Long-term cost-effectiveness analysis shows that IDegLira is associated with improved outcomes and lower costs compared with insulin glargine U100 plus insulin aspart in the US

Abstract

Aims: The clinical and economic impact of diabetes is growing in the US. Choosing therapies that are both effective and cost-effective is becoming increasingly important. The aim of the present analysis was to assess the long-term cost-effectiveness of IDegLira for treatment of patients with type 2 diabetes mellitus not meeting glycemic targets on basal insulin, vs insulin glargine U100 plus insulin aspart, in the US setting.

Materials and methods: Long-term projections of cost-effectiveness outcomes were made using the IQVIA CORE Diabetes Model. Clinical inputs were based on the DUAL VII trial, with costs (accounted from a healthcare payer perspective) and utilities based on published sources. Future costs and clinical benefits were discounted at 3% annually.

Results: IDegLira was associated with increased discounted life expectancy by 0.02 years and increased discounted quality-adjusted life expectancy by 0.22 quality-adjusted life years compared with insulin glargine U100 plus insulin aspart. Evaluation of direct medical costs suggested that the mean cost per patient with IDegLira was $3,571 lower than with insulin glargine U100 plus insulin aspart. The cost saving was driven predominantly by the lower acquisition cost of IDegLira compared with insulin glargine U100 plus insulin aspart, with further cost savings identified as a result of avoided treatment of diabetes-related complications. IDegLira was associated with improved clinical outcomes at a reduced cost compared with insulin glargine U100 plus insulin aspart.

Conclusions: Based on clinical trial data, the present analysis suggests that IDegLira is associated with improved clinical outcomes and cost savings compared with treatment with insulin glargine U100 plus insulin aspart for patients with type 2 diabetes not achieving glycemic control on basal insulin in the US. Therefore, IDegLira is likely to be considered dominant (cost saving and more effective) and, consequently, highly cost-effective in the US setting.

Keywords:

• Cost
• cost-effectiveness
• diabetes mellitus
• GLP-1 receptor agonist
• IDegLira
• insulin
• USA

JEL Classification Codes:

• H51
• I10

Introduction

Worldwide in 2015, healthcare expenditure related to diabetes was estimated to be $673–1,197 billion, with approximately half of this ($320–561 billion) occurring in the US alone¹. The economic impact of diabetes is expected to grow in the coming years, with expenditure globally increasing to $802–1,452 billion in 2040, and to $349–621 billion in the US¹. Treatment of diabetes-related complications makes up the majority of the total cost, at 48–64% over patient lifetimes depending on the age at diagnosis². Therefore, choosing therapies that are both effective and cost-effective is becoming increasingly important both in the US and worldwide.

Improving care for patients with type 2 diabetes receiving basal insulin represents a significant unmet need in the US, with data suggesting that 67% of patients with type 2 diabetes receiving basal insulin in the US are not achieving the treatment target of glycated hemoglobin (HbA1c) < 7.0% recommended by the American Diabetes Association^3,4. Current options for treatment intensification in these patients include up-titration of the basal insulin dose, addition of prandial insulin (such as insulin aspart) to form a basal-bolus insulin regimen, switching to pre-mixed insulin, or addition of a glucagon-like peptide 1 (GLP-1) receptor agonist to basal insulin⁵. IDegLira represents a simple treatment option for patients with type 2 diabetes uncontrolled on basal insulin.

IDegLira is a fixed-ratio combination of insulin degludec and the GLP-1 receptor agonist liraglutide in a single injection device. The fixed-ratio combination was developed to take advantage of the combined effects of a basal insulin and a GLP-1 receptor agonist on glycemic control through their complementary mechanisms of action. The use of a GLP-1 receptor agonist in combination with basal insulin reduces the increased risk of hypoglycemia and weight gain often associated with insulin therapy. Slower titration of the GLP-1 receptor agonist as part of the fixed-ratio combination reduces nausea rates compared with initiation of a GLP-1 receptor agonist alone^6,7. The safety and efficacy of IDegLira has been assessed in the DUAL trial program^8–12. Additionally, the single daily injection required with IDegLira may be a favorable treatment characteristic, as clinical inertia around initiation of more complex treatment regimens requiring multiple daily injections may represent a barrier to bringing patients to treatment targets¹³.

DUAL VII was a 26-week trial comparing the efficacy and safety of IDegLira with insulin glargine U100 plus insulin aspart. A total of 506 patients with type 2 diabetes not achieving glycemic control targets (HbA1c 7.0–10.0%) on 20–50 IU of insulin glargine U100 were enrolled¹². The aim of the present analysis was to assess the long-term cost-effectiveness of IDegLira for treatment of patients with type 2 diabetes mellitus not meeting glycemic targets on basal insulin, vs insulin glargine U100 plus insulin aspart, from a healthcare payer perspective in the US setting. IDegLira was compared with insulin glargine U100 plus three times daily insulin aspart. This approach was chosen as, while American Diabetes Association guidelines recommend addition of one dose of prandial insulin with the largest meal, this was the most common dosing schedule in DUAL VII, with 66.5% of participants in the insulin glargine U100 plus insulin aspart arm using three or more bolus insulin injections per day at the end of the study¹².

Methods

Model description

The analysis was performed using the IQVIA CORE Diabetes Model, the architecture, assumptions, features, and capabilities of which have been previously published¹⁴. The model is a validated, non-product specific diabetes policy analysis tool. It is based on a series of inter-dependent sub-models that simulate the complications of diabetes (angina, myocardial infarction, congestive heart failure, stroke, peripheral vascular disease, diabetic retinopathy, macular edema, cataract, hypoglycemia, ketoacidosis, lactic acidosis, nephropathy including end-stage renal disease, neuropathy, foot ulcer and amputation, and non-specific mortality). Each sub-model has a semi-Markov structure and uses time, state, time-in-state, and diabetes type-dependent probabilities derived from published sources. Monte Carlo simulation using tracker variables overcomes the memory-less properties of the standard Markov model, and allows interconnectivity and interaction between individual complication sub-models. Long-term outcomes projected by the model have been validated against real life data in 2004 and more recently in 2014^15,16.

In line with good practice guidance for economic evaluation of interventions for type 2 diabetes, outcomes were projected over the lifetimes of patients, in order to capture all relevant long-term complications, associated costs, and to assess their impact on life expectancy and quality-adjusted life expectancy¹⁷. Future clinical benefits and costs were discounted at 3% annually, based on health economic guidance for the US¹⁸. The approach of the analysis was consistent with previously published analyses of IDegLira in patients failing to achieve glycemic control on basal insulin^19,20.

While no formal health technology assessment agency exists in the US, the Institute for Clinical and Economic Review is a non-profit organization that is becoming increasingly influential in healthcare decision-making²¹. The Institute for Clinical and Economic Review has suggested that incremental cost-effectiveness ratios (ICERs) between $100,000–150,000 per QALY gained serve as a benchmark for a value-based price²².

Clinical data

Clinical data to inform the analysis were taken from the treat-to-target, non-inferiority DUAL VII trial (NCT02420262, https://clinicaltrials.gov/ct2/show/NCT02420262)¹². Baseline characteristics of the cohort are shown in Table 1. Treatment effects applied in the first year of the analysis were based on the 26-week end of trial data, with least-square means used to account for differences in baseline characteristics between the two treatment arms (Table 2). IDegLira and insulin glargine U100 plus insulin aspart were associated with similar reductions in HbA1c. Change in body mass index (BMI) was significantly different between the treatment arms (a reduction with IDegLira rather than an increase with insulin glargine U100 plus insulin aspart). The rate of non-severe hypoglycemic events was also significantly lower with IDegLira than with insulin glargine U100 plus insulin aspart (non-severe hypoglycemia was defined as an episode that is blood-glucose confirmed by a plasma glucose value <3.1 mmol/L [56 mg/dL] with or without symptoms consistent with hypoglycemia, but does not meet the ADA classification of a severe event).

Table 1. Baseline cohort characteristics.

	IDegLira, mean (SD)	Insulin glargine U100 plus insulin aspart, mean (SD)	Total, mean (SD)
Start age (years)	58.6 (9.0)	58.0 (8.6)	58.3 (8.8)
Duration of diabetes (years)	13.2 (7.0)	13.3 (6.8)	13.2 (6.9)
Percentage male (%)	43.7	46.1	44.9
HbA1c (%)	8.2 (0.8)	8.2 (0.8)	8.2 (0.8)
Systolic blood pressure (mmHg)	131.3 (13.1)	132.2 (13.7)	131.8 (13.4)
Total cholesterol (mg/dL)	176.5 (46.0)	170.7 (41.8)	173.6 (44.0)
HDL cholesterol (mg/dL)	46.9 (13.3)	46.3 (12.1)	46.6 (12.7)
LDL cholesterol (mg/dL)	95.5 (35.9)	93.3 (34.6)	94.4 (35.2)
Triglycerides (mg/dL)	180.1 (203.5)	161.1 (100.64)	170.6 (160.7)
BMI (kg/m^2)	31.7 (4.4)	31.7 (4.5)	31.7 (4.4)

Abbreviations. BMI, body mass index; HbA1c, glycated hemoglobin; HDL, high density lipoprotein; LDL, low density lipoprotein; SD, standard deviation.

A weighted average of the two treatment arms presented in Billings et al.¹² was used in the present analysis.

Table 2. Treatment effects applied in the first year of the analysis.

	IDegLira, mean (SD)	Insulin glargine U100 plus insulin aspart, mean (SD)
HbA1c (%)	−1.48 (0.78)	−1.46 (0.78)
Systolic blood pressure (mmHg)	−4.60 (10.95)*	−0.90 (10.95)
Total cholesterol (mg/dL)	−6.84 (32.90)*	+0.54 (32.90)
HDL cholesterol (mg/dL)	−0.19 (7.18)*	+1.53 (7.18)
LDL cholesterol (mg/dL)	−1.17 (28.29)	+2.36 (28.29)
Triglycerides (mg/dL)	−32.29 (63.82)	−24.09 (63.82)
Body mass index (kg/m^2)	−0.35 (1.27)*	+0.96 (1.27)
Severe hypoglycemia event rate (events per 100 patient years)	0.03	0.11
Non-severe hypoglycemia event rate (events per 100 patient years)	228.34*	1,091.44

Abbreviations. HbA1c, glycated hemoglobin; HDL, high density lipoprotein; LDL, low density lipoprotein.

*Statistically significant difference.

Non-severe hypoglycemia was defined as an episode that is blood-glucose confirmed by a plasma glucose value <3.1 mmol/L (56 mg/dL) with or without symptoms consistent with hypoglycemia, but does not meet the ADA classification of a severe event. Parameters listed above were derived from the DUAL VII trial¹². It should be noted that the changes presented by Billings et al. are not adjusted for differences between the IDegLira and insulin glargine U100 plus insulin aspart arms at baseline, but the estimated treatment difference presented is adjusted for these differences. The present analysis used the adjusted values for each treatment arm, reflecting the estimated treatment difference between the arms presented by Billings et al.¹². Change in HbA1c (the primary endpoint of the trial) was analyzed using a liner mixed model, with secondary continuous endpoints analyzed using a mixed model for repeated measurements (MMRM), and hypoglycemic events analyzed using a negative binomial regression model.

Patients receiving IDegLira were assumed to receive the treatment for 5 years before intensifying treatment to basal-bolus insulin therapy (this assumption was varied in sensitivity analyses). Patients in the insulin glargine U100 plus insulin aspart arm were assumed to remain on this therapy for the duration of their lifetime. Following application of the treatment effects in the first year of the analysis, systolic blood pressure, and serum lipids were assumed to follow the natural progression algorithms built into the IQVIA CORE Diabetes Model, based on the UK Prospective Diabetes Study (UKPDS) or Framingham data (as described by Palmer et al.¹⁴). The small difference in terms of HbA1c was assumed to persist for the 5 years patients received IDegLira and were abolished on treatment switching. This approach was chosen as there is growing evidence from long-term studies that, in patients with type 2 diabetes, particularly those receiving some form of insulin therapy, HbA1c remains stable and does not increase over time^23–27. The BMI and hypoglycemia benefits were also assumed to persist while patients remained on IDegLira, and were abolished on treatment intensification.

Costs and utilities

Diabetes medication resource use was based on the 26-week DUAL VII trial, with end of trial doses applied to wholesale acquisition costs to calculate the annual cost of treatment²⁸. Patients receiving IDegLira were assumed to use one needle per day. Patients receiving insulin glargine U100 plus insulin aspart were assumed to use four needles per day, as once-daily injection of insulin glargine U100 and three-times daily injection of insulin aspart was the most common dosing schedule in the DUAL VII trial. The annual cost of self-monitoring of blood glucose (SMBG) testing was based on an analysis of insurance claims in the US, and was inflated using the consumer price index for health^29,30. Following treatment intensification to basal-bolus therapy at 5 years, treatment costs were the same in both arms (matched to the insulin glargine U100 plus insulin aspart arm).

As diabetes progresses, most patients develop complications that influence their overall health-related quality-of-life. The modeling analysis captured the cost of treating diabetes-related complications in the year of the event and in subsequent years based on a literature review^31–35. Costs were inflated if necessary. As well as being associated with costs and mortality, complications result in increased morbidity. It was, therefore, important to address the utility levels associated with each of the complications modeled. Utilities were taken from published sources^14,36–39.

Sensitivity analyses

The extrapolation of clinical results by modeling the long-term consequences is associated with uncertainty. Sensitivity analyses were, therefore, performed on key parameters in the model to assess the robustness of the base case findings. The influence of time horizon on the outcomes projected by the model was investigated by running analyses over 10 and 20 years. It should be noted that a time horizon of 50 years was required for all modeled patients to have died, and, therefore, shorter time horizons did not capture all potential late-stage complications and costs. To examine the effect of discounting on cost-effectiveness outcomes, simulations were performed with (symmetric) discount rates of 0% and 6% annually. Five simulations were run to assess the key drivers of clinical benefits associated with IDegLira. In the IDegLira arm, changes in HbA1c, systolic blood pressure, serum lipids (total cholesterol, high-density lipoprotein [HDL] cholesterol, low-density lipoprotein [LDL] cholesterol and triglycerides), BMI and hypoglycemia were set to the value in the insulin glargine U100 plus insulin aspart arm in turn. This allowed the contribution of individual clinical effects to long-term health economic outcomes to be assessed. A further analysis was prepared with only statistically significant differences between the treatment arms applied (Table 2). The base case analysis used modeled outcomes to account for differences in baseline characteristics, and, therefore, a sensitivity analysis was performed with unadjusted outcomes from the DUAL VII trial applied in the two arms.

Two alternative approaches to HbA1c progression were explored. In the first, no HbA1c changes were applied following the treatment effects applied in the first year of the analysis. In the second, the UKPDS HbA1c progression equation was applied in both arms of the simulation. HbA1c increased over time in both arms of the analysis, with the HbA1c benefit in the IDegLira arm gradually reduced. Analyses were run with the upper and lower 95% confidence interval of the HbA1c change seen in the IDegLira arm of DUAL VII, with all other parameters in the IDegLira and insulin glargine U100 plus insulin aspart arms remaining unchanged. The base case analysis assumed that the BMI difference between the treatment arms was abolished on treatment switching. An alternative to this was explored in a sensitivity analysis, with the difference maintained for the duration of the analysis.

To investigate the effect of the timing of treatment switching on cost-effectiveness, simulations were performed, with the year of treatment switch to basal-bolus therapy brought forward to the end of year 3 in the IDegLira arm, pushed back to the end of year 7 in the IDegLira arm, and with no treatment switching applied.

The effect of over- or under-estimating the direct cost of treating diabetes-related complications was investigated in two scenarios. In the first, the cost of treating complications was increased by 10% and in the second the cost was reduced by 10%. The impact of applying alternative disutilities for severe and non-severe hypoglycemic events was assessed by using the values published by Currie et al.⁴⁰ (−0.0118 per severe hypoglycemic event and −0.0035 per non-severe hypoglycemic event).

To assess the impact of more frequent insulin dosing, a scenario was investigated in which 28% of patients receiving insulin glargine U100 plus insulin aspart were assumed to require twice daily basal insulin (as some patients with type 2 diabetes may benefit from splitting the basal insulin dose) based on a 5-year parallel group study of insulin glargine vs neutral protamine Hagedorn (NPH) insulin⁴¹. This incurred the cost of a further needle for subcutaneous injection and increased the total number of injections per day to five (this is further supported by the DUAL VII trial, as a number of patients in the insulin glargine U100 plus insulin aspart arm received five daily injections of insulin). An analysis was also conducted where patients receiving insulin glargine U100 plus insulin aspart required only once-daily insulin aspart, so only two needles per day (initiating basal-bolus insulin therapy with a single injection of rapid-acting insulin with the largest meal is recommended in treatment guidelines)⁵. Insulin doses in the comparator arm were assumed to remain unchanged in these analyses. To further investigate the impact of consumables on cost-effectiveness outcomes, a scenario was evaluated with costs of needles and SMBG testing excluded. The effect of the cost of basal insulin was investigated in analyses with the cost of the comparator basal insulin replaced with the cost of biosimilar insulin glargine U100 and NPH insulin in two sensitivity analyses.

In February 2014, an update to the IQVIA CORE Diabetes Model incorporating data from the UKPDS 82 was released, and an analysis using this version of the model has been conducted. While a validation study of the revised model has been published, the model proprietors suggest that the update is used in a sensitivity analysis, with the previous version being used in the base case¹⁶.

Probabilistic sensitivity analysis (PSA) was performed using the pre-defined function in the IQVIA CORE Diabetes Model. Cohort characteristics, treatment effects, and complication costs and utilities were sampled from distributions. The simulation was run using a second order Monte Carlo approach. Cohorts of 1,000 patients were run through the model 1,000 times for the PSA, as results were not subject to random statistical variation with these settings.

Compliance with ethics guidelines

This cost-effectiveness analysis was based on a previously conducted study, and does not contain any studies with human participants or animals performed by any of the authors.

Results

Base case analysis

Long-term projections of clinical outcomes suggested that IDegLira was associated with increased discounted life expectancy by 0.02 years and increased discounted quality-adjusted life expectancy by 0.22 quality-adjusted life years (QALYs) compared with insulin glargine U100 plus insulin aspart (Table 3). Improved clinical outcomes were driven by a small reduction in the cumulative incidence of the majority of diabetes-related complications and a delayed time to their onset with IDegLira. Mean time to onset of any diabetes-related complication in the modeling analysis was ∼0.1 years longer with IDegLira than with insulin glargine U100 plus insulin aspart. Benefits were observed consistently across all micro- and macro-vascular complications included in the analysis.

Table 3. Long-term cost-effectiveness outcomes.

	IDegLira, Mean (SD)	Insulin glargine U100 plusinsulin aspart, Mean (SD)	Difference
Discounted life expectancy (years)	14.33 (0.20)	14.31 (0.18)	+0.02
Discounted quality-adjusted life expectancy (QALYs)	9.55 (0.14)	9.33 (0.13)	+0.22
Discounted direct costs ($)	174,471 (2,362)	178,042 (2,174)	−3,571
ICER based on life expectancy and direct costs	IDegLira dominant
ICER based on quality-adjusted life expectancy and direct costs	IDegLira dominant

Abbreviations and symbols. $, United States dollars; ICER, incremental cost-effectiveness ratio; QALYs, quality-adjusted life years; SD, standard deviation.An intervention which is more effective than an alternative, while reducing costs is considered to be dominant over the comparator⁴².

Evaluation of direct medical costs suggested that the mean cost per patient in the IDegLira arm was $3,571 lower than in the insulin glargine U100 plus insulin aspart arm over patient lifetimes. The cost saving was driven predominantly by the lower acquisition cost of IDegLira compared with insulin glargine U100 plus insulin aspart over the first 5 years of the analysis. Further cost savings were identified as a result of avoided treatment of diabetes-related complications, particularly severe and non-severe hypoglycemic events (mean cost saving of $439 per patient due to a the mean cumulative non-severe hypoglycemic events per patient falling from 226 events with insulin glargine U100 plus insulin aspart to 186 events with IDegLira) and cardiovascular complications (mean cost saving of $299 per patient due to the cumulative incidence of cardiovascular events falling by between 0.1% and 0.8% with IDegLira compared with insulin glargine U100 plus insulin aspart).

IDegLira was associated with improved clinical outcomes at a reduced cost from a healthcare payer perspective compared with insulin glargine U100 plus insulin aspart. An intervention which is more effective than an alternative, while reducing costs is considered to be dominant over the comparator⁴². Therefore, IDegLira was considered dominant over insulin glargine U100 plus insulin aspart, and no calculation of an ICER was required (Table 3).

Sensitivity analyses

IDegLira remained dominant over insulin glargine U100 plus insulin aspart in all sensitivity analyses, except when the cost of needles and SMBG testing were not included, and when the cost of insulin glargine U100 was replaced with the cost of NPH insulin (Table 4). Exclusion of needle and SMBG costs resulted in IDegLira becoming associated with an increased cost of $886 over patient lifetimes compared with insulin glargine U100 plus insulin aspart, leading to an ICER of $4,050 per QALY gained. In the comparison with NPH insulin plus insulin aspart, IDegLira was associated with an increased cost of $5,839, resulting in an ICER of $26,699 per QALY gained. However, use of NPH insulin is very low in the US, making the probability of this scenario unlikely in most populations. Additionally, IDegLira remained dominant when compared with biosimilar insulin glargine U100 plus insulin aspart. In the analyses where IDegLira was associated with increased costs, ICERs remained well below the value based price benchmark of $100,000–150,000 per QALY gained suggested by the Institute for Clinical and Economic Review.

Table 4. Sensitivity analysis results.

Analysis	Discounted quality-adjusted life expectancy (QALYs)			Discounted direct costs ($)			ICER ($ per QALY gained)
	IDegLira	Insulin glargine U100 plus insulin aspart	Difference	IDegLira	Insulin glargine U100 plus insulin aspart	Difference
Base case	9.55	9.33	+0.22	174,471	178,042	−3,571	IDegLira dominant
20 year time horizon	8.28	8.06	+0.22	144,726	148,177	−3,451	IDegLira dominant
10 year time horizon	5.48	5.28	+0.20	89,446	93,041	−3,595	IDegLira dominant
0% discount rates	13.49	13.23	+0.26	256,548	260,288	−3,740	IDegLira dominant
6% discount rates	7.20	7.01	+0.19	127,387	130,716	−3,329	IDegLira dominant
HbA1c difference abolished	9.55	9.33	+0.23	174,592	178,042	−3,450	IDegLira dominant
Systolic blood pressure difference abolished	9.54	9.33	+0.21	174,611	178,042	−3,431	IDegLira dominant
Lipid difference abolished (total cholesterol, HDL cholesterol, LDL cholesterol and triglycerides)	9.55	9.33	+0.22	174,575	178,042	−3,467	IDegLira dominant
Body mass index difference abolished	9.50	9.33	+0.17	174,448	178,042	−3,594	IDegLira dominant
Hypoglycemia difference abolished	9.39	9.33	+0.06	174,799	178,042	−3,242	IDegLira dominant
Statistically significant differences only	9.55	9.33	+0.22	174,497	178,042	−3,545	IDegLira dominant
Observed treatment effects	9.57	9.33	+0.23	174,606	177,677	−3,071	IDegLira dominant
HbA1c benefit maintained	9.56	9.33	+0.23	174,647	178,042	−3,394	IDegLira dominant
UKPDS HbA1c creep	8.90	8.67	+0.23	175,390	178,732	−3,342	IDegLira dominant
Upper 95% CI of HbA1c change in IDegLira arm	9.56	9.33	+0.23	174,462	178,042	−3,579	IDegLira dominant
Lower 95% CI of HbA1c change in IDegLira arm	9.54	9.33	+0.21	174,631	178,042	−3,410	IDegLira dominant
Body mass index benefit maintained after treatment switch	9.57	9.33	+0.24	174,439	178,042	−3,603	IDegLira dominant
Treatment switching at 3 years in IDegLira arm	9.48	9.33	+0.15	175,874	178,042	−2,168	IDegLira dominant
Treatment switching at 7 years in IDegLira arm	9.62	9.33	+0.29	173,359	178,042	−4,682	IDegLira dominant
No treatment switching	10.00	9.33	+0.67	166,496	178,042	−11,546	IDegLira dominant
Costs of complications +10%	9.55	9.33	+0.22	175,978	179,631	−3,654	IDegLira dominant
Costs of complications −10%	9.55	9.33	+0.22	173,019	176,525	−3,506	IDegLira dominant
Alternative hypoglycemia disutilities	9.62	9.43	+0.20	174,471	178,042	−3,571	IDegLira dominant
28% of patients in insulin glargine U100 plus insulin aspart arm receiving twice daily insulin glargine U100 (IDegLira matched after intensification)	9.55	9.33	+0.22	174,918	178,679	−3,761	IDegLira dominant
Two injection per day in insulin glargine U100 plus insulin aspart arm (IDegLira matched after intensification)	9.55	9.33	+0.22	170,870	172,914	−2,045	IDegLira dominant
Needle and SMBG costs not included	9.55	9.33	+0.22	152,465	151,580	+886	4,050
Cost of NPH insulin applied in insulin glargine U100 plus insulin aspart arm (IDegLira matched after intensification)	9.55	9.33	+0.22	152,271	146,432	+5,839	26,699
Cost of biosimilar insulin glargine U100 applied in insulin glargine U100 plus insulin aspart arm (IDegLira matched after intensification)	9.55	9.33	+0.22	166,989	167,390	−400	IDegLira dominant
UKPDS 82 equations used	9.89	9.67	+0.22	182,525	185,820	−3,295	IDegLira dominant
PSA	9.25	9.02	+0.23	171,487	174,897	−3,411	IDegLira dominant

Abbreviations. $, United States dollars; CI, confidence interval; HbA1c, glycated hemoglobin; HDL, high-density lipoprotein; ICER, incremental cost-effectiveness ratio; LDL, low-density lipoprotein; NPH, neutral protamine Hagedorn; PSA, probabilistic sensitivity analysis; SMBG, self-monitoring of blood glucose; UKPDS, United Kingdom Prospective Diabetes Study.

An intervention which is more effective than an alternative, while reducing costs, is considered to be dominant over the comparator⁴².

Abolishing each of the changes in physiological parameters associated with IDegLira identified that the key drivers of improved clinical outcomes were low rates of hypoglycemia and the reduction in BMI with IDegLira (rather than the increase seen with insulin glargine U100 plus insulin aspart). Abolishing these differences between the treatment arms resulted in quality-adjusted life expectancy benefits with IDegLira falling to 0.06 and 0.17 QALYs, respectively, from the base case value of 0.22 QALYs. Applying only the statistically significant differences between the treatment arms resulted in only small changes in the projected outcomes, as did applying the unadjusted changes from baseline from the DUAL VII trial.

Changing the assumptions around treatment switching had a notable impact on the calculated health economic outcomes. Maintaining patients on IDegLira for longer increased the incremental clinical benefit and cost saving associated with IDegLira, while shortening the treatment duration had the converse effect. When no treatment switching took place, IDegLira was associated with a clinical benefit of 0.67 QALYs and a cost saving of $11,546.

Variation in other model parameters, including time horizon, discount rates, HbA1c progression, costs of treating complications, hypoglycemia disutilities and risk equations used had a relatively small impact on the calculated cost-effectiveness outcomes.

PSA with sampling around cohort characteristics, treatment effects, complication costs and utilities showed similar mean results to the base case, but increased measures of variance around the mean outcomes. Based on this analysis, and using the value-based price benchmark set by the Institute of Clinical and Economic Review of $100,000–150,000 per QALY gained, the modeling analysis indicated that there was a 96.9% probability that IDegLira would be cost-effective vs insulin glargine U100 plus insulin aspart.

Discussion

Based on clinical efficacy data from the DUAL VII trial, the present cost-effectiveness analysis found that, from a healthcare payer perspective in the US, IDegLira was dominant over insulin glargine U100 plus insulin aspart over the long-term. Sensitivity analyses identified that the conclusions were robust to changes in input parameters and modeling assumptions, with IDegLira associated with improved clinical outcomes and cost savings in the majority of scenarios investigated. IDegLira was associated with increased costs in only two scenarios, and in these ICERs remained well under $100,000 per QALY gained, which is the lower end of the value-based price benchmark suggested by the Institute for Clinical and Economic Review. In the base case analysis, IDegLira was associated with improved clinical outcomes, driven predominantly by a lower rate of hypoglycemic events and a reduction (rather than an increase) in BMI compared with insulin glargine U100 plus insulin aspart. However, changes in other risk factors, such as systolic blood pressure and serum lipids, show the multi-factorial benefits of treatment with IDegLira⁴³.

These long-term clinical benefits were achieved at a cost saving from a healthcare payer perspective. The key driver of this was the lower annual treatment costs with IDegLira compared with insulin glargine U100 plus insulin aspart. This was due to similar daily drug costs in both treatment arms, but reduced costs of needle and SMBG testing with IDegLira, leading to cost savings. This aspect of the analysis was assessed in the sensitivity analysis with needle and SMBG costs excluded, with IDegLira becoming associated with increased costs of $886 per patient. However, this sensitivity analysis is theoretical, as patients with type 2 diabetes using injectable medications will require some form of glucose monitoring (either SMBG or continuous glucose monitoring), but it shows how the treatment characteristics of IDegLira, requiring fewer injections and lower risk of hypoglycemia, can result in significant cost savings for healthcare payers. However, even when the costs of needles and SMBG testing were excluded, IDegLira was found to be cost-effective vs insulin glargine U100 plus insulin aspart. Further cost savings as a result of avoided diabetes-related complications were also identified in the IDegLira arm.

Other treatment options for patients with type 2 diabetes failing to achieve glycemic control on basal insulin include up-titration of the basal insulin dose, switching to pre-mixed insulin, and addition of a GLP-1 receptor agonist. Previously published cost-effectiveness analyses conducted using equivalent methodology to the present analysis have compared IDegLira with these interventions in the US^19,20. Compared with up-titration of insulin glargine U100, IDegLira was associated with improved clinical outcomes and increased costs, with an ICER of $63,678 per QALY gained¹⁹. This ICER is below the lower end of the value-based price benchmark of $100,000 per QALY suggested by the Institute of Clinical and Economic Review. Versus liraglutide added to basal insulin, IDegLira was associated with increased quality-adjusted life expectancy and reduced costs. The present analysis combined with the previous studies allows comparison of the cost-effectiveness of IDegLira with all available treatment options for patients failing to achieve glycemic control on basal insulin in the US. IDegLira has been shown to be either cost-effective or cost-saving compared with other treatment options.

A potential limitation of the analysis was the open-label nature of the DUAL VII study. A double-blind study was not possible due to the differing injection schedules and titration algorithms of IDegLira and insulin glargine U100 plus insulin aspart. The open-label design may have led to different expectations of the study medications, which in turn may have affected adverse event reporting and/or adherence to lifestyle recommendations. Quantifying the impact on the results of the DUAL VII study and, therefore, the present analysis is difficult. However, changes in outcomes in the IDegLira arm were similar to those observed in DUAL II and DUAL V, which also enrolled patients failing to achieve glycemic control on basal insulin^8,11.

A further limitation of the study (common to a number of health economic analyses) was the reliance on relatively short-term clinical trial data to make long-term projections. In terms of uncertainty around making long-term projections from short-term data, this remains one of the essential tenets of health economic modeling, and it remains arguably one of the best available options to inform decision-making in the absence of long-term clinical trial data. While there is always an element of doubt around the accuracy of such an approach, every effort was made in the present analysis to minimize this, primarily by using a model of diabetes that has been extensively published and validated against real-life data both on first publication and recently following a series of model updates^15,16. Projecting outcomes over patient lifetimes is recommended in guidelines for economic evaluation of interventions for patients with diabetes mellitus¹⁷.

A final limitation may be that long-term projections were made based on clinical trial data, with only a small difference in HbA1c between the IDegLira and insulin glargine U100 plus insulin aspart arms. Glycemic control, as measured through HbA1c, has been shown to influence rates of complications over the long-term, and the key drivers of cost-effectiveness in the present analysis were changes in BMI and hypoglycemic event rates, which mainly affect quality-of life over the short-term. However, the DUAL VII trial identified differences in systolic blood pressure and serum lipids between IDegLira and insulin glargine U100 plus insulin aspart. These changes, although less important than HbA1c, will also drive differences in long-term complication rates, and, therefore, projection of outcomes over patient lifetimes is worthwhile.

Conclusions

Trial data has shown that the fixed-ratio combination of IDegLira utilizes the complementary mechanisms of action of a basal insulin and a GLP-1 receptor agonist to achieve glycemic control while mitigating the risk of hypoglycemia and avoiding weight gain. The present long-term cost-effectiveness analysis suggests that IDegLira is likely to increase quality-adjusted life expectancy for patients with type 2 diabetes not achieving glycemic control on basal insulin in the US, compared with treatment with insulin glargine U100 plus insulin aspart. These improvements come at a cost saving over patient lifetimes. Therefore IDegLira is likely to be considered dominant and, therefore, highly cost-effective in the US setting.

Transparency

Declaration of funding

The present cost-effectiveness analysis was supported by funding from Novo Nordisk A/S.

Declaration of financial/other relationships

MD has received clinical research grants from Novo Nordisk and has received consulting fees from Novo Nordisk. MM is an employee of Novo Nordisk Inc. JL is an employee of Novo Nordisk Pharma Ltd and a shareholder of Novo Nordisk A/S. BH is an employee of Ossian Health Economics and Communications, which received consulting fees from Novo Nordisk A/S to support preparation of the analysis. A peer reviewer on this manuscript declares receipt of funding from Eli Lilly and Co to conduct research in the field of diabetes. The remaining peer reviewers have no conflicts of interest to disclose.

Previous presentations

The research has not been presented previously.

Acknowledgments

No assistance in the preparation of this article is to be declared.