orig

inal

artic

le

Diabetes, Obesity and Metabolism 2014. 2014 John Wiley & Sons Ltdoriginal article

Association between rst-line monotherapy withsulphonylurea versus metformin and risk of all-causemortality and cardiovascular events: a retrospective,observational study

C. Ll. Morgan1, J. Mukherjee2, S. Jenkins-Jones1, S. E. Holden1,3 & C. J. Currie1,31Global Epidemiology, Pharmatelligence, Cardiff, UK2Global Health Economics and Outcomes Research, Bristol-Myers Squibb, Wallingford, CT, USA3Cochrane Institute of Primary Care and Public Health, Cardiff University, Cardiff, UK

Aims: To evaluate the risk of all-cause mortality and major adverse cardiovascular events (MACE) for patients exposed to rst-line monotherapywith sulphonylurea or metformin.Methods: Data were from the Clinical Practice Research Datalink (CPRD). Patients with type 2 diabetes were selected if initiated withmetformin or sulphonylurea monotherapy as their rst-line glucose-lowering regimen 20002012. The primary endpoint was all-causemortality; the secondary endpoint was MACE (myocardial infarction or stroke). Times to endpoints were compared using Cox proportionalhazards models. Additional analyses were performed on subsets matched directly on key characteristics and by propensity score.Results: In the main analysis, 76 811 patients were prescribed metformin monotherapy (mean follow-up 2.9 years) and 15 687 sulphonylureamonotherapy (mean follow-up 3.1 years). A total of 2604 patients were included in each arm of the directly matched cohorts and 8836 in thepropensity-matched. With respect to all-cause mortality, using all three analytical approaches the hazard ratio (HR) was signicantly increasedfor sulphonylurea compared with metformin: adjusted HR= 1.580 (95% CI 1.4831.684) for the main analysis, 1.902 (1.7332.088) for thosematched on propensity score, and 1.272 (1.0211.584) for the directly matched cohort analysis. For MACE, the respective HRs were 1.196(1.0901.313), 1.202 (1.0011.442) and 0.814 (0.5781.148), respectively.Conclusions: All-cause mortality was signicantly increased in patients prescribed sulphonylurea compared with metformin monotherapy.Whilst residual confounding and confounding by indication may remain, this study indicates that rst-line treatment with sulphonylureamonotherapy should be reconsidered.Keywords: rst-line therapy, MACE, metformin, mortality, myocardial infarction, stroke, sulphonylurea

Date submitted 10 February 2014; date of first decision 3 March 2014; date of final acceptance 4 April 2014

IntroductionType 2 diabetes has an estimated prevalence of around 5%in the UK [1]. The general focus of diabetes treatment is themaintenance of normoglycaemia to reduce progression to long-term microvascular and macrovascular complications. Initialmanagement may consist of diet and lifestyle interventionsprior to the introduction of oral hypoglycaemic agents(OHAs). Current guidelines in the UK [2] recommend that,in the absence of contraindications, metformin should be thefirst-line choice of OHA. As an alternative, treatment withsulphonylureas is recommended. In the USA, the proportionof patients initially treated with sulphonylurea monotherapywas 18% in 2008 [3]. However, recent findings from both

Correspondence to: Prof. Craig J. Currie, Cochrane Institute of Primary Care and PublicHealth, Cardiff University, The Pharma Research Centre, Cardiff Medicentre, Cardiff CF144UJ, UK.E-mail: currie@cardiff.ac.uk

Parts of this study were presented in abstract form at the 49th Annual Meeting of theEuropean Association for the Study of Diabetes, Barcelona, Spain, 2327 September 2013.

clinical and observational studies have raised concerns aboutthe safety of intensive blood glucose management in type2 diabetes, especially treatment with either sulphonylureaor insulin [46]. The principal purpose of this study wasto characterize all-cause mortality and progression to majoradverse cardiovascular events (MACE) in patients with type2 diabetes treated with either metformin or sulphonylurea asfirst-line monotherapy.

MethodsData Source

The study was conducted using data from the Clinical PracticeResearch Datalink (CPRD), a longitudinal, anonymizedresearch database derived from more than 600 primarycare practices in the UK. CPRD contains clinical recordsfrom over 13 million people (based on the July 2012release), of whom approximately seven million are activelyregistered and can be followed prospectively. Available data

original article DIABETES, OBESITY AND METABOLISMincluded demographics, medical history (including diagnosesand health contacts), clinical investigation results and drugprescriptions. Diagnostic information in CPRD is recordedusing the Read code classification, a UK general practicestandard. A subset of CPRD practices based in Englandis also linked to additional health-based datasets includingthe Health Episode Statistics (HES) inpatient data and theOffice for National Statistics (ONS) mortality data. HESprovides details of all National Health Service (NHS) inpatientadmissions in England since 1997, including primary andcontributory causes coded using the ICD-10 classification.ONS provides details of all deaths in England, with immediateand antecedent causes coded using the ICD-9 and ICD-10classifications.

Cohort Selection

Patients were extracted with a Read code indicative of diabetes.As not all Read codes for diabetes differentiate between type1 and type 2 diabetes, and some patient histories erroneouslycontain codes for both types, patients with type 2 diabetes weredefined by one or more of the following:

1 Read codes exclusively indicative of type 2 diabetes2 ARead code indicative of type 2 diabetes (regardless of others

indicative of type 1 or non-specific diabetes) and at least oneprescription for an OHA

3 Prescription of two or more classes of OHA4 Read codes indicative of both type 1 and type 2 diabetes but

an age of diagnosis older than 35 years.

Patients defined as incident diabetes cases based on a wash-in period of at least 180 days from practice registration todiabetes diagnosis were selected; of these, patients subsequentlyinitiating on a sulphonylurea or metformin were extracted.Index date was defined as the first prescription date andpatients were followed to each endpoint or censorship.

Study Endpoints

The two endpoints were all-cause mortality (deduced fromdeath date appearing in the patient record) and progressionto MACE. MACE, defined here as either acute myocardialinfarction (MI) or stroke, was ascertained from Read codes.

Statistical Methods

Comparison of baseline characteristics associated with eachtherapy regimen was presented using appropriate univariatestatistics (t-test or nonparametric equivalent for continuousdata; chi-squared test for categorical data). The followinga priori defined variables were included in the analyses:age at the index date (limited to accuracy of one wholeyear), gender, diabetes duration (time from incidence dateto index date), haemoglobin A1c (HbA1c), systolic bloodpressure (SBP), total cholesterol, body mass index (BMI) andsmoking status. Baseline HbA1c, SBP, cholesterol and BMIwere defined as the nearest value to index date, searchingin the following order (i) 30 days prior to baseline, (ii) 30days following baseline and (iii) 1 year prior to baseline.

Therapy history at baseline was modelled as binary variablesfor each of: antiplatelet agents, anti-hypertensives and lipid-lowering drugs. Baseline morbidity was modelled as thetotal number of contacts with the general practitioner inthe year prior to the index date and as the Charlson co-morbidity index [7]. Prior renal disease was indicated byclinical diagnosis or by baseline serum creatinine levelsabove 132mol/l for males or 123mol/l for females.Where appropriate, missing data were handled using multipleimputation.

Patient follow-up time was defined as the period fromindex date to the earliest of (i) the date of the target event,(ii) censoring by the cases transition to a different treatmentcohort plus 90 days, (iii) the date of the patients leavingthe participating primary-care practice or (iv) the last data-collection date for that particular practice.

In addition to an analysis of all patients adjusting for baselinevariables, two additional analyses were conducted to addressissues of confounding by indication:

1 Sulphonylurea patients matched to metformin patients.Matched variables were age (2 years), gender, year of index,diabetes duration (1 year), BMI (3 kg/m2), serum creati-nine (10mol/l), and HbA1c (1% [11mmol/mol]).

2 Sulphonylurea patients matched to metformin patients bypropensity score. This method matches exposed subjects(in this instance, those exposed to sulphonylurea) withnon-exposed subjects (those exposed to metformin) on theprobability of their being initiated on sulphonylurea basedupon their baseline covariates. Covariates included in thepropensity matching were age, gender, serum creatinine,HbA1c, BMI, smoking status, systolic blood pressure, totalcholesterol, primary-care contacts in the preceding year,prior antihypertensive scripts, prior lipid-lowering scripts,prior antiplatelet scripts, Charlson index, prior cancer andMACE status.

In both sensitivity analyses only patients with complete (i.e.non-imputed) data for the matching criteria were consideredfor matching.

Analysis

Crude rates for all-cause mortality and MACE by person-time for metformin versus sulphonylurea monotherapies werecompared using the mid-P exact test. For all three analysisgroups, progression to each outcome was tested by Coxproportional hazards modelling (CPHM). Adjusted hazardratios (aHRs) for each endpoint were calculated. Thresholdstatistical significance in all tests was p= 0.05 and 95%confidence intervals were presented for aHRs. All candidatecovariates with p< 0.20 were included in the final model.

In addition, to explore issues of residual confounding, asubset of patients who failed on monotherapy and switched todual therapy with metformin and sulphonylurea were followedfrom date of dual therapy initiation until last date in thedataset. Baseline characteristics were re-calculated for date ofdual therapy initiation.

Initial data processing was undertaken using Microsoft SQLServer 2008. Statistical analysis was conducted using IBM SPSS

2 Morgan et al. 2014

DIABETES, OBESITY AND METABOLISM original articleTable 1. Baseline characteristics of patients initiating either metformin or sulphonylurea by study design: main analysis, propensity matched and directlymatched.

Main analysis Propensity-matched Directly matched

Metformin Sulphonylurea Metformin Sulphonylurea Metformin Sulphonylurea

Patients, n 76811 15687 8836 8836 2604 2604Gender, n (%)

Male 43282 (56.3) 9121 (58.1) 3736 (60.5) 3747 (60.7) 931 (35.8) 931 (35.8)Female 33529 (43.7) 6566 (41.9) 2435 (39.5) 2424 (39.3) 1673 (64.2) 1673 (64.2)

Age, years, mean (s.d.) 61.4 (12.8) 68.1 (12.9) 68.2 (11.4) 68.5 (12.7) 66.6 (10.4) 66.6 (10.4)Diabetes duration, years, mean (s.d.) 1.5 (2.4) 1.8 (3.0) 2.0 (2.8) 2.3 (3.1) 1.4 (1.8) 1.5 (1.8)Serum creatinine, mol/l, mean (s.d.) 85.4 (19.1) 98.1 (33.7) 95.0 (22.5) 95.1 (27.9) 89.6 (16.5) 89.8 (16.7)HbA1c, %, mean (s.d.) 8.6 (1.8) 9.1 (2.1) 8.9 (2.0) 8.9 (1.9) 8.6 (1.5) 8.6 (1.6)HbA1c, mmol/mol, mean (s.d.) 70.5 (19.7) 76.0 (23.0) 73.8 (21.9) 73.8 (20.8) 70.5 (16.4) 70.5 (17.5)BMI, kg/m2, mean (s.d.) 32.3 (5.8) 27.1 (4.8) 27.8 (4.3) 27.4 (4.8) 28.4 (3.7) 27.9 (3.9)Systolic BP, mmHg, mean (s.d.) 139.0 (17.0) 140.3 (19.4) 138.9 (17.5) 138.8 (18.8) 139.7 (17.4) 139.2 (18.0)Total cholesterol, mmol/l, mean (s.d.) 5.0 (1.2) 5.1 (1.2) 5.0 (1.2) 5.0 (1.2) 5.1 (1.2) 5.0 (1.2)HDL, mmol/l, mean (s.d.) 1.2 (0.3) 1.2 (0.4) 1.2 (0.3) 1.2 (0.4) 1.2 (0.3) 1.2 (0.3)LDL, mmol/l, mean (s.d.) 2.9 (1.0) 2.9 (1.1) 2.8 (1.0) 2.9 (1.0) 2.9 (1.0) 2.9 (1.0)Triglycerides, mmol/l, mean (s.d.) 2.3 (1.5) 2.3 (1.5) 2.2 (1.4) 2.2 (1.4) 2.3 (1.5) 2.1 (1.3)GP contacts preceding year, mean (s.d.) 11.1 (9.7) 11.7 (10.5) 12.2 (10.8) 11.9 (10.1) 10.4 (8.2) 12.0 (9.8)Charlson index, mean (s.d.) 1.9 (1.3) 2.2 (1.6) 2.4 (1.7) 2.3 (1.7) 2.0 (1.3) 2.1 (1.5)Prior anti-hypertensive scripts, n (%) 51188 (66.6) 9773 (62.3) 4272 (69.2) 4195 (68.0) 1784 (68.5) 1726 (66.3)Prior lipid-lowering scripts, n (%) 37834 (49.3) 5117 (32.6) 2940 (47.6) 2937 (47.6) 1266 (48.6) 1272 (48.8)Prior antiplatelet scripts, n (%) 28327 (36.9) 5904 (37.6) 2721 (44.1) 2682 (43.5) 1066 (40.9) 1100 (42.2)Smoking history, n (%)

Non-smoker 31199 (40.6) 7079 (45.1) 2435 (39.5) 2516 (40.8) 1047 (68.5) 1047 (68.5)Ex-smoker 31902 (41.5) 5432 (34.6) 2687 (43.5) 2571 (41.7) 1215 (48.6) 1215 (48.6)Current smoker 13614 (17.7) 2995 (19.1) 1049 (17.0) 1084 (17.6) 342 (40.9) 342 (40.9)

Missing data for metformin, sulphonylurea, respectively: serum creatinine 8653 (11.3%), 4715 (30.1%); HbA1c 14 558 (19%), 5229 (33.3%); BMI 10 886(14.2%), 4717 (30.1%); systolic BP 3839 (5%), 2144 (13.7%); total cholesterol 8813 (11.5%), 5078 (32.4%); HDL 21 531 (28%), 8722 (55.6%); LDL 32 915(42.9%), 10 576 (67.4%); triglycerides 20 269 (26.4%), 8126 (51.8%); smoking history 181 (0.2%), 96 (0.6%). HbA1c, haemoglobin A1c; BMI, body massindex; BP, blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein.

Statistics 20. Studies using the CPRD are covered by ethicsapproval granted by the Trent Multicentre Research EthicsCommittee (reference 05/MRE04/87). This study was grantedCPRD Independent Scientific Advisory Committee approval(ISAC 12155).

ResultsIn the main analysis, 76 811 patients were prescribedmetformin monotherapy (mean follow-up 2.9 years) and15 687 sulphonylureas (3.1 years). Of the patients prescribedsulphonylurea the majority were initiated with gliclazide(12 948; 82.5%). Other agents were glimepiride (1092; 7.0%),glipizide (713; 4.5%), glibenclamide (629; 4.0%) and tolbu-tamide (305; 1.9%). A total of 2604 patients were includedin each arm of the directly matched cohorts and 8836 in thepropensity-matched. Baseline characteristics for these groupsare shown in Table 1. For the overall cohort, there were sig-nificant differences between those treated with metformin andsulphonylurea, including age (61.4 vs. 68.1 years), creatinine(85.4 vs. 98.1mol/l), Charlson index (1.9 vs. 2.2), and HbA1c[8.6% (70.5mmol/mol) vs. 9.1% (76.0mmol/mol)]. Duringfollow-up, 357 (2.3%) patients treated with sulphonylurea hadat least one recording of a hypoglycaemic event compared with546 (0.7%) patients treated with metformin.

Main Analysis

There were with 2172 deaths in the sulphonylurea cohortcompared with 3209 in the metformin cohort, representingcrude rates of 44.6 and 13.6 events per 1000 person-years,respectively, and a crude relative risk of 3.270 (95% CI3.0963.453) (Table 2). After adjustment in theCPHM, theHRwas 1.580 (1.4831.684), p< 0.001. In sub-group analyses byage, gender, glucose control, prior renal disease and morbiditystatus, all HRs were significantly greater for sulphonylureacompared with metformin, ranging from 1.476 (1.3031.671)for patients with a Charlson index of 1 to 2.280 (1.8572.799)for those aged under 63 years (Figure 1). Notably, aHRs weresimilar for patients with or without prior renal disease: 1.654(1.4271.916) and 1.577 (1.4661.695), respectively.

There were 787 first MACE events in the sulphonylureacohort compared with 2035 in the metformin cohort,representing crude rates of 20.1 and 9.7 events per 1000patient-years, respectively, and a crude relative risk of 2.079(1.9142.257) (Table 3). After adjustment in the CHPM, therewas a significantly increased HR for sulphonylurea relative tometformin of 1.196 (1.0901.313), p< 0.001.

Directly Matched Analysis

In the directly matched analysis, there were 174 and 154 deathsin the sulphonylurea and metformin cohorts, representing

2014 doi:10.1111/dom.12302 3

original article DIABETES, OBESITY AND METABOLISMTable 2. Events, crude rates, risk ratios and adjusted HRs for all-cause mortality for patients treated with sulphonylurea and metformin monotherapy.

Cohort n EventsCruderates (pkpy) Risk ratio (95% CI) HR (95% CI) p-Value

All subjects Sulphonylurea 15687 2172 44.6 3.270 (3.0963.453) 1.580 (1.4831.684)* 7.3 1.64 (1.48-1.64) (2835/55,081)Prior renal impairmentAbsent 1.58 (1.47-1.58) (4,290/81,017)Present 1.65 (1.43-1.65) (1,091/11,481)

5

0.5 1.0 2.0aHR

Figure 1. Adjusted hazard ratios for all-cause mortality by sub-groups for sulphonylurea versus metformin.

crude rates of 21.7 and 15.6 events per 1000 person years,respectively, and a crude relative risk of 1.390 (1.1191.727)(Table 2). After adjustment, the HR was 1.272 (1.0211.584).There were 62 first MACE events for patients treated withsulphonylurea and 85 for those treated with metformin;respective rates of 10.7 and11.7 per 1000patient years (Table 3).The crude relative risk was 0.913 (0.6591.265).

Propensity-matched Analysis

In the propensity-matched cohorts, there were 1121 deathsin those treated with sulphonylurea and 739 deaths in those

treated with metformin; respective rates of 41.3 and 22.9events per 1000 person-years and a crude relative risk of 1.806(1.6461.982) (Table 2). In the CPHM, the HR was 1.902(1.7332.088) prior to adjustment and 1.504 (1.3671.654)following adjustment. For MACE, there were 249 events inthe sulphonylurea cohort and 216 in the metformin cohort;respective ratesof 15.3 and12.7per1000person-years (Table 3).

Survival Following Discontinuation

Following failure of first-line monotherapy, 20 341 patientsswitched to a dual therapy of metformin and sulphonylurea;

Table 3. Events, crude rates, risk ratios and adjusted HRs for major adverse cardiovascular events (MACE) for patients treated with sulphonylurea andmetformin monotherapy.

Cohort n EventsCruderates (pkpy) Crude risk ratio (95% CI) HR (95% CI) p-Value

All subjects Sulphonylurea 12860 787 20.1 2.079 (1.9142.257) 1.196 (1.0901.313)*

DIABETES, OBESITY AND METABOLISM original article14 621 (71.9%) were previously treated with metformin and5720 (28.1%) with sulphonylurea. There were 987 deaths(29.6 per 1000 person-years) in those initially treated withsulphonylurea and1102 (17.5) in those treatedwithmetformin.The aHR for sulphonylurea versus metformin was 1.026 (95%CI 0.9311.131).

DiscussionThis study reports an increased risk ofmortality associatedwithsulphonylurea monotherapy when compared with patientstreatedwithmetformin; a finding observedusing three differinganalytical approaches. Comparable findings from similar retro-spective cohort designs have been published previously [810].

For the secondary endpoint of MACE the results wereless clear, with significantly increased HRs for sulphonylurearelative to metformin observed in the main and unadjustedpropensity-matched analyses, but no significant differencefound in the adjustedpropensity-matchedanddirectlymatchedapproaches. The latter may have been underpowered forthe MACE endpoint. In the USA, a recent cohort studyreported significantly increasedHRsofnon-fatal cardiovascularendpoints for sulphonylurea relative to metformin, whichwere similar regardless of the type of sulphonylurea used[9]. A meta-analysis of randomized controlled trials (RCTs)and cohort studies [11] reported similar findings, althougha significant difference was not observed when the meta-analysis was restricted to RCTs. However, comparative trialsof sulphonylurea and metformin have tended to have beenpowered for efficacy rather than for longer-term safetyoutcomes such as either mortality or cardiovascular events[1214]. The United Kingdom Prospective Diabetes Study(UKPDS), with a 10-year follow-up, reported significantreduction in both myocardial infarction and mortality forobese patients initiated with metformin compared with thosetreated with either sulphonylurea or insulin [15].

Metformin is contraindicated in patients with renalimpairment due to the risk of lactic acidosis resulting from theinhibition of hepatic gluconeogenesis. However, it is knownthat patients with a degree of renal impairment are treatedwith metformin in real-world clinical practice [16] and thatconsequent lactic acidosis is a rare event [17]. In our study,patients with renal impairment or elevated serum creatininewere represented equally in both cohorts (metformin 11.3% vs.sulphonylurea 12.7%). In contrast to other studies [8,9], we didnot exclude these patients but adjusted for them in our analysesand also performed a subgroup analysis for those with andwithout a history of renal impairment and/or elevated serumcreatinine. It is of interest that, in this sub-group analysis, theHR for all-cause mortality remained significantly higher (aHR=1.654) for patients treated with sulphonylurea. The decisionnot to treat a patient with metformin due to contraindicationshould therefore be balanced against other risks and benefits asdiscussed in two recent commentaries [17,18].

It is not clear from our study whether the difference inthe risk of all-cause mortality is due to the adverse impactof sulphonylurea or to the beneficial effect of metformin.Sulphonylureas are known to have an increased risk of

hypoglycaemia and there was a threefold increase in our study.There is evidence fromepidemiological studies [19] and clinicaltrials [20] suggesting that hypoglycaemia is associated withincreased risk of all-cause mortality and cardiovascular events.Sulphonylureas are also known to lead to weight gain [21]and may inhibit ischaemic preconditioning [22]. In contrast,metformin is associated with lower rates of cancer [23] andis also believed to have an impact upon myocardial infarctionbeyond its glucose-lowering properties [24,25].

This study has a number of limitations common to observa-tional studies. Whilst observational studies cannot replacerandomized trials they can be considered complementaryas they do not omit patients on the basis of strict inclu-sion/exclusioncriteria andwill usuallyhave increased follow-uptime. This may be of particular importance in evaluating out-comes with long latencies.

As cases were not randomized to each cohort, systematicbaseline differences between the treatment cohorts existed.Furthermore, treatments may have been dictated by individualpatient profile. For example, sulphonylureas may be usedin patients contraindicated to metformin due to renalimpairment, whilst metformin may be preferred in patientsprone to weight gain. Although the survival models accountedfor some of these differences as factors and covariates, thereis still potential for some unseen selection bias to remain. Topartly address this, we analysed two subsets of patients, thefirst matched directly on key characteristics and the secondby propensity score. Furthermore, following cessation ofmonotherapy, we followed those patients who switched to aregimen ofmetformin and sulphonylurea dual therapy to deathor last inclusion in the dataset. The HR for initial first-linetherapy (sulphonylurea vs. metformin) for all-cause mortalitywas unity (1.026), indicating that there was no underlyingdifference between these two cohorts. It is accepted that, asthese patients were not contraindicated to either metformin orsulphonylurea, theymay represent a subgroup that is not gener-alizable to the cohort as a whole. However, it does indicate that,at least for these patients, residual confounding is negligible.

In our study, exposure to either sulphonylurea ormetforminwasbasedonprimary-careprescription.Wehavenodata as to whether the patient actually filled the prescription atthe pharmacy or, further, as to whether they took the medicineat the recorded dosage. Patterns of adherence may have beendifferent between the two cohorts due to characteristics of boththe individual therapy and of the cohort itself at baseline.

The weight of scientific evidence so far shows that sulphony-lurea represents an increased hazard of serious adverse eventsover metformin [26]. This study confirms these findings, withsulphonylurea being associated with increased risk of all-causemortality compared with metformin. Guidelines recom-mending metformin as first-line monotherapy are thereforeappropriate. However, for those patients for whommetforminis deemed unsuitable due to contraindication, there must besome question as to whether sulphonylurea should still be con-sidered the first-choice alternative. An RCT may be requiredto determine the appropriate alternative, as these data raisequestions about the safety of sulphonylurea more generally.

2014 doi:10.1111/dom.12302 5

original article DIABETES, OBESITY AND METABOLISMAcknowledgementsThis research was funded by AstraZeneca and Bristol-MyersSquibb.

Conict of InterestC. Ll. M. is a contractor of Pharmatelligence, S. J. J. and S.E. H. are employed by Pharmatelligence and C. J. C. is adirector of Pharmatelligence, a research consultancy receivingfunding from pharmaceutical companies. J. M. is an employeeof Bristol-Myers Squibb.

C. Ll. M. was the principal investigator, performed thestatistical analysis, wrote the first draft of the manuscript andreviewed and edited subsequent versions. J. M. contributed tothe study design and reviewed the data and manuscript. S. J. J.extracted and reviewed the data and contributed to and editedthe manuscript. S. E. H. contributed to the study design andmanuscript. C. J. C. conceived, designed and supervised thestudy, and contributed to and reviewed themanuscript. C. J. C.is the guarantor of this work and, as such, had full access to allthe data in the study and takes responsibility for the integrityof the data and the accuracy of the data analysis.

References

1. Diabetes UK. Diabetes in the UK 2011/2012: Key Statisticson Diabetes. London: Diabetes UK 2011. Available from URL:http://www.diabetes.org.uk/Documents/Reports/Diabetes-in-the-UK-2011-12.pdf. Accessed 7 February 2014.

2. The National Collaborating Centre for Chronic Conditions. Type 2Diabetes: The Management of Type 2 Diabetes (Update) (CG66).London: Royal College of Physicians 2008. Available from URL:http://guidance.nice.org.uk/CG66. Accessed 7 February 2014.

3. Desai NR, Shrank WH, Fischer MA et al. Patterns of medication initiationin newly diagnosed diabetes mellitus: quality and cost implications. Am JMed 2012; 125: 302.e1302.e7.

4. Simpson SH, Majumdar SR, Tsuyuki RT, Eurich DT, Johnson JA.Doseresponse relation between sulfonylurea drugs and mortality intype 2 diabetes mellitus: a population-based cohort study. CMAJ 2006;174: 169174.

5. Currie CJ, Poole CD, Gale EAM. The inuence of glucose-lowering therapieson cancer risk in type 2 diabetes. Diabetologia 2009; 52: 17661777.

6. Garratt KN, Brady PA, Hassinger NL, Grill DE, Terzic A, Holmes DR Jr.Sulfonylurea drugs increase early mortality in patients with diabetesmellitus after direct angioplasty for acute myocardial infarction. J Am CollCardiol 1999; 33: 119124.

7. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method ofclassifying prognostic comorbidity in longitudinal studies: developmentand validation. J Chronic Dis 1987; 40: 373383.

8. Wheeler S, Moore K, Forsberg CW et al. Mortality among veteranswith type 2 diabetes initiating metformin, sulfonylurea or rosiglitazonemonotherapy. Diabetologia 2013; 56: 19341943.

9. Roumie CL, Hung AM, Greevy RA. Comparative effectiveness ofsulfonylurea and metformin monotherapy on cardiovascular events in

type 2 diabetes mellitus: a cohort study. Ann Intern Med 2012; 157:601610.

10. Tzoulaki I, Molokhia M, Curcin V et al. Risk of cardiovascular disease andall cause mortality among patients with type 2 diabetes prescribed oralantidiabetes drugs: retrospective cohort study using UK general practiceresearch database. BMJ 2009; 339: b4731.

11. Phung OJ, Schwartzman E, Allen RW, Engel SS, Rajpathak SN.Sulphonylureas and risk of cardiovascular disease: systematic reviewand meta-analysis. Diabet Med 2013; 30: 11601171.

12. DeFronzo RA, Goodman AM. Efcacy of metformin in patients with non-insulin-dependent diabetes mellitus. The Multicenter Metformin StudyGroup. N Engl J Med 1995; 333: 541549.

13. Garber AJ, Donovan DS Jr, Dandona P, Bruce S, Park JS. Efcacy ofglyburide/metformin tablets compared with initial monotherapy in type2 diabetes. J Clin Endocrinol Metab 2003; 88: 35983604.

14. Kahn SE, Haffner SM, Heisse MA, Herman WH, Holman RR. Glycemicdurability of rosiglitazone, metformin, or glyburide monotherapy. N Engl JMed 2006; 355: 24272443.

15. UK Prospective Diabetes Study (UKPDS) Group. Effect of intensive blood-glucose control with metformin on complications in overweight patientswith type 2 diabetes (UKPDS 34). Lancet 1998; 352: 854865.

16. Lipska KJ, Bailey CJ, Inzucchi SE. Use of metformin in the setting of mild-to-moderate renal insufciency. Diabetes Care 2011; 34: 14311437.

17. Emslie-Smith AM, Boyle DIR, Evans JMM, Sullivan F, Morris AD.Contraindications to metformin therapy in patients with Type 2diabetesa population-based study of adherence to prescribingguidelines. Diabet Med 2001; 18: 483488.

18. Kajbaf F, Arnouts P, de Broe M, Lalau J-D. Metformin therapy and kidneydisease: a review of guidelines and proposals for metformin withdrawalaround the world. Pharmacoepidemiol Drug Saf 2013; 22: 10271035.

19. Currie CJ, Peters JR, Tynan A et al. Survival as a function of HbA1c in peoplewith type 2 diabetes: a retrospective cohort study. Lancet 2010; 375:481489.

20. Zoungas S, Patel A, Chalmers J et al. ADVANCE Collaborative Group. Severehypoglycemia and risks of vascular events and death. N Engl J Med 2010;363: 14101418.

21. Morgan CL, Jenkins-Jones S, Evans M, Barnett AH, Poole CD, Currie CJ.Weight change in people with type 2 diabetes: secular trends and theimpact of alternative antihyperglycaemic drugs. Diabetes Obes Metab2012; 14: 424432.

22. Cleveland JC, Meldrum DR, Cain BS, Banerjee A, Harken AH. Oralsulfonylurea hypoglycemic agents prevent ischemic preconditioning inhuman myocardium. Two paradoxes revisited Circulation 1997; 96: 2932.

23. Soranna D, Scotti L, Zambon A et al. Cancer risk associated with use ofmetformin and sulfonylurea in type 2 diabetes: a meta-analysis. Oncologist2012; 17: 813822.

24. Kirpichnikov D, McFarlane SI, Sowers JR. Metformin: an update. Ann InternMed 2002; 137: 2533.

25. Roussel R, Travert F, Pasquet B et al. Reduction of Atherothrombosisfor Continued Health (REACH) Registry Investigators. Metformin use andmortality among patients with diabetes and atherothrombosis. Arch InternMed 2010; 170: 18921899.

26. Holden SE, Currie CJ. Mortality risk with sulfonylureas compared tometformin. Diabetes Obes Metab 2014; DOI: 10.1111/dom.12280 [Epubahead of print].

6 Morgan et al. 2014