Cost-effectiveness of sensor-augmented pump therapy versus standard insulin pump therapy in patients with type 1 diabetes in Denmark

Accepted Manuscript Cost-effectiveness of sensor-augmented pump therapy versus standard insulin pump therapy in patients with type 1 diabetes in denmark S. Roze, S. de Portu, J. Smith-Palmer, Alexis Delbaere, W. Valentine, M. Ridderstråle PII: DOI: Reference:

S0168-8227(16)30266-2 http://dx.doi.org/10.1016/j.diabres.2017.02.009 DIAB 6865

To appear in:

Diabetes Research and Clinical Practice

Received Date: Revised Date: Accepted Date:

25 July 2016 9 January 2017 7 February 2017

Please cite this article as: S. Roze, S. de Portu, J. Smith-Palmer, A. Delbaere, W. Valentine, M. Ridderstråle, Costeffectiveness of sensor-augmented pump therapy versus standard insulin pump therapy in patients with type 1 diabetes in denmark, Diabetes Research and Clinical Practice (2017), doi: http://dx.doi.org/10.1016/j.diabres. 2017.02.009

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COST-EFFECTIVENESS OF SENSOR-AUGMENTED PUMP THERAPY VERSUS STANDARD INSULIN PUMP THERAPY IN PATIENTS WITH TYPE 1 DIABETES IN DENMARK

Authors:

a

b

c

b

c

Roze S , de Portu S , Smith-Palmer J , Alexis Delbaere ,Valentine W , Ridderstråle Md

Affiliations:

a

HEVA HEOR, Lyon, France

b

Medtronic International Sàrl, Tolochenaz, Switzerland

c

Ossian Health Economics and Communications, Basel, Switzerland

d

Steno Diabetes Center, Niels Steensens Vej 2-4, DK-2820, Gentofte, Denmark Corresponding author:

Dr Jayne Smith-Palmer Ossian Health Economics and Communications GmbH Bäumleingasse 20, 4051 Basel, Switzerland

Telephone:

+41 61 271 6214

E-mail:

[email protected]

Running header:

Cost-effectiveness of SAP in Denmark

Grant support:

This study was supported by funding from Medtronic International Sàrl.

ABSTRACT Aims The use of continuous subcutaneous insulin infusion (CSII) in type 1 diabetes (T1D) has increased in recent years. Sensor-augmented pump therapy (SAP) with low glucose suspend (allowing temporary suspension of insulin delivery if blood glucose level falls below a pre-defined threshold level) provides additional benefits over CSII alone, but is associated with higher acquisition costs. Therefore, a costeffectiveness analysis of SAP versus CSII in patients with T1D was performed. Methods Analyses were performed using the CORE Diabetes Model in two different patient cohorts in Denmark, one with hyperglycemia at baseline and one with increased risk for hypoglycemic events. Clinical input data were sourced from published data. The analysis was performed over a lifetime time horizon from a societal perspective. Future costs and clinical outcomes were discounted at 3% per annum. Results In patients who were hyperglycemic at baseline the use of SAP versus CSII resulted in improved quality-adjusted life expectancy (12.44 versus 10.99 quality-adjusted life years [QALYs]) but higher mean lifetime costs (DKK 2,027,316 versus DKK 1,801,293) leading to an incremental cost-effectiveness ratio (ICER) of DKK 156,082 per QALY gained. For patients at increased risk for hypoglycemic events the ICER for SAP versus CSII was DKK 89,868 per QALY gained. Conclusions In Denmark, the use of SAP is likely to be considered cost-effective relative to CSII for patients with T1D who are either hyperglycemic despite CSII use or who experience frequent severe hypoglycemic events. Key words

2

Cost; cost-effectiveness; sensor-augmented pump therapy; type 1 diabetes; hyperglycemia; hypoglycemia; Denmark Word count 236

3

INTRODUCTION In Denmark, there are approximately 30,000 people with type 1 diabetes (T1D) [1] and in 2010 the incidence of T1D amongst children aged 0–14 years was 22 per 100,000 persons, which is one of the highest incidence rates in Europe.[2] T1D is associated with a risk of long-term diabetes-related complications including cardiovascular and renal disease as well as ophthalmic complications. Patients with T1D have an elevated mortality risk compared with the general population, largely due to diabetes-related complications. Moreover, as a chronic condition T1D is associated with a considerable economic burden over patient lifetimes. For example, in Denmark in 2011, annual per patient spending for patients with diabetes (including T1D and T2D patients) was estimated at USD 6,648 (approx. DKK 43,500 [June 2016 exchange rate]).[3]

In Denmark, all patients with T1D are managed in hospital outpatient clinics. After diagnosis, treatment is typically initiated in the form of multiple daily injections (MDI) of insulin. However, some patients do not achieve adequate glycemic control on MDI, and for these patients continuous subcutaneous insulin infusion (CSII), or insulin pump therapy, is indicated. CSII is also indicated for patients who experience frequent severe hypoglycemic events and/or have impaired awareness of hypoglycemia as well as for children who experience difficulties with insulin injections.[3] CSII has been shown to improve glycemic control in patients who struggle to achieve HbA1c targets on MDI. Moreover, this improvement is sustained over several years.[4] Recent long-term (>6 years) data from Sweden has shown that the incidence of cardiovascular disease and all-cause mortality is reduced in T1D patients on CSII versus those on MDI.[5] In Denmark, HbA1c in T1D patients aged 0–15 years was significantly better with CSII than MDI and was sustained over a follow-up period of >5 years.[6] The use of insulin pumps in children and adolescents in Denmark increased substantially from <5% in 2005 to 50% in 2011.[6] Pump use in adult T1D patients is lower at an estimated 7%,[7] although this is subject to substantial local variation with a single center study estimating pump use in adults as

4

high as 16%;[8] a recent data in adults with type 1 diabetes in Denmark have also shown CSII to be associated with clinically significant improvements in HbA1c, but no significant change in weight at 1 year after transition from MDI.[9]

Sensor augmented pump therapy (SAP) couples continuous glucose monitoring (CGM) with CSII and has also been shown to improve HbA1c in T1D patients as well as reducing both the frequency and magnitude of glycemic excursions.[10,11,12] Some SAP devices are also equipped with a suspend before low feature that automatically suspends insulin delivery for up to 2 hours if blood glucose levels fall below a pre-defined threshold value as well as automatically resuming insulin delivery once glucose levels are restored. Previous studies have shown that more frequent monitoring of blood glucose and in particular the use of CGM is associated with improved glycemic control.[13] Moreover, the use of SAP+LGS specifically has been shown to reduce the incidence of severe hypoglycemic events in patients with impaired hypoglycemia awareness.[14]

Although country level data relating to SAP usage in Denmark are lacking, a single center study reported that over one-third of T1D patients on CSII were using SAP.[8] Initial device costs associated with SAP are higher than for CSII alone. Long-term health economic analyses are therefore needed to establish whether the clinical benefits associated with SAP mitigate the higher costs. Consequently, a cost-effectiveness analysis of SAP versus CSII in two different T1D populations was performed to establish whether SAP is cost-effective in T1D patients in Denmark.

5

MATERIALS AND METHODS

Model description and outcomes Cost-effectiveness analysis was performed using the CORE Diabetes Model (CDM; IMS Health, Basel, Switzerland). The CDM is a published and validated non-product-specific policy analysis tool for costeffectiveness analysis in both T1D and T2D.[15,16,17] The model is based on a series of interdependent sub-models that simulate disease progression and diabetes-related complications (angina, myocardial infarction, congestive heart failure, stroke, peripheral vascular disease, diabetic retinopathy, macula edema, cataract, hypoglycemia, ketoacidosis, lactic acidosis, depression, edema, nephropathy and end-stage renal disease, neuropathy, foot ulcer and amputation and non-specific mortality). The sub-models have a semi-Markov structure and use time, time-in-state and diabetes type-dependent probabilities derived from published sources to simulate disease progression. Monte Carlo simulation using tracker variables is used to overcome the memory-less properties of a standard Markov model and allows for interconnectivity and interaction between individual sub-models. Outcomes from the model include life expectancy, quality-adjusted life expectancy, direct and indirect costs, incremental cost-effectiveness ratios (ICERs) and time to onset of diabetes-related complications.

Simulation cohorts and treatment effects Two separate analyses were performed in different cohorts. The first cohort was T1D patients who were hyperglycemic at baseline (mean baseline HbA1c 8.1% [65 mmol/mol]) and the second cohort was T1D patients with an increased risk for hypoglycemic events (due to impaired awareness of hypoglycemia).

6

Cohort characteristics for the group with hyperglycemia at baseline were sourced from an individual patient level meta-analysis by Pickup et al.,[13] and supplemented where necessary with data from the DCCT study (Table 1).[18] Treatment effects for this cohort were derived from the meta-analysis by Pickup et al. with HbA1c reduction of −0.56% (6 mmol/mol) and −0.13% (1 mmol/mol) for the SAP group and CSII group used, based on a use of 49 sensor per year (each lasting 6 days) in the SAP group. Rates of severe hypoglycemic events were assumed to be the same in both treatment arms with a rate of 2.6 events per 100 patient years.[13]

Treatment effects and baseline characteristics for the cohort at increased risk for hypoglycemic cohort were sourced from a randomized controlled trial by Ly et al. in patients with impaired hypoglycemia awareness (Table 1).[14] At 6 months, Ly et al. reported severe hypoglycemic event rates of 2.2 events per 100 patient months for CSII versus 0 events per 100 patient months for SAP, which were applied in the base case analysis. No treatment effect in terms of HbA1c was modeled in this cohort and sensor use in the SAP arm was assumed to be 49 sensors per year.

Costs and utilities Direct medical costs for diabetes-related complications were sourced from published literature (Table 2) and where necessary inflated to 2015 DKK. Indirect costs due to lost productivity were incorporated using average male and female salaries from Statistics Denmark [19] and days off work due to diabetes-related complications sourced from a study by Sørensen et al. [20]

In terms of intervention costs the analysis included only the incremental cost between the SAP and CSII arm, which included additional costs in the SAP arm for 49 sensors per year and the sensor kit including MiniLink™ transmitter, MiniLink™ charger, MiniLink™ tester, batteries and Enlite™ serter™. Intervention costs also captured reduced use of SMBG in the SAP arm, based on an observational

7

study by Lynch et al. [21] in Sweden that showed SAP reduced SMBG use versus CSII from 7.11 to 4.35 strips per day. The total incremental cost for SAP versus CSII was DKK 16,559 per year.

Utilities for diabetes and complication health states were also sourced from Beaudet et al. [22] Additionally, for the cohort with hyperglycemia at baseline a utility based on fear of hypoglycemic events (FoH) was used. Here, a utility of 0.0552 was applied to the SAP arm, based on the findings of the INTERPRET study, which showed that the use of SAP was associated with a 6.9 unit decrease in the hypoglycemic fear survey (HFS) [23,24] together with findings from Currie et al., which reported that a 1 unit increase in HFS score corresponds to a 0.008 unit decrease on the EQ-5Dindex.[25]

For the cohort at increased risk of hypoglycemic events a quality of life adjustment was made to the SAP arm that considered the combined effects of reduced severe hypoglycemic event rate and reduced fear of hypoglycemia with SAP in line with a previous analysis by McBride et al. [26] A utility of 0.036 was applied to the SAP arm and a disutility of −0.036 was applied to the comparator arm.

Other model settings For each simulation in the analysis a simulated cohort of 1,000 identical patients were run through the model 1,000 times using first order Monte Carlo simulation. The base case analysis was performed from the societal perspective incorporating indirect costs due to lost productivity using the human capital approach. Future costs and clinical outcomes were discounted at a rate of 3% per annum and the analysis was performed over a time horizon of patient lifetimes.

Sensitivity analyses

8

For both cohorts, a series of one way sensitivity analyses were performed to determine key drivers of results. Sensitivity analyses around time horizon and discount rates were performed for both cohorts. As the base case analysis was performed from the societal perspective, taking into account indirect costs associated with lost productivity a sensitivity analysis was performed in which only direct costs were taken into account.

For the cohort with hyperglycemia at baseline, the effect of baseline glycemic control was assessed by changing baseline HbA1c values to 7.5% (58 mmol/mol), 8.5% (69 mmol/mol) and 9.0% (75 mmol/mol) (versus 8.1% [65 mmol/mol] in the base case). The impact of changes in sensor use in the SAP group was explored by increasing sensor use to 61 sensors per year and decreasing it to 43 per year, versus 49 per year in the base case. The influence of SMBG use was also explored by performing scenarios in which SMBG use was assumed to be 7.11 per day in both arms, as well as scenarios in which SMBG use in the SAP arm were increased and decreased to 6.11 per day and 2.11 per day (versus 4.35 per day in the base case). The role of FoH as a driver of outcomes was also explored in a series of one way sensitivity analyses. In the cohort with hyperglycemia a sensitivity analysis in which the FoH utility was negated in the SAP arm was explored as well as one in which a FoH utility of 0.0184 was used based on the findings of Beck et al. [27]

In the cohort at increased risk for hypoglycemic events, sensitivity analyses were performed in which the hypoglycemic event rate was set to 1 per 100 patient months and 8 per 100 patient months, compared with 0 per 100 patient months in the base case analysis.

9

RESULTS

Cohort with hyperglycemia at baseline For patients with T1D the use of SAP was associated with a quality of life benefit of 1.45 qualityadjusted life years (QALYs) relative to CSII (12.44 QALYs versus 10.99 QALYs for CSII) (Table 3). Total costs were higher with SAP (DKK 2,027,316 for SAP versus DKK 1,801,293 for CSII), resulting in an incremental cost-effectiveness ratio (ICER) of DKK 156,082 per QALY gained for SAP versus CSII. The higher overall costs in the SAP arm were primarily due to higher treatment costs associated with SAP. Analysis of the cost-effectiveness acceptability curve in this cohort showed that at a commonly accepted willingness-to-pay threshold of DKK 225,000 (approx. EUR 30,000) per QALY there was a 90% probability of being considered cost-effective versus CSII (Figure 1). If the willingness-to-pay threshold was increased to DKK 375,000 (approx. EUR 50,000) per QALY the likelihood of costeffectiveness versus CSII increased to >99%.

The improved glycemic control in the SAP group led to a substantial anticipated delay in the onset of diabetes-related complications, with the exception of cataract, all other complications were delayed more than a year. Gross proteinuria, first ulcer and neuropathy were delayed by >1.5 years.

The base case analysis was performed from the societal perspective. If only direct costs were taken into account the ICER increased to DKK 211,061 per QALY gained. Additional one way sensitivity analyses in the hyperglycemic cohort showed that the key driver of outcomes in the utility benefit was associated with reduced FoH in the SAP arm (Table 4). In a sensitivity analysis in which this benefit was negated, the quality of life benefit associated with SAP was reduced to 0.38 QALYs. Similarly, in a

10

second analysis in which a benefit from reduced FoH of 0.0184, sourced from Beck et al.,[27] was used the quality of life benefit was with SAP was reduced to 0.73 QALYs.

Sensitivity analysis showed that the results were sensitive to baseline HbA1c in that SAP was most beneficial in those patients with the poorest (highest) HbA1c at baseline. In a sensitivity analysis where the baseline HbA1c was 9.0% (75 mmol/mol) the quality of life benefit with SAP increased to 1.53 QALYs (versus 1.45 QALYs in the base case analysis) resulting in a decrease in the ICER to DKK 116,755 per QALY gained for SAP versus CSII.

Cohort at increased risk for hypoglycemic events The base case analysis for T1D patients at increased risk for severe hypoglycemic events showed that relative to CSII alone the use of SAP improved quality-adjusted life expectancy by 1.88 QALYs (Table 3). Over patient lifetimes total, direct and indirect costs in the SAP arm were DKK 168,683 higher than in the CSII arm, leading to an ICER of DKK 89,868 per QALY gained. If only direct medical costs were considered, the ICER increased to DKK 121,360 per QALY gained for SAP versus CSII (which is still likely to be considered cost-effective in the Danish setting). Analysis of the cost-effectiveness acceptability curve for this cohort showed that at a willingness-to-pay threshold of DKK 225,000 (approx. EUR 30,000) per QALY, the probability of SAP being cost-effective versus CSII was 100% (Figure 1).

In this cohort the use of SAP was also associated with a delay in the onset of diabetes-related complications compared with CSII. However, the magnitude of this benefit was lower than in the cohort with hyperglycemia at baseline. In the cohort with increased hypoglycemia risk the use of SAP delayed the onset of diabetes-related complications by 0.1–0.4 years versus CSII.

11

Sensitivity analysis in this cohort showed that hypoglycemic event rates were the most important driver of outcomes. In a scenario in which the rate of severe hypoglycemic events in the CSII arm was increased to 8 events per 100 patient months (versus 2.2 per 100 patient months in the base case), SAP was dominant to CSII (Table 4). Similarly, if the event rate in the CSII arm was reduced to 1 per 100 patient months the ICER increased to DKK 138,793 per QALY gained for SAP versus CSII.

12

DISCUSSION

The findings from cost-effectiveness analysis of SAP versus CSII alone in T1D patients in Denmark presented here show that in patients who are poorly controlled at baseline (HbA1c ≥8.1% [69 mmol/mol]), SAP is associated with an ICER of DKK 156,082 per QALY gained compared with CSII. Similarly, in patients at an elevated risk for hypoglycemic events, the corresponding figure is DKK 89,868 per QALY gained. Consequently, in both cohorts considered in the analysis SAP is likely to be considered cost-effective relative to CSII in Denmark, assuming a commonly accepted willingnessto-pay threshold of EUR 30,000 (approx. DKK 225,000) per QALY gained.

Sensitivity analyses showed that in the cohort with hyperglycemia at baseline the key drivers of results included the utility benefit applied for FoH and HbA1c at baseline. The cost-effectiveness of SAP increased markedly as baseline HbA1c increased, with the ICER for patients with a baseline HbA1c of 9.0% (75 mmol/mol) being DKK 116,755 per QALY gained for SAP versus CSII, suggesting that the patients with poorest glycemic control at baseline are likely to derive the greatest benefit from SAP. In a single center study in Denmark, Gjessing et al. report that 15% of patients on CSII had an HbA1c of >9.0% (75 mmol/mol); this group also had a median age of 21 years.[8] Although it not possible to know if this figure is representative of the CSII-treated T1D population on a national level, it does suggest that there is likely to be a substantial number of patients in Denmark for whom switching to SAP would be clinically beneficial and highly cost-effective. In the cohort at increased risk of hypoglycemia sensitivity analyses showed the hypoglycemic event rate to be the most influential parameter in terms of cost-effectiveness. In particular, in a scenario in which the event rate in the CSII group was 8 events per 100 patient-months in the CSII group SAP was dominant to CSII.

13

The higher device acquisition costs associated with SAP may represent a barrier to uptake in some instances. However, the findings of cost-effectiveness analyses show that these costs are at least partly mitigated over patient lifetimes due to the improved glycemic control associated with SAP and the resultant decrease in the incidence of long-term diabetes-related complications as well as a reduced incidence of severe hypoglycemic events and improved quality of life.

It is also possible that the benefits of reduced severe hypoglycemic event rates provided by SAP extend beyond those included in health economic analyses. For example, findings from a metaanalysis by Blasetti et al., as well as several individual studies suggests that recurrent severe hypoglycemic events and/or chronic hyperglycemia in childhood may negatively influence some aspects of cognitive development in children with T1D.[28,29,30] A limited number of studies have even shown small but significant differences in some school tests between children with T1D and controls.[31,32] Although this is an area that is currently poorly characterized, changes in white matter volume have also been reported in people with T1D.[33,34] Additionally, there is some evidence to suggest that frequent severe hypoglycemia is associated with an elevated mortality risk in T1D.[35,36] Evidence from a single center study conducted at the Frederica Hospital, Denmark over the period 2005–2013 suggest that the benefits associated with SAP are already recognized in some centers in Denmark. In their study, Gjessing et al. report that in their center, 16% of adult T1D patients were 8

using CSII and that of a total of 143 patients using CSII; 52 patients (37%) were using SAP. Further, of the 52 patients using SAP, 46 (88%) were using SAP devices that included a LGS feature. Over the 5 year period CSII was shown to improve glycemic control and reduce the incidence of hypoglycemic events as well as being associated with high levels of patient satisfaction (assessed using the Diabetes Treatment Satisfaction Questionnaire). Notably, the authors suggest that SAP and in particular the threshold suspend feature may have been instrumental in the low incidence of severe hypoglycemic events (5 events in 134 patients in the most recent year of data) reported in their study.[8]

14

The effect of reduced FoH and reduced incidence of severe hypoglycemic events with SAP may be particularly relevant for patients with T1D in Denmark. Changes in legislation in 2011 mean that patients with T1D who experience frequent severe hypoglycemic episodes (>1 event per year) may lose their driving license. For many adult patients losing their driving license may have dramatic consequences in terms of their independence and many aspects of everyday life such as being able to travel to and from work or taking children to and from school.[8]

In conclusion, the findings of long-term health economic modeling analysis suggest that for patients with T1D in Denmark who use insulin pumps, the incremental benefits providing by switching to SAP is likely to represents good value for money for both patients who are unable to achieve glycemic targets on CSII and for those who are at elevated risk for severe hypoglycemia. Moreover, patient groups in which SAP is likely to be most cost-effective include those with frequent hypoglycemic events and those with the poorest glycemic control at baseline.

CONFLICT OF INTEREST SdP and AD are current employees of Medtronic International Sàrl, which manufacturers insulin pumps. SR is a current employee of HEVA HEOR, which has received consulting fees from Medtronic. JSP and WV are current employees of Ossian Health Economics and Communications, which has received consulting fees from Medtronic. MR is an employee of the Steno Diabetes Center A/S and has served on advisory boards and received honoraria for lectures from several pharmaceutical companies.

15

TABLES AND FIGURES Table 1

Baseline cohort characteristics

Cohort with hyperglycemia at baseline Mean age, years

27

Male, %

48.5

Duration of diabetes, years

13.2

HbA1c, % (mmol/mol)

8.1 (64)

Cohort with increased risk of hypoglycemic events Mean age, years

18.6

Male, %

49.5

Duration of diabetes, years

11

HbA1c, % (mmol/mol)

7.5 (58)

HbA1c, glycated hemoglobin

Table 2

Cost of diabetes-related complications

Complication

Cost/DKK

Reference

Myocardial infarction, year of event

56,408

[37, 38, 39, 40]

Myocardial infarction, subsequent years

1,508

[37, 38, 39, 40]

Angina, first year

120,938

[37, 38, 39, 40]

Angina, subsequent years

1,508

[37, 38, 39, 40]

Congestive heart failure, first year

66,975

[37, 38, 39, 40]

Congestive heart failure, subsequent years

1,465

[37, 38, 39, 40]

Stroke, year of event

85,243

[37, 38, 39, 40]

Stroke, subsequent years

27,337

[37, 38, 39, 40]

Stroke death within 30 days

57,906

[37, 38, 39, 40]

Peripheral vascular disease, first year

26,982

[37, 38, 39, 40]

Peripheral vascular disease, subsequent years

4,151

[41]

16

Complication

Cost/DKK

Reference

Hemodialysis, first year

403,881

[42]

Hemodialysis, subsequent years

403,881

[42]

Peritoneal dialysis, first year

259,582

[42]

Peritoneal dialysis, subsequent years

259,582

[42]

Renal transplant, first year

560,652

[37, 38, 39, 40]

Renal transplant, subsequent years

41,601

[37, 38, 39, 40]

Severe hypoglycemic event

25,959

[37]

Minor hypoglycemic event

0

[39]

Ketoacidosis event

32,912

[37]

Lactic acidosis event

32,912

[37]

Edema onset

136

[43]

Edema follow-up

136

[43]

Laser photocoagulation

1,764

[43]

Cataract operation

13,604

[37, 43]

Cataract operation follow-up

388

[44]

Blindness, year of onset

86,176

[45]

Blindness, subsequent years

86,176

[45]

Neuropathy, year of onset

21,609

[37]

Neuropathy, subsequent years

177

[38]

Amputation event

94,080

[37]

Amputation prosthesis

14,700

[46]

Gangrene treatment

227,543

[46]

After healed ulcer

27,839

[47]

Infected ulcer

152,179

[46]

Standard uninfected ulcer

132,418

[46]

Healed ulcer, history of amputation

51,911

[47]

17

Table 3

Summary of base case analyses

SAP

CSII

∆ SAP − CSII

Quality-adjusted life expectancy, QALYs

12.44

10.99

1.45

Total costs, DKK

2,027,316

1,801,293

226,023

Total direct costs, DKK

1,193,880

888,242

305,638

Treatment costs

560,263

226,341

333,922

Management costs

19,143

18,681

462

Cardiovascular complication costs

54,569

53,860

709

Renal complication costs

68,681

82,615

−13,934

Ulcer/amputation/neuropathy costs

192,988

210,867

−17,879

Ophthalmic complication costs

284,375

282,346

−2,029

Hyperglycemic at baseline cohort

ICER, DKK per QALY gained

156,082

Increased risk for hypoglycemia cohort Quality-adjusted life expectancy, QALYs

13.08

11.2

1.88

Total costs, DKK

2,277,868

2,109,186

168,682

Total direct costs, DKK

1,296,315

1,068,552

227,793

Treatment costs

603,645

247,523

356,122

Management costs

20,566

20,400

166

Cardiovascular complication costs

45,459

44,648

811

Renal complication costs

69,617

67,777

1,840

Ulcer/amputation/neuropathy costs

219,533

216,547

2,986

Ophthalmic complication costs

336,605

330,522

6,083

ICER, DKK per QALY gained

89,868

CSII, continuous subcutaneous insulin infusion; ICER, incremental cost-effectiveness ratio; QALY, quality-adjusted life year; SAP, sensor-augmented pump therapy

18

Table 4

Summary of sensitivity analyses

Quality-adjusted life expectancy, QALYs

Costs, DKK

SAP

CSII

∆

SAP

CSII

∆

ICER, DKK per QALY

Hyperglycemic at baseline cohort Base case

12.44

10.99

1.448

2,027,316

1,801,293

226,023

156,082

Direct costs only

12.44

10.99

1.448

1,193,880

888,242

305,637

211,061

Sensor + kit cost +20%

12.44

10.99

1.448

1,943,618

1,801,293

142,325

98,284

Sensor + kit cost −10%

12.44

10.99

1.448

1,985,467

1,801,293

184,174

127,183

Sensor + kit cost +10%

12.44

10.99

1.448

2,069,165

1,801,293

267,872

184,982

Baseline HbA1c 7.5% (58 mmol/mol)

12.78

11.38

1.399

1,947,612

1,695,008

252,605

180,552

Baseline HbA1c 8.5% (69 mmol/mol)

12.22

10.73

1.486

2,080,649

1,876,760

203,889

137,253

Baseline HbA1c 9.0% (75 mmol/mol)

11.92

10.39

1.528

2,151,798

1,973,338

178,459

116,755

Complication costs +20%

12.44

10.99

1.448

2,154,040

1,933,674

220,366

152,176

Complication costs −20%

12.44

10.99

1.448

1,900,593

1,668,913

231,680

159,989

FoH utility = 0

11.37

10.99

0.376

2,027,316

1,801,293

226,023

601,925

FoH utility = 0.0184

11.73

10.99

0.733

2,027,316

1,801,293

226,023

308,353

SAP SMBG use = 7.11/day

12.44

10.99

1.448

2,117,268

1,801,293

315,975

218,200

SAP SMBG use = 6.11/day

12.44

10.99

1.448

2,084,677

1,801,293

283,284

195,693

19

Quality-adjusted life expectancy, QALYs

Costs, DKK

SAP

CSII

∆

SAP

CSII

∆

ICER, DKK per QALY

SAP SMBG use = 2.11/day

12.44

10.99

1.448

1,954,312

1,801,293

153,018

105,668

Time horizon 5 years

3.33

3.07

0.26

168,975

97,576

71,339

274,930

Time horizon 10 years

5.87

5.37

0.496

372,083

248,310

123,773

249,341

Time horizon 20 years

9.36

8.47

0.895

879,170

698,634

180,535

201,693

Time horizon 40 years

12.09

10.73

1.352

1,775,459

1,564,360

211,099

156,127

0% discount rate

20.03

17.34

2.683

4,447,661

4,077,919

369,742

137,819

1.5% discount rate

15.51

13.58

1.927

2,934,441

2,652,851

281,590

146,151

Sensor use = 43 per year

12.34

10.99

1.35

2,008,730

1,801,293

207,436

153,634

Sensor use = 61 per year

12.63

10.99

1.631

2,067,966

1,801,293

266,672

163,512

Increased risk of hypoglycemic events cohort Base case

13.08

11.20

1.877

2,277,868

2,109,186

168,683

89,868

Direct costs

13.08

11.20

1.877

1,296,315

1,068,552

227,793

121,360

0% discount rate

21.84

18.49

3.35

5,494,966

5,190,240

304,726

90,974

1.5% discount rate

16.57

14.12

2.451

3,448,931

3,228,393

220,538

89,993

Time horizon 10 years

5.82

5.09

0.731

337,707

266,168

71,539

97,892

Time horizon 20 years

9.44

8.19

1.25

810,180

696,609

113,571

90,879

CSII SHE rate = 1 per 100 patient months

13.08

11.32

1.761

2,277,868

2,033,496

244,373

138,793

CSII SHE rate = 8 per 100

13.08

10.82

2.257

2,277,868

2,353,237

−75,369

SAP

20

patient months

Quality-adjusted life expectancy, QALYs

Costs, DKK

SAP

SAP

CSII

∆

CSII

∆

ICER, DKK per QALY dominant

CSII, continuous subcutaneous insulin infusion; FoH, fear of hypoglycemia; ICER, incremental cost-effectiveness ratio; QALY, quality-adjusted life year; SAP, sensor-augmented pump therapy; SHE, severe hypoglycemic event

21

Figure 1

Cost-effectiveness acceptability curve for SAP versus CSII in type 1 diabetes patients

Likelihood of being cost-effective, %

A. Patients with hyperglycemia at baseline

100

80

60

40

20

0 0

50000

100000 150000 200000 250000 300000 350000 Willingness to pay, DKK/QALY

Likelihood of being cost-effective, %

B.

Patients at increased risk of hypoglycemic events 100

80

60

40

20

0 0

50000

100000

150000

200000

250000

Willingness to pay, DKK/QALY

CSII, continuous subcutaneous insulin infusion; QALY, quality-adjusted life year; SAP, sensoraugmented pump therapy

22

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27

Cost-effectiveness of sensor-augmented pump therapy versus standard insulin pump therapy in patients with type 1 diabetes in Denmark

Highlights •

In type 1 diabetes SAP provides additional clinical benefits over standard CSII alone

•

SAP improves quality adjusted life expectancy in type 1 diabetes patients

•

SAP is associated with higher costs than standard CSII

•

SAP is likely to be cost-effective versus standard CSII for some patients

28