Current3247006.80.88 (0.74 to 1.04)0.93 (0.79 to 1.10)
Recent<63575.61.45 (0.64 to 3.25)1.44 (0.64 to 3.20)
Past<68761.11.37 (1.21 to 1.56)1.37 (1.21 to 1.55)

Current use=in previous 90 days from start of a 90 day interval; recent use=between 91 and 180 days from start of a 90 day interval; past use=more than 180 days from start of a 90 day interval. All analyses adjusted for current, recent, past use of all drug use groups.

*Adjusted for age and sex.

†Adjusted for age, sex, body mass index, alcohol use, smoking status, cardiovascular disease, chronic heart failure, and use of loop diuretics.

‡Sulphonylurea only use stratified by most recent dose: low dose, <5 mg glibenclamide equivalents; medium dose, 5-10 mg glibenclamide equivalents; high dose, >10 mg glibenclamide equivalents.

§Patients only received one prescription; a minimum of two are required to estimate the prescribed daily dose.

¶Other than sulphonylurea and metformin use.

Risk of hypoglycaemia in participants with diabetic using non-insulin antidiabetic agents (NIAAs), sulphonylurea only users stratified by most recent prescribed daily dose Current use=in previous 90 days from start of a 90 day interval; recent use=between 91 and 180 days from start of a 90 day interval; past use=more than 180 days from start of a 90 day interval. All analyses adjusted for current, recent, past use of all drug use groups. *Adjusted for age and sex. †Adjusted for age, sex, body mass index, alcohol use, smoking status, cardiovascular disease, chronic heart failure, and use of loop diuretics. Sulphonylurea only use stratified by most recent dose: low dose, <5 mg glibenclamide equivalents; medium dose, 5-10 mg glibenclamide equivalents; high dose, >10 mg glibenclamide equivalents. §Patients only received one prescription; a minimum of two are required to estimate the prescribed daily dose. ¶Other than sulphonylurea and metformin use. Table 3 shows that the risk of hypoglycaemic events also increased with reduced renal function. Patients with an eGFR of less than 30 mL/min/1.73 m2 using sulphonylureas only had a fivefold increased risk compared with users of metformin only (4.96, 3.76 to 6.55), whereas this risk was noticeably lower among patients with an eGFR of 30-59 mL/min/1.73 m2 (2.69, 2.25 to 3.20) or ≥60 mL/min/1.73 m2 (2.04, 1.73 to 2.41).
Table 3

Risk of hypoglycaemia in current users of sulphonylureas only compared with current users of metformin only; current sulphonylurea only users stratified by renal function and active versus inactive metabolites

NIAA useRisk of hypoglycaemia
No of eventsPerson yearsIncident rateAdjusted hazard ratio (95% CI)*Fully adjusted hazard ratio (95% CI)†
Current metformin only836205 3514.1ReferenceReference
Current sulphonylurea only45733 82913.53.30 (2.94 to 3.69)2.50 (2.23 to 2.82)
Renal function <30 mL/min/1.73 m2:56170232.97.98 (6.08 to 10.46)4.96 (3.76 to 6.55)
 Sulphonylureas with active metabolites< 61109.72.24 (0.32 to 15.94)1.48 (0.21 to 10.52)
 Sulphonylureas with inactive metabolites55151736.38.41 (6.40 to 11.05)5.20 (3.94 to 6.88)
Renal function 30-59 mL/min/1.73 m2:15610 14315.43.79 (3.19 to 4.49)2.69 (2.25 to 3.20)
 Sulphonylureas with active metabolites1790618.84.65 (2.88 to 7.52)3.48 (2.15 to 5.64)
 Sulphonylureas with inactive metabolites138883715.63.68 (3.08 to 4.41)2.60 (2.16 to 3.13)
Renal function ≥60 mL/min/1.73 m2:17416 71110.52.52 (2.14 to 2.97)2.04 (1.73 to 2.41)
 Sulphonylureas with active metabolites19156212.72.91 (1.85 to 4.59)2.46 (1.56 to 3.88)
 Sulphonylureas with inactive metabolites15514 46610.72.48 (2.09 to 2.95)2.01 (1.69 to 2.39)
Unknown71527413.53.32 (2.60 to 4.23)2.63 (2.06 to 3.36)

NIAA=non-insulin antidiabetic agent. Current use=in previous 90 days from start of a 90 day interval.

Results are corrected for all other possible combinations of NIAA use (see table 2).

*Adjusted for age and sex.

†Adjusted for age, sex, body mass index, alcohol use, smoking status, cardiovascular disease, chronic heart failure and use of loop diuretics.

Risk of hypoglycaemia in current users of sulphonylureas only compared with current users of metformin only; current sulphonylurea only users stratified by renal function and active versus inactive metabolites NIAA=non-insulin antidiabetic agent. Current use=in previous 90 days from start of a 90 day interval. Results are corrected for all other possible combinations of NIAA use (see table 2). *Adjusted for age and sex. †Adjusted for age, sex, body mass index, alcohol use, smoking status, cardiovascular disease, chronic heart failure and use of loop diuretics. No substantial differences in risk were observed between sulphonylureas with active metabolites and those with inactive metabolites, with hazard ratios estimating a similar twofold to threefold increase in risk (tables 3 and 4). It seems that the risk of hypoglycaemic events was highest among current users of sulphonylureas with active metabolites. As there were fewer outcomes, however, this analysis had limited power. Particularly, there were insufficient numbers of current users of sulphonylureas with active metabolites and an eGFR less than 30 mL/min/1.73 m2 to make a valid comparison in patients with chronic kidney disease stage 4 or 5. Risk of hypoglycaemia in current users of sulphonylureas only compared with current users of metformin only; current sulphonylurea only users stratified by type of sulphonylurea NIAA=non-insulin antidiabetic agent. Results are corrected for all other possible combinations of NIAA use (see table 2). Current use=in previous 90 days from start of a 90 day interval. *Adjusted for age and sex. †Adjusted for age, sex, body mass index, alcohol use, smoking status, cardiovascular disease, chronic heart failure, and use of loop diuretics. When we stratified further to individual sulphonylureas, our results showed that use of glibenclamide was associated with the highest risk of hypoglycaemic events (7.48, 4.89 to 11.44) compared with current use of metformin (table 4). Gliclazide use, often recommended as the first choice sulphonylurea, did not coincide with a significantly lower risk, as it appeared to be similar to the risk of glimepiride, glipizide, and tolbutamide.
Table 4

Risk of hypoglycaemia in current users of sulphonylureas only compared with current users of metformin only; current sulphonylurea only users stratified by type of sulphonylurea

NIAA useRisk of hypoglycaemia
No of eventsPerson yearsIncident rateAdjusted hazard ratio (95% CI)*Fully adjusted hazard ratio (95% CI)†
Current metformin only use836205 3514.1ReferenceReference
Current sulphonylurea only use45733 82913.53.30 (2.94 to 3.69)2.50 (2.23 to 2.82)
Sulphonylureas with active metabolites:50324115.43.60 (2.70 to 4.78)2.91 (2.18 to 3.87)
 Glimepiride28262910.72.46 (1.69 to 3.59)1.97 (1.35 to 2.87)
 Glibenclamide2261036.18.76 (5.73 to 13.39)7.48 (4.89 to 11.44)
Sulphonylurea with inactive metabolites:40629 14113.93.26 (2.90 to 3.67)2.46 (2.18 to 2.78)
 Glipizide14127311.02.61 (1.54 to 4.43)2.11 (1.24 to 3.58)
 Tolbutamide<64107.31.75 (0.56 to 5.42)1.24 (0.40 to 3.87)
 Gliclazide38927 43314.23.32 (2.94 to 3.74)2.50 (2.21 to 2.83)
Combination of metabolites<66415.73.75 (0.53 to 26.68)2.65 (0.37 to 18.86)

NIAA=non-insulin antidiabetic agent.

Results are corrected for all other possible combinations of NIAA use (see table 2). Current use=in previous 90 days from start of a 90 day interval.

*Adjusted for age and sex.

†Adjusted for age, sex, body mass index, alcohol use, smoking status, cardiovascular disease, chronic heart failure, and use of loop diuretics.

In a post hoc analysis we compared current users of metformin only with renal impairment to current users of sulphonylureas only with renal impairment (see supplementary appendix B). Compared with users of metformin only with low renal function, users of sulphonylureas only with low renal function had a fourfold increase in risk for a hypoglycaemic event (4.12, 2.72 to 6.25). When current use of sulphonylureas only was stratified by daily dose and high or low haemoglobin A1c values (see supplementary appendix C), we identified that patients with a high daily dose (>10 mg glibenclamide equivalents) and low haemoglobin A1c value (<7%) had an increased risk of hypoglycaemic events (4.88, 3.40 to 6.99).

Discussion

Compared with current use of metformin only, current use of sulphonylureas only was associated with an increased risk of hypoglycaemic events, and this risk was increased in patients with a high prescribed daily dose and stage 4 or 5 chronic kidney disease. We also identified a similar risk of hypoglycaemia between current users of sulphonylureas with active or inactive metabolites. Interestingly, gliclazide is the first choice sulphonylurea in many countries, as it is associated with lower rates of hypoglycaemia, yet in our study we did not observe a decreased risk compared with glimepiride, glipizide, and tolbutamide. This could greatly influence the treatment decision making process of doctors and should be investigated further. We found a 2.5-fold increased risk of hypoglycaemic events in current users of sulphonylureas only compared with current users of metformin only. This is consistent with the UK Prospective Diabetes Study and the studies by Ben Salem et al and Bodmer et al.24 25 26 Results also confirmed an increased risk when sulphonylureas were used in combination with metformin or with other non-insulin antidiabetic agents,26 and also among patients receiving a high sulphonylurea dose. Our study provides an important addition to the existing literature by providing new information about the role of renal function and different sulphonylureas on risk of hypoglycaemic events. When patients were stratified by renal function, an eGFR of less than 30 mL/min/1.73 m2 was associated with a significantly increased risk of a hypoglycaemic event in users of sulphonylureas only, suggesting that impaired renal function is a risk factor for hypoglycaemia. Schloot et al17 reported similar results for risk of severe hypoglycaemia (requiring third party assistance). However, results were not generalisable to general care, as the study population consisted of patients treated in specialised diabetes centres. Therefore, our study is the first with real life data on the rates of hypoglycaemic events in patients with renal impairment during routine sulphonylurea treatment in general clinical practice. Remarkably, the results showed no difference between current users of sulphonylureas with active metabolites and those with inactive metabolites. Because of the mechanism of action, we expected sulphonylureas with active metabolites to show an increased risk, yet found no conclusive evidence of this. However, it is noteworthy that among sulphonylurea users with renal impairment most hypoglycaemic events were among those receiving sulphonylureas with inactive metabolites, limiting comparisons with active metabolites. Moreover, among sulphonylureas with active metabolites, the risk of hypoglycaemic events was lower in current users of glimepiride compared with current users of glibenclamide (twofold v 7.5-fold increase); however, we were unable to stratify this by renal function. Several underlying mechanisms might explain the difference between glibenclamide and glimepiride. The active metabolite of glimepiride has less hypoglycaemic effect than the parent drug,7 and glimepiride is known to exhibit a higher exchange rate and lower binding affinity to the pancreatic β cells than glibenclamide.27 28 Thus, although not affecting treatment efficacy, smaller amounts of insulin are secreted in the fasting state or postprandially with use of glimepiride compared with glibenclamide.29 30 While unexpected, one of our most interesting findings is that gliclazide may not be accompanied by a lower risk of hypoglycaemia compared with other sulphonylureas. Gliclazide is a sulphonylurea of first choice in many countries, including the UK, the Netherlands, and Canada, as it is assumed to be associated with a lower risk of hypoglycaemia and lower mortality and morbidity compared with other sulphonylureas.8 9 A meta-analysis of 25 randomised controlled trials found a lower proportion of glicalazide users at risk of hypoglycaemia (0.1%) compared with users of other sulphonylureas (0.9-15.5%).9 However, as is often the case, participants in randomised controlled trials may not be representative of the general population with type 2 diabetes receiving sulphonylureas in clinical practice (eg, age, general state of health, and comorbidities, including renal impairment). Results from two observational studies suggest that severe hypoglycaemic events are uncommon among gliclazide users,31 32 although the number of patients in these studies was relatively low (800 and 1397, respectivly). Thus, although in contrast with the findings of previous studies,8 9 the results of this large real world cohort suggest that gliclazide may not be superior to other sulphonylureas. This result could greatly impact the current clinical decision making for diabetes care, and should therefore be further assessed, particularly in relation to renal function. In addition to those already mentioned, the study has some limitations. Firstly, we were unable to identify patients with mild hypoglycaemia that was corrected at home with glucose. Consequently, we expect our results may be an underestimation of the overall incidence of hypoglycaemia. We excluded patients with a history of a hypoglycaemic event before the index date, as this is risk factor for a second event and these patients may have experienced in home management. While this may have resulted in an underestimation of hypoglycaemia, we do not believe the misclassification of mild outcomes to be differential between metformin users and sulphonylurea users. Moreover, non-differential misclassification would result in masking the true effect (bias towards the null) leading to insignificant findings. As we found a significant association, we do not believe our main conclusions are influenced by the potential non-differential misclassification of outcome. A second, and similar, limitation was the inability to distinguish severe hypoglycaemia from mild hypoglycaemia. In light of this, we completed a post hoc analysis using CPRD Read codes for admission to hospital or visit to an emergency room as a proxy indicator of severity (data not shown). However, there were few cases where the hypoglycaemic event date and the date of hospital admission or emergency room visit were identical. As we cannot confirm the reason for hospital admission, it presumably led to misclassification, in particular for identifying severe cases. We therefore encourage future research to examine further the differences between severe and mild hypoglycaemic events in sulphonylurea users with renal impairment. A third limitation was that two prescriptions are required to estimate the prescribed daily dose. A patient had to have sufficient follow-up time in the database before an event (or censoring) to estimate the given daily dose (at least six months), otherwise the dose was reported as unknown. However, there was no indication that doses were selectively missing in one of the three groups (low, medium, or high dose). Similarly, there is the potential that missing data on lifestyle factors, such as body mass index and smoking, may have introduced bias. Missing data can be dealt with in many ways, including, as in our analysis, the use of an indicator variable for “missingness.” Another option is the so called complete case analysis, where only patients with complete information on all confounders are included. Both methods were examined, and results and interpretation were similar (data not shown). Fourthly, although there were many hypoglycaemic events in our database, we did not have adequate statistical power to stratify current sulphonylurea only users by type of sulphonylurea, renal function, and average prescribed daily dose. Similarly, the number of events (<6) in the sulphonylurea group with active metabolites and chronic kidney disease stage 4 or 5 was low. This may explain the absence of the expected higher risk of hypoglycaemic events in this group. Fifthly, there is the potential for off-label use of metformin in women of reproductive age with polycystic ovarian syndrome; however, in a sensitivity analysis excluding all affected women (n=82) at baseline (data not shown), results were unchanged. Finally, there is the potential for residual confounding. While participants of randomised controlled trials are highly selected and randomly allocated to one of the treatment options, this is not the case in general practice. Indeed, our data show that metformin users were characterised by higher body mass index and renal clearance compared with sulphonylurea users at baseline, although this is not unexpected. To tackle this, we adjusted or stratified our analysis by the most important clinical risk factors (body mass index, renal function, and age), yet we acknowledge that we were unable to correct for all potential confounders, such as autonomic neuropathy, exercise,33 and amount of alcohol consumption.34 A major strength of this study is the long follow-up period in a large database, representative of the total UK population. As information is present for a wide range of confounding factors, such as smoking status, body mass index, and comorbidities, we were able statistically to adjust our results for several potentially important confounders. We were also able to classify drug use and covariates in a time varying classification. Although we were unable to identify severity, the evaluation of hypoglycaemia using Read codes results in a lower chance of overestimating the risk of hypoglycaemic events compared with glucose levels. Additionally, we excluded patients with a history of hypoglycaemic events, as a previous episode of hypoglycaemia is known to increase the risk of a second event.35 Finally, we employed a new user design, which eliminates the influence of previous treatment.

Conclusions

The findings of this large observational study suggest that the risk of hypoglycaemia is significantly increased in current users of sulphonylureas only with severe renal impairment compared with users of metformin only. Moreover, the results of this study provide evidence that the use of high sulphonylurea doses should be considered with caution in patients with renal impairment. Interestingly, we did not find evidence of superiority of gliclazide to other sulphonylureas in reducing the risk of hypoglycaemia compared with metformin users. Since current guidelines suggest gliclazide as the first choice in many countries, the findings of this study provide grounds for further investigation as they may have a substantial impact on current clinical decision making in diabetes care. Hypoglycaemia is a well known side effect of treatment with sulphonylureas Gliclazide is the first choice sulphonylurea for type 2 diabetes in many countries as it is associated with a lower risk of hypoglycaemia Data on the incidence of hypoglycaemia in sulphonylurea treated patients with impaired renal function are sparse and conflicting The risk of a hypoglycaemic event is significantly increased in sulphonylurea only users with severe renal impairment receiving general care The risk of hypoglycaemia did not differ between users of sulphonylureas with active metabolites and users of sulphonylureas with inactive metabolites Our study does not confirm current guidelines that suggest the superiority of gliclazide to other sulphonylureas in reducing the risk of hypoglycaemia
  30 in total

1.  Rates of hypoglycemia in users of sulfonylureas.

Authors:  T van Staa; L Abenhaim; J Monette
Journal:  J Clin Epidemiol       Date:  1997-06       Impact factor: 6.437

2.  Lower incidence of severe hypoglycaemia in patients with type 2 diabetes treated with glimepiride versus glibenclamide.

Authors:  A Holstein; A Plaschke; E H Egberts
Journal:  Diabetes Metab Res Rev       Date:  2001 Nov-Dec       Impact factor: 4.876

3.  Comparative effects of glimepiride and glibenclamide on blood glucose, C-peptide and insulin concentrations in the fasting and postprandial state in normal man.

Authors:  S A Raptis; E Hatziagelaki; G Dimitriadis; K E Draeger; C Pfeiffer; A E Raptis
Journal:  Exp Clin Endocrinol Diabetes       Date:  1999       Impact factor: 2.949

4.  Incidence of and risk factors for severe hypoglycaemia in treated type 2 diabetes mellitus patients in the UK--a nested case-control analysis.

Authors:  S G Bruderer; M Bodmer; S S Jick; G Bader; R G Schlienger; C R Meier
Journal:  Diabetes Obes Metab       Date:  2014-03-19       Impact factor: 6.577

5.  Individual sulfonylureas and serious hypoglycemia in older people.

Authors:  R I Shorr; W A Ray; J R Daugherty; M R Griffin
Journal:  J Am Geriatr Soc       Date:  1996-07       Impact factor: 5.562

6.  Hypoglycaemia in sulphonylurea-treated subjects with type 2 diabetes undergoing Ramadan fasting: a five-country observational study.

Authors:  S R Aravind; Khaled Al Tayeb; Shaiful Bahari Ismail; Naim Shehadeh; Ghaida Kaddaha; Rose Liu; Robert Balshaw; Nadia Lesnikova; Olaf Heisel; Cynthia J Girman; Bret J Musser; Michael J Davies; Harvey L Katzeff; Samuel S Engel; Larry Radican
Journal:  Curr Med Res Opin       Date:  2011-04-20       Impact factor: 2.580

7.  Severe hypoglycaemia leading to hospital admission in type 2 diabetic patients aged 80 years or older.

Authors:  D Greco; M Pisciotta; F Gambina; F Maggio
Journal:  Exp Clin Endocrinol Diabetes       Date:  2010-01-12       Impact factor: 2.949

8.  Gliclazide modified release: results of a 2-year study in patients with type 2 diabetes.

Authors:  P Drouin; E Standl
Journal:  Diabetes Obes Metab       Date:  2004-11       Impact factor: 6.577

Review 9.  Avoiding hypoglycemia: a key to success for glucose-lowering therapy in type 2 diabetes.

Authors:  Bo Ahrén
Journal:  Vasc Health Risk Manag       Date:  2013-04-24

10.  Metformin, sulfonylureas, or other antidiabetes drugs and the risk of lactic acidosis or hypoglycemia: a nested case-control analysis.

Authors:  Michael Bodmer; Christian Meier; Stephan Krähenbühl; Susan S Jick; Christoph R Meier
Journal:  Diabetes Care       Date:  2008-09-09       Impact factor: 17.152

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  20 in total

1.  Type 2 diabetes treatment and progression of chronic kidney disease in Italian family practice.

Authors:  G Ermini; C Tosetti; D Zocchi; M Mandreoli; M T Caletti; G Marchesini
Journal:  J Endocrinol Invest       Date:  2018-11-21       Impact factor: 4.256

2.  A systematic quality appraisal of clinical practice guidelines for Ménière's disease using the AGREE II instrument.

Authors:  Louis-Xavier Barrette; Katherine Xu; Neeraj Suresh; Jacob Harris; Kevin T Chorath; Alvaro G Moreira; Karthik Rajasekaran
Journal:  Eur Arch Otorhinolaryngol       Date:  2021-10-18       Impact factor: 2.503

3.  Brain activities of streptozotocin-induced diabetic Wistar rats treated with gliclazide: Behavioural, biochemical and histomorphology studies.

Authors:  Moses B Ekong; Francis N Odinukaeze; Amaobi C Nwonu; Christopher C Mbadugha; Agnes A Nwakanma
Journal:  IBRO Neurosci Rep       Date:  2022-04-14

4.  The Real-Life Effectiveness and Care Patterns of Diabetes Management Study for Balkan Region (Slovenia, Croatia, Serbia, Bulgaria): A Multicenter, Observational, Cross-Sectional Study.

Authors:  Sanja Klobucar Majanovic; Andrej Janez; Ivaylo Lefterov; Sanja Tasic; Tatjana Cikac
Journal:  Diabetes Ther       Date:  2017-07-10       Impact factor: 2.945

Review 5.  Consensus Recommendations on Sulfonylurea and Sulfonylurea Combinations in the Management of Type 2 Diabetes Mellitus - International Task Force.

Authors:  Sanjay Kalra; Silver Bahendeka; Rakesh Sahay; Sujoy Ghosh; Fariduddin Md; Abbas Orabi; Kaushik Ramaiya; Sameer Al Shammari; Dina Shrestha; Khalid Shaikh; Sachitha Abhayaratna; Pradeep K Shrestha; Aravinthan Mahalingam; Mazen Askheta; Aly Ahmed A Rahim; Fatimah Eliana; Hari K Shrestha; Sandeep Chaudhary; Nancy Ngugi; Jean Claude Mbanya; Than Than Aye; Tint Swe Latt; Zhanay A Akanov; Abbas Raza Syed; Nikhil Tandon; A G Unnikrishnan; S V Madhu; Ali Jawa; Subhankar Chowdhury; Sarita Bajaj; Ashok Kumar Das
Journal:  Indian J Endocrinol Metab       Date:  2018 Jan-Feb

6.  Risk of a first-ever acute myocardial infarction and all-cause mortality with sulphonylurea treatment: A population-based cohort study.

Authors:  Judith van Dalem; Martijn C G J Brouwers; Coen D A Stehouwer; André Krings; Olaf H Klungel; Johanna H M Driessen; Frank de Vries; Andrea M Burden
Journal:  Diabetes Obes Metab       Date:  2017-12-27       Impact factor: 6.577

7.  The associations of sedentary time and breaks in sedentary time with 24-hour glycaemic control in type 2 diabetes.

Authors:  Aye C Paing; Kathryn A McMillan; Alison F Kirk; Andrew Collier; Allan Hewitt; Sebastien F M Chastin
Journal:  Prev Med Rep       Date:  2018-09-05

8.  Interaction between Omeprazole and Gliclazide in Relation to CYP2C19 Phenotype.

Authors:  Tanja Dujic; Sandra Cvijic; Amar Elezovic; Tamer Bego; Selma Imamovic Kadric; Maja Malenica; Alisa Elezovic; Ewan R Pearson; Aida Kulo
Journal:  J Pers Med       Date:  2021-05-03

9.  Comparative Evaluation of Safety and Efficacy of Glimepiride and Sitagliptin in Combination with Metformin in Patients with Type 2 Diabetes Mellitus: Indian Multicentric Randomized Trial - START Study.

Authors:  T V Devarajan; S Venkataraman; Narayanan Kandasamy; Abraham Oomman; Hari Kishan Boorugu; S K P Karuppiah; Dushyant Balat
Journal:  Indian J Endocrinol Metab       Date:  2017 Sep-Oct

Review 10.  Diabetes in the older patient: heterogeneity requires individualisation of therapeutic strategies.

Authors:  Guntram Schernthaner; Marie Helene Schernthaner-Reiter
Journal:  Diabetologia       Date:  2018-02-07       Impact factor: 10.122

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