Obesity and metabolic syndrome in patients with heart failure with preserved ejection fraction: a cross-sectional analysis of the Veradigm Cardiology Registry.

BACKGROUND: The proportion of heart failure patients with preserved ejection fraction has been rising over the past decades and has coincided with increases in the prevalence of obesity and metabolic syndrome. The relationship between these interconnected comorbidities and heart failure with preserved ejection fraction (HFpEF) is still poorly understood. This study characterized obesity and metabolic syndrome among real-world patients with HFpEF. METHODS: We identified adults with heart failure in the Veradigm Cardiology Registry, previously the PINNACLE Registry, with a left ventricular ejection fraction measurement ≥ 50% between 01/01/2016 and 12/31/2019. Patients were stratified by obesity diagnosis and presence of metabolic syndrome (≥ 3 of the following: diabetes, hypertension, hyperlipidemia, and obesity). We captured baseline demographic and clinical characteristics and used multivariable logistic regression to examine the odds of having cardiac (atrial fibrillation, coronary artery disease, coronary artery bypass surgery, myocardial infarction, and stroke/transient ischemic attack) and non-cardiac (chronic kidney disease, chronic liver disease, and peripheral artery disease) comorbidities of interest. The models adjusted for age and sex, and the main covariates of interest were obesity and metabolic burden score (0-3 based on the presence of diabetes, hypertension, and hyperlipidemia). The models were run with and without an obesity*metabolic burden score interaction term. RESULTS: This study included 264,571 patients with HFpEF, of whom 55.7% had obesity, 52.5% had metabolic syndrome, 42.5% had both, and 34.3% had neither. After adjusting for age, sex, and burden of other metabolic syndrome-associated diagnoses, patients with HFpEF with obesity had lower odds of a diagnosis of other evaluated comorbidities relative to patients without obesity. The presence of metabolic syndrome in HFpEF appears to increase comorbidity burden as each additional metabolic syndrome-associated diagnosis was associated with higher odds of assessed comorbidities except atrial fibrillation. CONCLUSION: Obesity was common among patients with HFpEF and not always co-occurring with metabolic syndrome. Multivariable analysis suggested that patients with obesity may develop HFpEF in the absence of other driving factors such as cardiovascular disease or metabolic syndrome.

An Economic Evaluation of the Relationship Between Glycemic Control and Total Healthcare Costs for Adults with Type 2 Diabetes: Retrospective Cohort Study.

INTRODUCTION: Glycemic control is associated with better outcomes among individuals with type 2 diabetes (T2D). This research examines total US all-cause medical costs for adults with T2D with recommended glycemic control (HbA1c < 7%) compared to poor glycemic control (HbA1c ≥ 7%). METHODS: The study used administrative claims data linked to HbA1c laboratory test results from January 1, 2015 through June 30, 2021 to identify adults with T2D with a recorded HbA1c test. Patients with recommended glycemic control at index date were propensity score matched to patients with poor glycemic control. General linear models and two-part models were used to compare all-cause outpatient, drug, acute care and total costs for 1 year post index date. RESULTS: The study included 59,830 propensity-matched individuals. Results indicate that recommended glycemic control, compared to poor glycemic control, was associated with statistically significantly lower all-cause acute care ($23,868 ± $21,776 vs. $24,352 ± $22,223), drug ($10,277 ± $14,671 vs. $10,540 ± $14,928), and total medical costs ($41,381 ± $42,757 vs. $42,054 ± $43,422) but significantly higher outpatient costs ($7290 ± $12,028 vs. $7026 ± $11,587) (all p < 0.0001). Sensitivity analyses examined results based upon alternative HbA1c thresholds of ≤ 6.5% and < 8%. Results were generally robust to alternative HbA1c thresholds, with higher HbA1c thresholds associated with higher all-cause total costs as well as increased savings for having HbA1c below threshold. CONCLUSIONS: Glycemic control was associated with significantly lower all-cause total, drug, and acute care medical costs. Given the high prevalence of T2D in the USA, our results suggest potential economic benefits associated with glycemic control for healthcare providers.

Weight management treatment modalities in patients with overweight or obesity: A retrospective cohort study of administrative claims data.

Background: The purpose of this study was to describe demographic and clinical characteristics among patients who have medical encounters for weight management treatments and to investigate the association of those characteristics with treatment modality. Methods: This was a retrospective database study using medical claims, pharmacy claims, and enrollment information from commercial and Medicare Advantage with Part D members in the Optum Research Database from 01/01/2011-2/29/2020. Adult patients with a claim for a weight management treatment from 01/01/2012-2/28/2019 were categorized into cohorts according to the highest intensity intervention received. To examine the association between patient characteristics and treatment modality received, a multinomial logit model was performed. Results: Cohorts by increasing intensity included lifestyle intervention (LSI, n = 67,679), weight reduction pharmacotherapy (WRRx) with an anti-obesity medication (AOM, n = 6,905), weight reduction procedure (WRP, n = 1,172), and weight reduction surgery (WRS, n = 18,036). Approximately 32.1% and 16.6% of patients who received WRS or WRP had an LSI during the 12-month baseline, and only 0.6% and 0.4% had treatment with long-term AOMs. In a multinomial logit model, patients with type 2 diabetes (not including WRRx cohort), respiratory disorders, cardiovascular risk factors, pain disorders, and mental health conditions had increased odds of treatment with higher intensity intervention versus LSI. Patients who were male, received an intervention more recently (2016-2019), or had a Charlson comorbidity score of 1 (compared to 0) had decreased odds of treatment with higher intensity interventions. Conclusion: In this study, age, sex, body mass index, obesity-related complications, and Charlson comorbidity score appeared to influence the type of weight management treatment modality received. This study improves understanding of weight management treatment utilization and identifies gaps and opportunities to improve obesity care with the appropriate use of different treatment modalities.

Real-world primary nonadherence to antiobesity medications.

BACKGROUND: Primary nonadherence (PNA), when a medication is newly prescribed but not filled, has been identified as a major research gap potentially impacting the optimal treatment of patients with overweight and obesity who are newly prescribed antiobesity medications (AOMs). OBJECTIVES: To assess PNA among patients with newly prescribed AOMs and to examine factors associated with PNA to AOMs. METHODS: This was a retrospective study that used the Optum Integrated Clinical plus Claims database to identify individuals who had at least 1 prescription order for an AOM the US Food and Drug Administration approved for long-term use. Individuals with prescription orders between January 1, 2012, and February 28, 2019, were identified, and patient demographics, clinical characteristics, medication prescribed, baseline health care utilization, and obesity-related complications were described by PNA status. PNA was defined as no pharmacy claim for the AOM within 60 days of the date of the new prescription order as identified in electronic health record data. A multivariable logistic regression model was used to examine factors associated with PNA. RESULTS: The study sample included a total of 1,563 patients. The mean body mass index was 38.4 kg/m2; 10.7% were prescribed liraglutide 3.0 mg, 26.0% were prescribed lorcaserin, 36.3% of patients were prescribed naltrexone-bupropion, 5.4% were prescribed orlistat, and 21.6% were prescribed phentermine-topiramate. Most patients (91.1%) exhibited PNA, with only 8.9% filling their newly prescribed AOM within 60 days. Both the adherent and nonadherent groups were predominately female sex, White, and covered by commercial insurance. The mean age was similar between the 2 groups. Most obesity-related complications were less prevalent in the adherent group, although the Charlson comorbidity index score was similar between the 2 groups. After adjustment for patient demographics and clinical characteristics, there was not a statistically significant association between the specific AOM and PNA (P = 0.299). Patients with depression or living in the Midwest or South regions were at significantly increased risk of PNA. CONCLUSIONS: The rate of PNA to AOMs was very high, suggesting barriers in effective medical management of patients with overweight and obesity. Future research is warranted to understand reasons for PNA to AOMs and how to address these barriers. DISCLOSURES: Dr Kan, Dr Bae, Dr Dunn, and Dr Ahmad are employees of Eli Lilly and Company. Ms Buysman and Dr Gronroos are employees of Optum. Dr Swindle was an employee of Optum at the time the study was conducted and is currently employed at Evidera. Dr Bengtson is employed at Boehringer Ingelheim Pharmaceuticals, Inc. (Boehringer Ingelheim has no connection to this study), and during the conduct of this study was employed at Optum.

Five-year morbidity and mortality rates in a U.S. population with obesity with and without prediabetes.

AIMS: This research examines the prevalence of morbidity and mortality among people with obesity with or without prediabetes. METHODS: This observational study uses Optum® Market Clarity deidentified data from 2007 to 2020. Individuals with obesity without prediabetes (obesity only) were matched 1:1 to adults with prediabetes plus obesity based upon age, sex, race, ethnicity, and region. Age and sex adjusted prevalence rates and 95 % CIs were calculated for morbidity and mortality for each 365-day period post index date and over the entire 5-year post-period. RESULTS: After 5-years, the adjusted mortality rate was 10.1 % for adults with obesity plus prediabetes and 6.9 % for adults with obesity only (p < 0.05). Five years post index date, the prevalence of type 2 diabetes was 25.3 % for people with obesity plus prediabetes and 9.2 % for people with obesity only (p < 0.05). Prevalence rates after 5 years for atherosclerotic cardiovascular disease (13.1 % v 8.1 %), composite cardiovascular outcome (7.0 % v 4.4 %) and composite cardio-renal outcome (8.9 % v 5.0 %) were significantly higher for adults with obesity plus prediabetes compared to adults with obesity only (all p < 0.05). CONCLUSIONS: Results of this study indicate that the presence of prediabetes contributes to the development of additional morbidity and mortality in adults with obesity.

An Early Assessment of the Real-World Treatment Patterns of Type 2 Diabetes: A Comparison to the 2018 ADA/EASD Consensus Report Recommendations.

INTRODUCTION: Using the American Diabetes Association (ADA) Hyperglycemic Pharmacotherapy Guidelines for type 2 diabetes, we evaluated the medication use patterns in real-world patients with type 2 diabetes in the USA. METHODS: Health care claims among patients with type 2 diabetes were analyzed (IBM® MarketScan® 2007 to 2019 Commercial and Medicare Databases). Diabetes treatment patterns were evaluated for the total patient sample of 580,741 during the year 2019. Prior years' claims data were used to construct patient history and determine clinical groups per the 2018 ADA/EASD consensus statement: atherosclerotic cardiovascular disease (ASCVD), chronic kidney disease (CKD), heart failure (HF), hypoglycemia (hypo), and obesity. The recommended therapy use rates (RTUR) were calculated for clinical groups. Univariate chi-square tests were performed to compare RTUR within and outside clinical groups. Multivariate logistic regression was used to identify variables associated with recommended therapy use. RESULTS: A large proportion of patients belonged to multiple clinical groups; this was more common in the Medicare cohort. Each clinical group in the Commercial cohort had a substantially higher RTUR than in the Medicare cohort. However, no clinical group achieved > 40% RTUR. The RTUR was the highest in the CKD and obesity groups in the Commercial cohort and in the hypo and obesity groups in the Medicare cohort, but lowest in hypo and HF groups in the Commercial and Medicare cohorts, respectively. CONCLUSION: Prevalence of guideline-aligned treatment use in 2019 was low, particularly since many patients fit into multiple risk groups with established treatment benefits.

A Framework for Integrating Continuous Glucose Monitor-Derived Metrics into Economic Evaluations in Type 1 Diabetes.

Economic models in type 1 diabetes have relied on a change in haemoglobin A1c as the link between the blood glucose trajectory and long-term clinical outcomes, including microvascular and macrovascular disease. The landscape has changed in the past decade with the availability of regulatory approved, accurate and convenient continuous glucose monitoring devices and their ability to track patients' glucose levels over time. The data emerging from continuous glucose monitoring have enriched the clinical understanding of the disease and indirectly of patients' behaviour. This has triggered the development of new measures proposed to better define the quality of glycaemic control, beyond haemoglobin A1c. The objective of this paper is to review recent developments in clinical knowledge brought into focus with the application of continuous glucose monitoring devices, and to discuss potential approaches to incorporate the concepts into economic models in type 1 diabetes. Based on a targeted review and a series of multidisciplinary workshops, an influence diagram was developed that captures newer concepts (e.g. continuous glucose monitoring metrics) that can be integrated into economic models and illustrates their association with more established concepts. How the additional continuous glucose monitoring-based indicators of glycaemic control may contribute to economic modelling beyond haemoglobin A1c, and more accurately reflect the economic value of novel type 1 diabetes treatments, is discussed.

Type 2 diabetes pharmacotherapy trends in high-risk subgroups.

Medication use trends among patients with type 2 diabetes from 2015 to 2019 were investigated in relation to the clinical group-specific recommendations from the 2018 American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) consensus report. Data were drawn from a large health insurance claims database representing Commercial (total patient-year count: 2,379,704) and Medicare (total patient-year count: 845,823) insurance programmes (IBM® MarketScan®). The utilization of sodium-glucose co-transporter-2 inhibitors or glucagon-like peptide-1 receptor agonists increased over time but was lower in the Medicare cohort in every year evaluated. Patients diagnosed with obesity received recommended therapies at higher rates than those without obesity. Differences were more modest between those with versus without atherosclerotic cardiovascular disease (ASCVD) or chronic kidney disease, with greater treatment adoption in those without ASCVD in the Medicare cohort. Utilization of recommended treatments was paradoxically lower in those with versus without heart failure, and worse in the Medicare than in the Commercial cohort. Utilization of sulphonylureas was not different in those with versus without severe hypoglycaemia history. In conclusion, utilization of therapies recommended in the guidelines is increasing overall, which is not preferentially guided by ADA/EASD-defined clinical groups, and there exists a persistent gap in utilization between Commercial and Medicare populations.

Obesity and glycemic control among people with type 2 diabetes in the United States: A retrospective cohort study using insurance claims data.

AIMS: To examine body mass index (BMI) and HbA1c for individuals with type 2 diabetes (T2D) in the United States. METHODS: The retrospective study utilized data from IBM® MarketScan® Explorys® Claims-EMR Data for the years 2012-2019. Individuals with T2D and a recorded HbA1c laboratory result and BMI were included. The relationship between BMI and HbA1c was assessed descriptively and logistic regressions examined the relationship between benchmark BMI and the probability of having HbA1c above targets of 7% or 8% in the 1year post-period. RESULTS: In our sample of 44,723 patients, results indicated that compared to individuals of normal weight, those classified as obese class I or obese class II were 24% more likely to have a last HbA1c≥7% (Odds Ratio [OR]=1.24; 95% Confidence Interval [CI] 1.14-1.35 for both obese class I and obese class II), while those classified as obese class III were 16% more likely (OR=1.16; 95% CI 1.06-1.27). Results were similar when using a HbA1c threshold of 8%. CONCLUSIONS: Given the importance of glycemic control for people with T2D, these results suggest that treatments which reduce rates of obesity may help to improve health outcomes.

Trends in HbA1c and Body Mass Index Among Individuals with Type 2 Diabetes: Evidence from a US Database 2012-2019.

INTRODUCTION: Given the high rates of obesity and poor glycemic control among individuals with type 2 diabetes (T2D), this study examines current trends in HbA1c and body mass index (BMI) as well as the association between HbA1c and BMI among adults with T2D. METHODS: Data from the IBM® MarketScan® Explorys® Claims-EMR Data were used to construct eight annual cohorts for the years 2012-2019. Each annual cohort included adults identified with T2D who had at least one recorded HbA1c laboratory result and BMI value in the year of interest. Given these cohorts, trends in HbA1c and BMI were described over time using generalized estimating equation (GEE) tests. RESULTS: Results indicate that, over the study period from 2012-2019, average BMI increased significantly and there was a decrease in the percentage of adults with T2D who achieved glycemic control. In addition, for all years, higher BMI classification was associated with higher HbA1c values. When examining results for patients in different age groups, the findings were generally consistent with the overall population. In each age group, but most notably the age 18-44 group, the mean BMI increased over time and higher BMI was associated with higher HbA1c. CONCLUSION: Given the increase in BMI and decreasing percentage of individuals achieving glycemic control among adults with T2D found over the study period, therapies which decrease BMI as well as HbA1c can potentially have a significant impact on the management of T2D. The growing proportion of the younger age group with higher mean BMI may remain a key subgroup of interest.

The association between the severity of chronic kidney disease and medical costs among patients with type 2 diabetes.

AIMS: Examine healthcare costs across chronic kidney disease (CKD) stages for US patients with type 2 diabetes (T2D). MATERIALS AND METHODS: IQVIA Real World Data Adjudicated Claims linked electronic medical records and insurance claims from January 1, 2012 through March 31, 2017 were used for this retrospective study. Adults diagnosed with T2D and comorbid CKD were included. General linear models incorporating splines were constructed, and information from these regressions were used to inform the relationship between medical costs and CKD. Multivariable analyses controlled for patient characteristics, vital signs, general health, prior medication use, prior visit to specialists, index A1c, and year of index date. RESULTS: There were 6,645 individuals who met the study criteria. Results generally indicate sharp increases in annual total medical costs and non-drug medical costs in the 1 year post-period for patients with Stage 4 or 5 CKD (estimated glomerular filtration rate [eGFR] ≤ 30 mL/min/1.73 m2) with each 1 point reduction in eGFR from 30 associated with an increase of $1,870 in all-cause total medical costs (p < 0.0001) and $1,805 of all-cause non-drug medical costs (p < 0.0001). Similarly, each point decline below 30 mL/min was associated annual cost increases of $1,701 for CKD-related total medical costs, $1,695 for CKD-related non-drug medical costs, $173 for diabetes-related medical costs, and $187 for diabetes-related non-drug medical costs (all p < 0.0001). LIMITATIONS: The investigation included only patients with medical insurance and laboratory test results, and results may not be generalizable to all T2D patients with CKD. The methodology allowed us to determine associations, not causation, and potential confounders, such as duration of diabetes, diet, exercise, or social support, could not be assessed. CONCLUSIONS: Results indicate there are sharp and significant increases in medical costs among T2D patients with Stage 4 and 5 CKD compared to those with earlier stages of CKD.

Bridging the Gap Between Self-Reported and Claims-Derived Adherence Measures for Basal Insulin Among Patients with Type 2 Diabetes Mellitus.

INTRODUCTION: Complex or personalized insulin regimens challenge traditional adherence measures. Our objective was to develop an improved basal insulin (BI) adherence measure using both patient-reported and administrative claims data, resulting in a more complete measure. METHODS: Patients' self-reported BI utilization over the previous 12 months was linked with their claims data for the same period. Hybrid medication possession ratio (MPR) was derived by calculating expected days of insulin supply [total dispensed insulin units from claims over 12 months divided by self-reported total daily dose (TDD)]. The hybrid MPR was compared against traditional claims-based MPR, adjusted claims-based MPR, and patient-reported MPR. For all MPR measures, the adherence threshold was ≥ 0.8. A logistic model was used to predict non-adherence per hybrid MPR. The predicted model-based MPR was compared with existing measures in a larger cohort. RESULTS: The study sample consisted of 296 patients. TDD derived from claims was higher than self-reported TDD [77.9 (71.8) vs. 57.7 (38.3)], implying average dispensed insulin would last longer than claims-based days supply. Correspondingly, hybrid and MPRs adjusted for package size (56% and 71%, respectively) were higher than claims-based MPR (50%). Age, total claims-based days supply, retinopathy, adjusted MPR-based adherence, and non-insulin injectable use were key predictors of hybrid MPR-based adherence. Applying the claims-based prediction model to a larger cohort to test validity showed high correlations with predicted and adjusted MPR-based adherence. CONCLUSIONS: Traditional claims-based MPR underestimated adherence while adjusted MPR overestimated adherence when self-reported total daily dose was taken as benchmark insulin dose. The predicted model may help identify patients with poor basal insulin adherence. More research is needed to further confirm the findings. FUNDING: Eli Lilly and Company, Indianapolis, IN, USA.

Non-adherence to basal insulin among patients with type 2 diabetes in a US managed care population: Results from a patient survey.

The aim of this study was to assess insulin non-adherence among patients with type 2 diabetes (T2DM) to better understand relationships between adherence, basal insulin (BI) usage, and patient experiences. A cross-sectional survey of patients with T2DM using BI was conducted. Adherence was measured by the Morisky Medication Adherence Scale 8-Items (MMAS-8). Low adherence (LA) was defined as MMAS-8 score < 6, high adherence (HA) as MMAS-8 score = 8, and medium adherence as MMAS-8 score = 6 to < 8. Patients with MMAS-8 scores = 6 to < 8 were excluded from the analysis. Of 400 completed surveys, 395 patients (98.8%) completed all MMAS-8 items, 112 with LA, 134 with HA. Compared with HA patients, greater proportions of LA patients followed more complex BI dosing patterns (57.1% vs. 39.5%, P = 0.014), had some difficulty calculating their correct BI dose (40.2% vs. 6.8%, P < 0.001), reported having missed ≥1 dose per month (79.3% vs. 12.6%, P < 0.001), and temporarily stopped BI in the past year (23.2% vs. 0.7%, P < 0.001). In conclusion, understanding patients' experiences with BI therapy can help formulate strategies to improve adherence.

Clinical course of nonalcoholic fatty liver disease: an assessment of severity, progression, and outcomes.

PURPOSE: To identify the characteristics and initial disease severity of patients with nonalcoholic fatty liver disease (NAFLD) and assess incidence and risk factors for disease progression in a retrospective study. METHODS: Patients ≥18 years of age without alcoholism or other liver diseases (eg, hepatitis B/C) were selected from Geisinger Health System electronic medical record data from 2004 to 2015. Initial disease stage was stratified into uncomplicated NAFLD, advanced fibrosis, cirrhosis, hepatocellular carcinoma (HCC), and liver transplant using clinical biomarkers, diagnosis, and procedure codes. Disease progression was defined as stage progression or death and analyzed via Kaplan-Meier plots and multistate models. RESULTS: In the NAFLD cohort (N=18,754), 61.5% were women, 39.0% had type 2 diabetes mellitus (T2DM), and the mean body mass index was 38.2±10.2 kg/m2. At index, 69.9% had uncomplicated NAFLD, 11.7% had advanced fibrosis, and 17.8% had cirrhosis. Of 18,718 patients assessed for progression, 17.3% progressed (11.0% had stage progression, 6.3% died without evidence of stage progression) during follow-up (median=842 days). Among subgroups, 12.3% of those without diabetes mellitus progressed vs 24.7% of those with T2DM. One-year mortality increased from 0.5% in uncomplicated NAFLD to 22.7% in HCC. After liver transplant, mortality decreased to 5.6% per year. CONCLUSIONS: In 2.3 years of follow-up, approximately 17% of patients progressed or died without evidence of stage progression. T2DM was associated with approximately twice the risk of disease progression, and mortality risk increased with disease stage. Early diagnosis and monitoring of disease progression, especially in patients with T2DM, is warranted.

Risk Factors for Nocturnal Hypoglycemia in Insulin-treated Patients With Type 2 Diabetes: A Secondary Analysis of Observational Data Derived From an Integrated Clinical Trial Database.

PURPOSE: A trade-off exists in most diabetes therapies between the benefits of good glycemic control and the morbidity of hypoglycemia. Balancing these factors to achieve desired outcomes is a key consideration for personalized diabetes therapy. Hypoglycemia at night (nocturnal hypoglycemia [NH]) is a common but often under-reported problem in insulin-treated patients with type 2 diabetes. To better understand the risk for NH, we pooled data from multiple clinical trials of insulin treatment and specifically examined NH risk factors in relation to glycemic goals. METHODS: Of 53 randomized trials involving insulin treatment, 18 trials that collected NH data were included. Risk factors associated with NH were identified by using gradient-boosting methods. A proportional hazards model was used to quantify the hazard ratio (HR) for risk factors. By modeling with individual patient data, a patient-level NH risk score distribution was created. Finally, results of the model were used to quantify an adjustment to the glycemic goal that would fully offset each risk factor, all other factors being equal. FINDINGS: Data pooling resulted in the inclusion of 7341 patients with type 2 diabetes from 18 randomized clinical trials. In the mean 6-month treatment period, 43% of patients experienced at least 1 episode of NH (mean [SD], 1.1 [1.5] events/month). Reduction of glycosylated hemoglobin (HbA1c) levels during the trial was a risk factor for NH (HR, 1.40 [95% CI, 1.38-1.43] per -1% of HbA1c). Higher baseline HbA1c level was a protective factor against NH (HR, 0.76 [95% CI, 0.74-0.77] per +1% of HbA1c); and the adjustment to HbA1c goal required to offset 1% higher baseline HbA1c was -0.825%. Patient characteristics for risk of NH included older age (HR, 1.02 [95% CI, 1.01-1.02]) per 1-year increase), female sex (HR, 1.18 [95% CI, 1.15-1.22]), black or African-American race (HR, 1.41 [95% CI, 1.33-1.50] vs white race), longer diabetes duration (HR, 1.02 [95% CI, 1.01-1.02] per 1-year increase), diabetic nephropathy (HR, 1.40 [95% CI, 1.27-1.54]), and concomitant sulfonylurea use (HR, 1.10 [95% CI, 1.05-1.15]). Asian race was associated with a lower risk of NH (HR, 0.50 [95% CI, 0.48-0.53] vs white race); this finding could be offset with a 2.03% adjustment to the HbA1c goal. IMPLICATIONS: Data on NH are scarce. By pooling multiple clinical trials, this study was able to evaluate patient-level data. A quantitative understanding of the trade-off between individual risk factors for NH and glycemic reduction may help clinicians to personalize patients' glycemic goals, while effectively managing NH risk. Limitations of the study include that patients were selected through inclusion/exclusion criteria and that patient compliance may be better in a trial setting. Validating the findings in the real world will be helpful.

The Prime Diabetes Model: Novel Methods for Estimating Long-Term Clinical and Cost Outcomes in Type 1 Diabetes Mellitus.

BACKGROUND: Recent publications describing long-term follow-up from landmark trials and diabetes registries represent an opportunity to revisit modeling options in type 1 diabetes mellitus (T1DM). OBJECTIVES: To develop a new product-independent model capable of predicting long-term clinical and cost outcomes. METHODS: After a systematic literature review to identify clinical trial and registry data, a model was developed (the PRIME Diabetes Model) to simulate T1DM progression and complication onset. The model runs as a patient-level simulation, making use of covariance matrices for cohort generation and risk factor progression, and simulating myocardial infarction, stroke, angina, heart failure, nephropathy, retinopathy, macular edema, neuropathy, amputation, hypoglycemia, ketoacidosis, mortality, and risk factor evolution. Several approaches novel to T1DM modeling were used, including patient characteristics and risk factor covariance, a glycated hemoglobin progression model derived from patient-level data, and model averaging approaches to evaluate complication risk. RESULTS: Validation analyses comparing modeled outcomes with published studies demonstrated that the PRIME Diabetes Model projects long-term patient outcomes consistent with those reported for a number of long-term studies. Macrovascular end points were reliably reproduced across five different populations and microvascular complication risk was accurately predicted on the basis of comparisons with landmark studies and published registry data. CONCLUSIONS: The PRIME Diabetes Model is product-independent, available online, and has been developed in line with good practice guidelines. Validation has indicated that outcomes from long-term studies can be reliably reproduced. The model offers new approaches to long-standing challenges in diabetes modeling and may become a valuable tool for informing health care policy.

Health-related quality of life burden of nonalcoholic steatohepatitis: a robust pragmatic literature review.

OBJECTIVE: Nonalcoholic steatohepatitis (NASH) is a form of chronic liver disease (CLD): patients have an increased risk of developing cirrhosis, liver failure, and complications (e.g. hepatocellular carcinoma). NASH has a high clinical burden, and likely impairs patients' health-related quality of life (HRQoL), but there are currently no licensed therapies. The objective of this robust pragmatic literature review was to identify and describe recent studies on the HRQoL burden of NASH from the patient perspective. METHODS: English-language primary research studies were identified that measured HRQoL in adults with NASH (population-based studies or clinical trials of pharmacological therapy). Searches were conducted in the following bibliographical databases: MEDLINE, EMBASE, Cochrane Database of Systematic Reviews (CDSR), Cochrane Central Register of Controlled Trials (CENTRAL), Database of Abstracts of Reviews of Effects (DARE), and Health Technology Assessment Database (HTA). Abstracts from selected congresses (2015/2016) were hand searched. Articles were assessed for relevance by two independent reviewers, and HRQoL data were extracted. RESULTS: A total of 567 de-duplicated abstracts were identified, and 20 full-text articles were reviewed. Eight studies were included: five quantitative, two interventional, and one qualitative. The quantitative and interventional studies measured HRQoL using the Short-Form 36 (SF-36) and the Chronic Liver Disease Questionnaire (CLDQ), and the qualitative study involved focus groups and individual interviews. Overall, the studies showed that NASH affects HRQoL, especially physical functioning, with many patients reporting being fatigued. In quantitative studies, overall, patients with NASH had a reduced HRQoL versus normative populations and nonalcoholic fatty liver disease (NAFLD) patients, but not versus chronic liver diseases. A longitudinal study showed that when weight loss was achieved, HRQoL improvement over 6 months was greater in patients with NASH versus NAFLD. Qualitative research suggested that, in addition to fatigue, other symptoms are also burdensome, having a broad negative impact on patients' lives. The impact of pharmacological treatment on HRQoL was explored in only two included studies. CONCLUSIONS: HRQoL is impaired in patients with NASH. Patients experience a range of symptoms, especially fatigue, and the impact on their lives is broad. Further research is needed to understand the HRQoL burden of NASH (e.g. assessing NASH-specific impacts not captured by SF-36 and CLDQ) and the impact of future NASH therapies on HRQoL.

The role of imperfect surrogate endpoint information in drug approval and reimbursement decisions.

Approval of new drugs is increasingly reliant on "surrogate endpoints," which correlate with but imperfectly predict clinical benefits. Proponents argue surrogate endpoints allow for faster approval, but critics charge they provide inadequate evidence. We develop an economic framework that addresses the value of improvement in the predictive power, or "quality," of surrogate endpoints, and clarifies how quality can influence decisions by regulators, payers, and manufacturers. For example, the framework shows how lower-quality surrogates lead to greater misalignment of incentives between payers and regulators, resulting in more drugs that are approved for use but not covered by payers. Efficient price-negotiation in the marketplace can help align payer incentives for granting access based on surrogates. Higher-quality surrogates increase manufacturer profits and social surplus from early access to new drugs. Since the return on better quality is shared between manufacturers and payers, private incentives to invest in higher-quality surrogates are inefficiently low.

Clinical and cost implications of amyloid beta detection with amyloid beta positron emission tomography imaging in early Alzheimer's disease - the case of florbetapir.

OBJECTIVE: Amyloid beta (Aß) positron emission tomography (PET) imaging helps estimate Aß neuritic plaque density in patients with cognitive impairment who are under evaluation for Alzheimer's disease (AD). This study aims to evaluate the cost-effectiveness of the Aß-PET scan as an adjunct to standard diagnostic assessment for diagnosis of AD in France, using florbetapir as an example. METHODS: A state-transition probability analysis was developed adopting the French Health Technology Assessment (HTA) perspective per guidance. Parameters included test characteristics, rate of cognitive decline, treatment effect, costs, and quality of life. Additional scenarios assessed the validity of the analytical framework, including: (1) earlier evaluation/treatment; (2) cerebrospinal fluid (CSF) as a comparator; and (3) use of other diagnostic procedures. Outputs included differences in quality-adjusted life years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). All benefits and costs were discounted for time preferences. Sensitivity analyses were performed to assess the robustness of findings and key influencers of outcomes. RESULTS: Aß-PET used as an adjunct to standard diagnostic assessment increased QALYs by 0.021 years and 10 year costs by €470 per patient. The ICER was €21,888 per QALY gained compared to standard diagnostic assessment alone. When compared with CSF, Aß-PET costs €24,084 per QALY gained. In other scenarios, Aß-PET was consistently cost-effective relative to the commonly used affordability threshold (€40,000 per QALY). Over 95% of simulations in the sensitivity analysis were cost-effective. CONCLUSION: Aß-PET is projected to affordably increase QALYs from the French HTA perspective per guidance over a range of clinical scenarios, comparators, and input parameters.

Evaluating health-related quality of life in type 1 diabetes: a systematic literature review of utilities for adults with type 1 diabetes.

BACKGROUND AND AIMS: Type 1 diabetes is a chronic condition associated with micro- and macrovascular complications that have a notable impact on health-related quality of life, the magnitude of which can be quantified via the use of utility values. The aim of this review was to conduct a systematic literature review to identify and compare published health state utility values for adults with type 1 diabetes both, with and without diabetes-related complications. METHODS: Literature searches of the PubMed, EMBASE, and Cochrane Library databases were performed to identify English language studies on adults with type 1 diabetes, published from 2000 onward, reporting utility values for patients with or without diabetes-related complications or assessing the impact of changes in HbA1c or body mass index on quality of life. For inclusion, studies were required to report utilities elicited using validated methods. RESULTS: A total of 20 studies were included in the final review that included utility values elicited using the EuroQuol five dimensions questionnaire (n=9), 15D questionnaire (n=2), Quality of Well-Being scale (n=4), time trade-off (n=3), and standard gamble (n=2) methods. For patients with no complications, reported utility values ranged from 0.90 to 0.98. Complications including stroke (reported disutility range, -0.105 to -0.291), neuropathy (range, -0.055 to -0.358), and blindness (range, -0.132 to -0.208) were associated with the largest decrements in utility values. The magnitude of utility values and utility decrements was influenced by the assessment method used. CONCLUSION: Complications lead to impaired health-related quality of life in patients with type 1 diabetes, the magnitude of which is influenced by the method used to determine utilities. There is currently a lack of utility data for certain complications of type 1 diabetes, meaning that many economic evaluations have relied on a combination of type 1 and type 2 diabetes utilities, despite differences between the conditions and populations, or type 1 diabetes-specific utilities derived from different instruments.