Preference for Type 2 Diabetes Therapies in the United States: A Discrete Choice Experiment.

INTRODUCTION: Type 2 diabetes mellitus (T2DM) is a chronic condition associated with substantial clinical and economic burden. As multiple therapeutic options are available, patient preferences on treatment characteristics are key in T2DM therapeutic decision-making. This study aimed to determine the preferences of US patients with T2DM for therapies recommended for first pharmacologic intensification after metformin. METHODS: As part of a discrete choice experiment, an online survey was designed using literature review and qualitative interview findings. Eligibility was met by US patients with T2DM who were aged 18 years or older with an HbA1c ≥ 6.5%. Anonymized therapy profiles were created from six antidiabetic therapies including oral and injectable semaglutide, dulaglutide, empagliflozin, sitagliptin, and thiazolidinediones. RESULTS: Eligible patients (n = 500) had a mean HbA1c of 7.4%, and a mean BMI of 32.0 kg/m2, the majority of which (72.2%) were injectable-naïve. The treatment characteristic with greatest importance was mode and frequency of administration (35.5%), followed by body weight change (29.2%), cardiovascular event risk (19.1%), hypoglycemic event risk (9.9%), and HbA1c change (6.5%). An oral semaglutide-like profile was preferred by 91.9-70.1% of respondents depending on the comparator agent, and preference was significant in each comparison (p < 0.05); an injectable semaglutide-like profile was preferred by 89.3-55.7% of respondents in each comparison depending on the comparator agent. CONCLUSION: Patients with T2DM in the USA are significantly more likely to prefer oral or injectable semaglutide-like profiles over those of key comparators from the glucagon-like peptide 1 receptor agonist, sodium-glucose cotransporter 2 inhibitor, dipeptidyl peptidase 4 inhibitor, and thiazolidinedione classes.

Lifetime Cost-effectiveness of Oral Semaglutide Versus Dulaglutide and Liraglutide in Patients With Type 2 Diabetes Inadequately Controlled With Oral Antidiabetics.

PURPOSE: To estimate the incremental cost-utility ratio of oral semaglutide (14 mg once daily) vs other glucagon-like peptide 1 receptor agonist treatments among adults with type 2 diabetes that was inadequately controlled with 1 to 2 oral antidiabetic drugs from a US payer perspective. METHODS: A state-transition model with a competing risk approach was developed for diabetic complications and risk of cardiovascular events based on the UK Prospective Diabetes Study Outcomes Model 1 equations. Baseline population characteristics reflect the PIONEER 4 trial (Efficacy and Safety of Oral Semaglutide Versus Liraglutide and Versus Placebo in Subjects With Type 2 Diabetes Mellitus) of oral semaglutide. Model comparators included subcutaneous semaglutide, dulaglutide, and liraglutide. Treatment effects (change in glycosylated hemoglobin, weight, and systolic blood pressure) were estimated by network meta-analysis. Drug, management, and event costs (in 2019 US dollars), survival after nonfatal events, and utilities were obtained from the literature. Costs and quality-adjusted life-year (QALY) outcomes were discounted at 3% annually over a lifetime horizon. Probabilistic and 1-way sensitivity analyses were performed. FINDINGS: Total estimated costs and QALYs were $144,065 and 12.98 for oral semaglutide, $145,721 and 12.96 for dulaglutide, $145,833 and 12.99 for SC semaglutide, and $149,428 and 12.97 for liraglutide, respectively. Oral semaglutide was less costly and more effective than dulaglutide and liraglutide but less costly than subcutaneous semaglutide with similar effectiveness. Oral semaglutide was favored versus subcutaneous semaglutide in 52.10% of model replications at a willingness-to-pay of $150,000 per QALY. IMPLICATIONS: Oral semaglutide is predicted to offer health benefits similar to subcutaneous semaglutide and ahead of dulaglutide and liraglutide. Oral semaglutide is a cost-effective glucagon-like peptide 1 receptor agonist treatment option.

Quality of life in patients with type 2 diabetes after switching to insulin degludec: results from a cross-sectional survey.

PURPOSE: Five quality of life (QoL) domains are particularly important to patients with type 2 diabetes (T2D) using basal insulin-sense of physical well-being, sense of safety regarding hypoglycemia, sense of diabetes as burdensome, feelings of freedom and flexibility, and sleep quality. METHODS: An online survey assessed these QoL domains in adult patients with T2D in the USA who had switched from a previous basal insulin to insulin degludec (IDeg): modified versions of the World Health Organization (Five) Well-Being Index (WHO-5), Hypoglycemia Attitudes and Behavior Scale (HABS; confidence and anxiety subscales only), and Diabetes Distress Scale (DDS; emotional burden and regimen-related distress subscales only); three items assessing feelings of freedom and flexibility; and one item assessing sleep quality (hours of restful sleep). Patients rated each item for their previous basal insulin and currently while using IDeg. Correlations between sleep quality and the other QoL scales were also assessed. RESULTS: In total, 152 patients completed the survey and were included in the study sample. Patients reported significantly improved scores while using IDeg on all WHO-5, DDS, HABS, feelings of freedom and flexibility item scores, and total raw/mean subscale scores (P < 0.0001). Patients also reported a significantly greater number of hours of restful sleep [mean (SD) 6.6 (2.0) vs. 5.5 (1.8); P < 0.0001]. Better sleep quality statistically significantly correlated with improved QoL in all other domains assessed. CONCLUSIONS: Treatment with IDeg after switching from a previous basal insulin was associated with statistically significant improvements in all QoL domains assessed.

Assessing Prevalence of Hypoglycemia in a Medical Transcription Database.

PURPOSE: The prevalence of hypoglycemia in patients with diabetes mellitus is likely underreported, particularly with regard to non-severe episodes, and representative estimates require more detailed data than claims or typical electronic health record (EHR) databases provide. This study examines the prevalence of hypoglycemia as identified in a medical transcription database. PATIENTS AND METHODS: The Amplity Insights database contains medical content dictated by providers detailing patient encounters with health care professionals (HCPs) from across the United States. Natural language processing (NLP) was used to identify episodes of hypoglycemia using both symptom-based and non-symptom-based definitions of hypoglycemic events. This study examined records of 41,688 patients with type 1 diabetes mellitus and 317,399 patients with type 2 diabetes mellitus between January 1, 2016, and April 30, 2018. RESULTS: Using a non-symptom-based definition, the prevalence of hypoglycemia was 18% among patients with T1DM and 8% among patients with T2DM. These estimates show the prevalence of hypoglycemia to be 2- to 9-fold higher than the 1% to 4% prevalence estimates suggested by claims database analyses. CONCLUSION: In this exploration of a medical transcription database, the prevalence of hypoglycemia was considerably higher than what has been reported via retrospective analyses from claims and EHR databases. This analysis suggests that data sources other than claims and EHR may provide a more in-depth look into discrepancies between the mention of hypoglycemia events during a health care visit and documentation of hypoglycemia in patient records.

CHANGING TO BASAL-BOLUS INSULIN THERAPY FOR THE INPATIENT MANAGEMENT OF HYPERGLYCEMIA-A NATURAL EXPERIMENT.

Objective: Most acute-care hospitals have transitioned from sliding-scale to basal-bolus insulin therapy to manage hyperglycemia during hospitalization, but there is limited scientific evidence demonstrating better short-term clinical outcomes using the latter approach. The present study sought to determine if using basal-bolus insulin therapy favorably affects these outcomes in noncritical care settings and, if so, whether the magnitude of benefit differs in patients with known versus newly diagnosed type 2 diabetes. Methods: This natural experiment compared outcomes in 10,120 non-critically ill adults with type 2 diabetes admitted to an academic teaching hospital before and after hospital-wide implementation of a basal-bolus insulin therapy protocol. A group of 30,271 inpatients without diabetes (type 1 or 2) served as controls. Binomial models were used to compare percentages of patients with type 2 diabetes who were transferred to intensive care, experienced complications, or died in the hospital before and after implementation of the protocol, controlling for changes in the control group. The analysis also evaluated before-after changes in length of stay and glucometric indicators. Results: Implementation of basal-bolus therapy did not reduce intensive care use (the primary outcome), complications, mortality, or median length of stay, except in patients with newly diagnosed diabetes (n = 234), who experienced a statistically significant decline in the incidence of complications (P<.01). The absence of effect in previously diagnosed patients was observed in spite of a 32% decline (from 3.7% to 2.5%) in the proportion of inpatient days with hypoglycemia <70 mg/dL (P<.01) and a 16% decline (from 13.5% to 11.3%) in the proportion of days with hyperglycemia >300 mg/dL (P<.01). Conclusion: Despite achieving significant reductions in both hyperglycemia and hypoglycemia, use of basal-bolus insulin therapy to manage hyperglycemia in non-critically ill hospitalized patients did not improve short-term clinical outcomes, except in the small minority of patients with newly diagnosed diabetes. The optimal management of hyperglycemia for improving these outcomes has yet to be determined. Abbreviation: ICD-9 = International Classification of Diseases-Ninth Revision.

Fishing Quotas, Induced Allee Effect, and Fluctuation-Driven Extinction.

We explore the potential of modifications to standard fishery models (for example Gordon-Schafer-Munro) to help understand events such as the collapse of the North Atlantic cod fishery. In particular we find that quota-driven and similar harvesting strategies induce an effective strong Allee effect (collapse if the population falls below a critical level). In the presence of environmental noise, fish population dynamics is similar to a random walk with (non-linear) drift. The expected survival time (first passage time to collapse) is shown to depend sensitively upon the amount of environmental noise and size of the 'safe zone' between the deterministic steady state population and the critical population level at which the system collapses; more precisely it is exponential in the cube of the size of the safe zone divided by the variance of the noise process. Similar scaling can be expected for more survival in more general systems with multiple steady states. Our calculations imply an amplification effect under which small increases in harvest yield large decreases in expected survival time, and one should be cautious in changes in harvesting, especially in fisheries with poor or limited data and fisheries affected by climate change.

ß-Cell death is decreased in women with gestational diabetes mellitus.

BACKGROUND: Gestational diabetes mellitus (GDM) affects approximately 7-17 % of all pregnancies and has been recognized as a significant risk factor to neonatal and maternal health. Postpartum, GDM significantly increases the likelihood of developing type 2 diabetes (T2D). While it is well established that insulin resistance and impaired ß-cell function contribute to GDM development, the role of active ß-cell loss remains unknown. Differentially methylated circulating free DNA (cfDNA) is a minimally invasive biomarker of ß-cell loss in type 1 diabetes mellitus. Here we use cfDNA to examine the levels of ß-cell death in women with GDM. METHODS: Second to third-trimester pregnant women with GDM were compared with women with normal pregnancy (PRG), women at postpartum (PP), and non-pregnant (NP) women. Fasting glucose levels, insulin, and C-peptide levels were measured. Serum samples were collected and cfDNA purified and bisulfite treated. Methylation-sensitive probes capable of differentiating between ß-cell-derived DNA (demethylated) and non-ß-cell-derived DNA (methylated) were used to measure the presence of ß-cell loss in the blood. RESULTS: GDM was associated with elevated fasting glucose levels (GDM = 185.9 ± 5.0 mg/dL) and reduced fasting insulin and c-peptide levels when compared with NP group. Interestingly, ß-cell derived insulin DNA levels were significantly lower in women with GDM when compared with PRG, NP, and PP groups (demethylation index: PRG = 7.74 × 10(-3) ± 3.09 × 10(-3), GDM = 1.01 × 10(-3) ± 5.86 × 10(-4), p < 0.04; NP = 4.53 × 10(-3) ± 1.62 × 10(-3), PP = 3.24 × 10(-3) ± 1.78 × 10(-3)). CONCLUSIONS: These results demonstrate that ß-cell death is reduced in women with GDM. This reduction is associated with impaired insulin production and hyperglycemia, suggesting that ß-cell death does not contribute to GDM during the 2nd and 3rd trimester of pregnancy.

Pitfalls in hemoglobin A1c measurement: when results may be misleading.

Since the beginning of clinical use in the 1970s, hemoglobin A1c (A1c) has become the standard tool for monitoring glycemic control in patients with diabetes. The role of the A1c test was broadened in 2010, when the American Diabetes Association added A1c as a diagnostic criterion for diabetes. Because of hemoglobin A1c's integral role in diagnosis and treatment, it is important to recognize clinical scenarios and interfering factors that yield false results. The purpose of this review is to describe the A1c measurement, outline clinical scenarios or factors that may yield false results, and describe alternative laboratory biomarkers.

Spatial effects and turing instabilities in the invasive species model.

This paper demonstrates that a recently proposed dynamical model for the ecology of Easter Island admits periodic and chaotic attractors, not previously reported. Such behavior may more realistically depict the population dynamics of general ecosystems and illustrates the power of simple models to produce the kind of complex behavior that is ubiquitous in such systems.

Familial recurrent atrial myxoma: Carney's complex.

We report on a family of 4 members, all of whom have had multifocal, recurrent atrial myxomas associated with skin pigmentation, melanotic schwannomas, mucocutaneous myxomas, and tumors of the ovary and pituitary, adrenal, and thyroid glands. Immunochemistry of the myxoma cells is positive for calretinin, confirming their neuroendocrine origin. Genetic studies confirmed mutations in the gene coding protein kinase A, regulatory subunit 1-α (PRKAR1α). This is Carney's complex, characterized by multiple, mucocutaneous myxomas; pigmented lesions over the lips, conjunctiva, and genitalia; adenomas of the breast and thyroid; schwannomas; and endocrinal abnormalities including Cushing syndrome and acromegaly. Members of the family require vigorous screening, including urinary free cortisol, plasma transforming growth factor-ß(1) and thyrotropin-releasing hormone, testicular ultrasound, routine echocardiographic screening, searches for cardiac and mucocutaneous myxomas in multiple locations, and genetic studies for the PRKAR1α gene sequence.

Rat instigated human population collapse on easter island.

In this paper we develop an invasive species differential equations model for the population collapse on Easter Island. This model, motivated by recent archaeological results of T. Hunt, allows us to examine the role of rats in the collapse. In Hunt's theory, the decline of resources was accelerated by Polynesian rats and not merely the result of the overuse by the island's human population. Hunt uses archaeological data which suggests a different timeline for the settlement and the long term population dynamics of Easter Island. Our goal is to estimate the plausibility of Hunt's hypothesis.

Dynamics of a discrete population model for extinction and sustainability in ancient civilizations.

We analyze a discrete version of a recently developed ratio dependent population-resource model. This model has been used to study the decline of the human and resource populations on Easter Island and the chaotic dynamics of moose and wolf populations in Canada. The dynamical system exhibits a rich behavior of fractal basins of attraction and a Neimark-Sacker bifurcation route to chaos. The model consists of a coupled pair of logistic equations, with the carrying capacity for the predators proportional to the number of prey.