Diabetes and Metabolism Journal
Transcript of Diabetes and Metabolism Journal
Title: Concurrent use of oral anticoagulants and sulfonylureas in individuals with type 2diabetes and risk of hypoglycaemia: A UK population-based cohort study.
Type of Manuscript: Original Article
Running Title: Oral anticoagulants and sulfonylureas and risk of
Abstract
OBJECTIVE: To investigate the association of concurrent use of oral anticoagulants (OACs) and sulfonylureas andthe risk of hypoglycaemia in individuals with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN ANDMETHODS: A retrospective cohort study was conducted between (2001-2017) using The Health ImprovementNetwork (THIN) database. Individuals with T2DM who received OAC prescription and sulfonylureas wereincluded. We compared the risk of hypoglycaemia with sulfonylureas and OACs using propensity score matchingand Cox regression. RESULTS: 109,040 individuals using warfarin and sulfonylureas and 77,296 using DOACs andsulfonylureas were identified and included. There were 285 hypoglycaemia events in the warfarin withsulfonylureas group (incidence rate = 17.8 per 1000 person-years), while in the sulfonylureas only, 304hypoglycaemia events were observed (incidence rate = 14.4 per 1000 person-years). There were 14hypoglycaemic events in the DOACs with sulfonylureas group (incidence rates = 14.8 per 1000 person-years),while in the sulfonylureas alone group, 60 hypoglycaemia events were observed (incidence rate =23.7 per 1000person-years). Concurrent use of warfarin and sulfonylureas was associated with increased risk of hypoglycaemiacompared with sulfonylureas alone, (HR 1.38; 95% CI 1.10–1.75). However, we found no evidence of anassociation between concurrent use of DOACs and sulfonylureas and risk of hypoglycaemia (HR 0.54; 95% CI,0.27–1.10) when compared with sulfonylureas only. CONCLUSIONS: We provide real-world evidence of possibledrug-drug interactions between warfarin and sulfonylureas. The decision to prescribe warfarin with coexistentsulfonylureas to individuals with T2DM should be carefully evaluated in the context of other risk factors ofhypoglycaemia,
Editorial membersDiabetes and Metabolism Journal Editorial Office101-2104, Lotte Castle President, 109 Mapo-daero, Mapo-gu, Seoul 04146, KoreaTEL: +82-2-714-9064FAX: +82-2-714-9084E-mail : [email protected]: http://submit.e-dmj.org/
101-2104, Lotte Castle President, 109 Mapo-daero, Mapo-gu, Seoul 04146, Korea
Copyright© Korean Diabetes Association.
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ABSTRACT (257 words) 1
OBJECTIVE: To investigate the association of concurrent use of oral anticoagulants (OACs) 2
and sulfonylureas and the risk of hypoglycaemia in individuals with type 2 diabetes mellitus 3
(T2DM). 4
RESEARCH DESIGN AND METHODS: A retrospective cohort study was conducted 5
between (2001-2017) using The Health Improvement Network (THIN) database. Individuals 6
with T2DM who received OAC prescription and sulfonylureas were included. We compared 7
the risk of hypoglycaemia with sulfonylureas and OACs using propensity score matching and 8
Cox regression. 9
RESULTS: 109,040 individuals using warfarin and sulfonylureas and 77,296 using DOACs 10
and sulfonylureas were identified and included. There were 285 hypoglycaemia events in the 11
warfarin with sulfonylureas group (incidence rate = 17.8 per 1000 person-years), while in the 12
sulfonylureas only, 304 hypoglycaemia events were observed (incidence rate = 14.4 per 1000 13
person-years). There were 14 hypoglycaemic events in the DOACs with sulfonylureas group 14
(incidence rates = 14.8 per 1000 person-years), while in the sulfonylureas alone group, 60 15
hypoglycaemia events were observed (incidence rate =23.7 per 1000 person-years). Concurrent 16
use of warfarin and sulfonylureas was associated with increased risk of hypoglycaemia 17
compared with sulfonylureas alone, (HR 1.38; 95% CI 1.10–1.75). However, we found no 18
evidence of an association between concurrent use of DOACs and sulfonylureas and risk of 19
hypoglycaemia (HR 0.54; 95% CI, 0.27–1.10) when compared with sulfonylureas only. 20
CONCLUSIONS: We provide real-world evidence of possible drug-drug interactions between 21
warfarin and sulfonylureas. The decision to prescribe warfarin with coexistent sulfonylureas to 22
individuals with T2DM should be carefully evaluated in the context of other risk factors of 23
hypoglycaemia, and availability of alternative medications. 24
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Keywords: Diabetes mellitus, Oral anticoagulants, Drug-drug interactions, Sulfonylureas 25
BACKGROUND 26
Individuals with type 2 diabetes mellitus (T2DM) are often suffering from cardiovascular 27
complications (1). Cardiovascular diseases (CVDs) such as atrial fibrillation (AF), venous 28
thromboembolism, and stroke are amongst the leading causes of mortality worldwide (2). 29
Individuals with T2DM are initially treated with metformin therapy to control the blood 30
glucose levels. However, for many individuals with T2DM, this type of treatment fails to 31
control blood glucose levels and they are often prescribed additional or alternative therapies 32
(3). The most common second-line therapy for T2DM is sulfonylureas (4). 33
T2DM individuals are at an increased risk of developing adverse drug reactions due to their 34
multiple comorbidities, renal impairment and multiple uses of drugs (5). In a systematic review, 35
reporting adverse drug reaction (ADR)s hospitalization worldwide, Hamid and colleagues 36
reported that 33.9% and 9% of all ADRs were due to cardiovascular and antidiabetic 37
medications (6). Similarly, the United States health and human service department reported 38
that “ Warfarin accounts for about 33% of all hospitalization due to adverse drug events (ADEs), 39
while it is 10.7% for oral hypoglycaemic agents” (7). 40
Oral anticoagulant medications (OACs) including warfarin and direct oral anticoagulants 41
(DOACs) are widely prescribed for the prevention and treatment of CVDs (8). However, their 42
use may be considered a public health concern, especially due to their high prescription 43
frequency, high probability of drug-drug interactions, and their association with serious 44
adverse events, such as bleeding and hypoglycaemia (9). In the last few years, DOACs have 45
been introduced for the treatment of different CVDs, and many guidelines recommend them as 46
a first-line therapy for the management of CVDs (8, 10). DOACs have several advantages 47
over warfarin including: less drug-drug interactions (due to their predominantly renal 48
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metabolism), and predictable pharmacokinetics and pharmacodynamics. However, they are 49
expensive and there is no standardised test to monitor blood levels (11). 50
Hypoglycaemia is an expected dose-related complication of sulfonylureas (12), which can be 51
potentiated by several risk factors including drug-drug interaction via inhibition of hepatic 52
cytochrome P450 (CYP) enzymes which are responsible for the metabolism of sulfonylureas 53
(13). Drug-drug interactions resulting in the risk of hypoglycaemia are widely documented in 54
the literature (14). 55
Previous pre-clinical studies have reported a possible drug-drug interaction between warfarin 56
and sulfonylureas through the displaced plasma protein binding and hepatic metabolism 57
CY450 (15). In addition, two case reports, showed a possible drug-drug interaction between 58
warfarin and glibenclamide (16, 17). Two previous studies reported a significant association 59
between warfarin and sulfonylurea (18, 19), however, both studies used data only from the 60
United States. 61
Previous studies have demonstrated that the prevalence of AF in individuals with T2DM 62
ranges from 8% to 14.9% and that individuals with T2DM have 40% higher risk of 63
developing AF compared with individuals without T2DM (20, 21). Given the fact that 64
diabetes and AF are highly prevalent, and that antidiabetic and anticoagulant medications are 65
largely prescribed concomitantly and the possibility of developing drug-drug interactions (9, 66
22, 23), and the lack of published evidence, we aimed to investigate the association between 67
concurrent OAC and sulfonylurea use and risk of hypoglycaemia. 68
RESEARCH DESIGN AND METHODS 69
Study design 70
This was a population-based cohort study in individuals with T2DM from 2001 to 2017. 71
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Data source 72
The Health Improvement Network (THIN) database, now known as IQVA Medical Research 73
Data (IMRD) UK Database was used for this study. THIN is a UK primary care database 74
containing anonymised administrative, clinical, and prescribing data from over 587 practices 75
with more than 13 million individuals (24, 25). THIN is one of the largest sources for primary 76
care data in the UK and has been validated for epidemiological research purposes (22, 23, 25). 77
It holds data on personal information, health related behaviours, and diagnoses information 78
which is recorded and identified using Read codes. THIN contains records of prescriptions 79
issued only by GPs and recorded in the individual’s records (24, 25). Data from practices that 80
met the acceptable mortality reporting (AMR) measures of quality assurance for THIN data 81
were used in this study (26). 82
This study was reviewed, and scientific approval was obtained by THIN SRC in 2018 83
(18THIN046). The research was reported in accordance with strengthening the reporting of 84
observational studies in epidemiology (STROBE) Statement. 85
Study cohort 86
The study population included people aged at least 18 years old, with a recorded diagnosis of 87
T2DM. To ensure accurate measurement of medical history, we included individuals only if 88
they had an observation period of at least 12 months before the first T2DM diagnosis and were 89
registered with the general practice during the study period. Individuals were followed up until 90
the end of September 2017 and were censored if they experienced the outcome of interest, died, 91
left their general practice during the study period, or stopped medications during the 92
overlapping period of both medications, whichever came first. 93
The study covered a period of 17 calendar years (2001-2017), and two separate but similar 94
analyses were carried out. The first and second analyses comprised individuals with T2DM 95
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who received at least one prescription for one of the OACs of interest (including warfarin 96
(Analysis 1) or DOACs (Analysis 2)) and sulfonylureas and were identified using drug codes 97
recorded in THIN. The index date (start date) was defined as the date on which users were first 98
co-exposed (concurrently) to both medications (OACs and sulfonylureas), regardless of which 99
medication was first. Individuals with records of prescriptions of both medications during the 100
follow up were included in the study. The index date was defined as: a) if sulfonylurea 101
prescription was between the first and last warfarin prescriptions then the date of sulfonylurea 102
was accounted as the index date) if warfarin prescription was between the first and last 103
sulfonylurea prescriptions then the date of warfarin was accounted as the index date. 104
Individuals who did not meet these criteria were categorised as ‘no overlap’ and excluded. We 105
also excluded individuals if they had less than 12 months observation period, were <18 years 106
old, were diagnosed with malignancy or metastatic tumours (as they are at higher risk of 107
glucose level fluctuations due to anticancer therapy) and individuals with incomplete data for 108
transfer out or death data. Details of the exclusion criteria are provided in figures 1-2. 109
Exposure definition 110
The exposure of interest was person-time concomitantly exposed to OACs and sulfonylureas 111
after the diagnosis of T2DM. OACs included warfarin and DOACs (dabigatran, apixaban, 112
rivaroxaban and edoxaban). Individuals with records of acenocoumarol or phenindione only 113
were not included, because of the very low number of individuals and because it is very 114
unlikely to be prescribed in the UK. Sulfonylureas were of a second generation and included: 115
gliclazide, glipizide, glyburide and glimepiride. For analysis 1, we compared individuals using 116
warfarin and sulfonylureas concurrently, versus individuals using sulfonylureas only, and the 117
index date for this group was the first prescription of sulfonylureas). For analysis 2, we 118
compared individuals using DOACs and sulfonylureas concurrently, versus individuals using 119
sulfonylureas only, and the index date for this group was the first prescription of sulfonylureas. 120
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only individuals who were new users from 2011 onwards were included in analysis 2, as 121
DOACs were first approved on the market from 2011. 122
Study outcomes 123
The study outcome was incident hypoglycaemia during the follow up time defined as the first 124
record of hypoglycaemia after the index date. 125
Study covariates 126
Demographics, comorbidities, and medications associated with developing hypoglycaemia 127
were included as covariates, based on previous studies (18, 19, 27) and clinician 128
recommendation. They included; age, gender, smoking status (never-smoked, ex-smoker and 129
current smoker), body mass index (BMI), alcohol consumption (never-drink, ex-drinker and 130
current drinker), Townsend deprivation score, CVDs disease, history of hyperglycaemia, 131
hyperlipidaemia, hypertension (HTN), AF, stroke/ transient ischaemic attack (TIA), deep vein 132
thrombosis (DVT), peripheral vascular disease (PVD), chronic kidney disease (CKD), liver 133
disease, anxiety, depression, chronic obstructive pulmonary disease (COPD), use of multiple 134
antidiabetics (intensification), beta-blockers (BBs), angiotensin converting enzyme inhibitor 135
(ACEIs), angiotensin II receptor blocker inhibitor (ARBs), calcium channels blockers (CCBs), 136
statins, corticosteroids, , antiplatelets. Information for comorbidities was evaluated at any time 137
on/or before the index date and was identified using the Read codes. Medications were 138
identified using the drug codes within 180-days on/or before the start date. We did not account 139
for international normalised ratio (INR) results because the data was not complete. Details of 140
the Read codes are provided in supplement. 141
Propensity score matching 142
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To minimise potential bias due to non-randomised, a propensity score matching cohort (within 143
±0.05, comprising 1:1 controls were created (28). To address confounding by indication, when 144
individuals with T2DM with more severe illness are likely to be treated with insulin, 145
sulfonylurea or multiple antidiabetic medications or individuals with T2DM using OACs might 146
be prescribed OACs for different indications, we included the following variables (AF, DVT 147
and stroke/TIA) in the PS model (29). We used a logistic regression model to estimate the 148
propensity score for each individual and variables listed in the previous section were included. 149
Absolute Standardised Differences (ASD) for all baseline variables were calculated to assess 150
the differences in individuals’ characteristics and covariates balance between treatment groups 151
before and after the propensity score matching. We used a cut-off point of 0.2 ASD (30-32). 152
Therefore, characteristics with an ASD greater than 0.2 after propensity score matching were 153
included as covariates in the subsequent regression model. 154
Statistical analysis 155
Individuals characteristics were presented as number (percentage) for categorical variables and 156
as mean (±SD) for continuous variables. Crude incidence rates were calculated by dividing 157
the number of hypoglycaemia events by person-time at risk and were expressed as rates per 158
1000 person-years. Person-year was calculated as the time from the index date until the end of 159
follow up. The Cox proportional hazard model before and after propensity score was used to 160
estimate the time to an event, and to investigate the association between the use of OACs with 161
co-existent sulfonylurea and the risk of hypoglycaemia; results were presented as HR with 95% 162
confidence interval (CI). We performed Kaplan-Meier survival curves plots on the matched 163
datasets to compare outcomes between the cohorts over time. The hazard assumption was 164
examined by both visual graphs and by applying tests using ph statement (proc PHREG) in 165
SAS statistical software. All analysis was performed using SAS version 9.4 (SAS Institute). 166
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Sensitivity analysis 167
To confirm the robustness of our results we conducted five sensitivity analyses. First, we re-168
analysed the data taking into account subsequent changes in the exposure status. Individuals 169
were censored if they stopped the treatment. The gap between expected prescription end date 170
and the start date of any subsequent prescription were no more than 90 days. 171
Second, we repeated the analysis using the IPTW method to address the risk difference between 172
groups at baseline (33). The stabilised IPTW was calculated by multiplying the IPTW by the 173
marginal probability of receiving the actual treatment (33). Stabilisation was used to reduce the 174
variability of the IPTW weights (34). The predictor variables inserted in the IPTW models 175
included the same covariates as in the PS matching. PS trimming for the IPTW was also 176
conducted. We re-analysed the IPTW based on (1st percentile of the PS distribution in exposure 177
and the 99th percentile of the PS in non-exposed treated) (35). Third, the missing data on 178
smoking status, BMI, alcohol consumption and Townsend scores were imputed by the multiple 179
imputation (MI) method (36, 37). All PS covariates, the outcome and survival time were 180
included in the MI model, and 25 imputed datasets were generated, analysed separately and 181
then combined using Rubin’s rule. 182
Patient and public involvement 183
It was not appropriate or possible to involve individuals or the public in the design, or conduct, 184
or reporting, or dissemination plans of this research. 185
Data and Resource Availability 186
Data access is through permission from THIN only. 187
RESULTS 188
Individuals characteristics 189
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A total of 418,613 individuals with T2DM were identified, of whom only 178,084 received a 190
prescription for sulfonylureas and OACs at some point during the study period between 2001 191
and 2017. We excluded 49,317 (22%) individuals in the warfarin group (Analysis 1) and 192
16,413 (17.5%) individuals in the DOACs group (Analysis 2) for missing data in the main 193
analysis. Finally, after we applied exclusion criteria, 109,040 using warfarin and sulfonylureas 194
(Analysis 1) and 77,296 using DOACs and sulfonylureas (Analysis 2) were included for the 195
analyses. Details of the identification of the study cohort, including the study cohort of 196
individuals included in Analyses 1 and 2 are presented in Figures 1-2. 197
At baseline, before propensity score matching, compared to individuals who received 198
sulfonylureas only, individuals who received warfarin with sulfonylureas were older (mean 199
age: 73.3 vs 61.0), had a higher cardiovascular profile: CVDs (14.7% vs 4.5%), HTN (68% vs 200
50%), stroke/TIA (19% vs 5.7%), AF (61% vs 1.8%), and DVT (21% vs 2%). At least 50% of 201
the study population had a BMI ≥30, with nearly similar BMI ratios in individuals who received 202
warfarin with sulfonylureas compared to individuals who received sulfonylureas only. 203
However, gender and the mental health profile including depression and anxiety showed little 204
difference between the two groups (61% females vs 57%females, 20% vs 23% and 13% vs 205
15%, respectively). After matching, all baseline individuals’ characteristics had standardised 206
differences less than 0.2 (Table 2). Details of the study characteristics, including individuals’ 207
characteristics of Analysis 2 (DOACs with sulfonylureas vs sulfonylureas), are presented in 208
Table S1. 209
Hypoglycaemia 210
Warfarin with sulfonylureas vs sulfonylureas 211
There were 578 hypoglycaemia events in the warfarin and sulfonylureas group (crude 212
incidence rates = 16.7 per 1000 person-years), while 7307 hypoglycaemia events were recorded 213
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in the sulfonylureas only group with a total follow up of 526,422.49 person-years, (crude 214
incidence rates = 13.8 per 1000 person-years). The risk of developing hypoglycaemia was 215
higher for individuals receiving warfarin with sulfonylureas compared to individuals receiving 216
sulfonylureas alone (HR 1.20; 95% CI, 1.10 – 1.30), p<0,0001), Table 3. 217
DOACs with sulfonylureas vs sulfonylureas 218
Individuals using DOACs with sulfonylureas concomitantly contributed to a total of 957 219
person-years, during which 14 hypoglycaemic events were recorded (crude incidence rates = 220
15.0 per 1000 person-years), while in the (sulfonylureas only group, a total of 246,345.65 221
person-years, with4,514 hypoglycaemia events were recorded (crude incidence rates = 18.0 per 222
1000 person-years). The risk of developing hypoglycaemia was lower for individuals receiving 223
DOACs with sulfonylureas compared to individuals receiving sulfonylureas alone. However, 224
this was not statistically significant (HR 0.66; 95% CI, 0.39 – 1.11, p=0.118), Table 3. 225
Propensity score matched analysis 226
Warfarin with sulfonylureas vs sulfonylureas 227
After matching, 5,379 individuals were included in each group. There were a total of 15,959.04 228
of concomitant exposure and, 285 hypoglycaemia events in the warfarin with sulfonylureas 229
group (incidence rates = 17.8 per 1000 person-years), while users of sulfonylureas only 230
contributed to 21,028.52 person-years, during which 304 hypoglycaemia events were observed 231
(incidence rates = 14.4 per 1000 person-years). The risk of hypoglycaemia was 38% higher in 232
individuals with concomitant use of warfarin with sulfonylureas, compared to sulfonylureas 233
alone users (HR 1.38; 95% CI, 1.10 – 1.76, P= 0.010), Table 4. Kaplan-Meier curves for the 234
incidence of hypoglycaemia of analysis 1 are shown in Figure 3. 235
DOACs with sulfonylureas vs sulfonylureas 236
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A total of 1,027 in each group were included in the analysis, with a total of 942, and 2,532 237
person-years were recorded, 14 and 60 hypoglycaemic events happened in the DOACs with 238
sulfonylureas and sulfonylureas alone groups, respectively (incidence rates =14.8 per 1000 239
person-years and 23.7 per 1000 person-years, respectively), Table 4. The risk of developing 240
hypoglycaemia was again lower for individuals receiving DOACs with sulfonylureas 241
compared to individuals receiving sulfonylureas alone (HR 0.54; 95% CI, 0.27 – 1.10, 242
P=0.091). However, this was not statistically significant (Table 4). Kaplan-Meier curves for 243
the incidence of hypoglycaemia of analysis 2 are shown in Figure 4. 244
Sensitivity analysis 245
The results of the sensitivity analyses are presented in Tables S2-4. When re-analysing the data 246
taking into account only individuals who received subsequent prescriptions within no more 247
than 90-days, the risk of hypoglycaemia was higher in individuals receiving warfarin with 248
sulfonylureas compared to individuals receiving sulfonylurea alone (HR 1.14; 95% CI, 1.01 – 249
1.30, P= 0.032), Table S2. However, the results of the matching analysis based on 90-days 250
grace period showed non-statistically significant results between both groups (HR 1.10; 95% 251
CI, 0.71 – 1.22, P= 0.634), Table S2. 252
Results from the inverse probability of treatment weighting (IPTW) were similar to main 253
analyses. Individuals had a higher risk of hypoglycaemia by 24% when receiving warfarin with 254
sulfonylureas compared to individuals receiving sulfonylureas alone (HR 1.24; 95% CI, 1.20- 255
1.25, P <0.0001) (Table S3). The results of IPTW were different from main analysis when 256
comparing individuals receiving DOACs and sulfonylureas concomitantly against individuals 257
receiving sulfonylureas alone. The risk of hypoglycaemia was again lower for individuals 258
receiving DOACs and sulfonylureas, but significant in the IPTW analysis (HR 0.56; 95% CI, 259
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0.36 – 0.90, P= 0.011). Results from the inverse probability of treatment weighting (IPTW), 260
including PS trimming, are presented in Table S3. 261
Results from multiple imputations were also similar to the main analyses, demonstrating 262
warfarin with sulfonylurea treatment was associated with a higher risk of hypoglycaemia 263
compared to sulfonylureas alone (HR=1.08; 95% CI, 1.03 – 1.13; p=<0.001), Table S4. 264
DISCUSSION 265
In this large population-based study in UK primary care, we investigated the association 266
between the concurrent use of OACs and sulfonylureas and the risk of hypoglycaemia in 267
individuals with T2DM. This study found that warfarin was associated with 38% increased risk 268
of hypoglycaemia when used with sulfonylureas concurrently in individuals with T2DM, (HR 269
1.38; 95% CI, 1.10 – 1.75). We found no evidence of an association between the use of DOACs 270
and sulfonylureas concurrently and the risk of hypoglycaemia (HR 0.54; 95% CI, 0.27 – 1.10). 271
The study results support the hypothesis that warfarin is associated with an increased risk of 272
hypoglycaemia when given concomitantly with sulfonylureas in individuals with T2DM. 273
Comparison with other studies 274
There are limited studies that explored the safety of the concurrent use of warfarin with 275
sulfonylureas. Previous RCTs focused on younger population with fewer number of 276
comorbidities. While the probability of adverse events was more common among elderly. This 277
could be related to the difference in excretion rates between different age groups which is vital 278
to maintain correct therapeutic levels (38). 279
The findings of increased risk of hypoglycaemia among the use of warfarin with sulfonylureas 280
are consistent with two previous large database studies using the Medicare claims and 281
Medicaid programmes in the United States (18, 19). Romley et al. reported that the concurrent 282
use of warfarin and sulfonylureas was associated with a 22% higher risk for hypoglycaemia 283
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(18) in a cohort study of 465,918 individuals. Similarly, in a self‐ controlled case series design, 284
Nam et al. reported an elevated rate of serious hypoglycaemia when warfarin was given 285
concomitantly with sulfonylureas (glipizide, glyburide, glyburide), (RR, 1.72; 95% CI, 1.29 – 286
2.29), (RR, 1.57; 95% CI, 1.15 – 2.15), and (RR, 1.56; 95% CI, 0.97 – 2.50), respectively (19). 287
However, in this study, we included DOAC use and had a longer follow-up than the other two 288
studies. 289
Our findings indicated that there is no evidence of an association found between the use of 290
DOACs and sulfonylureas concurrently and the risk of hypoglycaemia (HR 0.54; 95% CI, 0.27 291
– 1.10). We suggest that our estimate did not reach the significant level due to the small sample 292
size in the compared group and ultimately number if events. DOAC therapy has multiple 293
advantages over warfarin therapy, which include lack of the need for regular monitoring of the 294
degree of anticoagulation and wider therapeutic range (39, 40). 295
Potential mechanisms 296
The underlying mechanism of action for the concurrent use of warfarin with sulfonylureas and 297
increased risk of hypoglycaemia is unclear. Previous pre-clinical hypotheses suggest some 298
potential mechanisms for this association through a drug-drug interaction between the warfarin 299
and sulfonylureas. First, there may be a displaced protein binding mechanism, where 300
interaction between warfarin and sulfonylureas may occur on the site of the protein binding, 301
and thus warfarin may enhance the plasma concentration of sulfonylureas in the blood, and 302
hence increase its activity and risk of hypoglycaemia (15). However, previous studies and 303
reviews have described this mechanism of drug interaction to be overestimated and not to have 304
meaningful clinical effects, as it only applies to data from in vitro studies, or to drugs that are 305
given through loading intravenous doses (41, 42). Second, a drug-drug interaction through 306
inhibition of the cytochrome CYP2C9 hepatic metabolic pathway has also been suggested. 307
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Warfarin, glimepiride, and glipizide are all largely metabolised by hepatic cytochrome 308
CYP2C9 (15), and therefore, warfarin may limit the rate at which the sulfonylurea can be 309
metabolised in the liver (43). This mechanism may explain the findings of this study, especially 310
the fact that widely used drug references warn that the concurrent use of warfarin with 311
sulfonylureas may increase the risk of bleeding (44). However, no previous human studies exist 312
to validate this hypothesis, and future studies to investigate this association are needed. 313
Furthermore, pre-clinical studies have suggested that osteocalcin which is one of the important 314
bone proteins produced by the bone (45), is involved in the metabolism of glucose and insulin 315
sensitivity through the process of bone mineralisation and formation, which requires high 316
energy (46). It has been postulated that the uncarboxylated form of osteocalcin enhances the 317
glucose tolerance by the beta cells in the pancreatic islets and increases the insulin sensitivity 318
in peripheral tissues (46). However, this function is mainly dependent on Vitamin K, and 319
therefore, administration of warfarin may block the activation of the carboxylation forum of 320
osteocalcin and thus increase the uncarboxylated forum in the plasma (46). In vitro studies 321
have suggested stimulation in the production of undercarboxylated osteocalcin by insulin 322
through a positive feedback mechanism between the pancreas, adipose tissue and bone, which 323
in turn enhances insulin production and sensitivity (47). 324
Meaning of the study 325
Warfarin therapy is indicated as a prophylaxis and treatment for a wide range of life-threatening 326
health conditions including venous thrombosis, pulmonary embolism, and thromboembolic 327
complications associated with AF and cardiac valve replacement. Additionally, warfarin 328
therapy proven to reduce the risk of death, recurrent MI and thromboembolic events (48). 329
Nonetheless, warfarin therapy needs precise dosing regimen and follow-up by the patients and 330
their healthcare professionals due to its associated potential drug-drug interaction and 331
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contraindications. In specific clinical settings, warfarin therapy has higher risk of 332
complications and adverse events, these include hepatic impairment, moderate to severe 333
hypertension, and diabetes mellitus. Given the fact that diabetes and AF are highly prevalent, 334
and that antidiabetic and anticoagulant medications are largely prescribed concomitantly (22, 335
23), this urge us to weight the benefit-risk ratio in the case of the concurrent use of antidiabetic 336
and anticoagulant medications therapy. Several important drug references have warned that 337
warfarin may have some drug interactions when given with sulfonylureas. However, this 338
possible drug interaction has not been studied extensively or appreciated in the literature. This 339
study provides the first evidence for this drug interaction of two widely used medications in 340
the UK, and it is also consistent with the findings from the previous studies in the US. In 341
addition, this study found an insignificant reduced risk of hypoglycaemia when DOACs are 342
used concurrently with sulfonylureas. 343
Implication of the study 344
Individuals with T2DM receiving OACs are older and more susceptible to polypharmacy and 345
drug-drug interactions (Mallet et al., 2007)(22, 23). Doctors and clinical pharmacists must be 346
vigilant when prescribing warfarin with sulfonylureas and must be alert to both immediate and 347
delayed-onset hypoglycaemia when prescribing this drug combination. Clinical surveillance, 348
frequent blood glucose measurements, INR monitoring, diet changes and patient education 349
may be necessary to reduce the risk of hypoglycaemia if individuals are prescribed these 350
medications together (49, 50). 351
Additionally, given that DOACs are widely available nowadays, these medications may be an 352
alternative therapy when OACs and sulfonylureas are indicated in individuals with T2DM. 353
DOACs have a more predictable pharmacokinetic profile and have less drug-drug interactions. 354
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This research has also highlighted a possible protective effect of DOACs against 355
hypoglycaemia when prescribed with sulfonylureas; however, the sample size was small, and 356
we did not have a long follow-up time. Therefore, considering these results in the context of 357
the currently available literature, we underline the need for future research with a longer follow-358
up time, and large sample sizes to examine the association of DOACs and sulfonylureas and 359
the risk of hypoglycaemia or bleeding in individuals with T2DM. 360
Strengths and limitations of the study 361
Our study has several strengths. First; this study had a longer follow up period compared to the 362
previous studies (18, 19). Second, this study used the population representative data from the 363
UK primary care database – THIN. It is therefore, reasonable to assume that our findings are 364
generalised and may broadly reflects real world practice in the UK and the world. Third, we 365
used advanced statistical method (i.e. PS matching and IPTW) to address the measured 366
confounder issue at baseline. In addition, to confirm the robustness of our results, we conducted 367
several sensitivity analyses that suggest our results are robust, including multiple prescriptions 368
grace periods, IPWT and multiple imputations. 369
This study has some limitations. First, this study is an observational cohort study, and unlike 370
RCTs, the residual confounding cannot be excluded. Second, due to the emergency nature of 371
the outcomes of interest (hypoglycaemia), we did not have access to hospital data, also, mild 372
hypoglycaemia may not be reported to the doctors, and this could lead to underestimations of 373
the cases. Despite that wide range of confounders were adjusted for in our analyses, which is 374
potentially justified, this could increase the risk of the model fit being affected when there is a 375
small sample size or frequency of outcomes. THIN is an administrative database and therefore, 376
data on medication adherence, the actual ingestion of medications or diet is lacking. However, 377
we tackled this by conducting a sensitivity analysis to account only for prescription refills of 378
fewer than 90 days. 379
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CONCLUSION 380
In summary, the study found that warfarin was associated with an increased risk of 381
hypoglycaemia when given concomitantly with sulfonylureas in individuals with T2DM. 382
Concurrent use of DOACs with sulfonylureas however was associated with an insignificant 383
reduced risk of hypoglycaemia. The decision to prescribe warfarin with coexistent 384
sulfonylureas to individuals with T2DM should be carefully evaluated in the context of other 385
risk factors of hypoglycaemia, and the availability of alternative medications. Future studies 386
are needed to validate the finding of the protective effect of DOACs and sulfonylureas on 387
hypoglycaemia on larger sample size and longer follow-up periods. 388
Funding. 389
Alwafi’s PhD project was supported by a scholarship from the Saudi Arabian Ministry of 390
Higher Education. 391
Conflict of interest 392
The authors declare no conflict of interest. 393
Author Contributions. 394
HA, IW and LW had full access to all the data in the study and take responsibility for the 395
integrity of the data and the accuracy of the data analysis. Concept and design: HA, IW and 396
LW. Acquisition, analysis, or interpretation of data: HA, IW, AB, PM, CW and LW. Drafting 397
of the manuscript: HA, IW, AB, AYN, CW and LW. Critical revision of the manuscript for 398
important intellectual content: All authors. Statistical analysis: HA, PM and LW. 399
Administrative, technical, or material support: HA. Study supervision: IW, CW and LW. 400
Ethics approval. 401
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The present study is based on anonymised and unidentifiable THIN data; thus, the need for 402
informed consent was waived by the THIN scientific review committee (SRC). This study 403
was reviewed and scientific approval was obtained by THIN SRC in 2018 (18THIN046). 404
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545
546
TABLES LEGENDS 547
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550
551
Table 1. Individuals’ characteristics among the cohort of first analysis (sulfonylureas and warfarin versus sulfonylureas only) 552
Variable Before propensity score matching
No. (%) of participant
After propensity score matching
No. (%) of participant
Sulfonylurea
s + warfarin
(n= 10,076)
Sulfonylurea
s
(n= 98,964)
Crude ASD Sulfonylurea
s + warfarin
(n= 5,379)
Sulfonylurea
s
(n= 5,379)
Matched
ASD
Demographics
Age mean (SD) 73.3 (10.0) 61.0 (12.8) 0.918 69.9 (10.8) 70.0 (11.8) 0.054
Male, n (%) 6,918 (61.1) 63,965
(57.0)
0.083 3,114
(57.89)
3041 (56.53) -0.027
BMI 0.037 0.038 Diabetes
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BMI < 25 1,715 (15.5) 18,491
(16.5)
- 877 (16.3) 923 (17.1) -
BMI 25-30 3,942 (34.8) 38,351
(34.2)
- 1837 (34.1) 1894 (35.2) -
BMI 30 5,665 (50.0) 55,341
(49.3)
- 2665 (49.5) 2562 (47.6) -
Smoking 0.228 -0.011
Non-smokers 10,068
(88.9)
90,649
(80.8)
- 4673 (86.8) 4652 (86.4) -
Smokers 1,254 (11.0) 21,534
(19.2)
- 706 (13.3) 727 (13.5) -
Alcohol 0.035 0.006
Non-drinker 3,604 (31.8) 33,899
(30.2)
- 1740 (32.3) 1757 (32.6) -
Drinker 7,718 (68.2) 78,284
(69.8)
- 3639 (67.7) 3622 (67.3) - Diabetes
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Townsend 0.053 0.036
1 (Least deprived) 2026 (20.1) 19174 (19.4) - 1075 (19.9) 1021 (19.0) -
2 2140 (21.2) 19555 (19.7) - 1091 (20.3) 1057 (19.6) -
3 2168 (21.6) 21773 (22.0) - 1149 (21.4) 1203 (22.4) -
4 2167 (21.5) 21523 (21.7) - 1199 (22.3) 1222 (22.7) -
5 (Most deprived) 1575 (15.6) 16939 (17.2) - 865 (16.0) 876 (16.3) -
Comorbid conditions, n (%)
CVDs 1670 (14.7) 5039 (4.5) 0.353 684 (12.7) 656 (12.2) -0.016
Hypertension 7693 (68.0) 56550 (50.4) 0.363 3399 (63.2) 3370 (62.6) 0.011
Stroke/TIA 2154 (19.0) 6429 (5.7) 0.412 838 (15.6) 866 (16.1) -0.014
Bleeding 2112 (18.6) 15302 (13.6) 0.137 1009 (18.7) 970 (18.0) -0.019
Hyperlipidaemia 2652 (23.4) 19747 (17.6) 0.144 1187 (22.0) 1194 (22.2) -0.003
AF 6952 (61.4) 1973 (1.8) 1.673 1862 (34.6) 1750 (32.5) 0.044
DVT 2403 (21.2) 2300 (2.0) 0.627 1453 (27.0) 1571 (29.2) -0.049
Chronic kidney disease 3016 (26.6) 10991 (9.8) 0.447 1099 (20.4) 1105 (20.5) -0.003
COPD 1208 (10.7) 5081 (4.5) 0.233 481 (9.0) 518 (9.6) -0.024
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Hyperglycaemia 422 (3.7) 3451 (3.0) 0.036 212 (3.9) 216 (4.0) -0.004
Liver diseases 59 (0.5) 678 (0.6) 0.011 36 (0.7) 49 (0.9) -0.027
Depression 2323 (20.5) 25934 (23.1) 0.063 1202 (22.3) 1254 (23.3) -0.023
Anxiety 1542 (13.6) 17554 (15.6) 0.057 811 (15.0) 843 (15.7) -0.017
Baseline medication use, n (%)
Aspirin use 4264 (37.6) 34978 (31.8) 0.137 2223 (41.3) 2480 (46.1) -0.096
Antiplatelet drugs use 716 (6.3) 3636 (3.2) 0.145 368 (6.8) 394 (7.3) -0.019
Beta blockers use 5264 (46.5) 23663 (21.0) 0.558 1943 (36.1) 36.12 (38.8) -0.055
ACEs /ARBs use 8061 (71.2) 50245 (44.8) 0.555 3337 (62.0) 3328 (61.9) 0.003
Corticosteroids use 1276 (11.2) 6854 (6.1) 0.184 578 (10.7) 616 (11.4) -0.022
Multiple antidiabetic
medications use
(intensification)
7705 (68.0) 76835 (68.5) 0.009 3559 (66.1) 3425 (63.7) 0.052
553
554
555
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Table 2. Number of events, incidence rates and crude HR, for risk of hypoglycaemia 556
Exposure group No. of event Person-years
at risk, year
IR, per 1000
person-years
(95% CI)
Crude HR
(95% CI)
Sulfonylurea+warfarin
(n=10,076)
578 34422.40 16.7 1.20
(1.10 – 1.30)
Sulfonylurea only
(n=98,964)
7307 526422.49 13.8
Sulfonylurea+DOAC
*(n=1,045)
14 956.9 15.0 0.66
(0.39- 1.11)
Sulfonylurea only *
(n=76251)
4514 246345.6 18.0
* This analysis included individuals only from 2011 onward. 557
558
559
560
561
562
563
564
565
566
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567
568
Table 3. Number of events, incidence rates and HR, for risk of hypoglycaemia for the 569
matched cohort 570
Exposure group No. of event Person-years
at risk, year
IR, per 1000
person-years
(95% CI)
Matched HR
(95% CI), p-
value
Sulfonylurea+warfarin
(n=5379)
285 15959.04 17.8
1.38
( 1.10-1.75)
Sulfonylurea only
(n=5379)
304 21028.52 14.4 1.00
Sulfonylurea+DOAC
*(n=1027)
14 942.2 14.8
0.54
(0.27- 1.10)
Sulfonylurea only *
(n=1027)
60 2532.0 23.7 1.00
* This analysis included individuals only from 2011 onward. 571
572
573
574
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581
Figure 1. Flow chart of the study cohort (analysis 1) 582
583
584
585
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586
587
588
589
Figure 2. Flow chart of the study cohort (analysis 2) 590
591
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592
Figure 3. Kaplan-Meier curves for the incidence of hypoglycaemia during the follow-up 593
period (sulfonylureas and warfarin versus sulfonylureas only). 594
595
596
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