/pdf/about-the-national-institute-for-health-and-care-excellence-4zmiguft2a.pdf

About the National Institute for Health and Care Excellence - NICE.

Digital diabetes: Perspectives for diabetes prevention, management and research.

Aim To assess the efficacy and safety of combination therapy with a glucagon-like peptide-1 receptor agonist (GLP-1 RA) and a sodium-glucose co-transporter-2 inhibitor (SGLT2i) in patients with type 2 diabetes. Methods We searched Medline, Embase, the Cochrane Library and grey literature sources up to 2 December 2019 for randomized controlled trials in adults with type 2 diabetes assessing the combination of GLP-1RA and SGLT2i, either as co-initiation therapy or as add-on to each other, against placebo or an active comparator. The primary outcome was change in HbA1c . Secondary outcomes included change in body weight, blood pressure and estimated glomerular filtration rate, and incidence of severe hypoglycaemia, all-cause mortality, cardiovascular mortality, myocardial infarction, stroke and hospitalization for heart failure. We pooled data using random effects meta-analyses. Results Seven trials (1913 patients) were eligible. Compared with GLP-1RA, GLP-1RA/SGLT2i combination therapy was associated with a greater reduction in HbA1c (weighted mean difference -0.61%, 95% CI -1.09% to -0.14%, four studies), body weight (-2.59 kg, -3.68 to -1.51 kg, three studies) and systolic blood pressure (-4.13 mmHg, -7.28 to -0.99 mmHg, four studies). Compared with SGLT2i, GLP-1RA/SGLT2i combination therapy reduced HbA1c (-0.85%, -1.19% to -0.52%, six studies) and systolic blood pressure (-2.66 mmHg, -5.26 to -0.06 mmHg, six studies), but not body weight (-1.46 kg, -2.94 to 0.03 kg, five studies). After excluding data for one trial that had a considerably longer duration than the remaining studies, body weight was also reduced versus SGLT2i (-1.79 kg, -2.99 to -0.59 kg, five studies). Combination therapy did not increase the incidence of severe hypoglycaemia. Data for mortality and cardiovascular outcomes were scarce. Conclusions GLP-1RA/SGLT2i combination therapy seems to reduce HbA1c , body weight and systolic blood pressure without increasing the risk of severe hypoglycaemia compared with either GLP-1RA or SGLT2i. No conclusions can be made regarding long-term effectiveness or the effect on cardiovascular outcomes.

Glucagon-like peptide-1 receptor agonists and sodium-glucose co-transporter-2 inhibitors as combination therapy for type 2 diabetes: A systematic review and meta-analysis.

GLP-1 receptor agonists (GLP-1RA) and SGLT2 inhibitors (SGLT2i) have been associated with improved glycemic control, body weight loss and favorable changes in cardiovascular risk factors and outcomes. We conducted a systematic review and meta-analysis to evaluate the effects of the addition of GLP-1RA to SGLT2i in patients with type 2 diabetes mellitus and inadequate glycemic control. Six databases were searched until March 2019. Randomized controlled trials (RCT) with a follow-up of at least 24 weeks reporting on HbA1c, body weight, systolic blood pressure, lipids, achievement of HbA1c < 7%, requirement of rescue therapy due to hyperglycemia and hypoglycemic events were selected. Four RCTs were included. Compared to SGLT2i, the GLP-1RA/SGLT2i combination was associated with greater reduction in HbA1c (−0.74%), body weight (−1.61 kg), and systolic blood pressure (−3.32 mmHg). A higher number of patients achieved HbA1c < 7% (RR = 2.15), with a lower requirement of rescue therapy (RR = 0.37) and similar incidence of hypoglycemia. Reductions in total and LDL cholesterol were found. The present review supports treatment intensification with GLP-1RA in uncontrolled type 2 diabetes on SGLT2i. This drug regimen could provide improved HbA1c control, together with enhanced weight loss and blood pressure and lipids control.

/pdf/efficacy-and-safety-of-glp-1-receptor-agonists-as-add-on-to-38aja17zkn.pdf

Efficacy and safety of GLP-1 receptor agonists as add-on to SGLT2 inhibitors in type 2 diabetes mellitus: A meta-analysis.

Durability of insulin degludec plus liraglutide versus insulin glargine U100 as initial injectable therapy in type 2 diabetes (DUAL VIII): a multicentre, open-label, phase 3b, randomised controlled trial.

AIM To investigate the efficacy and safety of insulin degludec/liraglutide (IDegLira) versus insulin glargine 100 units/mL (IGlar U100) as add-on to sodium-glucose co-transporter-2 (SGLT2) inhibitor therapy. MATERIALS AND METHODS In this 26-week, phase IIIb, open-label, parallel-group, treat-to-target trial, conducted at 74 sites in 11 countries, insulin-naive people aged ≥18 years with glycated haemoglobin (HbA1c) 53-97 mmol/mol (7.0-11.0%), body mass index 20-40 kg/m2 and inadequately controlled type 2 diabetes (T2D) on SGLT2 inhibitor ± oral antidiabetic drugs were randomized 1:1 to once-daily IDegLira or IGlar U100, both as add-on to existing therapy. The primary endpoint was change in HbA1c from baseline to week 26. RESULTS A total of 210 participants were randomized to each treatment arm. Mean HbA1c reductions were 21 mmol/mol (1.9%-points) with IDegLira and 18 mmol/mol (1.7%-points) with IGlar U100; confirming non-inferiority (P < 0.0001) and superiority of IDegLira (difference in HbA1c change -3.90 mmol/mol; 95% confidence interval [CI] -5.45; -2.35 (-0.36%-points; 95% CI -0.50, -0.21)). Superiority for IDegLira over IGlar U100 was also confirmed for: body weight (difference -1.92 kg; 95% CI -2.64, -1.19); severe or blood-glucose-confirmed symptomatic hypoglycaemia (rate ratio 0.42; 95% CI 0.23, 0.75); total daily insulin dose (difference -15.37 U; 95% CI -19.60, -11.13). The overall treatment-emergent adverse event rate was higher with IDegLira as a result of higher increased lipase and nausea rates. CONCLUSIONS The favourable safety and efficacy profile of IDegLira in people with uncontrolled T2D on SGLT2 inhibitors, and lower weight gain and hypoglycaemia risk versus IGlar U100, suggest that clinicians should consider IDegLira initiation in this population.

Superior efficacy of insulin degludec/liraglutide versus insulin glargine U100 as add-on to sodium-glucose co-transporter-2 inhibitor therapy: A randomized clinical trial in people with uncontrolled type 2 diabetes.

In a recent article published in Expert Opinion on Pharmacotherapy (Nov 5 2017), Cai XL and colleagues reported a systematic review and meta-analysis of randomized controlled trials of insulin degludec/liraglutide(IDegLira; Novo Nordisk) and insulin glargine/lixisenatide(IGlarLixi; Sanofi), both fixed ratio combinations (FRC) of a basal insulin and a glucagon-like peptide-1 receptor agonist (GLP-1RA) [1]. In the absence of head-to-head comparisons of drugs, meta-analyses can provide additional evidence not available from single trials; however, any conclusions must be based on proper methodology. Cai et al. [1] concluded that \"Comparisons between the two treatment groups indicated no significant differences between groups in absolute HbA1c or body weight changes relative to baseline.\" We question the validity of these overall conclusions, based on concerns about both the heterogeneity of the trials included and the statistical methods used.

https://www.tandfonline.com/doi/pdf/10.1080/14656566.2018.1444882

Methodological concerns with the meta-analysis comparing insulin degludec/liraglutide and insulin glargine/lixisenatide.

Diabetes therapy aims for stable glycemic control and minimal hypoglycemia risk, previously linked to day-to-day variability. In a post-hoc analysis, day-to-day fasting glycemic variability with IDegLira was compared with IGlar U100, in DUAL V (IDegLira vs. IGlar U100) and VII (IDegLira vs. IGlar U100 and bolus insulin aspart) (NCT 01952145 and 02420262). Weekly and overall measures of day-to-day fasting glycemic variability were calculated using subjects’ daily fasting SMPG values, overall measure was used to divide the populations into tertiles, and proportional odds were statistically significant favoring IDegLira (Table). More subjects treated with IDegLira had lower overall day-to-day fasting glucose variability vs. IGlar 100 (Table). Hypoglycemia rates were reduced with lower variability with IDegLira vs. comparators in all tertiles (Table). In DUAL V (IDegLira vs. IGlar U100) and DUAL VII (IDegLira vs. IGlar U100 plus bolus insulin aspart) respectively, statistical analysis of weekly variances showed a 32% (p Disclosure I. Lingvay: Advisory Panel; Self; Novo Nordisk A/S, Eli Lilly and Company, AstraZeneca, Intarcia Therapeutics, Inc., Sanofi-Aventis. Research Support; Self; Novo Nordisk A/S, Merck Sharp & Dohme Corp., Pfizer Inc., GI Dynamics Inc., Novartis AG. Other Relationship; Self; Sanofi, AstraZeneca, Boehringer Ingelheim GmbH, Novo Nordisk A/S. A. Doshi: Advisory Panel; Self; Pfizer Inc. P.A. Garcia-Hernandez: Research Support; Self; Novo Nordisk A/S, PAREXEL International Corporation, Amgen Inc., ICON plc.. Speaker9s Bureau; Self; Eli Lilly and Company, Novo Nordisk A/S, Amgen Inc., AstraZeneca. J. Merino Torres: Advisory Panel; Self; AstraZeneca, Eli Lilly and Company, Novo Nordisk A/S. Speaker9s Bureau; Self; Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi-Aventis, Janssen Pharmaceuticals, Inc. M. Rodacki: Research Support; Self; Faperj. Speaker9s Bureau; Self; Allergan, Novo Nordisk A/S. Speaker9s Bureau; Spouse/Partner; Biogen. S. Eggert: Employee; Self; Novo Nordisk A/S. R. Gron: Employee; Self; Novo Nordisk A/S. E. Jaeckel: Advisory Panel; Self; Novo Nordisk A/S, Lilly, AstraZeneca, Boehringer, Merck Sharp & Dohme Corp., Janssen, Roche, Novartis. Board Member; Self; Novo Nordisk A/S, Lilly. Research Support; Self; Novo Nordisk A/S, Novartis, Gilead Sciences, Inc., Roche, Miltenyi Biotec, Biotest Pharmaceuticals Corporation, Fresenius SE & Co. KGaA, DFG, BMBF, EU, JDRF, VolkswagenStiftung. Speaker9s Bureau; Self; Novo Nordisk A/S, Lilly, AstraZeneca, Boehringer, Merck Sharp & Dohme Corp., Janssen, Roche, Novartis AG.

Lower Day-to-Day Fasting Self-Measured Plasma Glucose (SMPG) Variability with Insulin Degludec/Liraglutide (IDegLira) vs. Insulin Glargine 100 Units/mL (IGlar U100)

Machine learning allows extensive analysis of big complex data. This study had two aims: 1) characterize patients on BI who add a GLP-1RA and 2) identify predictors of ≥1% decline in A1C. Patients with T2D who were prescribed BI for ≥90 days but not GLP-1RA for 180 days beforehand (in the U.S. IBM Explorys database between 2010 and 2016) were included (N=80,019). For the A1C analysis, A1C readings ≤180 days before, and 180-360 days after initiating GLP-1RA were required (N=8731). Logistic regression with 23 pre-specified variables, and subsequent hypothesis-free machine learning models, with 155000 additional variables covering clinical, claims and billing data addressed both aims. GLP-1RA initiators were characterized by a BI duration of >180 days (vs. ≤180 days) estimated odds ratio (OR) 5.87 (95% CI: 5.49-6.27), receiving oral antidiabetic drugs(s) OR 1.70 (1.64-1.77) and co-medication(s) (both vs. none) OR 3.22 (2.96-3.50), a BMI >30 kg/m 2 (vs. 2 ) OR 1.93 (1.84-2.03), age Disclosure E. Zimmermann: Employee; Self; Novo Nordisk A/S. Stock/Shareholder; Spouse/Partner; Novo Nordisk A/S. A. Lenart: Employee; Self; Novo Nordisk A/S. J. da Rocha Fernandes: Employee; Self; Novo Nordisk A/S, International Diabetes Federation. S. Eggert: Employee; Self; Novo Nordisk A/S. M.F. Ranthe: Employee; Self; Novo Nordisk A/S. Stock/Shareholder; Self; Novo Nordisk A/S.

Use of Big-Data Algorithms to Characterize Patients with T2D on Basal Insulin (BI) Who Add a Glucagon-Like Peptide-1 Receptor Agonist (GLP-1 RA) and Predict Their A1C Response

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Superior efficacy of insulin degludec/liraglutide versus insulin glargine U100 as add-on to sodium-glucose co-transporter-2 inhibitor therapy: A randomized clinical trial in people with uncontrolled type 2 diabetes.

Methodological concerns with the meta-analysis comparing insulin degludec/liraglutide and insulin glargine/lixisenatide.

Lower Day-to-Day Fasting Self-Measured Plasma Glucose (SMPG) Variability with Insulin Degludec/Liraglutide (IDegLira) vs. Insulin Glargine 100 Units/mL (IGlar U100)

Use of Big-Data Algorithms to Characterize Patients with T2D on Basal Insulin (BI) Who Add a Glucagon-Like Peptide-1 Receptor Agonist (GLP-1 RA) and Predict Their A1C Response