J Gordon

Improved glycaemic control by switching from insulin NPH to insulin glargine: a retrospective observational study

BackgroundInsulin glargine (glargine) and insulin NPH (NPH) are two basal insulin treatments. This study investigated the effect on glycaemic control of switching from a NPH-based regimen to a glargine-based regimen in 701 patients with type 1 (n= 304) or type 2 (n= 397) diabetes, using unselected primary care data.MethodsData for this retrospective observational study were extracted from a UK primary care database (The Health Improvement Network). Patients were required to have at least 12 months of data before and after switching from NPH to glargine. The principal analysis was the change in HbA1c after 12 months treatment with glargine; secondary analyses included change in weight and total daily insulin dose. Inconsistent reporting of hypoglycemic episodes precludes reliable reporting of this outcome. Multivariate analyses were used to adjust for baseline characteristics and confounding variables.ResultsAfter adjustment, both diabetic cohorts showed statistically significant reductions in mean HbA1c 12 months after the switch, by 0.38% (p < 0.001) in type 1 patients and 0.31% (p < 0.001) in type 2 patients. Improvement in HbA1c was positively correlated with baseline HbA1c; patients with baseline HbA1c ≥ 8% had reductions of 0.57% (p < 0.001) and 0.47% (p < 0.001), respectively. There was no significant change in weight or total daily insulin dose while on glargine. The majority of patients received a basal-bolus regimen prior to and after the switch (mean 79.3% before and 77.2% after switch in type 1 patients, and 80.4% and 76.8%, respectively in type 2 patients, p > 0.05).ConclusionIn routine clinical practice, switching from NPH to glargine provides the opportunity for improving glycaemic control in diabetes patients inadequately controlled by NPH.

Assessing the Relationship between Computational Speed and Precision: A Case Study Comparing an Interpreted versus Compiled Programming Language using a Stochastic Simulation Model in Diabetes Care

AbstractBackground: Simulation techniques are well suited to modelling diseases yet can be computationally intensive. This study explores the relationship between modelled effect size, statistical precision, and efficiency gains achieved using variance reduction and an executable programming language. Methods: A published simulation model designed to model a population with type 2 diabetes mellitus based on the UKPDS 68 outcomes equations was coded in both Visual Basic for Applications (VBA) and C++. Efficiency gains due to the programming language were evaluated, as was the impact of antithetic variates to reduce variance, using predicted QALYs over a 40-year time horizon. Results: The use of C++ provided a 75- and 90-fold reduction in simulation run time when using mean and sampled input values, respectively. For a series of 50 one-way sensitivity analyses, this would yield a total run time of 2 minutes when using C++, compared with 155 minutes for VBA when using mean input values. The use of antithetic variates typically resulted in a 53% reduction in the number of simulation replications and run time required. When drawing all input values to the model from distributions, the use of C++ and variance reduction resulted in a 246-fold improvement in computation time compared with VBA — for which the evaluation of 50 scenarios would correspondingly require 3.8 hours (C++) and approximately 14.5 days (VBA). Conclusions: The choice of programming language used in an economic model, as well as the methods for improving precision of model output can have profound effects on computation time. When constructing complex models, more computationally efficient approaches such as C++ and variance reduction should be considered; concerns regarding model transparency using compiled languages are best addressed via thorough documentation and model validation.

Switching from premixed insulin to glargine-based insulin regimen improves glycaemic control in patients with type 1 or type 2 diabetes: a retrospective primary care-based analysis

BackgroundInsulin glargine (glargine) and premixed insulins (premix) are alternative insulin treatments. This analysis evaluated glycaemic control in 528 patients with type 1 (n = 183) or type 2 (n = 345) diabetes, after switching from premix to a glargine-based regimen, using unselected general practice (GP) data.MethodsData for this retrospective observational analysis were extracted from a UK GP database (The Health Improvement Network). Patients were required to have at least 12 months of available data, before and after, switching from premix to a glargine-based regimen. The principal analysis was the change in HbA1c after 12 months of treatment with glargine; secondary analyses included change in weight, bolus usage and total daily insulin dose. Inconsistent reporting of hypoglycemic episodes precludes reliable assessment of this outcome. Multivariate analyses were used to adjust for baseline characteristics and confounding variables.ResultsBoth cohorts showed significant reduction in mean HbA1c 12 months after the switch: by -0.67% (p < 0.001) in the type 1 cohort and by -0.53% (p < 0.001) in the type 2 cohort (adjusted data). The size of HbA1c improvement was positively correlated with baseline HbA1c; patients with a baseline HbA1c ≥ 10% had the greatest mean reduction in HbA1c, by -1.7% (p < 0.001) and -1.2% (p < 0.001), respectively. The proportion of patients receiving co-bolus prescriptions increased in the type 1 (mean 24.6% to 95.1%, p < 0.001) and type 2 (mean 16.2% to 73.9%, p < 0.001) cohorts. There was no significant change in weight in either cohort. Total mean insulin use increased in type 2 diabetes patients (from 0.67 ± 1.35 U/Kg to 0.88 ± 1.33 U/Kg, p < 0.001) with a slight decrease in type 1 diabetes patients (from 1.04 ± 2.51 U/Kg to 0.98 ± 2.58 U/Kg, p < 0.001).ConclusionIn everyday practice, patients with type 1 or type 2 diabetes inadequately controlled by premix insulins experienced significant improvement in glycaemic control over 12 months after switching to a glargine-based insulin regimen. These findings support the use of a basal-bolus glargine-based regimen in patients poorly controlled on premix.