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Objective: To compare ultra-long-acting insulin degludec with glargine for efficacy and safety in insulin-naive patients with type 2 diabetes inadequately controlled with oral antidiabetic drugs (OADs).Research Design and Methods: In this 1-year, parallel-group, randomized, open-label, treat-to-target trial, adults with type 2 diabetes with A1C of 7-10% taking OADs were randomized 3:1 to receive once daily degludec or glargine, both with metformin. Insulin was titrated to achieve prebreakfast plasma glucose (PG) of 3.9-4.9 mmol/L. The primary end point was confirmation of noninferiority of degludec to glargine in A1C reduction after 52 weeks in an intent-to-treat analysis.Results: In all, 1,030 participants (mean age 59 years; baseline A1C 8.2%) were randomized (degludec 773, glargine 257). Reduction in A1C with degludec was similar (noninferior) to that with glargine (1.06 vs. 1.19%), with an estimated treatment difference of degludec to glargine of 0.09% (95% CI -0.04 to 0.22). Overall rates of confirmed hypoglycemia (PG <3.1 mmol/L or severe episodes requiring assistance) were similar, with degludec and glargine at 1.52 versus 1.85 episodes/patient-year of exposure (PYE). There were few episodes of nocturnal confirmed hypoglycemia in the overall population, and these occurred at a lower rate with degludec versus glargine (0.25 vs. 0.39 episodes/PYE; P = 0.038). Similar percentages of patients in both groups achieved A1C levels <7% without hypoglycemia. End-of-trial mean daily insulin doses were 0.59 and 0.60 units/kg for degludec and glargine, respectively. Adverse event rates were similar.Conclusions: Insulins degludec and glargine administered once daily in combination with OADs provided similar long-term glycemic control in insulin-naive patients with type 2 diabetes, with lower rates of nocturnal hypoglycemia with degludec. [ABSTRACT FROM AUTHOR]

Background: Recent communications have argued that often it may not be appropriate to analyse cross-sectional studies of prevalent outcomes with logistic regression models. The purpose of this communication is to compare three methods that have been proposed for application to cross sectional studies: (1) a multiplicative generalized linear model, which we will call the log-binomial model, (2) a method based on logistic regression and robust estimation of standard errors, which we will call the GEE-logistic model, and (3) a Cox regression model.Methods: Five sets of simulations representing fourteen separate simulation conditions were used to test the performance of the methods.Results: All three models produced point estimates close to the true parameter, i.e. the estimators of the parameter associated with exposure had negligible bias. The Cox regression produced standard errors that were too large, especially when the prevalence of the disease was high, whereas the log-binomial model and the GEE-logistic model had the correct type I error probabilities. It was shown by example that the GEE-logistic model could produce prevalences greater than one, whereas it was proven that this could not happen with the log-binomial model. The log-binomial model should be preferred. [ABSTRACT FROM AUTHOR]

Objective: Glucagon/glucagon-like peptide-1 (GLP-1) receptor co-agonists may provide greater weight loss than agonists targeting the GLP-1 receptor alone. We report results from three phase 1 trials investigating the safety, tolerability, pharmacokinetics and pharmacodynamics of the glucagon/GLP-1 receptor co-agonist NNC9204-1177 (NN1177) for once-weekly subcutaneous use in adults with overweight or obesity., Methods: Our focus was a 12-week, multiple ascending dose (MAD), placebo-controlled, double-blind trial in which adults (N = 99) received NN1177 (on an escalating dose regimen of 200, 600, 1300, 1900, 2800, 4200 and 6000 μg) or placebo. Two other trials also contributed to the findings reported in this article: a first human dose (FHD)/single ascending dose (SAD), placebo-controlled, double-blind trial in which adults (N = 49) received NN1177 (treatment doses of 10, 40, 120, 350, 700 and 1100 μg) or placebo, and a drug-drug interaction, open-label, single-sequence trial in which adults (N = 45) received a 4200-μg dose of NN1177, following administration of a Cooperstown 5 + 1 index cocktail. Safety, tolerability, pharmacokinetic and pharmacodynamic endpoints were assessed., Results: For the FHD/SAD and MAD trials, baseline characteristics were generally balanced across treatment cohorts. The geometric mean half-life of NN1177 at steady state was estimated at between 77 and 111 h, and clinically relevant weight loss was achieved (up to 12.6% at week 12; 4200 μg in the MAD trial). Although NN1177 appeared tolerable across trials, several unexpected treatment-related safety signals were observed; increased heart rate, decreased reticulocyte count, increased markers of inflammation (fibrinogen and C-reactive protein), increased aspartate and alanine aminotransferase, impaired glucose tolerance and reduced blood levels of some amino acids., Conclusion: Although treatment with NN1177 was associated with dose-dependent and clinically relevant weight loss, the observed safety signals precluded further clinical development., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Martin Friedrichsen, Lars Endahl, Frederik Kreiner, Søren Toubro and Sune Nygård are employees of Novo Nordisk A/S. Martin Friedrichsen, Lars Endahl and Frederik Kreiner are shareholders in Novo Nordisk A/S. Martin Kankam has received funding from Diffusion Pharmaceutical Inc., Grifols, Urovant Sciences, ViroDefense, Merck, PhaseBio Pharmaceuticals, Inc., Idorsia Pharmaceuticals Ltd, DynPort Vaccine company/FDA/NIH, and Aerovate Therapeutics. Ronald Goldwater is an employee of Parexel International., (Copyright © 2023 The Authors. Published by Elsevier GmbH.. All rights reserved.)

In the approval process for new weight management therapies, regulators typically require estimates of effect size. Usually, as with other drug evaluations, the placebo-adjusted treatment effect (i.e., the difference between weight losses with pharmacotherapy and placebo, when given as an adjunct to lifestyle intervention) is provided from data in randomized clinical trials (RCTs). At first glance, this may seem appropriate and straightforward. However, weight loss is not a simple direct drug effect, but is also mediated by other factors such as changes in diet and physical activity. Interpreting observed differences between treatment arms in weight management RCTs can be challenging; intercurrent events that occur after treatment initiation may affect the interpretation of results at the end of treatment. Utilizing estimands helps to address these uncertainties and improve transparency in clinical trial reporting by better matching the treatment-effect estimates to the scientific and/or clinical questions of interest. Estimands aim to provide an indication of trial outcomes that might be expected in the same patients under different conditions. This article reviews how intercurrent events during weight management trials can influence placebo-adjusted treatment effects, depending on how they are accounted for and how missing data are handled. The most appropriate method for statistical analysis is also discussed, including assessment of the last observation carried forward approach, and more recent methods, such as multiple imputation and mixed models for repeated measures. The use of each of these approaches, and that of estimands, is discussed in the context of the SCALE phase 3a and 3b RCTs evaluating the effect of liraglutide 3.0 mg for the treatment of obesity.

Introduction: Individuals who enroll in intensive behavioral therapy (IBT) programs are asked to make several lifestyle changes simultaneously. However, few studies have examined the relative effects of adherence to different treatment components on weight loss., Objective: This secondary analysis of the SCALE IBT trial assessed adherence to the medication regimen, dietary self-monitoring, and physical activity recommendations and their relative contributions to weight change in individuals with obesity who were provided with IBT combined with either liraglutide 3.0 mg or placebo., Methods: SCALE IBT was a double-blinded, multicenter, randomized controlled trial comparing 56-week weight losses in individuals with obesity who received liraglutide 3.0 mg (n = 142) or placebo (n = 140), as an adjunct to IBT. Adherence to dietary self-monitoring, physical activity, and medication usage (liraglutide or placebo) were measured during the 56-week treatment period. A regression model was used to estimate the relative contribution of adherence to each treatment component to weight loss at week 56., Results: The proportion of individuals who adhered to each intervention component decreased over time. Compared with non-adherence, complete adherence to dietary self-monitoring and physical activity recommendations were associated with estimated weight changes of -7.2% (95% CI -10.4 to -4.0; p < 0.0001) and -2.0% (95% CI -3.2 to -0.8; p = 0.0009), respectively. Complete adherence to liraglutide predicted an additional weight loss of -6.5% (95% CI -10.2 to -2.9; p = 0.0005) relative to individuals who did not adhere to the medication regimen, while adherence to placebo did not have a statistically significant effect on weight loss (p = 0.33)., Conclusions: High adherence to dietary self-monitoring and use of liraglutide 3.0 mg was associated with clinically relevant weight loss with IBT and adjunctive pharmacotherapy. The effect of adherence to physical activity was significant but smaller., (© 2020 The Author(s) Published by S. Karger AG, Basel.)

Background: In 2013, a randomized, double-blind, active comparator-controlled, event-driven cardiovascular outcomes trial (DEVOTE) was initiated to compare the cardiovascular safety of insulin degludec (degludec) versus insulin glargine 100 units/mL (glargine U100) in patients with type 2 diabetes at high risk of cardiovascular events. The FDA agreed that an interim analysis could form the basis for an early regulatory approval. We report here the operational model developed to support the DEVOTE interim analysis and the results., Methods: The interim analysis model was designed to reduce the risk of any confidentiality breaches. The Data Access Management Plan comprehensively described the interim analysis operational processes and procedures to maintain the integrity of the ongoing trial while the interim analysis was conducted, submitted, and acted upon by the FDA, and also until completion of the full trial. Most importantly, those who were unblinded to the interim results were limited to a team of 14 members., Results: A total of 150 first major adverse cardiovascular events were recorded at cut-off for the interim analysis. The estimated hazard ratio was 0.92 (95% CI 0.67, 1.27) and non-inferiority to glargine U100 was confirmed as the upper bound of the confidence interval was below 1.8, as prespecified. Based on these results, the FDA approved the use of degludec and degludec/insulin aspart (IDegAsp) in the United States in 2015 before trial completion., Conclusions: The DEVOTE interim analysis succeeded as a model by which to conduct an interim analysis and submit confidential data for regulatory review and action while continuing the trial to address a primary hypothesis.

Aims: Weight loss-induced serum creatinine reduction may increase creatinine-based estimated glomerular filtration rate (eGFR) producing incorrect estimates of kidney function. We investigated whether weight changes in the SCALE program with liraglutide 3.0mg were associated with changes in serum creatinine., Methods: Post hoc analysis of two 56-week, randomized, double-blind trials: SCALE Obesity and Prediabetes (n=3731, without type 2 diabetes [T2D], randomized [2:1] to liraglutide 3.0mg [n=2487] or placebo [n=1244]); SCALE Diabetes (n=846 with T2D, randomized [2:1:1] to liraglutide 3.0mg [n=423], 1.8mg [n=211, excluded from this analysis] or placebo [n=212]). NCT01272219/NCT01272232., Results: In SCALE Obesity and Prediabetes, mean (±SD) weight loss (baseline to week 56) with liraglutide was 8.0±6.7% (2.6±6.9% with placebo); baseline creatinine with liraglutide was 76±15μmol/L and 74±15μmol/L after 56weeks (similar across treatment groups). In SCALE Diabetes, weight loss with liraglutide was 5.9±5.5% (2.0±4.3% with placebo); baseline creatinine was 79±19μmol/L (77±16μmol/L, placebo) and 79±20μmol/L after 56weeks (76±15μmol/L, placebo). No association between changes in weight and changes in serum creatinine was observed (P≥0.05, both trials, all tests)., Conclusions: Moderate gradual body weight reductions observed in the SCALE program were not associated with changes in serum creatinine., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: Insulin degludec/insulin aspart (IDegAsp) is a soluble co-formulation of insulin degludec (70%) and insulin aspart (IAsp: 30%). Here, we compare the efficacy and safety of IDegAsp, an alternative IDegAsp formulation (AF: containing 45% IAsp), and biphasic IAsp 30 (BIAsp 30)., Design: Sixteen-week, open-label, randomised, treat-to-target trial., Methods: Insulin-naive subjects with type 2 diabetes (18-75 years) and a HbA1c of 7-11% were randomised to twice-daily IDegAsp (n=61), AF (n=59) or BIAsp 30 (n=62), all in combination with metformin. Insulin was administered pre-breakfast and dinner (main evening meal) and titrated to pre-breakfast and pre-dinner plasma glucose (PG) targets of 4.0-6.0 mmol/l., Results: Mean HbA1c after 16 weeks was comparable for IDegAsp, AF and BIAsp 30 (6.7, 6.6 and 6.7% respectively). With IDegAsp, 67% of subjects achieved HbA1c 7.0% Without confirmed hypoglycaemia in the last 4 weeks of treatment compared with 53% (AF) and 40% (BIAsp 30). Mean fasting PG was significantly lower for IDegAsp vs BIAsp 30 (treatment difference (TD): -0.99 mmol/l (95% confidence interval: -1.68; 0.29)) and AF vs BIAsp 30 (TD: -0.88 mmol/l (-1.58; -0.18)). A significant, 58% lower rate of confirmed hypoglycaemia was found for IDegAsp vs BIAsp 30 (rate ratio (RR): 0.42 (0.23; 0.75)); rates were similar for AF vs BIAsp 30 (RR: 0.92 (0.54; 1.57)). IDegAsp and AF had numerically lower rates of nocturnal confirmed hypoglycaemia vs BIAsp 30 (RR: 0.33 (0.09; 1.14) and 0.66 (0.22; 1.93) respectively)., Conclusions: IDegAsp provided comparable overall glycaemic control to BIAsp 30 with a significantly lower rate of hypoglycaemia.

Insulin detemir (detemir) has previously been shown to be associated with lower within-subject variability compared with other basal insulin preparations in adults with type 1 diabetes mellitus (T1DM). This randomized, double-blind, crossover trial compared the within-subject variability of detemir and insulin glargine (glargine) in pharmacokinetic properties in children and adolescents with T1DM. The trial enrolled 32 children and adolescents (19 girls and 13 boys; mean +/- SD: age 13 +/- 2.5 yr and T1DM duration 6.3 +/- 3.0 yr) with a hemoglobin A1c (HbA1c) of 7.9 +/- 1.0%. Participants were randomized to a specific treatment sequence in which a dose of 0.4 U/kg of detemir and glargine was injected subcutaneously 24 h apart at each of two dosing visits. Insulin concentrations were measured at frequent intervals for a period of 16-h post-dosing. Detemir showed statistically significantly less within-subject variability compared with glargine with a 3.1-fold and 2.9-fold lower coefficient of variation (CV, %) for the area under the concentration-time curve [AUC((0-16) (h))] and the maximum concentration (C(max)), respectively. Separate analyses demonstrated a 2.5-fold and 2.9-fold lower CV (%) with detemir in children (8-12 yr) and a 4-fold and 3.8-fold lower CV (%) with detemir in adolescents (13-17 yr). No safety concerns were raised during the trial. In conclusion, within-subject variability in pharmacokinetic properties was significantly lower for detemir than for glargine in children and adolescents with T1DM. This indicates a less variable absorption with detemir, which is expected to be associated with a more predictable therapeutic effect also in this population.

The aim of this randomized double-blind study was to compare the within-subject variability of the glucose-lowering effect of a novel insulin analog, insulin detemir, with that of insulin glargine and NPH insulin in people with type 1 diabetes. Fifty-four subjects (32 males and 22 females, age 38 +/- 10 years [mean +/- SD], BMI 24 +/- 2 kg/m(2), HbA(1c) 7.5 +/- 1.2%, diabetes duration 18 +/- 9 years) participated in this parallel group comparison. Each subject received four single subcutaneous doses of 0.4 units/kg of either insulin detemir (n = 18), insulin glargine (n = 16), or human NPH insulin (n = 17) under euglycemic glucose clamp conditions (target blood glucose concentration 5.5 mmol/l) on four identical study days. The pharmacodynamic (glucose infusion rates [GIRs]) and pharmacokinetic (serum concentrations of insulin detemir, human insulin, and insulin glargine) properties of the basal insulin preparations were recorded for 24 h postdosing. Insulin detemir was associated with significantly less within-subject variability than both NPH insulin and insulin glargine, as assessed by the coefficient of variation (CV) for the pharmacodynamic end points studied [GIR-AUC((0-12 h)) 27% (detemir) vs. 59% (NPH) vs. 46% (glargine); GIR-AUC((0-24 h)) 27 vs. 68 vs. 48%; GIR(max) 23 vs. 46 vs. 36%; P < 0.001 for all comparisons]. Insulin detemir also provided less within-subject variability in the pharmacokinetic end points: maximal concentration (C(max)) 18 vs. 24 vs. 34%; INS-AUC((0- infinity )) 14 vs. 28 vs. 33%. The results suggest that insulin detemir has a significantly more predictable glucose-lowering effect than both NPH insulin and insulin glargine.

Objectives: A program called the Project on Research and Intervention in Monotonous Work (PRIM) was initiated in 1994 as a prospective cohort study of work-related musculoskeletal disorders. The group-based exposure assessment strategy, focusing on task-related exposure and used to obtain baseline measures of physical exposures, is reported in this paper., Methods: Monotonous, repetitive worktasks were evaluated at 19 factories. Tasks with an estimated similarity in physical exposure were aggregated before 103 exposure groups were formed. Subjects from the exposure groups were randomly sampled for measurements, and task-related exposure levels were quantified by 43 single exposure items using a real-time video-based observation method that allowed computerized estimates of repetitiveness, body postures, force, and velocity. In combination with questionnaire-based data on task distribution, the duration of exposure was calculated at the individual level., Results: The video-based observational method and the large number of exposure variables enabled the establishment of detailed quantitative exposure profiles in 103 task-based exposure groups. However, methodological problems associated with the use of grouped exposure assessment were revealed. Despite efforts to optimize group homogeneity, the within-group variance was larger than the between-group variance for several shoulder postural variables., Conclusions: A task-based exposure-assessment strategy can be successful in solving some of the main problems associated with the assessment of physical workplace exposures. The large within-group variance in exposure to nonneutral shoulder postures may eventually require individual assessment or the inclusion of groups with maximal contrast in exposure or both.

Logistic regression with random effects is used to study the relationship between explanatory variables and a binary outcome in cases with nonindependent outcomes. In this paper, we examine in detail the interpretation of both fixed effects and random effects parameters. As heterogeneity measures, the random effects parameters included in the model are not easily interpreted. We discuss different alternative measures of heterogeneity and suggest using a median odds ratio measure that is a function of the original random effects parameters. The measure allows a simple interpretation, in terms of well-known odds ratios, that greatly facilitates communication between the data analyst and the subject-matter researcher. Three examples from different subject areas, mainly taken from our own experience, serve to motivate and illustrate different aspects of parameter interpretation in these models.