We conducted a systematic review of health economic evaluations comparing GLA versus NPH as the basal component of an ICT in type 1 diabetes. 7 economic evaluations from 4 different countries (Germany, Canada, England, Switzerland) were included: 6 cost-utility analyses based on complex modelling and 1 cost-comparison analysis based on claims data. In 1 cost-utility analysis GLA was dominant over NPH due to 0.238 additional QALYs gained together with cost savings of € 796 (time horizon 40 years). In the other 5 studies of this type additional costs per QALY gained for treatment with GLA ranged between € 3,859 and € 57,002.
There is no unique willingness-to-pay threshold for a QALY across different countries. However NICE judges a technology acceptable if the ICER is below £ 20,000 to £ 30,000 (€ 23,577 to € 35,365, based on 2009 PPP values) [38
] and there are other statements that imply comparable threshold values for other countries [39
]. Taking the upper threshold value into account, GLA would be judged cost-effective in 4 of the 6 of CUAs identified.
The cost-comparison analysis in the German SHI setting showed € 160 higher diabetes-specific costs per patient per 12 months for therapy with GLA compared to NPH.
The identified systematic reviews [27
] only gave little detail on health economic evaluations comparing GLA versus NPH, all of them dealing with the GLA-NPH comparison among several other interventions related to type 1 diabetes. These reviews identified no additional studies compared to our search and reported no additional aspects.
Keeping in mind the challenges associated with modelling a chronic disease such as type 1 diabetes the methods of health economic evaluation are highly developed in this field of comparing different strategies of insulin therapy.
Overall the assessment of the quality of the studies using standardised check lists revealed acceptable to good quality of the included studies. General guidelines and recommendations on health economic evaluations [13
] emphasise, that publications must be optimally transparent about the model's structure, the input data, the algorithms used and the assumptions made in the study. In a minority of publications the structure of the model used could only be assumed. More transparency is necessary in the presentation of unit costs. Especially precise information on unit prices of the compared insulins was often missing.
More diligence should be spent on the presentation of the utilities used. This is of paramount importance, because these factors have a strong impact on the total results of a cost-utility analysis. In some studies the period corresponding to utility decrements incurred by hypoglycaemia remained unclear or could only be determined from other referenced articles. Furthermore, when comparing utility values for the same type of event between different studies (Table ), we found considerable differences. These differences pose a challenge to the comparison of economic evaluations. Our approach to coping with this issue was to make the differences transparent as shown in Table .
In some publications a clear research question and the perspective of the health economic evaluation was missing. Also the discussion of strengths and weaknesses was not always satisfying.
The parameters of clinical effectiveness should be obtained from meta-analyses that include all existing clinical evidence [10
].This has only been realised by Brändle et al. [25
], McEwan et al. [23
] Cameron et al. [21
] and partly by Warren et al. [20
]. Choice of a single RCT from the pool of existing studies by the other evaluations was weakly motivated. Information synthesis would have been possible, because already in 2002, when the first evaluations were done, several studies comparing GLA with NPH in type 1 diabetes did exist.
Only 1-Brändle et al. [25
]-out of 6 modelling studies included cost of self-monitoring of blood glucose, which is a substantial cost in insulin treatment (about 30% of all prescription costs [26
Specifically for modelling of diabetes a consensus panel of the American Diabetes Association (ADA) [15
] has developed recommendations, among which the most important are:
- As diabetes affects multiple organ systems, the models must include a wide range of complications.
- These complications of diabetes may take years or decades to occur, therefore the time horizon of the models must be sufficiently long.
- Because some of the diabetes complications greatly reduce a person's quality of life, this type of outcome should be considered in any analysis. Cost-utility analysis is the appropriate evaluation type for this.
These commonly accepted requirements for diabetes models were fulfilled by all of the included modelling studies.
However, the following issues are still under discussion regarding diabetes models and long-acting insulin analogues:
- The question has not been finally answered whether the therapy with long-acting insulin analogues predominantly affects frequency of hypoglycaemia or predominantly affects metabolic control. Also a combination of both effects seems possible. However all three possibilities should be considered in a modelling study by different scenarios based on adequate meta-analyses. Another option is the use of results from an individual patient data (IPD) meta-regression [7
] as Brändle et al. [25
] did. Still the relationship between the effect of GLA on HbA1c and on the frequency of hypoglycaemia as well as the use of this relationship in the economic model are not sufficiently transparent.
- The concept of fear of hypoglycaemia, which influences quality of life beyond the event of hypoglycaemia itself seems plausible. Though, there are only few data available [37
] and research on this should be improved. In economic evaluation, results of alternatives with and without utility reduction because of fear of hypoglycaemia should be clearly distinguishable.
- Until now, only few modelling studies consider the differences in the consumption of needles, test strips for blood glucose self-monitoring and lancets between the different basal insulins in type 1 diabetes.
This last point clearly shows, that claims data analyses and primary data collection of insulin consumption, test strips, needles, and lancets are a useful and necessary supplement to modelling studies. They provide the data of real life resource consumption, which in the models may be linked to clinical effectiveness and patient reported outcomes (PRO) data.
The aim of this systematic review was to make the results of the included evaluations comparable via different methodical steps. First, all relevant information about design, analysis and modelling techniques, input and output parameters were extracted by standardised checklists. Second, study quality was consistently evaluated by an internationally standardised tool. Finally, costs per QALY gained were converted into Euro using the purchasing power parities. This was necessary in order to express different values of different studies in different countries in comparable Euro values. The reference year of the original analysis was maintained.
The study used published PPPs that were derived from a general basket of goods and services. For the use in health economic evaluations a basket specifically of health care goods, e.g. drugs and supplies, and services, e.g. ambulatory and inpatient care services, may be more appropriate. However, such a health care related basket of goods and services does not yet exist [17
Other reasons may as well restrict the comparability of the included studies:
- The different economic evaluations are based on different health care settings and legislations, e.g. the Canadian Medicare system, the National Health Service (NHS) in the United Kingdom or the German Statutory Health Insurance setting.
- The information about the economic evaluations was not presented comparably transparent in all publications.
- One publication was identified in compliance with the pre-defined inclusion criteria from a congress abstract database [25
]. Data for the review was obtained form the congress poster and by extensive personal correspondence with the author. The inclusion of work published in an international scientific congress seemed justifiable in the rapidly evolving research area of health economic evaluation.