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      Hypoglycaemia and treatment patterns among insulin‐treated patients with type 2 diabetes who switched to insulin glargine 300 units/mL versus other basal insulin in a real‐world setting

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          Abstract

          Introduction

          Type 2 diabetes (T2D) is characterized by worsening pancreatic β‐cell function often requiring treatment escalation with oral antidiabetic drugs ( OADs), glucagon‐like peptide‐1 and eventually insulin. Although there is much evidence available on the initiation of basal insulins, fewer studies have investigated the effects of switching from one basal insulin to another. This study aims to evaluate treatment persistence and hypoglycaemia in adult patients with T2D on prior basal insulin who were switched to insulin glargine 300 units/mL (Gla‐300) or other basal insulins in a real‐world setting.

          Materials and methods

          This study is a retrospective cohort analysis of patient‐level data extracted from the Optum ® Clinformatics database between 1 October 2014 and 30 June 2016. Adult patients (≥18 years) with T2D who were being treated with basal insulin during the 6‐month baseline period, who switched to either Gla‐300 or other basal insulins, were followed up for ≥3 months after switching. Outcomes included treatment persistence, and incidence and number of hypoglycaemic events.

          Results

          Of the included patients, 1204 switched to Gla‐300 and 616 switched to other basal insulins. Adjusting for baseline confounders, patients who switched to Gla‐300 were 34% less likely to discontinue their basal insulin than patients who switched to other basal insulins (hazard ratio [ HR] 0.66; 95% confidence interval [ CI] 0.54‐0.81; P < 0.001). Patients who switched to Gla‐300 were less likely to experience hypoglycaemia at 3‐month follow‐up (odds ratio [ OR] 0.56, 95% CI 0.32‐0.97; P = 0.039) and at 6‐month follow‐up ( OR 0.58, 95% CI 0.38‐0.87; P = 0.009) compared with patients who switched to other basal insulins.

          Conclusions

          Patients with T2D on prior basal insulin in a real‐world setting who switched to Gla‐300 were more persistent with their basal insulin and experienced less hypoglycaemia than patients who switched to other basal insulins.

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          Glucose Variability: Timing, Risk Analysis, and Relationship to Hypoglycemia in Diabetes

          Glucose control, glucose variability (GV), and risk for hypoglycemia are intimately related, and it is now evident that GV is important in both the physiology and pathophysiology of diabetes. However, its quantitative assessment is complex because blood glucose (BG) fluctuations are characterized by both amplitude and timing. Additional numerical complications arise from the asymmetry of the BG scale. In this Perspective, we focus on the acute manifestations of GV, particularly on hypoglycemia, and review measures assessing the amplitude of GV from routine self-monitored BG data, as well as its timing from continuous glucose monitoring (CGM) data. With availability of CGM, the latter is not only possible but also a requirement—we can now assess rapid glucose fluctuations in real time and relate their speed and magnitude to clinically relevant outcomes. Our primary message is that diabetes control is all about optimization and balance between two key markers—frequency of hypoglycemia and HbA1c reflecting average BG and primarily driven by the extent of hyperglycemia. GV is a primary barrier to this optimization, including to automated technologies such as the “artificial pancreas.” Thus, it is time to standardize GV measurement and thereby streamline the assessment of its two most important components—amplitude and timing.
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            Avoiding hypoglycemia: a key to success for glucose-lowering therapy in type 2 diabetes

            Bo Ahrén (2013)
            Type 2 diabetes carries a risk for hypoglycemia, particularly in patients on an intensive glucose control plan as a glucose-lowering strategy, where hypoglycemia may be a limitation for the therapy and also a factor underlying clinical inertia. Glucose-lowering medications that increase circulating insulin in a glucose-independent manner, such as insulin and sulfonylurea therapy, are the most common cause of hypoglycemia. However, other factors such as a delayed or missed meal, physical exercise, or drug or alcohol consumption may also contribute. Specific risk factors for development of hypoglycemia are old age, long duration of diabetes, some concomitant medication, renal dysfunction, hypoglycemia unawareness, and cognitive dysfunction. Hypoglycemia is associated with acute short-term symptoms related to either counterregulation, such as tachycardia and sweating, or to neuroglycopenia, such as irritability, confusion, and in severe cases stupor, coma, and even death. However, there are also long-term consequences of hypoglycemia such as reduced working capacity, weight gain, loss of self-confidence with reduced quality of life, and increased risk for cardiovascular diseases. For both the patients, the health care system, and the society at large, hypoglycemia carries a high cost. Strategies to mitigate the risk of hypoglycemia include awareness of the condition; education of patients, relatives, and health care providers; and selecting appropriate glucose-lowering medication that also judges the risk for hypoglycemia to prevent this complication. This article summarizes the current knowledge of hypoglycemia and its consequences with a special emphasis on its consequences for the choice of glucose-lowering therapy.
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              Physician follow-up and provider continuity are associated with long-term medication adherence: a study of the dynamics of statin use.

              Many patients who initiate statin (3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitor) therapy discontinue treatment within 1 year. We sought to estimate the rate at which patients reinitiate treatment after long periods of nonadherence and to determine whether reinitiation of treatment is linked to potentially modifiable factors such as physician visits, cholesterol testing, or other encounters with the health care system. We studied new users of statins in British Columbia, Canada, who initiated treatment between January 1, 1997, and June 30, 2004, and who had an extended period of nonadherence, defined as at least 90 days after the completion of 1 prescription in which no refill for any statin medication was obtained. Survival analysis was used to estimate the rate of reinitiation of statin therapy. Case-crossover analysis was used to evaluate the predictors of reinitiation. We identified 239 911 new users of statins, of whom 129 167 (53.8%) had a period of nonadherence that lasted for at least 90 days. Of these patients, an estimated 48% restarted treatment within 1 year and 60% restarted treatment within 2 years. Case-crossover analysis revealed events that were associated with a return to adherence, including visits with the physician who initiated the statin regimen (odds ratio [OR], 6.1; 95% confidence interval [CI], 5.9-6.3), a visit with another physician (OR, 2.9; 95% CI, 2.8-3.0), and a cholesterol test (OR, 1.5; 95% CI, 1.4-1.5). Incident myocardial infarction (OR, 12.2; 95% CI, 8.9-16.9) and other cardiovascular disease-related hospitalizations (OR, 3.6; 95% CI, 3.1-4.3) were also strong predictors of reinitiation of treatment. Physicians should be aware that statin use is dynamic and that many patients have long periods of nonadherence. A follow-up visit with the physician who wrote the initial statin prescription and having a cholesterol test predicted reinitiation of statin therapy. Our results suggest that continuity of care combined with increased follow-up and cholesterol testing could promote long-term adherence by shortening or eliminating long gaps in statin use. This hypothesis should be confirmed in a randomized experiment.
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                Author and article information

                Contributors
                Liz.Zhou@sanofi.com
                Journal
                Endocrinol Diabetes Metab
                Endocrinol Diabetes Metab
                10.1002/(ISSN)2398-9238
                EDM2
                Endocrinology, Diabetes & Metabolism
                John Wiley and Sons Inc. (Hoboken )
                2398-9238
                14 June 2019
                July 2019
                : 2
                : 3 ( doiID: 10.1002/edm2.2019.2.issue-3 )
                : e00073
                Affiliations
                [ 1 ] Sanofi Bridgewater New Jersey
                [ 2 ] Sanofi Guildford UK
                [ 3 ] Statinmed Research Ann Arbor Michigan
                [ 4 ] University Of Texas Southwestern Medical Center and Parkland Health & Hospital System Dallas Texas
                Author notes
                [*] [* ] Correspondence

                Fang L. Zhou, Sanofi, Bridgewater, NJ.

                Email: Liz.Zhou@ 123456sanofi.com

                Author information
                https://orcid.org/0000-0003-1353-6376
                https://orcid.org/0000-0003-4856-4369
                https://orcid.org/0000-0003-4539-2725
                Article
                EDM273
                10.1002/edm2.73
                6613231
                31294087
                6d939beb-4819-4b5b-b9be-b09f1578c2de
                © 2019 The Authors. Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 25 February 2019
                : 24 April 2019
                : 28 April 2019
                Page count
                Figures: 4, Tables: 1, Pages: 9, Words: 5573
                Funding
                Funded by: Sanofi
                Funded by: American Diabetes Association
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                edm273
                July 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.5 mode:remove_FC converted:08.07.2019

                gla‐300,hypoglycaemia,persistence
                gla‐300, hypoglycaemia, persistence

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