A health economic model to assess the cost-effectiveness of OPTIFAST for the treatment of obesity in the United States

Abstract

Objectives: Obesity is associated with high direct medical costs and indirect costs resulting from productivity loss. The high prevalence of obesity generates a justified need to identify cost-effective weight loss approaches from a payer’s perspective. Within the variety of weight management techniques, OPTIFAST is a clinically recognized and scientifically proven total meal replacement Low Calorie Diet that provides meaningful results in terms of weight loss and reduction in comorbidities. The objective of this study is assess potential cost-savings of the OPTIFAST program in the US, as compared to “no intervention” and pharmacotherapy.

Methods: An event-driven decision analytic model was used to estimate payer’s cost-savings from reimbursement of the 1-year OPTIFAST program over 3 years in the US. The analysis was performed for the broad population of obese persons (BMI >30 kg/m²) undergoing the OPTIFAST program vs liraglutide 3 mg, naltrexone/bupropion and vs “no intervention”. The model included the risk of complications related to increased BMI. Data sources included published literature, clinical trials, official US price/tariff lists, and national population statistics. The primary perspective was that of a US payer; costs were provided in 2016 US dollars.

Results: OPTIFAST leads over a period of 3 years to cost-savings of USD 9,285 per class I and II obese patient (BMI 30–39.9 kg/m²) as compared to liraglutide and USD 685 as compared to naltrexone/bupropion. In the same time perspective, the OPTIFAST program leads to a reduction of cost of obesity complications of USD 1,951 as compared to “no intervention”, with the incremental cost-effectiveness ratio of USD 6,475 per QALY. Scenario analyses also show substantial cost-savings in patients with class III obesity (BMI ≥ 40.0 kg/m²) and patients with obesity (BMI = 30–39.9 kg/m²) and type 2 diabetes vs all three previous comparators and bariatric surgery.

Conclusions: Reimbursing OPTIFAST leads to meaningful cost-savings for US payers as compared with “no intervention” and liraglutide and naltrexone/bupropion in obese patients. Similar results can be expected in matching healthcare settings of other countries. Moreover, OPTIFAST has additional clinical and economic advantages through very low complication and adverse events rates.

Keywords:

• Obesity
• health economics
• model
• Optifast
• payer

JEL Classification Codes:

• I11
• I12
• I18

View correction statement:

Corrigendum

Introduction

Obesity constitutes a major public health problem of global significance¹. The number of people with obesity (BMI ≥ 30 kg/m²) has increased worldwide over the last decades². According to the World Health Organization (WHO)³, in 2014 over 600 million adults globally were obese. Remarkably, the prevalence of obesity in the US is among the highest in the world⁴. The US National Health and Nutrition Examination Survey (2015–2016) revealed that 39.8% of a nationally representative sample of the adult population was classified as obese^5,6.

Obesity is a leading cause of premature mortality, morbidity, and poorer quality-of-life⁸, with serious consequences for individuals and society^8,9. The most common and burdensome comorbidities of obesity include type 2 diabetes mellitus (T2DM) and cardiovascular disease⁸. The growing burden of obesity and associated comorbidities results in direct and indirect healthcare costs^10,11, 85% of them related to five diseases: hypertension, T2DM, coronary artery disease, hyperlipidemia, and stroke^12–14. A systematic review of 1992–2008 data estimated an additional 1,723 USD direct medical yearly cost of obesity, as compared to a person within the normal weight range¹⁵. Therefore, strategies aiming to reduce this burden should be included into public health policies. Health economic analyses providing evidence-based information of the cost-effectiveness of weight management programs may help decision-makers to choose their priorities^16–18. Although the appraisal of pharmacologic therapies by reimbursement authorities is based primarily on efficacy and safety outcomes of traditional clinical trials, reimbursement decisions are often driven by health economic data (cost-effectiveness and budgetary impact). Health economic data are progressively gaining importance for nutritional solutions, especially in cases of comparisons with pharmacologic therapies or surgical procedures like obesity management.

The OPTIFAST program is a medically supervised weight loss program for individuals with obesity or overweight in the presence of comorbidities. The OPTIFAST program has been proven effective in achieving acute and sustained weight loss and reduction of clinical complications of obesity in clinical studies since the 1980s^19–22. However, current data on the cost-effectiveness of OPTIFAST are missing, and such data could provide payers with better insights into the efficiency of the program. The objective of this health economic model is, therefore, to estimate cost-savings achievable with the OPTIFAST program and obtained with a reduction in medical costs for payers in the US healthcare setting.

Methods

Frameworks

An event-driven decision analytic model has been built to estimate the cost-effectiveness of the OPTIFAST program in the US healthcare setting. The analysis has been performed for individuals with class I and II obesity (BMI = 30–39.9 kg/m²) without T2DM. Scenario analyses included individuals with class III obesity (BMI ≥ 40 kg/m²) and patients with class I and II obesity (BMI = 30–39.9 kg/m²) and T2DM. Data sources included published literature, clinical trials, published US healthcare costs, and national population statistics. The primary perspective of the study is the third party payer and the costs used in the model are expressed in 2016 USD.

Model design

To perform the cost-effectiveness analysis of the OPTIFAST program, the authors have chosen a cost-minimization approach corresponding with financial accounting systems of the payers. An event-driven decision tree model estimates the monetary outcomes of the OPTIFAST program on obesity treatment. The choice of model design was based on: (1) results of clinical trials, in terms of weight loss and BMI improvement, (2) clinical guidelines on the treatment of obesity and its complications, and (3) available clinical and economic data that determine the complexity and validity of the model.

Figure 1 shows the structure of the model. The first node in the model reflects the populations in the model:

1. a broad population of subjects with class I and II (BMI = 30–39.9 kg/m²) obesity with initial BMI = 35 kg/m² (base case analysis);

2. a narrower population of individuals with class III obesity (BMI ≥ 40 kg/m²) with initial BMI = 45 kg/m² (scenario analysis); and

3. a population of patients with obesity (BMI = 30–39.9 kg/m²) and T2DM, with initial BMI = 35 kg/m² (scenario analysis).

Figure 1. Structure of the model used in the analysis.

The second node reflects the choice of obesity treatment: patients with class I and II obesity may receive OPTIFAST or pharmacologic therapy with liraglutide 3 mg or naltrexone/bupropion, while patients with class III obesity and those with T2DM may also undergo bariatric surgery according to the current guidelines. The model also includes “no intervention”.

The next node in the model describes the therapeutic outcome and allows two options:

• BMI reduction: a proportion of subjects who achieve a significant weight loss and BMI reduction with the OPTIFAST or comparator treatment. Although all the subjects with obesity may develop complications, the probability is lower among patients who achieve weight loss (responders) than in subjects who do not achieve weight loss (non-responders).

• No BMI reduction: A proportion of individuals will not lose weight (non-responders) and will not achieve any reduction in BMI. The risk of obesity complications in this group of patients remains constant.

After initial weight loss (and BMI reduction) patients may regain weight (with corresponding BMI increases), which would again raise the probability of complications. In the described model we have chosen the complications of obesity as key health economic events, while weight loss itself has not been considered to have clinical or economic consequences. Clinical trials in the weight management field provide primary clinical outcomes in terms of either weight loss or a BMI decrease. In the model we have included the direct relationship between BMI and risk of complications from the published evidence. Finally, we have chosen “BMI reduction” instead of “weight loss” because most of the economic literature reports economic outcomes based on BMI instead of body weight²³.

The sub-model for patients with obesity and T2DM includes diabetes complications. We assume that patients who have experienced T2DM remission along with body weight and BMI decrease have the same risk of developing complications as obese patients who never have had T2DM.

Perspective and time horizon

The analysis has been performed from a healthcare payer’s perspective in the US in 2016, considering a 3-year time horizon, that corresponds with their usual budgeting horizon. The extrapolation to a longer time perspective may not be relevant for our target audience and may increase the uncertainty associated with extrapolation of a long-term sustained effect of the obesity treatments. However, for the purpose of illustration, scenario analyses using 5- and 10-year time horizons have been added.

Economic outcomes

The model includes medical costs of obesity interventions (OPTIFAST, liraglutide, naltrexone/bupropion, and bariatric surgery), costs of the complications of each treatment, and costs of complications of obesity and T2DM. Costs used in the model are expressed in 2016 USD and adjusted to 2016 costs by using an inflation correction, where appropriate. Since the model’s time horizon was longer than 1 year, an annual discount rate of 5% was applied to costs and effects²⁴.

Data sources

General

The data used in a modeling study can be categorized into transition probabilities (e.g. reduction of obesity), healthcare utilization (e.g. drugs, consultations), and prices and tariffs. Data sources for the variables used in a model may originate from clinical trials, published review articles and meta-analyses, databases, and official tariff lists of allowable reimbursements. For clinical outcomes, the general assumption is that data are not country-specific and may be derived from studies performed outside the US.

Probabilities

Incidence complications due to overweight/obesity

The report prepared for the Health Research Council of New Zealand from 2010 provides gender- and age-specific data on annual incidence of complications and mortality in overweight and obese patients²³. We selected a specific age cohort of 40 years, based on epidemiology data from various clinical studies^13,25,26.

Table 1 shows the relative risks used in the model. Most of these data originate from the New Zealand report providing the most recent and detailed clinical data on the large number of complications of overweight and obesity, while most of the published literature has been focusing mainly on myocardial infarction and stroke. Missing data were derived from other publications (as stated); those have been transformed into a similar format as the New Zealand report data.

Table 1. Relative risks for complications in overweight and obese subjects (age 40) compared to normal weight subjects.

Complication	Overweight		Obese
	Male	Female	Male	Female
Myocardial infarction	1.40	1.48	2.21	2.47	New Zealand^23
Angina pectoris	1.16	1.23	1.46	1.52	Guh et al.^8
Chronic heart failure	1.19	1.22	1.50	1.58	New Zealand
Other chronic heart disease	1.48	2.21	2.21	2.47	New Zealand
Stroke	1.09	1.11	1.23	1.27	New Zealand
Hypertension	2.37	2.31	3.21	3.25	McPherson et al.^27
Diabetes	3.06	3.06	14.04	13.1	New Zealand
Osteoarthritis	2.03	2.03	5.40	5.40	New Zealand
Arthrosis hip	2.03	2.03	5.40	5.40	New Zealand
Arthrosis knee	1.23	1.23	1.63	1.63	New Zealand
Dorsopathy (spinal column disease)	1.18	1.18	1.48	1.48	New Zealand
Cancer rectum	1.13	1.13	1.28	1.33	New Zealand
Cancer colon	1.24	1.24	1.56	1.65	New Zealand
Cancer breast	1.07	1.00	1.00	1.16	New Zealand
Cancer prostate	1.00	1.35	1.35	1.00	New Zealand
Cancer kidney	1.51	1.51	2.67	2.67	New Zealand
Cancer endometrium	1.59	1.59	1.00	2.52	New Zealand
Cancer esophagus	1.00	1.11	0.99	1.02	Guh et al.^8
Cancer pancreas	1.13	1.20	1.87	1.36	Guh et al.^8
Gall bladder disease	1.09	1.68	1.47	2.36	Picot et al.^28^,^29
Back pain	1.41	1.53	2.29	2.40	Guh et al.^8
Asthma	1.06	1.21	1.16	1.52	Guh et al.^8
Pulmonary embolism	1.69	1.84	2.86	2.99	Guh et al.^8
Coronary artery disease	1.14	1.74	1.40	2.64	Guh et al.^8

Table 2. Probabilities of efficacy (remission of obesity).

Year	BMI (kg/m^2)
	No intervention	OPTIFAST^20^,^30	Liraglutide 3 mg^36^,^37	Naltrexone-bupropion^42^,^43
Year 1	35.00	35.00	35.00	35.00
Year 2	35.00	28.64	32.26	32.81
Year 3	35.00	32.00	32.77	32.88
Year 4	35.00	32.56	33.18	32.95
Year 5	35.00	32.87	33.52	33.02

OPTIFAST

Bischoff et al.²⁰ determined the effectiveness of the OPTIFAST program composed of a 12-week low-calorie total meal replacement diet followed by a transition and maintenance phase up to 52 weeks intended to stabilize weight and avoid weight regain. Additional interventions included nutritional education, physical activity, and behavioral training. A total of 8,296 participants with an average BMI of 43 kg/m² were included in the program in 8.5 years. After 1-year intervention the initial BMI decreased by 7.0 in women and by 8.0 in men²⁰. A study by Wadden and Frey³⁰ assessed long-term weight loss achieved with the OPTIFAST program in 621 subjects with obesity. According to the WHO definition of successful weight loss (10% loss of initial body weight), the grand majority of participants (81% according to per protocol and 64% according to intention to treat analyses) were successful after 1 year of treatment. At 3-year follow-up, 53% of the original population maintained a weight loss of ≥5%, and 35% of patients maintained a weight loss of ≥10%.

The base-case analysis is based on data from Bischoff et al.²⁰ that provides the biggest sample size (8,296 subjects) as compared to other studies. The average initial BMI of 43 kg/m² corresponds to class III obesity. The Wadden and Frey³⁰ study has a mean initial BMI of 40.8 kg/m², and provides long-term data. Therefore, the model uses short-term and long-term data from the Bischoff et al. and Wadden and Frey studies. BMI values from the clinical trials are adjusted linearly to an initial BMI of 35 and 45 kg/m² for class I + II and class III obese patients, respectively.

Liraglutide

Liraglutide 3 mg (Saxenda) was approved for the treatment of obesity in 2014^31,32. The product license requires an achievement of 5% weight loss after the initial 12 weeks of treatment. If a patient does not reach this target, the drug should be discontinued at week 16^33–35. The efficacy and safety of the drug have been assessed in three randomized controlled trials (RCTs): SCALE-Maintenance³⁶, SCALE-Obesity³⁷, and LEADER^38–40.

Pi-Sunyer et al.³⁷ conducted a 56-week, double-blind trial including 3,731 patients without T2DM and with BMI ≥ 30 kg/m² or a BMI ≥ 27 kg/m² with dyslipidemia or hypertension. At week 56, patients in the liraglutide 3 mg group had lost on average 3.0 BMI units (kg/m²), and those in the placebo group had lost on average 1.0 BMI unit. Wadden³⁶ assessed the efficacy of liraglutide 3 mg on maintaining weight loss achieved with a low-calorie diet over 48 weeks. The BMI values from the clinical trials have been adjusted linearly to an initial BMI of 35 and 45 kg/m² for, respectively, class I + II and class III obesity.

Substantially higher incidence of adverse effects in the liraglutide 3 mg arm has been reported as compared to placebo (nausea: 40.2% vs 14.7%, diarrhea: 20.9% vs 9.3%, vomiting: 16.3% vs 4.1%, and dyspepsia: 9.5% vs 3.1%); the data have been included in the model. The Wadden study also found a higher incidence of gastrointestinal disorders with liraglutide³⁶.

Naltrexone-bupropion

Naltrexone-bupropion combination was first approved for obesity treatment in the US in 2014 (Contrave)⁴¹. Greater weight loss was observed with naltrexone-bupropion vs placebo at week 28 (6.5% vs 1.9%) and week 56 (6.4% vs 1.2%) (p < .001)⁴². Another 56-week randomized placebo-controlled trial examined the efficacy and safety of naltrexone-bupropion in addition to intensive behavior modification (BMOD). At week 56, patients achieved a 5.1% initial body weight loss with placebo + BMOD vs 9.3% weight loss with naltrexone-bupropion + BMOD (p < .001)⁴³.

Bariatric surgery

Clegg et al.^13,14 assessed the clinical and cost-effectiveness of surgical interventions for patients with morbid obesity in a systematic review of RCTs, prospective clinical trials, and economic evaluations. As comped with non-surgical interventions, bariatric surgery resulted in significantly greater weight loss (of additional 23–37 kg) reported 8 years after surgery. Although a 2.2% re-intervention rate was reported⁴⁴ we have not included reoperations in the model.

T2DM

The study by Bischoff et al²⁰ showed a 63.6% T2DM remission rate in patients who completed the OPTIFAST program. In a liraglutide clinical trial, a remission on diabetes was not reported, but the prevalence of pre-diabetes decreased from 61.4% to 30.8%, which can be interpreted as a remission rate of 50%. Although we used remission of pre-diabetes as an approximation for remission of diabetes, it may actually over-estimate the effectiveness of liraglutide in this model³⁷. The naltrexone-bupropion clinical trials did not provide data on remission of T2DM; therefore, we have not included any T2DM remission for naltrexone-bupropion in the model^42,43.

Mortality

The base case analysis does not include mortality, because of the limited 3-year time horizon used in the model. A scenario analysis based on mortality data from the New Zealand report showed an increased risk of mortality in overweight and obese patients²³.

Costs

The OPTIFAST US program consists of 12 weeks diet with total meal replacement (5 servings per day), and two subsequent phases of transition to a food based diet for 12 weeks at 2–3 servings a day and the following 24 weeks at 1 serving a day. The complete OPTIFAST program requires nearly 800 servings of OPTIFAST with ex-factory cost for payers of USD 1,500 and an additional USD 3,000 for the weight management program.

For liraglutide (annual ex-factory cost USD 13,848) we assume that, after 16 weeks, only responders (63.2%) continue the pharmacologic therapy⁴⁵. The base case analysis assumes three physician office visits during the first year and one visit per year in subsequent years based on the schedule for medical management after bariatric surgery. The three physician visits during the first year consist of the first visit for diagnosis and initial liraglutide prescription, the second visit after 16 weeks to check if the patient is responding to the pharmacologic therapy (weight loss of at least 5% is required to continue the prescription), and one control visit after 36 weeks. It can be considered a conservative approach. The cost of consultation is USD 200, including the cost of a complementary program for diet and exercise. Adverse events for liraglutide are those reported in the literature (nausea = 40.2%, diarrhea = 20.9%, vomiting = 16.3%, and dyspepsia = 9.5%)³⁷. The base case analysis assumes one visit for each adverse event.

Patients with obesity undergoing naltrexone-bupropion therapy (annual ex-factory cost of USD 2,892) should only continue the treatment if 5% loss of initial body weight is achieved within the initial 16 weeks of treatment. As the total occurrence of adverse events summed up to more than 100%, the assumption is that, on average, every patient experienced at least one adverse event on naltrexone-bupropion therapy, e.g. headache = 23.8%, nausea = 34.1%, vomiting = 11.0%⁴³. The base case analysis assumes one physician’s visit for each adverse event.

The cost of bariatric surgery and complications of USD 25,854 in 2013 has been updated to 2016⁴⁶. The base case analysis assumes three physician visits during the first year and one visit every year thereafter for medical management after surgery.

Complications of obesity

Table 3 shows the costs of complications of obesity and T2DM in 2016, some of them occurring in both diseases. The probabilities of complications are higher for T2DM patients than for obese patients without diabetes, but we assumed the same complication costs. The main source was a US publication by Ward et al⁴⁷. For some of the complications and in the case of missing information from the US, annual costs from New Zealand were applied, assuming the same ratio of cost of chronic illness to general healthcare costs in New Zealand and in the US. We used cost of cardiovascular events from New Zealand and the US to calculate the ratio for the missing US costs estimate.

Table 3. Costs of complications of obesity and T2DM.

Complication		Cost in first year (USD) (event)	Cost in other years (USD) (state)	Source
AMI	T2DM	56,445	1,904	Ward et al.^47
Angina	Obesity, T2DM	21,406	1,904	Ward et al.^47
CHF	Obesity, T2DM	23,758	1,904	Ward et al.^47
Chronic heart failure	Obesity, T2DM	23,758	1,904	Ward et al.^47
Stroke	Obesity, T2DM	42,119	15,541	Ward et al.^47
Hemodialysis	T2DM	71,714	71,714	Ward et al.^47
Peritoneal dialysis	T2DM	71,714	71,714	Ward et al.^47
Renal transplantation	T2DM	71,714	71,714	Ward et al.^47
Major hypoglycemic event	T2DM	16,478	0	Ward et al.^47
Minor hypoglycemic event	T2DM	1,311	0	Ward et al.^47
Ketoacidosis	T2DM	176	0	Ward et al.^47
Cataract	T2DM	6,980	2,720	Ward et al.^47
Blindness	T2DM	2,862	2,862	Ward et al.^47
Neuropathy	T2DM	878	1,101	Ward et al.^47
Amputation	T2DM	9,041	0	Ward et al.^47
Gangrene	T2DM	2,147	0	Ward et al.^47
Infected ulcer	T2DM	2,147	0	Ward et al.^47
Uninfected ulcer	T2DM	2,147	0	Ward et al.^47
Healed ulcer	T2DM	2,147	0	Ward et al.^47
ACS	T2DM	21,406	1,904	Ward et al.^47
TIA	Obesity, T2DM	7,338	179	Ward et al.^47
Peripheral artery disease	Obesity, T2DM	126	126	Ward et al.^47
Polyneuropathy	T2DM	878	878	Ward et al.^47
Hypertension	T2DM	434	434	Ward et al.^47
Diabetes	Obesity	6,257	6,257	Ward et al.^47
Arthrosis hip	Obesity	878	1,101	Assume neuropathy
Arthrosis knee	Obesity	878	1,101	Assume neuropathy
Dorsopathy (spine disease)	Obesity	878	1,101	Assume neuropathy
Cancer rectum*	Obesity	3,400	3,400	NZ data I NZUSD**
Cancer colon*	Obesity	3,600	3,600	NZ data I NZUSD**
Cancer breast*	Obesity	1,690	1,690	NZ data I NZUSD**
Cancer prostate*	Obesity	2,300	2,300	NZ data I NZUSD**
Cancer kidney*	Obesity	2,150	2,150	NZ data I NZUSD**
Cancer endometrium*	Obesity	2,567	2,567	NZ data I NZUSD**
Gall bladder disease	Obesity	1,025	1,025	Assume neuropathy
Back pain	Obesity	878	878	Assume neuropathy
Asthma	Obesity	1,904	1,904	Assume angina
Pulmonary embolism	Obesity	6,327	0	Assume TIA
Cancer pancreatitis	Obesity	3,600	3,600	NZ data I NZUSD**, cancer colon
Cancer esophagus	Obesity	3,600	3,600	NZ data I NZUSD**, cancer colon

*age of 40; **NZ, New Zealand data.

Results

Base case analysis

Table 4 shows the results per patient with class I or II obesity over 3 years. OPTIFAST reduces costs of obesity complications from USD 9,382 to USD 7,431 (generating USD 1,951 saving) vs “no intervention”, leading to only USD 2,549 additional cost for the payer, but yielding higher quality-of-life for patients resulting from fewer obesity complications.

Table 4. Cost of interventions, per patient with obesity class I–II, 3-year perspective.

Treatment 3-year	Costs					Savings with OPTIFAST
	Treatment	Extra	Complications		Total
			Treatment	Obesity
No intervention	0	0	0	9,382	9,382	–2,549
OPTIFAST	1,500	3,000	0	7,431	11,931
Naltrexone-bupropion	2,892	937	237	8,523	12,589	658
Liraglutide	11,695	937	206	8,378	21,216	9,285

Treatment costs: ex factory costs of OPTIFAST product, liraglutide and naltrexone-bupropion; Extra costs: costs of the OPTIFAST weight management program and doctors’ visits for liraglutide and naltrexone-bupropion.

When compared to liraglutide, OPTIFAST reduces the costs of obesity complications from USD 8,378 to USD 7,431. Including costs of the OPTIFAST program and liraglutide raises the overall cost saving to USD 9,285 per covered patient.

Finally, OPTIFAST is associated with a major reduction of obesity complications and relative costs (USD 8,523) as compared to naltrexone-bupropion (USD 7,431), generating an estimated cost-saving of USD 658 over 3 year time.

Scenario analyses

Figure 2 shows the results of the scenario analyses, involving longer time horizons of 5 and 10 years per patient with class I–II obesity. In particular, the 10-year time horizon confirms payers’ cost savings resulting from reimbursing of OPTIFAST as compared to other interventions and “no treatment” (USD 4,030 additional costs with “no intervention” as compared to USD 1,951 over a 3-year period). Figure 3 illustrates the results of two further scenario analyses, in narrower populations: (1) patients with class III obesity and (2) patients with obesity and T2DM.

Figure 2. Scenario analyses for subjects with class I–II obesity with different time horizon (costs in USD).

Figure 3. Scenario analyses per patient with (a) class III obesity, and (b) per patient with class I–II obesity with T2DM in 3-year time horizon (costs in USD).

Remarkably, in patients with obesity and T2DM, the OPTIFAST program demonstrates more pronounced cost-savings vs all three previous comparators and vs bariatric surgery, which represents an additional therapeutic option according to the guidelines.

Discussion

In this study, a decision analytic model is used to estimate the cost-effectiveness of OPTIFAST from a third party payer perspective in the US (2016 USD).

In patients with class I–II obesity, the cost for OPTIFAST is nearly offset by the reduction in costs achieved due to a lower rate of obesity complications, from USD 9,382 to USD 7,431 per patient vs “no intervention” over 3 years. This reduction in complication frequency also results in better patients’ quality-of-life. When compared to liraglutide and naltrexone-bupropion, OPTIFAST leads to a total cost saving of USD 9,285 and USD 658 per patient, respectively, in a 3-year period.

In patients with class III obesity, bariatric surgery is USD 22,651 more expensive than OPTIFAST. A scenario analysis reveals that mortality has a minimal impact on the results of the model, given the low short-term mortality rate. Therefore, the base case analysis, excluding mortality, can be easily used for annual budgeting purposes for payers. Interestingly, the model reveals an increase in cost savings achieved with OPTIFAST, with a longer time horizon of up to 10 years. OPTIFAST also leads to remarkable cost savings in patients with obesity and T2DM vs all comparators, varying from USD 12,125 (liraglutide), to USD 1,739 (naltrexone-bupropion) and USD 3,980 (“no intervention”).

In this study, an event-driven decision analytic model is used to estimate the cost-effectiveness of OPTIFAST in the healthcare setting in the US. The model provides only monetary outcomes corresponding with the financial models of payers. However, the reduction in the costs of complications by OPTIFAST vs all comparators implicitly means that OPTIFAST also reduces the burden of disease due to fewer complications, thereby increasing patients’ quality-of-life. In summary, OPTIFAST is cost-effective vs liraglutide and naltrexone-bupropion, as it leads to overall cost savings; lower costs and a gain in Quality Adjusted Life Years (QALYs).

For adverse events we validated our assumptions additionally with the clinical experts participating in this study. However the exclusion of adverse events had only a minor impact on the study outcomes.

A QALY is calculated by combining the number of years lived with the quality-of-life measured with specific tools. One year lived in perfect health is equal to 1 QALY, while a patient has a QALY between zero and one. The US society threshold of willingness to pay for a new innovative, medicinal product is ∼ USD 50,000 per QALY. A scenario analysis was based on the inclusion of lower QALYs for the complications of obesity. The base case analysis leads to additional costs of only USD 2,549 vs “no intervention”, but a gain in QALYs of 0.394. This leads to an incremental cost-effectiveness ratio of USD 6,475 per QALY, which is far below the usual US threshold of USD 50,000, making OPTIFAST a cost-effective therapeutic option vs “no intervention”. As US society is willing to pay up to USD 50,000 for a gain of one QALY, OPTIFAST is extremely cost-effective.

Cost-savings in this analysis are much higher than the estimates reported by Willis et al.⁴⁸, who modeled the economic benefits of losing 10 pounds in a hypothetical cohort of patients with T2DM with a mean baseline BMI of 33.4 kg/m². The results showed direct cost-savings of USD 613 over an average of 14.6 years of survival, mainly due to a lower incidence of chronic heart failure. The advantage of our model is that it includes all obesity complications, and T2DM complications for diabetic patients, which may explain the higher cost-savings in our study.

The model is based on assumption that weight loss leads to a reduction of the complications of obesity. Some observational studies showed that weight regain may not be associated with adverse effects on body composition or fat distribution⁴⁹. However, recent findings from studies of experimental weight cycling have reinforced the notion that fluctuations of cardiovascular risk variables (such as blood pressure, heart rate, sympathetic activity, blood glucose, lipids, and insulin) with probable repeated overshoots above normal values during periods of weight regain put an additional stress on the cardiovascular system^50,51.

Some other research have proved the link between rising rates of obesity and increased medical spending. Finkelstein et al.⁵² demonstrated the extent to which excess weight increased annual medical spending for public and private payers alike. That study estimated the costs of overweight and obesity in 1998 being as high as US$78.5 billion; nearly half of this amount was financed by Medicare and Medicaid. In another study, Finkelstein et al.⁵³ quantified per capita and aggregate medical expenditures associated with overweight and obesity. They performed a cross-sectional analysis of the 2006 Medical Expenditure Panel Survey and the 2008 National Health and Wellness Survey. The annual medical cost per capita raised from USD 148 in overweight to USD 475 in grade I obesity, USD 824 in grade II obesity, reaching USD 1,269 in grade III obesity.

This cost-minimization model provides monetary outcomes to correspond with the financial models of payers. OPTIFAST was found to be cost saving overall in most analyses as compared to other treatment options. These cost savings are due to a lower incidence of complications of obesity, which also improves patients’ quality-of-life. The increase in quality-of-life with OPTIFAST has been shown in previous studies; for example, in the large-scale prospective single-arm study by Bischoff et al.²⁰, a 52-week OPTIFAST program resulted in a significant improvement in health-related quality-of-life (based on the SF-36, physical and psychological functioning) as compared to the baseline. The improvement in quality-of-life parameters were sustained at 3 years follow-up.

In the US alone, the annual cost of obesity is estimated from 98 billion to 147 billion USD^15,54. In 2008, 147 billion dollars spent in healthcare was attributable to obesity, accounting for 9.1% of all US health expenditures⁵⁴. Moreover it has been estimated that, by 2030, if the current prevalence of obesity persists, total healthcare costs attributable to obesity could reach 861–957 billion USD and absorb 16–18% of US health expenditure⁵⁵. In this context, even marginal cost savings at a patient level can lead to huge cost savings at the population level. Considering the latest obesity prevalence estimate from 2013/2014 at 37.7%⁵⁶, we can hypothesize that one dollar saved per patient every year would lead to USD 123 million in cost savings (37.7% of 325 million inhabitants). For example, OPTIFAST leads over 5 years to USD 1,092 cost savings per patient compared with naltrexone-bupropion, which would translate into a 26.9 billion dollar annual saving. Compared to liraglutide, OPTIFAST would lead to 5-year savings of USD 7,704 per patient, leading to 189.5 billion in annual savings.

Estimates indicate that 50–60% of total costs of obesity are indirect costs (e.g. due to premature mortality and productivity loss)⁵⁷. A reduction in obesity complications will also decrease those indirect costs, which we will explore from the perspective of the employer in further research.

Finally, indirect costs due to productivity loss are not included in this analysis focused on the payer perspective. Taking into consideration a broader, societal perspective, and adding the indirect costs of obesity and its complications would further improve the cost-effectiveness of OPTIFAST vs the comparators.

Conclusion

The results show that the OPTIFAST program leads to a reduction in the costs of obesity complications for third party payers in the US, as compared to “no intervention”, liraglutide or naltrexone-bupropion in patients with class I and II obesity. Cost savings in class III obese patients and patients with T2DM are even more meaningful than in the non-diabetic population, and further increase when a longer time horizon is used. In patients with class III obesity, OPTIFAST leads to lower healthcare costs, even if compared with bariatric surgery. Moreover, OPTIFAST has additional clinical and economic advantages that result from very few and mild adverse events. Hence, we conclude that the OPTIFAST program, leading to significant savings from a payer perspective, should be reimbursed in the US as a preferred choice of weight management treatment compared with “no intervention” and pharmacotherapy.

Transparency

Declaration of funding

The study was funded by Nestlé Health Science.

Declaration of financial/other relationships

All authors are employed by Nestlé Health Science, except MN, who received a consultancy fee. JME peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Acknowledgements

None reported.