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Original Investigation |

Comparison of Clinical Outcomes and Adverse Events Associated With Glucose-Lowering Drugs in Patients With Type 2 Diabetes A Meta-analysis

Suetonia C. Palmer, PhD1; Dimitris Mavridis, PhD2,3; Antonio Nicolucci, MD4; David W. Johnson, PhD5,6; Marcello Tonelli, MD7; Jonathan C. Craig, PhD8; Jasjot Maggo, MMed1; Vanessa Gray, MSc1; Giorgia De Berardis, MSc4; Marinella Ruospo, MSc9,10; Patrizia Natale, MSc10; Valeria Saglimbene, MSc10; Sunil V. Badve, MD5,11; Yeoungjee Cho, PhD5; Annie-Claire Nadeau-Fredette, MD12; Michael Burke, MD5,6; Labib Faruque, MSc13; Anita Lloyd, MSc14; Nasreen Ahmad, BSc14; Yuanchen Liu14; Sophanny Tiv, BSc14; Natasha Wiebe, MMath14; Giovanni F. M. Strippoli, PhD8,10,15
[+] Author Affiliations
1Department of Medicine, University of Otago Christchurch, Christchurch, New Zealand
2Department of Primary Education, School of Education, University of Ioannina, University Campus, Dourouti, Ioannina, Greece
3Department of Hygiene and Epidemiology, School of Health Sciences, University of Ioannina, University Campus, Dourouti, Ioannina, Greece
4Center for Outcomes Research and Clinical Epidemiology (CORESEARCH), Pescara, Italy
5Division of Medicine, Department of Renal Medicine, University of Queensland at the Princess Alexandra Hospital, Woolloongabba, Australia
6Translational Research Institute, University of Queensland, Woolloongabba, Australia
7Cumming School of Medicine, Health Sciences Centre, University of Calgary, Foothills Campus, Calgary, Alberta, Canada
8Sydney School of Public Health, University of Sydney, Sydney, Australia
9Division of Nephrology and Transplantation, Department of Translational Medicine, Amedeo Avogadro University of Eastern Piedmont, Novara, Italy
10Diaverum Medical Scientific Office, Lund, Sweden
11The George Institute for Global Health, Sydney, Australia
12Nephrology Division, Department of Medicine, University of Montreal, Montreal, Quebec, Canada
13Department of Medicine, Royal Alexandra Hospital, Edmonton, Alberta, Canada
14Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
15Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy
JAMA. 2016;316(3):313-324. doi:10.1001/jama.2016.9400.
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Published online

Importance  Numerous glucose-lowering drugs are used to treat type 2 diabetes.

Objective  To estimate the relative efficacy and safety associated with glucose-lowering drugs including insulin.

Data Sources  Cochrane Library Central Register of Controlled Trials, MEDLINE, and EMBASE databases through March 21, 2016.

Study Selection  Randomized clinical trials of 24 weeks’ or longer duration.

Data Extraction and Synthesis  Random-effects network meta-analysis.

Main Outcomes and Measures  The primary outcome was cardiovascular mortality. Secondary outcomes included all-cause mortality, serious adverse events, myocardial infarction, stroke, hemoglobin A1c (HbA1C) level, treatment failure (rescue treatment or lack of efficacy), hypoglycemia, and body weight.

Results  A total of 301 clinical trials (1 417 367 patient-months) were included; 177 trials (56 598 patients) of drugs given as monotherapy; 109 trials (53 030 patients) of drugs added to metformin (dual therapy); and 29 trials (10 598 patients) of drugs added to metformin and sulfonylurea (triple therapy). There were no significant differences in associations between any drug class as monotherapy, dual therapy, or triple therapy with odds of cardiovascular or all-cause mortality. Compared with metformin, sulfonylurea (standardized mean difference [SMD], 0.18 [95% CI, 0.01 to 0.34]), thiazolidinedione (SMD, 0.16 [95% CI, 0.00 to 0.31]), DPP-4 inhibitor (SMD, 0.33 [95% CI, 0.13 to 0.52]), and α-glucosidase inhibitor (SMD, 0.35 [95% CI, 0.12 to 0.58]) monotherapy were associated with higher HbA1C levels. Sulfonylurea (odds ratio [OR], 3.13 [95% CI, 2.39 to 4.12]; risk difference [RD], 10% [95% CI, 7% to 13%]) and basal insulin (OR, 17.9 [95% CI, 1.97 to 162]; RD, 10% [95% CI, 0.08% to 20%]) were associated with greatest odds of hypoglycemia. When added to metformin, drugs were associated with similar HbA1C levels, while SGLT-2 inhibitors offered the lowest odds of hypoglycemia (OR, 0.12 [95% CI, 0.08 to 0.18]; RD, −22% [−27% to −18%]). When added to metformin and sulfonylurea, GLP-1 receptor agonists were associated with the lowest odds of hypoglycemia (OR, 0.60 [95% CI, 0.39 to 0.94]; RD, −10% [95% CI, −18% to −2%]).

Conclusions and Relevance  Among adults with type 2 diabetes, there were no significant differences in the associations between any of 9 available classes of glucose-lowering drugs (alone or in combination) and the risk of cardiovascular or all-cause mortality. Metformin was associated with lower or no significant difference in HbA1C levels compared with any other drug classes. All drugs were estimated to be effective when added to metformin. These findings are consistent with American Diabetes Association recommendations for using metformin monotherapy as initial treatment for patients with type 2 diabetes and selection of additional therapies based on patient-specific considerations.

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Figures

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Figure 1.
Summary of Study Retrieval and Identification for Network Meta-analysis

aFourteen studies evaluated glucose-lowering strategies as both monotherapy and dual therapy.

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Figure 2.
Graphic Representation of Available Glucose-Lowering Drugs on Cardiovascular Mortality in Clinical Trials of Type 2 Diabetes

Connecting lines represent head-to-head drug comparisons, indicated by the connected nodes (size proportional to number of trials). Numbers above and below the lines indicate studies and patients respectively. Line thickness is proportional to the number of trials comparing the 2 drug classes.

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Figure 3.
Efficacy Rankings of Available Glucose-Lowering Drugs for Treatment of Type 2 Diabetes

Drug rankings for efficacy (cardiovascular mortality, treatment failure, and hemoglobin A1c [HbA1C] levels). Drug classes are stratified according to administration as monotherapy, as dual therapy in addition to metformin, or as triple therapy in addition to metformin and sulfonylurea. The lines show the probability of the drug ranking for each outcome between best and worst (ranking first, second, third, etc), and the peak indicates the ranking with the highest probability for the corresponding drug class. For example, for treatment failure, sodium-glucose–linked transporter 2 (SGLT-2) inhibitor monotherapy demonstrates a higher probability of ranking best than thiazolidinedione monotherapy. Basal insulin monotherapy has a 50% probability of ranking as the best drug for avoiding treatment failure and a 100% probability of ranking the worst (13th best) for hypoglycemia (see Figure 4). Rankogram lines without marked peaks (for example, for all drug classes as monotherapy and their association with odds of cardiovascular mortality) indicate similar probabilities of all rankings and lower confidence in comparative ranking of the relevant drug class for that outcome. Rankograms showing no data indicate observations were insufficient to generate a rankogram for the drug class for the corresponding outcome. For example, there were insufficient data for meglitinides as triple therapy to infer drug rankings for any outcome. Similarly, there were insufficient data to infer drug rankings for α-glucosidase inhibitor treatment in triple therapy for the outcome of cardiovascular mortality. The peak of the rankogram curve can be used to assess probabilities of drug classes between best and worst (for example, for treatment failure, SGLT-2 inhibitors, and glucagon-like peptide 1 (GLP-1) receptor agonists were most likely to be among the best treatments and had similar ranking). DPP-4 indicates dipeptidyl peptidase 4.

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Figure 4.
Adverse Effects Rankings of Available Glucose-Lowering Drugs for Treatment of Type 2 Diabetes

Drug rankings for adverse effects (serious adverse effects, hypoglycemia, and weight gain). See Figure 3 legend for additional information.

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Figure 5.
Funnel Plot for Cardiovascular Mortality When Glucose-Lowering Drugs Were Used as Monotherapy

A funnel plot is a scatterplot of the study effect size vs some measure of its precision, in this instance the standard error. A funnel plot that is asymmetrical with respect to the line of the summary effect (vertical red line) implies there are differences between the estimates derived from small and large studies. The studies are ordered from best to worst according to effects on cardiovascular mortality. Missing (small) studies lying on the right side of the zero line suggest that small studies tend to exaggerate the effectiveness of higher-ranked treatments compared with lower-ranked treatments. The cause of any small study effects is explored by meta-regression and is not necessarily attributable to publication bias (the absence of small, negative studies in the available literature). Red line represents the null hypothesis that the study-specific effect sizes do not differ from the respective comparison-specific pooled effect estimates. The 2 black dashed lines represent a 95% confidence interval for the difference between study-specific effect sizes and comparison-specific summary estimates. yixy is the noted effect size in study i that compares x with y. μxy is the comparison-specific summary estimate for x vs y. Treatments are ordered by the surface under the cumulative ranking (SUCRA) curve.

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