Dasiglucagon demonstrates reduced costs in the treatment of severe hypoglycemia in a budget impact model.

BACKGROUND: Approximately 7.3 million people with type 1 or type 2 diabetes (T1D/T2D) are treated with insulin, placing them at higher risk of severe hypoglycemia (SH). SH requires assistance of another individual and often necessitates the prompt administration of intravenous glucose, injectable glucagon, or both. Untreated, SH can progress to unconsciousness, seizures, coma, or death. Before 2018, all glucagon rescue treatments required reconstitution. The complexity of reconstitution is often a barrier to successful administration during a severe hypoglycemic event. Studies suggest successful administration of glucagon emergency kits range from 6%-56% of the time. Second-generation glucagon treatments and glucagon analogs do not require reconstitution and have caregiver administration success rates ranging from 94%-100%. Dasiglucagon is a glucagon analog administered via autoinjector or prefilled syringe and has been shown to result in rapid hypoglycemia recovery. Moreover, the autoinjector can be administered successfully 94% of the time by trained caregivers. Previous evaluation of costs in budget impact models (BIMs) demonstrated the potential for second-generation glucagon treatments to reduce the cost of SH events (SHEs). The current model expands on those findings with a treatment pathway and accompanying assumptions reflecting important aspects of real-world SHE treatment. OBJECTIVE: To evaluate the economic impact of dasiglucagon compared with available glucagon treatments for SHE management, considering direct cost of treatment and health care resource utilization. METHODS: A 1-year BIM with a hypothetical US commercial health plan of 1 million lives was developed with a target population of individuals with diabetes at risk of SHE. The treatment pathway model included initial and secondary treatment attempts, treatment administration success and failure, plasma glucose (PG) recovery within 15 minutes, emergency medical services, emergency department (ED) visits, and hospitalizations. A 1-way sensitivity analysis was conducted to assess the sensitivity of the model to changes in parameter values. RESULTS: In a 1 million-covered lives population, it was estimated that 12,006 SHEs would occur annually. The higher rate of initial treatment success and PG recovery within 15 minutes associated with dasiglucagon treatment resulted in lower total health care costs. Total SHE treatment costs with dasiglucagon were estimated at $13.4 million, compared with $16.7 million for injectable native glucagon, $20.7 million for nasal glucagon, $35.3 million for reconstituted glucagon, and $43.8 million for untreated individuals. Compared with untreated people, the number needed to treat (NNT) with dasiglucagon was 6 individuals to avoid 1 hospitalization. NNT for this same comparison was 59 for injectable native glucagon and 27 for nasal glucagon. CONCLUSIONS: Treatment of SH with dasiglucagon decreased total direct medical costs by reducing health care resource utilization (emergency calls, emergency transports, ED visits, and hospitalizations) and accompanying costs associated with the treatment of SH. DISCLOSURES: This research was funded by Zealand Pharma. Bromley, Hinahara, and Goss are employed by Boston Healthcare Associates, Inc., which received funding from Zealand Pharma for development of the health economic model and the manuscript. Kendall and Hammer are employed by Zealand Pharma. Weinzimer has received consulting fees from Zealand Pharma.

Congenital hyperinsulinism in infancy and childhood: challenges, unmet needs and the perspective of patients and families.

BACKGROUND: Congenital hyperinsulinism (CHI) is the most common cause of persistent hypoglycemia in infants and children, and carries a considerable risk of neurological damage and developmental delays if diagnosis and treatment are delayed. Despite rapid advances in diagnosis and management, long-term developmental outcomes have not significantly improved in the past years. CHI remains a disease that is associated with significant morbidity, and psychosocial and financial burden for affected families, especially concerning the need for constant blood glucose monitoring throughout patients' lives. RESULTS: In this review, we discuss the key clinical challenges and unmet needs, and present insights on patients' and families' perspective on their daily life with CHI. Prevention of neurocognitive impairment and successful management of patients with CHI largely depend on early diagnosis and effective treatment by a multidisciplinary team of specialists with experience in the disease. CONCLUSIONS: To ensure the best outcomes for patients and their families, improvements in effective screening and treatment, and accelerated referral to specialized centers need to be implemented. There is a need to develop a wider range of centers of excellence and networks of specialized care to optimize the best outcomes both for patients and for clinicians. Awareness of the presentation and the risks of CHI has to be raised across all professions involved in the care of newborns and infants. For many patients, the limited treatment options currently available are insufficient to manage the disease effectively, and they are associated with a range of adverse events. New therapies would benefit all patients, even those that are relatively stable on current treatments, by reducing the need for constant blood glucose monitoring and facilitating a personalized approach to treatment.

Congenital hyperinsulinism (CHI) is a rare disease that causes newborn babies and children to have low blood sugar because of the abnormal release of insulin. Insulin is a hormone produced by the pancreas that promotes the transfer of sugar from the blood into the body's cells. In a healthy person, insulin is released only after a meal when the level of blood sugar is high, but infants and children with CHI make insulin even if the blood sugar is low. This can lead to dangerously low blood sugar levels, which can cause brain damage if left untreated. Unfortunately, diagnosis and treatment are often delayed, resulting in avoidable brain damage and developmental delays in these children. CHI is associated with substantial stress and anxiety for the families, especially due to the need for frequent feeding and the fear of low blood sugars added to the constant need to measure blood sugar levels. This article discusses the most important challenges and unmet needs in this rare disease, including the limited treatment options, the side effects of available treatment options and the heavy psychological, social and financial burden on affected families. Effective screening of newborns for CHI needs to be improved, and quick referral to specialized treatment centers is necessary to ensure the best outcomes for patients and families. In addition, awareness of CHI has to be raised in all medical professions caring for newborns and infants, and new medications are urgently needed to ensure the best possible treatment for all patients with CHI.

A Comparative Study of Dasiglucagon Ready-to-Use Autoinjector and Glucagon Emergency Kit During Rescue from Simulated Severe Hypoglycemia.

Background: Severe hypoglycemic episodes are life-threatening events demanding rapid administration of glucagon by a caregiver or bystander. The glucagon analog dasiglucagon is stable in aqueous formulation and therefore suitable for delivery in a ready-to-use autoinjector, potentially increasing speed and ease of use compared with standard glucagon emergency kits (GEKs). Methods: In an open label, randomized, crossover, comparative device handling study, trained caregivers and untrained bystanders administered the dasiglucagon autoinjector or Eli Lilly GEK to manikins in a simulated emergency hypoglycemia situation. Results: In total, 54 participants were randomized (18 patient-caregiver pairs and 18 bystanders). Overall, 94% of trained caregivers were able to administer the dasiglucagon autoinjector successfully within 15 min, compared with 56% for the GEK (P < 0.05). A greater proportion of trained caregivers and untrained bystanders successfully prepared and administered the dasiglucagon autoinjector within 2 min compared with the GEK (P < 0.005 and P < 0.05, respectively). Time to successful completion was also significantly faster with the dasiglucagon autoinjector than with the GEK (P < 0.005 for both groups). Most study participants preferred the dasiglucagon autoinjector over the GEK (94%, P < 0.001) and rated it as easier (90%, P < 0.001) and less stressful to use (94%, P < 0.001) than the GEK. Conclusion: Dasiglucagon autoinjector was more rapidly and reliably administered, and users reported greater ease of use and usage satisfaction than with the GEK. Thus, dasiglucagon autoinjector has the potential to improve speed and ease of treatment in severe hypoglycemic events, providing a better usage experience for rescuing individuals and enabling faster recovery for patients.

Strengthening pharma's contract with society: the value of trusted partnerships between pharma and healthcare facilitated by real-world data.

This White Paper is authored by 11 industry real-world evidence (RWE) experts, with support from IQVIA, as part of the 'RWE Leadership Forum': a group of industry leaders who come together as noncompetitive partners to understand and respond to internal or external RWD/E challenges and opportunities with a single expert voice. Herein we aim to clarify the rules of engagement between pharma and healthcare in order to establish trust-based partnerships, which will unlock unique value for society, including the medical community and the ultimate beneficiary, the patient.

Association of obesity with healthcare resource utilization and costs in a commercial population.

OBJECTIVE: To examine the association of obesity with healthcare resource utilization (HRU) and costs among commercially insured individuals. METHODS: This retrospective observational cohort study used administrative claims from 1 January 2007 to 1 December 2013. The ICD-9-CM status codes (V85 hierarchy) from 2008 to 2012 classified body mass index (BMI) into the World Health Organizations' BMI categories. The date of first observed BMI code was defined as the index date and continuous eligibility for one year pre- and post- index date was ensured. Post-index claims determined individuals' HRU and costs. Sampling weights developed using the entropy balance method and National Health and Nutrition Examination Survey data ensured representation of the US adult commercially insured population. Baseline characteristics were described across BMI classes and associations between BMI categories, and outcomes were examined using multivariable regression. RESULTS: The cohort included 9651 individuals with BMI V85 codes. After weighting, the BMI distribution was: normal (31.1%), overweight (33.4%), obese class I (22.0%), obese class II (8.1%) and obese class III (5.4%). Increasing BMI was associated with greater prevalence of cardiometabolic conditions, including hypertension, type 2 diabetes and metabolic syndrome. The use of antihypertensives, antihyperlipidemics, antidiabetics, analgesics and antidepressants rose with increasing BMI. Greater BMI level was associated with increased inpatient, emergency department and outpatient utilization, and higher total healthcare, medical and pharmacy costs. CONCLUSIONS: Increasing BMI was associated with higher prevalence of cardiometabolic conditions and higher HRU and costs. There is an urgent need to address the epidemic of obesity and its clinical and economic impacts.

Association of obesity with healthcare utilization and costs in a Medicare population.

OBJECTIVES: To examine the association of obesity with healthcare resource utilization and costs in a Medicare population. METHODS: This study was a retrospective cohort study using Humana Medicare Advantage (MA) claims data. Body mass index (BMI) was assessed using ICD-9-CM status codes (V85 hierarchy) that have been validated in the data source to classify patients into BMI categories: normal (N), overweight (Ow), obese class I (ObI), obese class II (ObII), and obese class III (ObIII). Healthcare resource utilization (HRU) and costs were determined based on claims data. Descriptive statistics were used to examine baseline characteristics and HRU across BMI classes. Multivariable analysis was used to examine the association between BMI class and outcome measures. RESULTS: Among the 172,866 patients aged ≥65 years that were identified, BMI distribution was: N, 21%; Ow 37%; ObI, 24%, ObII, 10%; and ObIII, 9%. Inpatient, emergency department and outpatient utilization increased with greater BMI level, and greater BMI level was associated with higher total healthcare, medical and pharmacy costs. Greater prevalence of several cardiometabolic conditions, total medication use, and use of specific medication classes was observed with increasing BMI class. CONCLUSIONS: Greater BMI was associated with greater HRU and costs and observed increase in prevalence of cardiometabolic conditions. These results reflect an urgent need to address the epidemic of obesity and the resulting excessive clinical and economic burden on the healthcare system.

Predictors of glycemic control and diabetes-related costs among type 2 diabetes patients initiating therapy with liraglutide in the United States.

OBJECTIVE: Liraglutide has been shown to significantly improve glycemic control and reduce body weight while minimizing the risk of hypoglycemia in adult patients with type 2 diabetes (T2D). This study aimed to identify characteristics that predict clinical and economic outcomes associated with liraglutide therapy in clinical practice in the US. METHODS: Using the Truven Health MarketScan Laboratory Database, glycemic control (A1C <7%) and diabetes-related costs were evaluated in T2D patients initiating liraglutide between January 1, 2010 and June 30, 2012. Patients were required to have ≥1 post-index claim for liraglutide and A1C values at baseline and 6 months follow-up. All valid values of baseline A1C were included. Patients previously treated with GLP-1 receptor agonist(s) or insulin, or with evidence of type 1 diabetes, pregnancy, or gestational diabetes during the study period were excluded. Multivariable regression models were used to identify predictors of glycemic control and diabetes-related costs. RESULTS: Of 417 patients newly treated with liraglutide, 54.0% achieved glycemic control (A1C <7%) during follow-up. Factors associated with increased odds of glycemic control during follow-up were: being female, POS/EPO health plan type, baseline A1C, early liraglutide initiation (0-1 prior oral anti diabetics [OADs] vs ≥2), adherence to liraglutide (defined as the proportion of days covered [PDC]), and diabetic retinopathy. Being female, earlier liraglutide initiation (0-1 prior OADs), and higher patient share of liraglutide costs were associated with significantly lower diabetes-related costs during follow-up. Factors associated with significantly higher post-index diabetes-related costs were: higher baseline A1C, baseline use of sulfonylureas, and diabetic retinopathy. CONCLUSIONS: Within this commercially-insured population of T2D patients treated with liraglutide, gender, baseline A1C, early liraglutide initiation (0-1 prior OADs), diabetic retinopathy, better adherence, and patient share of liraglutide costs were associated with increased odds of achieving glycemic control and the odds of having higher or lower diabetes-related costs.

The Association Between Body Mass Index and Health and Economic Outcomes in the United States.

OBJECTIVE: The objective of this study is to provide current estimates of the association between obesity and health outcomes and to examine these associations among subgroups of interest (pre-diabetes, type 2 diabetes [T2D], and neither pre-diabetes nor T2D) in the United States. METHODS: Data were analyzed from the 2013 US National Health and Wellness Survey (N = 71,530). Respondents were categorized by body mass index (BMI) class (normal, overweight, obese class I, obese class II, obese class III). RESULTS: As BMI increased, health status decreased significantly (and to a clinically relevant degree) for respondents categorized as obese compared with normal weight. Work productivity impairment, physician visits, emergency room visits, and costs also increased significantly as BMI increased. The pattern of results was similar across the three subgroups. CONCLUSIONS: Increasing BMI was associated with decreasing health status and increasing work-related impairment, healthcare resource utilization, and costs.

Reporting error in weight and its implications for bias in economic models.

Most research on the economic consequences of obesity uses data on self-reported weight, which contains reporting error that has the potential to bias coefficient estimates in economic models. The purpose of this paper is to measure the extent and characteristics of reporting error in weight, and to examine its impact on regression coefficients in models of the healthcare consequences of obesity. We analyze data from the National Health and Nutrition Examination Survey (NHANES) for 2003-2010, which includes both self-reports and measurements of weight and height. We find that reporting error in weight is non-classical: underweight respondents tend to overreport, and overweight and obese respondents tend to underreport, their weight, with underreporting increasing in measured weight. This error results in roughly 1 out of 7 obese individuals being misclassified as non-obese. Reporting error is also correlated with other common regressors in economic models, such as education. Although it is a common misconception that reporting error always causes attenuation bias, comparisons of models that use self-reported and measured weight confirm that reporting error can cause upward bias in coefficient estimates. For example, use of self-reports leads to overestimates of the probability that an obese man uses a prescription drug, has a healthcare visit, or has a hospital admission. These findings underscore that models of the consequences of obesity should use measurements of weight, when available, and that social science datasets should measure weight rather than simply ask subjects to report their weight.

Prevalence and healthcare costs of obesity-related comorbidities: evidence from an electronic medical records system in the United States.

OBJECTIVE: This study estimated the economic burden of obesity-related comorbidities (ORCs) in the US, at both the person and population levels. METHODS: The Geisinger Health System provided electronic medical records and claims between January 2004 and May 2013 for a sample of 153,561 adults (50% males and 97% white). Adults with < 2 years of data, who were underweight (body mass index (BMI) < 18.5 kg/m(2)), or had diseases causing major weight change (e.g., malignancy) during the study period (i.e., continuous enrollment in health plans) were excluded. A total of 21 chronic conditions, with established association with obesity in the literature, were identified by diagnosis codes and/or lab test results. The total healthcare costs were measured in each year. The association between annual costs and ORCs was assessed by a regression, which jointly considered all the ORCs. The per-person incremental costs of a single comorbidity, without any of the other ORCs, were calculated. The population-level economic burden was the product of each ORC's incremental costs and the annual prevalence of the ORC among 100,000 individuals. The prevalence of ORCs was stratified by obesity status to estimate the economic burden among 100,000 individuals with obesity and among those without. RESULTS: This study identified 56,895 adults (mean age = 47 years; mean BMI = 29.6 kg/m(2)). The annual prevalence of ORCs ranged from 0.5% for pulmonary embolism (PE) to 41.8% for dyslipidemia. The per-person annual incremental costs of a single ORC ranged from $120 for angina to $1665 for PE. Hypertensive diseases (HTND), dyslipidemia, and osteoarthritis were the three most expensive ORCs at the population level; each responsible for ≥$18 million annually among 100,000 individuals. HTND and osteoarthritis were much more costly among individuals with obesity than those without obesity. LIMITATIONS: Data were from a small geographic region. CONCLUSIONS: ORCs are associated with substantial economic burden, especially for those requiring continuous treatments.

Impact of medication adherence and persistence on clinical and economic outcomes in patients with type 2 diabetes treated with liraglutide: a retrospective cohort study.

INTRODUCTION: Adherence to diabetes medication has been linked to improved glycemic levels and lower costs, but previous research on adherence has typically involved oral antidiabetic medication or insulin. This study examines how adherence and persistence to once-daily liraglutide impact glycemic control and economic outcomes in a real-world population of adult type 2 diabetes (T2D) patients. METHODS: A retrospective cohort study using administrative claims data from July 2009 through September 2013. Patients aged ≥18 years with T2D treated with liraglutide were identified (index date = first liraglutide prescription). Adherence was based on the proportion of days covered (PDC); with PDC ≥0.80 classified as adherent. Non-persistent patients were those with a gap in therapy of >90 days. Lab results for glycated hemoglobin (A1C) were used to identify whether patients achieved target levels of <7.0% and ≤ 6.5%, or experienced a reduction of ≥1.0% in A1C from pre-index (baseline) to post-index (follow-up). Logistic regression was used to estimate the likelihood of achieving the A1C goals, adjusted for baseline characteristics. Diabetes-related medical, pharmacy, and total costs were modeled and estimated for the adherence and persistence cohorts. RESULTS: A total of 1321 patients were identified. The mean PDC was 0.59 and 34% of patients were classified as adherent, while 60% were persistent over 12 months of follow-up. Adherent and persistent patients were more likely to achieve each of the A1C goals than their non-adherent and non-persistent counterparts after adjusting for patient characteristics. Adherence and persistence were associated with higher adjusted diabetes-related pharmacy and total healthcare costs during follow-up; whereas persistent patients had significantly lower diabetes-related medical costs than non-persistent patients. CONCLUSIONS: Adherence and persistence to liraglutide are associated with improved A1C outcomes. Persistent patients showed significantly lower medical costs versus those discontinuing liraglutide. Total healthcare costs were higher for adherent and persistent cohorts driven by higher pharmacy costs.

The Economic Burden of Obesity by Glycemic Stage in the United States.

BACKGROUND: Electronic medical records and insurance claims data from the Geisinger Health System were examined to assess the real-world healthcare costs of being overweight or obese at different glycemic stages, including normal glycemia, pre-diabetes (PreD), and type 2 diabetes (T2D). METHODS: The medical history of the sample subjects was segmented into different glycemic stages via diagnosis codes, glycosylated hemoglobin A1c or fasting plasma glucose laboratory results, and use of antidiabetic drugs. Healthcare resource utilization captured by the claims and associated costs (in 2013 values) were examined for each glycemic stage. The association between costs and body mass index (BMI) was estimated by regressions, and adjusted for sociodemographics. We predicted the adjusted incremental annual costs associated with high BMI, relative to normal BMI (18.5-24.9 kg/m(2)). RESULTS: We identified 48,344 adults in normal glycemic stage, 3,085 in the PreD stage, and 9,526 in the T2D stage (mean age 46, 58, and 60 years, respectively; mean BMI 29, 32, and 33 kg/m(2), respectively). The adjusted incremental annual costs associated with high BMI relative to normal BMI ranged from $336 for overweight (25-29.9 kg/m(2)) to $1,850 for class III obesity (≥40 kg/m(2)) during normal glycemic stage; were only significant for class III ($2,434) during the PreD stage; and ranged from $1,139 for overweight to $4,649 for class III during the T2D stage (all p < 0.05). CONCLUSIONS: Positive associations between healthcare costs and BMI levels were observed within each glycemic stage. Management of body weight is important in reducing the overall healthcare costs, especially for subjects with PreD or T2D.

Variation in the risk of progression between glycemic stages across different levels of body mass index: evidence from a United States electronic health records system.

OBJECTIVE: The purpose of this study was to assess how the risks of glycemic stage transitions observed in clinical practice vary with body mass index (BMI). These transitions included progression from euglycemia ('normal') to prediabetes (PreD) and from PreD to type 2 diabetes (T2D), as well as from normal directly to T2D, and reversions from PreD to normal. METHODS: We examined the Geisinger Health System electronic health records and insurance claims data, segmenting a subject's medical history into normal, PreD, and/or T2D glycemic stages via diagnosis codes, glycosylated hemoglobin A1c (HbA1c) or fasting plasma glucose lab results, and use of anti-diabetic drugs. Weibull survival models, adjusted for age, gender, race, and smoking, were used to estimate the glycemic progression hazard ratios for BMI categories relative to normal BMI. RESULTS: The sample included 32,864 adults with normal glycemic levels at baseline and 4483 with PreD. The adjusted hazard ratios for normal to PreD progression ranged from 1.8 (25 ≤ BMI < 30 kg/m(2)) to 6.5 (BMI ≥ 40 kg/m(2)); for PreD to T2D, 1.3 to 2.9; for normal to T2D, 1.8 to 9.5; and for PreD to normal, ∼0.7 across all BMI. LIMITATIONS: The glycemic transitions may be recognized after the true onset since periodic glycemic testing was not required across the study population. CONCLUSIONS: A positive association between the risks of progression along the glycemic continuum and BMI levels was observed in a real-world United States practice setting.

Savings in Medical Expenditures Associated with Reductions in Body Mass Index Among US Adults with Obesity, by Diabetes Status.

BACKGROUND: The prevalence of obesity has more than doubled in the USA in the past 30 years. Obesity is a significant risk factor for diabetes, cardiovascular disease, and other clinically significant co-morbidities. This paper estimates the medical care cost savings that can be achieved from a given amount of weight loss by people with different starting values of body mass index (BMI), for those with and without diabetes. This information is an important input into analyses of the cost effectiveness of obesity treatments and prevention programs. METHODS: Two-part models of instrumental variables were estimated using data from the Medical Expenditure Panel Survey (MEPS) for 2000-2010. Models were estimated for all adults as well as separately for those with and without diabetes. We calculated the causal impact of changes in BMI on medical care expenditures, cost savings for specific changes in BMI (5, 10, 15, and 20 %) from starting BMI levels ranging from 30 to 45 kg/m(2), as well as the total excess medical care expenditures caused by obesity. RESULTS: In the USA, adult obesity raised annual medical care costs by $US3,508 per obese individual, for a nationwide total of $US315.8 billion (year 2010 values). However, the relationship of medical care costs over BMI is J-shaped; costs rise exponentially in the range of class 2 and 3 obesity (BMI ≥35). The heavier the obese individual, the greater the reduction in medical care costs associated with a given percent reduction in BMI. Medical care expenditures are higher, and rise more with BMI, among individuals with diabetes than among those without diabetes. CONCLUSIONS: The savings from a given percent reduction in BMI are greater the heavier the obese individual, and are greater for those with diabetes than for those without diabetes. The results provide health insurers, employers, government agencies, and health economists with accurate estimates of the change in medical care expenditures resulting from weight loss, which is important information for calculating the cost effectiveness of interventions to prevent and treat obesity.

Real-world clinical and economic outcomes of liraglutide versus sitagliptin in patients with type 2 diabetes mellitus in the United States.

INTRODUCTION: The objective of this study was to compare the clinical effectiveness of liraglutide with sitagliptin and assess the associated economic outcomes in patients with type 2 diabetes mellitus (T2DM) treated in real-world practice in the United States (US). METHODS: This retrospective cohort study used a large US claims database to identify patients with T2DM who initiated liraglutide or sitagliptin between January 2010 and December 2012. Adults (≥18 years old) with persistent use of therapy for ≥3 months were included. Changes in glycated hemoglobin A1c (A1C) and the proportion of patients achieving A1C targets (≤6.5% and <7%) were examined at 6-month follow-up. Diabetes-related total, medical, and pharmacy costs over the follow-up period were assessed. Multivariable regression models were used to estimate the outcomes associated with liraglutide relative to sitagliptin, adjusting for differences in patient demographics and clinical characteristics. RESULTS: The study included 1,465 patients with T2DM who initiated liraglutide (N = 376) or sitagliptin (N = 1,089) (mean age [standard deviation (SD)]: 54 [8.9] vs. 58 [10.8] years; 43.9% vs. 61.8% males; both P < 0.01). After controlling for confounding factors, liraglutide patients experienced 0.31% points greater reduction in A1C (0.95% vs. 0.63% points; P < 0.01) at 6-month follow-up than sitagliptin patients and were more likely to reach A1C targets of ≤6.5% (odds ratio [OR]: 2.00; P < 0.01) and <7% (OR: 1.55; P < 0.01). Liraglutide patients had $994 lower mean diabetes-related medical costs ($1,241 vs. $2,235; P < 0.01), but $544 higher diabetes-related pharmacy costs ($2,100 vs. $1,556; P < 0.01) during the follow-up. No difference was found in the total mean diabetes-related costs between the two cohorts. CONCLUSION: Liraglutide showed greater improvement in glycemic outcomes than sitagliptin among adult patients with T2DM in real-world clinical practice. Although diabetes-related pharmacy costs for patients using liraglutide were higher compared with sitagliptin, these were offset by significantly lower diabetes-related medical costs, resulting in similar total diabetes-related costs between the two treatment groups.

Clinical effectiveness of liraglutide across body mass index in patients with type 2 diabetes in the United States: a retrospective cohort study.

INTRODUCTION: Clinical trials have shown that liraglutide effectively lowers glycated hemoglobin A1c (A1C) levels in adult patients with type 2 diabetes (T2D). However, no studies have evaluated the effectiveness of liraglutide by body mass index (BMI) in the United States (US) in clinical practice. This study examined liraglutide's clinical effectiveness to lower A1C and body weight after 6 months in T2D patients stratified by baseline BMI. METHODS: This was a retrospective cohort study using the General Electric Centricity electronic medical records database. Adult patients with T2D (≥18 years and BMI≥ 25 kg/m(2)) and A1C >7% at baseline who started liraglutide between January 1, 2010 and January 31, 2013 and who did not use insulin or a glucagon-like peptide-1 analog 12 months before initiating liraglutide (N = 3,005) were selected. Changes from baseline, stratified by BMI, in A1C, body weight, A1C <7% goal attainment, and incidence of severe hypoglycemia at 6-month follow-up were examined. RESULTS: After 6 months, A1C levels decreased on average by 0.95%, 1.02%, 0.99%, and 0.84% for BMI categories 25.0-29.9 (n = 333), 30.0-34.9 (n = 793), 35.0-39.9 (n = 821), and ≥40.0 kg/m(2) (n = 1,058), respectively (P = 0.30). The proportions of patients achieving A1C <7% at 6 months were 38.2%, 37.0%, 40.9%, and 41.0% (P = 0.54). The absolute body weight decreased by 1.5 to 4.0 kg across BMI and the rate of severe hypoglycemia (0.2%) was low. CONCLUSION: Patients with T2D experienced statistically significant decreases in A1C and body weight after initiating liraglutide regardless of their BMI. Liraglutide reduced A1C equally well across baseline BMI in clinical practice in the US.

The association of body mass index with the risk of type 2 diabetes: a case-control study nested in an electronic health records system in the United States.

OBJECTIVES: Obesity is a known risk factor for type 2 diabetes (T2D). We conducted a case-control study to assess the association between body mass index (BMI) and the risk of being diagnosed with T2D in the United States. METHODS: We selected adults (≥ 18 years old) who were diagnosed with T2D (defined by ICD-9-CM diagnosis codes or use of anti-diabetic medications) between January 2004 and October 2011 ("cases") from an electronic health records database provided by an integrated health system in the Middle Atlantic region. Twice as many individuals enrolled in the health system without a T2D diagnosis during the study period ("controls") were selected based on age, sex, history of cardiac comorbidities or hyperinflammatory state (defined by C-reactive protein and erythrocyte sedimentation rate), and use of psychiatric or beta blocker medications. BMI was measured during one year prior to the first observed T2D diagnosis (for cases) or a randomly assigned date (for controls); individuals with no BMI measure or BMI < 18.5 kg/m2 were excluded. We assessed the impact of increased BMI (overweight: 25-29.9 kg/m2; Obesity Class I: 30-34.9 kg/m2; Obesity Class II: 35-39.9 kg/m2; Obesity Class III: ≥40 kg/m2), relative to normal BMI (18.5-24.9 kg/m2), on a T2D diagnosis using odds ratios (OR) and relative risks (RR) estimated from multiple logistic regression results. RESULTS: We included 12,179 cases (mean age: 55, 43% male) and 25,177 controls (mean age: 56, 45% male). We found a positive association between BMI and the risk of a T2D diagnosis. The strength of this association increased with BMI category (RR [95% confidence interval]: overweight, 1.5 [1.4-1.6]; Obesity Class I, 2.5 [2.3-2.6]; Obesity Class II, 3.6 [3.4-3.8]; Obesity Class III, 5.1 [4.7-5.5]). CONCLUSIONS: BMI is strongly and independently associated with the risk of being diagnosed with T2D. The incremental association of BMI category on the risk of T2D is stronger for people with a higher BMI relative to people with a lower BMI.

Examining the ability to detect change using the TRIM-Diabetes and TRIM-Diabetes Device measures.

PURPOSE: Responsiveness is defined as the ability of an instrument to accurately detect change when it has occurred and is an essential psychometric property of a patient-reported outcomes (PRO) measure to understand and interpret study findings. This study examined the responsiveness of 2 Treatment Related Impact Measures (TRIMs): The TRIM-Diabetes (TRIM-D) and TRIM-Diabetes Device (TRIM-DD) as well as confirmed their measurement models in a randomized controlled trial (RCT) design. METHODS: The data were collected in a multi-center, randomized, open-label (2 × 12 week), cross-over study of two prefilled pens in subjects with type 1 or type 2 diabetes, age 18 or older. Internal and external responsiveness were examined. To confirm the measurement model identified in the previous study, the Bentler comparative fit index (CFI) and internal consistency for the RCT sample scores were examined and compared. RESULTS: Based on a priori criteria, tests of responsiveness were confirmed with patients having significant improvements over time ranging from 2.7 (Psychological Health) to 11.1 (Treatment Burden) (P < 0.01) (effect sizes ranging from 0.2 to 0.8). The previous measurement model factor structure was confirmed (CFI ranging from 0.8 to 1.0), and internal consistency of the TRIMs was similar to the developmental findings. CONCLUSIONS: The total score as well as all domain scores of the TRIMs was significantly responsive over time, thus acceptable internal and external responsiveness of TRIM-D and TRIM-DD are concluded. To date, all validation evidence supports the use of these two measures in future clinical trials.

A comparison of preferences for two GLP-1 products--liraglutide and exenatide--for the treatment of type 2 diabetes.

OBJECTIVE: To use time trade-off (TTO) to compare patient preferences for profiles of two glucagon-like peptide (GLP-1) products for the treatment of type 2 diabetes (liraglutide and exenatide) that vary on four key attributes - efficacy (as measured by hemoglobin A(1C)), incidence of nausea, incidence of hypoglycemia, and dosing frequency (QD vs. BID) - and measure the contribution of those attributes to preferences. METHODS: A total of 382 people with T2DM were recruited to participate in an internet-based survey consisting of a series of health-related questions, a conjoint exercise and a set of time trade-off items. In the conjoint exercise, respondents were presented with eight pairs of hypothetical GLP-1 profiles, and completed a time-tradeoff exercise for each pair. RESULTS: The product profile representing liraglutide was preferred by 96% of respondents and resulted in significantly higher health utilities (0.038) than the product profile representing exenatide (0.978 vs. 0.94, p < 0.05). Estimated preference scores from the conjoint analysis revealed that efficacy measured by hemoglobin A(1C) is the most important attribute, followed by nausea, hypoglycemia, and dosing schedule. LIMITATIONS: On-line participants may not represent 'typical' type 2 diabetes patients, and brief product profiles represented results from clinical trials, not clinical practice CONCLUSION: Based on the four attributes presented, patients prefer liraglutide over exenatide. Preference is based on superior efficacy and less nausea more than less hypoglycemia and once-daily dosing.