Evaluation of weight change and cardiometabolic risk factors in a real-world population of US adults with overweight or obesity.

Whether individuals in real-world settings are able to lose weight and improve cardiometabolic risk factors over time is unclear. We aimed to determine the management of and degree of body weight change over 2 years among individuals with overweight or obesity, and to assess associated changes in cardiometabolic risk factors and clinical outcomes. Using data from 11 large health systems within the Patient-Centered Outcomes Research Network in the U.S., we collected the following data on adults with a recorded BMI ≥25 kg/m2 between January 1, 2016 and December 31, 2016: body-mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDLC), triglycerides and glycated hemoglobin (HbA1c). We found that among 882,712 individuals with BMI ≥25 kg/m2 (median age 59 years; 56% female), 52% maintained stable weight over 2 years and 1.3% utilized weight loss pharmacotherapy. Weight loss of 10% was associated with small but significant lowering of mean SBP (-2.69 mmHg [95% CI -2.88, -2.50]), DBP (-1.26 mmHg [95% CI -1.35, -1.18]), LDL-C (-2.60 mg/dL [95% CI -3.14, -2.05]), and HbA1c (-0.27% [95% CI -0.35, -0.19]) in the same 12 months. However, these changes were not sustained over the following year. In this study of adults with BMI ≥25 kg/m2, the majority had stable weight over 2 years, pharmacotherapies for weight loss were under-used, and small changes in cardiometabolic risk factors with weight loss were not sustained, possibly due to failure to maintain weight loss.

The Relative Value of Anti-Obesity Medications Compared to Similar Therapies.

Purpose: To demonstrate a need for improved health insurance coverage for anti-obesity medications (AOMs) by comparing clinical and economic benefits of obesity treatments to covered medications for selected therapeutic areas. Methods: Using a grey literature search, we identified and prioritized therapeutic areas and treatment analogues for comparison to obesity. A targeted literature review identified clinical and economic outcomes research across the therapeutic area analogues. Associated comorbidities, clinical evidence, indirect costs (ie, absenteeism and productivity loss), and direct medical costs were evaluated to determine the relative value of treating obesity. Results: Four therapeutic areas/treatment analogues were selected for comparison to obesity: smoking cessation (varenicline), daytime sleepiness (modafinil), migraines (erenumab), and fibromyalgia (pregabalin). Obesity was associated with 17 comorbidities, more than migraine (9), smoking (8), daytime sleepiness (5), and fibromyalgia (2). Economic burden was greatest for obesity, followed by smoking, with yearly indirect and direct medical costs totaling $676 and $345 billion, respectively. AOMs resulted in cost savings of $2586 in direct medical costs per patient per year (PPPY), greater than that for varenicline at $930 PPPY, modafinil at $1045 PPPY, and erenumab at $468 PPPY; pregabalin utilization increased costs by $924 PPPY. AOMs were covered by 10-16% of United States health insurance plans, compared to 45-59% for the four comparators. Conclusion: Compared to four therapeutic analogues, obesity represented the highest economic burden and was associated with more comorbidities. AOMs provide greater cost savings compared to selected analogues. However, AOMs have limited formulary coverage. Improved coverage of AOMs may increase access to these treatments and may help address the clinical and economic burden associated with obesity and its comorbidities.

Clinical and Cost Benefits of Anti-Obesity Medication for US Veterans Participating in the MOVE! Weight Management Program.

Abstract This study investigated the clinical and economic impact of anti-obesity medications (AOMs; orlistat, liraglutide, phentermine/topiramate extended-release [ER], naltrexone ER/bupropion ER) among United States Veterans with obesity participating in Motivating Overweight/Obese Veterans Everywhere! (MOVE!), a government-initiated weight management program. The study population was identified from electronic medical records of the Veterans Health Administration (2010-2020). Clinical indices of obesity and health care resource utilization and costs were evaluated at 6, 12, and 24 months after the initial dispensing of an AOM in the AOM+MOVE! cohort (N = 3732, mean age 57 years, 79% male) or on the corresponding date of an inpatient or outpatient encounter in the MOVE! cohort (N = 7883, mean age 58 years, 81% male). At 6 months postindex, the AOM+MOVE! cohort had better cardiometabolic indices (eg, systolic blood pressure, diastolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, hemoglobin A1c) than the MOVE! cohort, with the trends persisting at 12 and 24 months. The AOM+MOVE! cohort was significantly more likely than the MOVE! cohort to have weight decreases of 5%-10%, 10%-15%, and >15% and lower body mass index at 6, 12, and 24 months. The AOM+MOVE! cohort also had fewer inpatient and emergency department visits than the MOVE! cohort, which was associated with lower mean total medical costs including inpatient costs. These results suggest that combining AOM treatment with the MOVE! program could yield long-term cost savings for the Veterans Affairs network and meaningful clinical improvements for Veterans with obesity.

Cost-effectiveness analysis of semaglutide 2.4 mg for the treatment of adult patients with overweight and obesity in the United States.

BACKGROUND: The rising prevalence and associated public health burden of obesity has led to advancements in pharmaceuticals for weight management. Semaglutide 2.4 mg, an anti-obesity medication (AOM) recently approved by the US Food and Drug Administration, has demonstrated clinically relevant weight loss in its phase 3 clinical trials. Economic evaluation comparing semaglutide 2.4 mg with other available weight management therapies is essential to inform payers for decision-making. OBJECTIVES: To assess the cost-effectiveness of semaglutide 2.4 mg in the treatment of adult patients with obesity (ie, body mass index [BMI] ≥ 30) and adult patients who are overweight (ie, BMI 27-29.9) with 1 or more weight-related comorbidities from a US third-party payer perspective. METHODS: A cohort Markov model was constructed to compare semaglutide 2.4 mg with the following comparators: no treatment, diet and exercise (D&E), and 3 branded AOMs (liraglutide 3 mg, phentermine-topiramate, and naltrexone-bupropion). All AOMs, including semaglutide 2.4 mg, were assumed to be taken in conjunction with D&E. Changes in BMI, blood pressure, cholesterol level, experience of acute and chronic obesity-related complications, costs, and quality-adjusted life years (QALYs) were simulated over 30 years based on pivotal trials of the AOMs and other relevant literature. Drug and health care prices reflect 2021 standardized values. Cost-effectiveness was examined with a willingness-to-pay (WTP) threshold of $150,000 per QALY gained. Sensitivity analyses were conducted to test the robustness of the cost-effectiveness results to plausible variation in model inputs. RESULTS: In the base-case analysis, treatment with semaglutide 2.4 mg was estimated to improve QALYs by 0.138 to 0.925 and incur higher costs by $3,254 to $25,086 over the 30-year time horizon vs comparators. Semaglutide 2.4 mg is cost-effective against all comparators at the prespecified WTP threshold, with the incremental cost per QALY gained ranging from $23,556 to $144,296 per QALY gained. In the sensitivity analysis, extended maximum treatment duration, types of subsequent treatment following therapy discontinuation, and weight-rebound rates were identified as key drivers for model results. The estimated probability of semaglutide 2.4 mg being cost-effective compared with comparators ranged from 67% to 100% when varying model parameters and assumptions. CONCLUSIONS: As a long-term weight management therapy, semaglutide 2.4 mg was estimated to be cost-effective compared with no treatment, D&E alone, and all other branded AOM comparators under a WTP threshold of $150,000 per QALY gained over a 30-year time horizon. DISCLOSURES: Financial support for this research was provided by Novo Nordisk Inc. The study sponsor was involved in several aspects of the research, including the study design, the interpretation of data, the writing of the manuscript, and the decision to submit the manuscript for publication. Dr Kim and Ms Ramasamy are employees of Novo Nordisk Inc. Ms Kumar and Dr Burudpakdee were employees of Novo Nordisk Inc at the time this study was conducted. Dr Sullivan received research support from Novo Nordisk Inc for this study. Drs Wang, Song, Wu, Ms Xie, and Ms Sun are employees of Analysis Group, Inc, who received consultancy fees from Novo Nordisk Inc in connection with this study.

Impact of Sustained Weight Loss on Cardiometabolic Outcomes.

Obesity increases the risk of developing type 2 diabetes, hypertension, and hyperlipidemia. We sought to determine the impact of obesity maintenance, weight regain, weight loss maintenance, and magnitudes of weight loss on future risk and time to developing these cardiometabolic conditions. This was a retrospective cohort study of adults receiving primary care at Geisinger Health System between 2001 and 2017. Using electronic health records, patients with ≥3-weight measurements over a 2-year index period were identified and categorized. Obesity maintainers (OM) had obesity (body mass index ≥30 kg/m²) and maintained their weight within ±3% from baseline (reference group). Both weight loss rebounders (WLR) and weight loss maintainers (WLM) had obesity at baseline and lost >5% body weight in year 1; WLR regained ≥20% of weight loss by end of year 2 and WLM maintained ≥80% of weight loss. Incident type 2 diabetes, hypertension, and hyperlipidemia, and time-to-outcome were determined for each study group and by weight loss category for WLM. Of the 63,567 patients included, 67% were OM, 19% were WLR, and 14% were WLM. The mean duration of follow-up was 6.6 years (SD, 3.9). Time until the development of electronic health record-documented type 2 diabetes, hypertension, and hyperlipidemia was longest for WLM and shortest for OM (log-rank test p <0.0001). WLM had the lowest incident type 2 diabetes (adjusted hazard ratio [HR] 0.676 [95% confidence interval [CI] 0.617 to 0.740]; p <0.0001), hypertension (adjusted HR 0.723 [95% CI 0.655 to 0.799]; p <0.0001), and hyperlipidemia (adjusted HR 0.864 [95% CI 0.803 to 0.929]; p <0.0001). WLM with the greatest weight loss (>15%) had a longer time to develop any of the outcomes compared with those with the least amount of weight loss (<7%) (p <0.0001). In an integrated delivery network population, sustained weight loss was associated with a delayed onset of cardiometabolic diseases, particularly with a greater magnitude of weight loss.

Retrospective descriptive analysis of a managed care population with obesity.

OBJECTIVES: To reveal the extent of obesity in a single healthcare system and provide a blueprint for other health systems to perform similar analyses, this study describes characteristics and weight change patterns of patients classified with overweight and obesity at a large integrated delivery network (IDN) in the South-Central United States. METHODS: A descriptive, observational, retrospective study was conducted using electronic medical records and claims data. Patients were ≥18 years old, body mass index (BMI) ≥27 kg/m2, and continuously enrolled in the IDN plan for ≥6 months before and ≥12 months after the index date. Demographics, comorbidities, BMI, and weight were collected. Weight changes were assessed annually, and anti-obesity medications (AOM) use was also captured. RESULTS: A total of 36,430 eligible patients were identified. A subset of 22,712 patients was continuously enrolled for the entire study period (mean age: 57.2) and were primarily white (83.3%) and commercially insured (54.3%). Most patients were categorized as overweight (40.1%) or obesity class I (32.5%) at baseline. At years 1 and 4 post-index, patients who maintained index weight (±3%) was 56.2% and 37.0%, respectively, whereas weight gain (≥3% increase) was 23.7% and 33.3%, respectively. AOM use (1.1%) primarily consisted of phentermine-hydrochloride (n = 114, 0.5%) and orlistat (n = 115, 0.5%). CONCLUSIONS: An increasing proportion of patients gained weight over time, combined with low AOM use, emphasizing the need for weight-loss interventions in this population. Findings from this study provide a foundation for health systems to perform similar analyses.

Assessing opportunities to advance quality measures in adult obesity.

OBJECTIVES: To evaluate the methodological soundness and performance of 3 obesity quality measures aimed at promoting improvements in obesity care. STUDY DESIGN: Retrospective, clinical, and administrative data-based observational research study to evaluate scientific soundness, feasibility, and performance of obesity quality measures. METHODS: Four test sites (clinicians/clinician groups) submitted clinical and administrative health data including patient demographics, diagnoses, and encounter information for patient panels encompassing individuals aged 18 to 79 years with at least 1 ambulatory visit between July 1, 2017, and June 30, 2018 (measurement period). Clinician/clinician group data were supplemented by an Optum data set contributing patient information from 21 health care organizations with approximately 6 million qualifying patients to assess the impact of using a larger data set for measure testing. Patients were excluded if they met any of the following criteria: were pregnant during the measurement period or in the 6 months prior to the measurement period, had died during the measurement year, or had evidence of palliative or hospice care during the measurement period. RESULTS: This study resulted in the identification of a clinician/clinician group-level measure, Documentation of Obesity Diagnosis, as being feasible and reliable; however, the measure requires additional evaluation and potential adjustments to determine validity. Other measures included in our evaluation had feasibility and methodological challenges due to data capture and coding limitations. CONCLUSIONS: Findings of our current study suggest that there are emerging opportunities to capture data and advance obesity measurement incrementally. A process measure focused on obesity diagnosis has the most potential for immediate implementation by clinicians, and additional measures focused on change in body mass index over time and use of evidence-based obesity treatment remain challenging to implement due to data capture and benefit coverage.

Effects of sustained weight loss on outcomes associated with obesity comorbidities and healthcare resource utilization.

OBJECTIVE: Determine the impact of long-term non-surgical weight loss maintenance on clinical relevance for osteoarthritis, cancer, opioid use, and depression/anxiety and healthcare resource utilization. METHODS: A cohort of adults receiving primary care within Geisinger Health System between 2001-2017 was retrospectively studied. Patients with ≥3 weight measurements in the two-year index period and obesity at baseline (BMI ≥30 kg/m2) were categorized: Obesity Maintainers (reference group) maintained weight within +/-3%; Weight Loss Rebounders lost ≥5% body weight in year one, regaining ≥20% of weight loss in year two; Weight Loss Maintainers lost ≥5% body weight in year one, maintaining ≥80% of weight loss. Association with development of osteoarthritis, cancer, opioid use, and depression/anxiety, was assessed; healthcare resource utilization was quantified. Magnitude of weight loss among maintainers was evaluated for impact on health outcomes. RESULTS: In total, 63,567 patients were analyzed including 67% Obesity Maintainers, 19% Weight Loss Rebounders, and 14% Weight Loss Maintainers; median follow-up was 9.7 years. Time until osteoarthritis onset was delayed for Weight Loss Maintainers compared to Obesity Maintainers (Logrank test p <0.0001). Female Weight Loss Maintainers had a 19% and 24% lower risk of developing any cancer (p = 0.0022) or obesity-related cancer (p = 0.0021), respectively. No significant trends were observed for opioid use. Weight loss Rebounders and Maintainers had increased risk (14% and 25%) of future treatment for anxiety/depression (both <0.0001). Weight loss maintenance of >15% weight loss was associated with the greatest decrease in incident osteoarthritis. Healthcare resource utilization was significantly higher for Weight Loss Rebounders and Maintainers compared to Obesity Maintainers. Increased weight loss among Weight Loss Maintainers trended with lower overall healthcare resource utilization, except for hospitalizations. CONCLUSIONS: In people with obesity, sustained weight loss was associated with greater clinical benefits than regained short-term weight loss and obesity maintenance. Higher weight loss magnitudes were associated with delayed onset of osteoarthritis and led to decreased healthcare utilization.

Associations of weight loss with obesity-related comorbidities in a large integrated health system.

AIMS: To determine the health outcomes associated with weight loss in individuals with obesity, and to better understand the relationship between disease burden (disease burden; ie, prior comorbidities, healthcare utilization) and weight loss in individuals with obesity by analysing electronic health records (EHRs). MATERIALS AND METHODS: We conducted a case-control study using deidentified EHR-derived information from 204 921 patients seen at the Cleveland Clinic between 2000 and 2018. Patients were aged ≥20 years with body mass index ≥30 kg/m2 and had ≥7 weight measurements, over ≥3 years. Thirty outcomes were investigated, including chronic and acute diseases, as well as psychological and metabolic disorders. Weight change was investigated 3, 5 and 10 years prior to an event. RESULTS: Weight loss was associated with reduced incidence of many outcomes (eg, type 2 diabetes, nonalcoholic steatohepatitis/nonalcoholic fatty liver disease, obstructive sleep apnoea, hypertension; P < 0.05). Weight loss >10% was associated with increased incidence of certain outcomes including stroke and substance abuse. However, many outcomes that increased with weight loss were attenuated by disease burden adjustments. CONCLUSIONS: This study provides the most comprehensive real-world evaluation of the health impacts of weight change to date. After comorbidity burden and healthcare utilization adjustments, weight loss was associated with an overall reduction in risk of many adverse outcomes.

Effectiveness of Combining Antiobesity Medication With an Employer-Based Weight Management Program for Treatment of Obesity: A Randomized Clinical Trial.

Importance: The clinical efficacy of antiobesity medications (AOMs) as adjuncts to lifestyle intervention is well characterized, but data regarding their use in conjunction with workplace wellness plans are lacking, and coverage of AOMs by US private employers is limited. Objective: To determine the effect of combining AOMs with a comprehensive, interdisciplinary, employer-based weight management program (WMP) compared with the WMP alone on weight loss, treatment adherence, and work productivity and limitations. Design, Setting, and Participants: This 1-year, single-center, open-label, parallel-group, real-world, randomized clinical trial was conducted at the Cleveland Clinic's Endocrinology and Metabolism Institute in Cleveland, Ohio, from January 7, 2019, to May 22, 2020. Participants were adults with obesity (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared] ≥30) enrolled in the Cleveland Clinic Employee Health Plan. Interventions: In total, 200 participants were randomized 1:1, 100 participants to WMP combined with an AOM (WMP+Rx), and 100 participants to WMP alone. The WMP was the Cleveland Clinic Endocrinology and Metabolism Institute's employer-based integrated medical WMP implemented through monthly multidisciplinary shared medical appointments. Participants in the WMP+Rx group initiated treatment with 1 of 5 US Food and Drug Administration-approved medications for chronic weight management (orlistat, lorcaserin, phentermine/topiramate, naltrexone/bupropion, and liraglutide, 3.0 mg) according to standard clinical practice. Main Outcomes and Measures: The primary end point was the percentage change in body weight from baseline to month 12. Results: The 200 participants were predominately (177 of 200 [88.5%]) women, had a mean (SD) age of 50.0 (10.3) years, and a mean (SD) baseline weight of 105.0 (19.0) kg. For the primary intention-to-treat estimand, the estimated mean (SE) weight loss was -7.7% (0.7%) for the WMP+Rx group vs -4.2% (0.7%) for the WMP group, with an estimated treatment difference of -3.5% (95% CI, -5.5% to -1.5%) (P < .001). The estimated percentage of participants achieving at least 5% weight loss was 62.5% for WMP+Rx vs 44.8% for WMP (P = .02). The rate of attendance at shared medical appointments was higher for the WMP+Rx group than for the WMP group. No meaningful differences in patient-reported work productivity or limitation measures were observed. Conclusions and Relevance: Clinically meaningful superior mean weight loss was achieved when access to AOMs was provided in the real-world setting of an employer-based WMP, compared with the WMP alone. Such results may inform employer decisions regarding AOM coverage and guide best practices for comprehensive, interdisciplinary employer-based WMPs. Trial Registration: ClinicalTrials.gov Identifier: NCT03799198.

Job Absenteeism Costs of Obesity in the United States: National and State-Level Estimates.

OBJECTIVE: To estimate the causal effect of obesity on job absenteeism and the associated lost productivity in the United States, both nationwide and by state. METHODS: We conducted a retrospective pooled cross-sectional analysis using the 2001 to 2016 Medical Expenditure Panel Survey and estimated two-part models of instrumental variables. RESULTS: Obesity, relative to normal weight, raises job absenteeism due to injury or illness by 3.0 days per year (128%). Annual productivity loss due to obesity ranges from $271 to $542 (lower/upper bound) per employee with obesity, with national productivity losses ranging from $13.4 to $26.8 billion in 2016. Trends in state-level estimates mirror those at the national level, varying across states. CONCLUSIONS: Obesity significantly raises job absenteeism. Reductions in job absenteeism should be included when calculating the cost-effectiveness of interventions to prevent or reduce obesity among employed adults.

Direct medical costs of obesity in the United States and the most populous states.

BACKGROUND: After a dramatic increase in prevalence over several decades, obesity has become a major public health crisis in the United States. Research to date has consistently demonstrated a correlation between obesity and higher medical costs for a variety of U.S. subpopulations and specific categories of care. However, by examining associations rather than causal effects, previous studies likely underestimated the effect of obesity on medical expenditures. OBJECTIVE: To estimate the causal effect of obesity on direct medical care costs at the national and state levels. METHODS: This study is a pooled cross-sectional analysis of retrospective data from the 2001-2016 Medical Expenditure Panel Surveys. Adults aged 20-65 years with a biological child living in the household were included in the study sample. Primary outcomes were individual-level medical expenditures due to obesity, overall, as well as separately by type of payer and category of medical care. Results were reported at the national level and separately for the 20 most populous states. The expenditure estimates were obtained from 2-part models of instrumental variables in which the respondent's body mass index (BMI) was instrumented using the BMI of their biological child. RESULTS: Adults with obesity in the United States compared with those with normal weight experienced higher annual medical care costs by $2,505 or 100%, with costs increasing significantly with class of obesity, from 68.4% for class 1 to 233.6% for class 3. The effects of obesity raised costs in every category of care: inpatient, outpatient, and prescription drugs. Increases in medical expenditures due to obesity were higher for adults covered by public health insurance programs ($2,868) than for those having private health insurance ($2,058). In 2016, the aggregate medical cost due to obesity among adults in the United States was $260.6 billion. The increase in individual-level expenditures due to obesity varied considerably by state (e.g., 24.0% in Florida, 66.4% in New York, and 104.9% in Texas). CONCLUSIONS: The 2-part models of instrumental variables, which estimate the causal effects of obesity on direct medical costs, showed that the effect of obesity is greater than suggested by previous studies, which estimated only correlations. Much of the aggregate national cost of obesity-$260.6 billion-represents external costs, providing a rationale for interventions to prevent and reduce obesity. DISCLOSURES: Novo Nordisk financed the development of the study design, analysis, and interpretation of data, as well as writing support of the manuscript. Cawley, Biener, and Meyerhoefer received financial support from Novo Nordisk to conduct the research study on which this manuscript is based. Smolarz and Ramasamy are employees of Novo Nordisk. Ding and Zvenyach have no conflicts to declare. Our research has been presented as a poster at the 2020 Academy Health Annual Research Meeting (Virtual), July 28-August 6, 2020.

Simulating the Fiscal Impact of Anti-Obesity Medications as an Obesity Reduction Strategy.

While substantial public health investment in anti-smoking initiatives has had demonstrated benefits on health and fiscal outcomes, similar investment in reducing obesity has not been undertaken, despite the substantial burden obesity places on society. Anti-obesity medications (AOMs) are poorly prescribed despite evidence that weight loss is not sustained using other strategies alone.We used a simulation model to estimate the potential impact of 100% uptake of AOMs on Medicare and Medicaid spending, disability payments, and taxes collected relative to status quo with negligible AOM use. Relative to status quo, AOM use simulation would result in Medicare and Medicaid savings of $231.5 billion and $188.8 billion respectively over 75 years. Government tax revenues would increase by $452.8 billion. Overall, the net benefit would be $746.6 billion. Anti-smoking efforts have had substantial benefits for society. A similar investment in obesity reduction, including broad use of AOMs, should be considered.

Measuring What Matters: Beyond Quality Performance Measures in Caring for Adults with Obesity.

Obesity is a chronic disease that poses serious health and societal burdens. Although guidelines exist for obesity management in primary care, evaluating the success of obesity treatment programs is hampered by lack of established, robust quality measures. This study aimed to develop, and test for feasibility, measures for operational tracking, quality performance, and patient-centered care in the context of a national collaborative to develop a model for obesity management in the US primary care setting. The authors developed and evaluated 7 measures used to track the care of patients with overweight or obesity (n = 226,727 at baseline) receiving care within 10 health care organizations (HCOs). Measure categories included: (1) operational tracking (obesity/overweight prevalence and prevalence of obesity-related complications); (2) quality performance (obesity diagnosis, change in weight over time, anti-obesity medication prescriptions, and assessment of obesity-related complications); and (3) patient-centered care (patient-reported outcomes). Measures were tested for feasibility, variability across HCOs, ability to detect differences over time, and value to the HCOs. All measures were feasible to collect, provided value to the participating HCOs, and demonstrated variation and ability to detect differences over time (eg, rates of documented diagnosis of obesity classes 1, 2, and 3 increased from 29%, 46%, and 66%, respectively, at baseline to 35%, 53%, and 71% at study end). This study confirmed the feasibility and perceived value of 7 operational, performance, and patient-centered measures collected in primary care practices in 10 HCOs over an 18-month period.

Economic value of nonsurgical weight loss in adults with obesity.

BACKGROUND: Obesity imposes a substantial economic burden on the United States. The short-term value of nonsurgical weight loss (WL) and nonsurgical sustained WL (i.e., WL not resulting from bariatric surgery) is poorly understood. OBJECTIVES: To assess short-term (1 year) effect of nonsurgical WL and sustained nonsurgical WL (i.e., approximately 2 years) on per-patient-per-month (PPPM) total all-cause health care costs among adults with obesity in the United States. METHODS: In this retrospective cohort study, we analyzed data from the IBM MarketScan Explorys Claims-EMR Data Set from January 1, 2012, through June 30, 2018. Adults aged 18-64 years with a body mass index (BMI) measurement ≥ 30 kg/m2 on the index date and BMI measurements at 12, 24, and 36 months were classified into weight-gain (≥ 3%), no-weight-change (within ± 3%), and WL (≥ 3%-≤ 5%, > 5%-≤ 10%, and > 10%-≤ 20%) cohorts based on the change from first to second BMI measurements (baseline), and sustained nonsurgical WL based on WL during baseline and < 3% weight gain from second to third BMI measurement. PPPM all-cause health care costs were calculated for baseline, first year, and second year of follow-up. Generalized linear models were used to examine if PPPM all-cause health care cost change (ΔPPPM) from baseline to follow-up differed significantly between nonsurgical WL/sustained WL and no-weight-change cohorts. Analyses were stratified by index obesity class (class 1: BMI 30- < 34.9 kg/m2, class 2: BMI 35- < 39.9 kg/m2, class 3: BMI ≥ 40 kg/m2). Specific nonsurgical WL treatments used by individuals in the study were not studied. RESULTS: The sample included 20,488 adults who were grouped as follows: weight-gain cohort (24.8%), no-weight-change cohort (56.6%), ≥ 3%- ≤ 5% WL cohort (8.2%), > 5%- ≤ 10% WL cohort (7.7%), and > 10%- ≤ 20% WL cohort (2.8%). Compared with the no-weight-change cohort, adjusted mean ΔPPPM all-cause health care cost from baseline to first year of follow-up was lower in all WL cohorts (≥ 3%- ≤ 5% WL: -$57.36, > 5%- ≤ 10% WL: -$135.35 [P < 0.05], > 10%- ≤ 20% WL: -$193.54 [P < 0.05]). In the second year of follow-up (n = 15,307), the cohorts were weight-gain (43.4%), no-weight-change (59.4%), ≥ 3%- ≤ 5% sustained WL (7.3%), ≥ 5%- ≤ 10% sustained WL (6.3%), and > 10%- ≤ 20% sustained WL (1.8%). Adjusted mean ΔPPPM all-cause health care cost was lower in all sustained WL groups (-$26.38, -$157.41 [P < 0.05], and -$185.41 for ≥ 3%- ≤ 5%, ≥ 5%- ≤ 10%, and > 10%- ≤ 20% WL, respectively). Greater nonsurgical WL and sustained nonsurgical WL were generally associated with larger reduction in short-term all-cause health care costs. Results stratified by index obesity class were mixed, due to small samples. CONCLUSIONS: Substantial all-cause health care cost savings were observed 1 year after nonsurgical WL and after sustained (on average for 2 years) nonsurgical WL in adults with obesity, with greater nonsurgical WL and sustained nonsurgical WL associated with greater cost savings. Comprehensive solutions to chronic weight management, including improved access to antiobesity medications in combination with lifestyle interventions, could be valuable to patients, employers, and payers. DISCLOSURES: This study was sponsored by Novo Nordisk, which also purchased the data. Blanchette is an employee of Novo Nordisk. Smolarz and Ramasamy are employees of Novo Nordisk and hold equity in Novo Nordisk. Ding, Fan, and Weng were employees of Novo Nordisk at the time this study was conducted. The findings from this study were previously presented at Obesity Week 2019; November 3-7, 2019; Las Vegas, NV.

Complication-specific direct medical costs by body mass index for 13 obesity-related complications: a retrospective database study.

BACKGROUND: Obesity, a multifactorial disease associated with many severe complications, affects more than 40% of adults in the United States. OBJECTIVE: To quantify the cost burden of 13 obesity-related complications (ORCs), overall and by body mass index (BMI) class. METHODS: Adult patients (aged ≥ 18 years) with ≥ 1 medical claim with an ICD-9/10 diagnosis code for the ORC of interest were identified using linked data from IQVIA's Ambulatory Electronic Medical Records and PharMetrics Plus. Thirteen ORCs were separately assessed (asthma, dyslipidemia, gastroesophageal reflux disease [GERD], heart failure with preserved ejection fraction [HFpEF], hypertension, musculoskeletal pain, obstructive sleep apnea [OSA], osteoarthritis [OA] of the knee, polycystic ovary syndrome [PCOS], prediabetes, psoriasis, type 2 diabetes mellitus [T2DM], and urinary incontinence); ORC cohorts were not mutually exclusive. For each ORC, the first claim identified for the ORC from January 2010-December 2016 was termed the index date. Patients had continuous enrollment in the 1-year pre-index (without a diagnosis code of the specific ORC under study) and the 1-year post-index, with ≥ 1 BMI value in the 6-months pre-index. Patients with underweight (BMI < 18.5 kg/m2) and those with cancer or pregnancy were excluded. Complication-specific costs were identified as claims with a diagnosis code for the ORC (primary position only for hospitalizations) or ORC-specific medications or procedures. Baseline demographic/clinical characteristics and complication-specific costs over the 1-year follow-up were assessed for each ORC cohort, overall and by BMI class (18.5-24.9; 25.0-29.9; 30.0-34.9; 35.0-39.9; ≥ 40 kg/m2). The association between total complication-specific costs and BMI class was assessed by generalized linear regression model for each ORC, adjusting for baseline characteristics. RESULTS: The total number of patients that comprised the ORC cohorts ranged from 1,275 (HFpEF) to 101,784 (musculoskeletal pain). Across ORC cohorts, 41.6% (musculoskeletal pain) to 73.5% (OSA) had obesity (BMI ≥ 30 kg/m2). For 4 ORC cohorts, more than one fifth of patients had class III obesity (BMI ≥ 40 kg/m2): T2DM, OSA, PCOS, and HFpEF. Baseline mean Charlson Comorbidity Index score increased with increasing BMI class for most ORC cohorts. The most costly ORCs overall based on mean total 1-year cost were: OA of the knee ($3,697 [range from normal weight (BMI: 18.5-24.9 kg/m2) to class III obesity: $2,453-$4,518]), HFpEF ($3,586 [range: $3,402-$4,685]), OSA ($2,768 [$2,442-$2,974]), and psoriasis ($2,711 [$2,131-$3,292]). The highest cost differences (≥20%) were observed among those with class III obesity versus those with normal weight for these aforementioned ORCs, as well as for GERD ($1,719 [$1,484-$1,893]) and asthma ($1,531 [$1,361-$1,780]). Following adjustment, most cost comparisons by BMI class were significantly higher versus those for normal weight for 6 ORCs. CONCLUSIONS: ORCs are important drivers of the economic burden of obesity, indicating an unmet need for the treatment of obesity. Appropriate weight management may reduce ORC-associated costs. DISCLOSURES: This study and its publication were supported by Novo Nordisk. Divino, Anupindi, and DeKoven are employed by IQVIA, which received funding from Novo Nordisk for this study. Ramasamy, Eriksen, Olsen, and Meincke are employed by and shareholders of Novo Nordisk. Material reported in this manuscript was presented in an abstract accepted by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) 2020, to be published in Value in Health. There was no presentation at ISPOR 2020.

Association between shared medical appointments and weight loss outcomes and anti-obesity medication use in patients with obesity.

OBJECTIVE: In shared medical appointments (SMAs), multiple patients with a similar clinical diagnosis are seen by a multidisciplinary team for interactive group sessions. Very few studies have specifically studied SMAs and weight loss in patients with obesity. This study compared weight loss outcomes and anti-obesity medication (AOM) access between patients with obesity managed through (SMAs) versus individual appointments. METHODS: Retrospective study of adults seen for obesity between September 2014 and February 2017 at Cleveland Clinic Institute of Endocrinology and Metabolism. Percent weight loss from baseline was compared between two propensity score-matched populations: patients who attended ≥1 SMA and patients managed with individual medical appointments. RESULTS: From all eligible patients identified (n=310 SMA, n=1,993 non-SMA), 301 matched pairs were evaluated for weight loss. The SMA group (n=301) lost a mean of 4.2%, 5.2% and 3.8% of baseline weight over 6, 12 and 24 months; the non-SMA group (n=301) lost significantly less weight (1.5%, 1.8% and 1.6%, respectively) (paired t-test, P<.05). All patients were eligible for US Food and Drug Administration-approved AOMs based on obesity diagnosis; however, 49.8% (150/301) of matched SMA patients were prescribed an AOM versus 12.3% (37/301) of matched non-SMA patients. CONCLUSION: This study suggests that SMAs may offer a promising alterative for obesity management and one that may facilitate greater utilization of AOMs. In propensity score-matched cohorts, SMAs were associated with greater weight loss outcomes when compared to usual care facilitated through individual medical appointments alone.

Direct, Absenteeism, and Disability Cost Burden of Obesity Among Privately Insured Employees: A Comparison of Healthcare Industry Versus Other Major Industries in the United States.

OBJECTIVE: To compare obesity-related costs of employees of the healthcare industry versus other major US industries. METHODS: Employees with obesity versus without were identified using the Optum Health Reporting and Insights employer claims database (January, 2010 to March, 2017). Employees working in healthcare with obesity were compared with employees of other industries with obesity for absenteeism/disability and direct cost differences. Multivariate models estimated the association between industries and high costs compared with the healthcare industry. RESULTS: Obesity-related absenteeism/disability and direct costs were higher in several US industries compared with the healthcare industry (adjusted cost differences of $-1220 to $5630). Employees of the government/education/religious services industry (GERS) with obesity (BMI of 30 or greater) had significantly higher odds of direct costs at the 80th percentile and above (odds ratio vs healthcare industry = 2.20; P < 0.05). CONCLUSIONS: Relative to the healthcare industry, employees of other industries, especially GERS, incurred higher obesity-related costs.

The Societal Value of Broader Access to Antiobesity Medications.

OBJECTIVE: Obesity and its complications place an enormous burden on society. Yet antiobesity medications (AOM) are prescribed to only 2% of the eligible population, even though few individuals can sustain weight loss using other strategies alone. This study estimated the societal value of greater access to AOM. METHODS: By using a well-established simulation model (The Health Economics Medical Innovation Simulation), the societal value of AOM for the cohort of Americans aged ≥ 25 years in 2019 was quantified. Four scenarios with differential uptake among the eligible population (15% and 30%) were modeled, with efficacy from current and next-generation AOM. Societal value was measured as monetized quality of life, productivity gains, and savings in medical spending, subtracting the costs of AOM. RESULTS: For the 217 million Americans aged ≥ 25 years, AOM generated $1.2 trillion in lifetime societal value under a conservative scenario (15% annual uptake using currently available AOM). The introduction of next-generation AOM increased societal value to $1.9 to $2.5 trillion, depending on uptake. Finally, societal value was higher for younger individuals and Black and Hispanic individuals compared with White individuals. CONCLUSIONS: This study suggests that AOM provide substantial gains to patients and society. Policies promoting broader clinical access to and use of AOM warrant consideration to reach national goals to reduce obesity.

Ten-year Medicare budget impact of increased coverage for anti-obesity intervention.

Aims: To estimate the long-term budget impact of expanding Medicare coverage of anti-obesity interventions among adults aged 65 and older in the US. Materials and methods: This study analyzed a representative sample of Medicare beneficiaries from the combined 2008-2016 National Health and Nutrition Examination Surveys. Population characteristics, cost and effectiveness of anti-obesity interventions, and the sustainability of weight loss in real-life were modeled to project the budgetary impact on gross Medicare outlay over 10 years. Hypothetical scenarios of 50% and 67% increases in intervention participation above base case were used to model moderate and extensive Medicare coverage expansion of intensive behavior therapy and pharmacotherapy. Results: For each Medicare beneficiary receiving anti-obesity treatment, we estimate Medicare savings of $6,842 and $7,155 over 10 years under moderate and extensive coverage utilization assumptions, respectively. The average cost of intervention is $1,798 and $1,886 per treated participant. Taking the entire Medicare population (treated and untreated) into consideration, the estimated 10-year budget savings per beneficiary are $308 and $339 under moderate and extensive assumptions, respectively. Sensitivity analysis of drug adherence rate and weight-loss efficacy indicated a potential variation of budget savings within 7% and 22% of the base case, respectively. Most of the projected cost savings come from lower utilization of ambulatory services and prescription drugs. Limitations: Due to the scarcity of studies on the efficacy of pharmacotherapy among older adults with obesity, the simulated weight loss and long-term maintenance effects were derived from clinical trial outcomes, in which older adults were mostly excluded from participation. The model did not include potential side-effects from anti-obesity medications and associated costs. Conclusions: This analysis suggests that expanding coverage of anti-obesity interventions to eligible individuals could generate $20-$23 billion budgetary savings to Medicare over 10 years.