Cost-effectiveness of saxagliptin vs glimepiride as a second-line therapy added to metformin in Type 2 diabetes in China

Figures & data

Table 1. Demographics and risk factors.

Variable*	Value†		Reference
	Mean	SE
Baseline demographics
Baseline age, years	48.51	1.21	Zhu and Song32
Proportion female, value: 0–1	0.48	0.06	Zhu and Song32
Duration of diabetes, years	6.7	0.07	Ji et al.55
Height, m	1.63	0	General Administration of Sport of China54
Proportion of smokers, value: 0–1	0.183	0.0046	Ji et al.55
Modifiable risk factors
HbA1c, %	8.70	0.09	Zhu and Song32
Total-cholesterol, mmol/L	5.13	0.14	Zhu and Song32
HDL cholesterol, mmol/L	1.11	0.0013	Xu et al.6
SBP, mmHg	130.99	2.26	Zhu and Song32
Weight, kg‡	71.34	2.15	Zhu and Song32

BMI, body mass index; HbA_1c, glycated hemoglobin; HDL, high-density lipoprotein; SBP, systolic blood pressure; SE, standard error.

*Most variables are taken from the Zhu and Song32 study. If these were not available in Zhu and Song, they have been obtained from a published observational study.

†Values are mean unless stated otherwise.

‡Weight was calculated from baseline BMI by assuming that the average height was 1.63 m; weight = BMI × (height)2.

Table 2. Clinical input variables.

Variable*	SAXA + MET	GLI + MET	Reference
HbA1c reduction, year 1, %	−1.40 (0.15)	−1.20 (0.13)	Zhu and Song32
Weight change, kg	−2.39 (3.06)	0.53 (3.33)	Zhu and Song32
Number symptomatic hypoglycemia	0.0264 (0.0264†)	0.1544 (0.0586†)	Zhu and Song32; Zheng et al.50
Probability severe hypoglycemia	0.0006 (0.0040†)	0.0034 (0.0095†)	Zhu and Song32; Zheng et al.50

GLI, glimepiride; HbA_1c, glycated hemoglobin; MET, metformin; SAXA, saxagliptin; SE, standard error.

*Values are mean (SE; SE for values sampled from a normal distribution in the probabilistic sensitivity analysis). Variables are taken from the Zhu and Song32 study.

†Calculated as √rate (1 − rate)/numbers of subjects.

Figure 1. Simulated progression of HbA_1c in the treatment (saxagliptin + metformin) and control (glimepiride + metformin) arms over the modeled time horizon. HbA_1c = glycated hemoglobin.

Figure 2. Simulated progression of weight in the treatment (saxagliptin + metformin) and control (glimepiride + metformin) arms over the modeled time horizon.

Table 3. Annual direct medical costs for diabetes-related complications and severe hypoglycemia (2014¥).

Event	Fatal		Non-fatal		Maintenance		Reference
	Mean	SE	Mean	SE	Mean	SE
Ischemic heart disease	–	0	39,041.39	0	6969.85	0	Gao et al.59
Myocardial infarction	46,547.02	0	46,547.02	0	10,692.45	0	Gao et al.59
Congestive heart failure	15,479.64	0	15,479.64	0	9409.36	0	Gao et al.59
Stroke	14,059.41	0	18,141.13	0	8169.26	0	Gao et al.59
Blind	–	–	12,047.60	0	9297.78	0	Gao et al.59
End-stage renal disease	–	–	114,640.49	0	91,981.79	0	Gao et al.59
Amputation	18,232.95	0	18,232.95	0	14,533.60	0	Gao et al.59
Ulcer*	0	0	13,989.07	443.2	4923.52	0	Survey; Li et al.60; Palmer et al.61
Severe hypoglycemia			3829.96				Zheng et al.50

SE, standard error.

*Ulcer, non-fatal costs, were obtained from hospital survey; maintenance cost obtained from two published studies (Li et al.60 and Palmer et al.61).

Table 4. Annual treatment costs for different drugs.

Drug (Brand)	Manufacturer	Specification	Highest retail price, ¥	Daily dose, mg/day	Annual treatment cost, ¥	Annual metformin cost, ¥	Total cost, ¥
Saxagliptin (Onglyza)	Bristol-Myers Squibb	5 mg*7 tablets	69.65	5	3631.75*	1577.28‡	5209.03
Glimepiride (Amaryl)	Sanofi	2 mg*15 tablets	77.90	2.8	2653.79†	1577.28‡	4231.07

*Official drug price list of Price Bureau for saxagliptin in eastern China62.

†Official drug price list of Price Bureau for glimepiride in eastern China63.

‡Obtained from Hou et al.64. The cost for metformin is ¥366.9 per 12 weeks, and thus the cost of metformin = 366.9 * 4 = 1467.6. Convert to 2014 using CPI from 2013 to 2014, annual cost of metformin = 1467.6*102.6/100*104.75/100 = ¥1577.28.

Table 5. BMI-related costs.*†.

BMI	Annual cost (2014¥)
20	0
21	0
22	0
23	0
24	1519.5
25	3742.7
26	5965.9
27	8189
28	10,412.2
29	12,635.4
30	14,858.6
31	17,081.7
32	19,304.9
33	21,528.1
34	23,751.2
35	25,974.4
36	28,197.6
37	30,420.8
38	32,643.9
39	34,867.1
40+	37,090.3

BMI, body mass index.

*Obtained from Guo et al.65

†Assumptions: The starting point BMI = 25, BMI-related costs per month = ¥246.8; the slope (cost per month/BMI) = ¥146.6 in 2007. For BMI ≤ 23 the cost was set to zero.

Table 6. Utility decrements.

Event disutilities	Utility decrement
	First year	Subsequent year	Reference
Ischemic heart disease	0.090	0.090	Clarke et al.66
Myocardial infarction	0.055	0.055	Clarke et al.66
Congestive heart failure	0.108	0.108	Clarke et al.66
Stroke	0.164	0.164	Clarke et al.66
Blind	0.074	0.074	Currie et al.67
End-stage renal disease	0.263	0.263	Currie et al.67
Amputation	0.280	0.280	Clarke et al.66
Ulcer	0.059	0.059	Clarke et al.66
Hypoglycemia
Symptomatic	0.0142	0.000	Currie et al.19
Severe	0.047	0.000	Currie et al.19
BMI-related changes
Per unit decrease in BMI	0.0171	0.0171	Lane et al.53
Per unit increase in BMI	0.0472	0.0472	Lane et al.53

BMI, body mass index.

Table 7. Results for SAXA + MET vs GLI + MET.

Total events predicted	GLI + MET (Control)		SAXA + MET (Treatment)		Difference	Total costs,* ¥	GLI + MET (Control)	SAXA + MET (Treatment)
	Non-fatal	Fatal	Non-fatal	Fatal
Macrovascular						Macrovascular
IHD	117.4	0.0	116.3	0.0	−1.0	IHD	8,705,008	8,678,793
MI	108.7	119.1	108.8	116.2	−2.8	MI	14,630,033	14,596,760
CHF	42.8	3.9	42.2	3.8	−0.7	CHF	2,542,758	2,517,399
Stroke	43.6	10.6	43.2	10.2	−0.8	Stroke	2,743,846	2,742,735
Microvascular						Microvascular
Blindness	43.7	0.0	42.5	0.0	−1.2	Blindness	2,983,962	2,939,578
Nephropathy	30.3	2.8	30.5	2.7	0.1	Nephropathy	13,824,176	14,013,694
Amputation	49.3	4.6	46.6	4.3	−3.0	Amputation	3,847,717	3,608,470
Fatal						Hypoglycemia	1,333,739	1,021,374
Macrovascular	–	133.6	–	130.2	−3.4	Treatment	63,754,426	68,357,021
Microvascular	–	7.4	–	7.0	−0.3	BMI costs	171,089,513	122,596,983
Other	–	857.1	–	860.8	3.7	Total	285,455,177	241,072,807
Cost-Effectiveness						Hypoglycemia†
Per Patient
Discounted Cost	285,455.18		241,072.81		−44,382	Symptomatic	13,981	11,557
Discounted QALYs	13.00		14.01		1.01	Severe	498	411
Discounted LY	16.64		16.67		0.03
Cost per QALY					−43,883
Cost per LY					−1,710,926

BMI, body mass index; CHF, congestive heart failure; GLI, glimepiride; IHD, ischemic heart disease; LY, life-year; MET, metformin; MI, myocardial infarction; QALY, quality-adjusted life-year; SAXA, saxagliptin.

*Treatment cost includes insulin therapy and rescue therapy with insulin drug costs. Analysis based on 1000 patients.

†Hypoglycemia in both the treatment and the control group includes hypoglycemia events generated by insulin therapy and rescue therapy.

Figure 3. Tornado diagram of the univariate sensitivity analysis. BMI, body mass index; HbA_1c, glycated hemoglobin; HDL, high-density lipoprotein; ICER, incremental cost effectiveness ratio; SBP, systolic blood pressure.

Table 8. Sensitivity analyses for SAXA + MET vs GLI + MET (results per patient).

Sensitivity analysis*	Total cost difference, ¥	QALYs gained	Cost/QALY, ¥
Base case	−44,382	1.01	−43,883
1-way sensitivity analysis
Baseline age 60.64 years (48.51·125%)	−33,390	0.79	−42,083
Baseline age 72.77 years (48.51·150%)	−21,972	0.53	−41,657
Baseline HbA1c decreased by 1% (7.7%)	−41,429	0.73	−56,940
GLI + MET HbA1c reduction as SAXA + MET	−40,670	0.74	−54,620
All hypoglycemia assumed to be symptomatic events	−44,380	1.01	−43,882
GLI + MET no. symptomatic hypoglycemia as SAXA + MET	−44,382	1.01	−43,961
GLI + MET prob. severe hypoglycemia as SAXA + MET	−44,372	1.01	−43,878
Discount rate (costs and benefits) 5%	−36,154	0.84	−43,257
Utility decrement of hypoglycemia halved (symptomatic, 0.0071; severe, 0.0235)	−44,382	0.99	−44,667
Utility decrement of hypoglycemia reduced by 75% (symptomatic, 0.00355;  severe, 0.01175)	−44,382	0.98	−45,070
Utility weight 0.014 per unit BMI decrease and −0.014 per unit BMI increased in all years	−44,382	0.38	−117,391
Utility decrement (first and subsequent years) per unit BMI gain halved  (−0.0472·0.5 = −0.0236)	−44,382	0.57	−77,906
Utility decrement (first and subsequent years) per unit BMI gain reduced by 75%  (−0.0472·0.25 = −0.0118)	−44,382	0.35	−127,225
GLI + MET annual therapy costs halved (2115.54)	−42,269	1.01	−41,794
Severe hypoglycemia cost halved (1914.98)	−44,226	1.01	−43,729
BMI costs halved	−20,136	1.01	−19,910
BMI costs reduced by 75%	−8013	1.01	−7923
BMI costs = 0	4110	1.01	4064
Alternative diabetes-related complications costs used	−44,498	1.01	−43,998
Probabilistic sensitivity analysis	−41,265	0.80	−51,588

BMI, body mass index; GLI, glimepiride; HbA_1c, glycated hemoglobin; MET, metformin; QALY, quality-adjusted life-year; SAXA, saxagliptin.

*Analysis for 1000 patients. Everything else is as described for the base-case analysis.

Figure 4. Scatter plot of incremental cost-effectiveness ratios for saxagliptin + metformin vs glimepiride + metformin with a CE threshold value of ¥43,320 (GDP per capita in China in 2013). CE, cost effectiveness; GDP, gross domestic product.

Figure 5. Cost-effectiveness acceptability curve for saxagliptin + metformin vs glimepiride + metformin.

Zhu F, Song XY. Therapeutic effects of dipeptidyl peptidase-4 inhibitor saxagliptin on patients with type 2 diabetes and its influences on β-cell function. Chinese J Diabetes 2014;22:494-6

 Google Scholar

Ji LN, Hu DY, Pan CY, et al. Primacy of the 3B approach to control risk factors for cardiovascular disease in type 2 Diabetes patients. Am J Med 2013;126:911-25

 Web of Science ®Google Scholar

General Administration of Sport of China. National Physique Monitoring Bulletin (2010). Beijing, China. 2011. http://www.sport.gov.cn/n16/n1077/n297454/2052709.html. Accessed 29 December 2014

 Google Scholar

Xu Y, Wang LM, He J, et al. Prevalence and control of diabetes in Chinese adults. JAMA 2013;310:948-58

 PubMed Web of Science ®Google Scholar

Chinese Diabetes Society. Chinese guideline for Type 2 diabetes prevention (2013). Chinese J Diabetes 2014;22:2-42

 Google Scholar

Zheng YM, Wu J, Xie K. Incidence and cost of hypoglycemia episode in patients with type 2 diabetes mellitus (T2DM). Chinese Rural Health Service Admin 2012;32:1195-8

 Google Scholar

Gao L, Zhao FL, Li SC. Cost-utility analysis of liraglutide versus glimepiride as add-on to metformin in type 2 diabetes patients in China. Int J Technol Assess Health Care 2012;28:436-44

 PubMed Web of Science ®Google Scholar

Li HC, Xu F, Wang F. Cost-effectiveness of biphasic insulin aspart 30 combined with metformin in patients with type 2 diabetes mellitus. Chinese J New Drugs 2011;20:2163-70

 Google Scholar

Palmer JL, Gibbs M, Scheijbeler H, et al. Cost-effectiveness of switching to biphasic insulin aspart in poorly-controlled type 2 diabetes patients in China. Adv Ther 2008;25:752-74

 PubMed Web of Science ®Google Scholar

Price Bureau. Official drug price list for saxagliptin. Zhejiang, China. 2014. http://www.zjpi.gov.cn/main/html/2014/CT10046/eec3f13a8b2d46258a93966273078df7.html. Accessed 27 December 2014

 Google Scholar

Price Bureau. Official drug price list for glimepiride. Zhejiang, China. 2014. http://www.zjpi.gov.cn/main/html/2014/CT10046/dd72e4240a7e4c1da820a849642f7b37.html. Accessed 27 December 2014

 Google Scholar

Hou XY, Zen Z, Tao X, et al. Cost-effectiveness analysis of 2 dosage forms of metformin hydrochloride in the treatment of type 2 Diabetes. China Pharmacy 2014;25:1844-7

 Google Scholar

Guo H, Li J, Jiang ZL. Follow-up effects of the increased physical activity on the glucolipid metabolic factors and medical costs in type 2 diabetic patients. Chinese J Rehab Med 2007;22:395-8

 Google Scholar

Clarke P, Gray A, Holman R. Estimating utility values for health states of type 2 diabetic patients using the EQ-5D (UKPDS 62). Med Decis Making 2002;22:340-9

 PubMed Web of Science ®Google Scholar

Currie CJ, McEwan P, Peters JR, et al. The routine collation of health outcomes data from hospital treated subjects in the Health Outcomes Data Repository (HODaR): descriptive analysis from the first 20,000 subjects. Value Health 2005;8:581-90

 PubMed Web of Science ®Google Scholar

Currie CJ, Morgan CL, Poole CD, et al. Multivariate models of health-related utility and the fear of hypoglycaemia in people with diabetes. Curr Med Res Opin 2006;22:1523-34

 PubMed Web of Science ®Google Scholar

Lane S, Levy AR, Mukherjee J, et al. The impact on utilities of differences in body weight among Canadian patients with type 2 diabetes. Curr Med Res Opin 2014;30:1267-73

 PubMed Web of Science ®Google Scholar