Conducting cost-effectiveness analyses of type 2 diabetes in low- and middle-income countries: can locally generated observational study data overcome methodological limitations?

Application of decision analytical models to diabetes in low- and middle-income countries: a systematic review

BACKGROUND

Decision analytical models (DAMs) are used to develop an evidence base for impact and health economic evaluations, including evaluating interventions to improve diabetes care and health services-an increasingly important area in low- and middle-income countries (LMICs), where the disease burden is high, health systems are weak, and resources are constrained. This study examines how DAMs-in particular, Markov, system dynamic, agent-based, discrete event simulation, and hybrid models-have been applied to investigate non-pharmacological population-based (NP) interventions and how to advance their adoption in diabetes research in LMICs.

METHODS

We systematically searched peer-reviewed articles published in English from inception to 8th August 2022 in PubMed, Cochrane, and the reference list of reviewed articles. Articles were summarised and appraised based on publication details, model design and processes, modelled interventions, and model limitations using the Health Economic Evaluation Reporting Standards (CHEERs) checklist.

RESULTS

Twenty-three articles were fully screened, and 17 met the inclusion criteria of this qualitative review. The majority of the included studies were Markov cohort (7, 41%) and microsimulation models (7, 41%) simulating non-pharmacological population-based diabetes interventions among Asian sub-populations (9, 53%). Eleven (65%) of the reviewed studies evaluated the cost-effectiveness of interventions, reporting the evaluation perspective and the time horizon used to track cost and effect. Few studies (6,35%) reported how they validated models against local data.

CONCLUSIONS

Although DAMs have been increasingly applied in LMICs to evaluate interventions to control diabetes, there is a need to advance the use of DAMs to evaluate NP diabetes policy interventions in LMICs, particularly DAMs that use local research data. Moreover, the reporting of input data, calibration and validation that underlies DAMs of diabetes in LMICs needs to be more transparent and credible.

A review of simulation models for the long-term management of type 2 diabetes in low-and-middle income countries

INTRODUCTION

The burden of type 2 diabetes is steadily increasing in low-and-middle-income countries, thereby posing a major threat from both a treatment, and funding standpoint. Although simulation modelling is generally relied upon for evaluating long-term costs and consequences associated with diabetes interventions, no recent article has reviewed the characteristics and capabilities of available models used in low-and-middle-income countries. We review the use of computer simulation modelling for the management of type 2 diabetes in low-and-middle-income countries.

METHODS

A search for studies reporting computer simulation models of the natural history of individuals with type 2 diabetes and/or decision models to evaluate the impact of treatment strategies on these populations was conducted in PubMed. Data were extracted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and assessed using modelling checklists. Publications before the year 2000, from high-income countries, studies involving animals and analyses that did not use mathematical simulations were excluded. The full text of eligible articles was sourced and information about the intervention and population being modelled, type of modelling approach and the model structure was extracted.

RESULTS

Of the 79 articles suitable for full text review, 44 studies met the inclusion criteria. All were cost-effectiveness/utility studies with the majority being from the East Asia and Pacific region (n = 29). Of the included studies, 34 (77.3%) evaluated the cost-effectiveness of pharmacological interventions and approximately 75% of all included studies used HbA1c as one of the treatment effects of the intervention. 32 (73%) of the publications were microsimulation models, and 29 (66%) were state-transition models. Most of the studies utilised annual cycles (n = 29, 71%), and accounted for costs and outcomes over 20 years or more (n = 38, 86.4%).

CONCLUSIONS

While the use of simulation modelling in the management of type 2 diabetes has been steadily increasing in low-and-middle-income countries, there is an urgent need to invest in evaluating therapeutic and policy interventions related to type 2 diabetes in low-and-middle-income countries through simulation modelling, especially with local research data. Moreover, it is important to improve transparency and credibility in the reporting of input data underlying model-based economic analyses, and studies.

Cost-effectiveness analyses using real-world data: an overview of the literature

Objectives: Real-world evidence (RWE) may provide good estimates of absolute event probabilities and costs in patients in actual clinical practice, but their use in decision-analytic models poses many challenges. A literature review based on a systematic search was conducted to summarize the limitations of using RWE in decision-analytic modeling reported in the literature, but also to identify existing recommendations about real-world modeling. Methods: A literature search was performed on Medline and Embase databases, as well as relevant websites. No restrictions in language or geographical scope were imposed. Results: A total of 14 references were included. RWE is recognized as a valuable source of data for market access and reimbursement, and as a complement to clinical trial evidence for treatment pathways, resource use, long-term natural history, and effectiveness. The main limitations identified in the literature were: confounding bias, missing data, lack of accurate data related to drug exposure and outcomes, errors during the record-keeping process, protection of private data, and insufficient numbers of patients. Although most submission guidelines recognized the potential biases associated with RWE, guidance on the appropriate methods to deal with these biases, and approaches to review different relevant evidence to inform model development, were scarce. Several initiatives have attempted to provide guidance on the use of RWE in decision-modeling. Conclusions: RWE is likely to be particularly valuable for informing healthcare policy-makers when formulating appropriate treatment pathways, encouraging the optimal allocation of scarce resources, and improving aggregate patient outcomes. However, little guidance is available on the relative merits of using efficacy and/or effectiveness evidence in Health Technology Appraisal submissions. Further research is needed to better understand these methods and their potential applications in a broader range of scenarios and simulation studies, and their impact on economic modeling.

An analysis of the cost-effectiveness of starting insulin detemir in insulin-naïve people with type 2 diabetes

AIMS

There is limited evidence with respect to the cost-effectiveness of starting insulin in people with diabetes outside the 'western' world. The aim of this study was to assess the cost-effectiveness of starting basal insulin treatment with insulin detemir in people with type 2 diabetes (T2D) inadequately controlled on oral glucose-lowering drugs (OGLDs) in Mexico, South Korea, India, Indonesia, and Algeria.

METHODS

The IMS CORE Diabetes Model was used to project clinical and cost outcomes over a 30-year time horizon. Clinical outcomes, baseline characteristics and health state utility data were taken from the A1chieve study. A 1-year analysis was also conducted based on treatment costs and quality-of-life data. Incremental cost-effectiveness ratios (ICERs) were expressed as a fraction of GDP per capita, and WHO-CHOICE recommendations (ICER < 3.0) used to define cost-effectiveness.

RESULTS

Starting insulin detemir was associated with a projected increase in life expectancy (≥1 year) and was considered cost-effective in all of the studied populations with ICERs of -0.02 (Mexico), 0.00 (South Korea), 0.48 (India), 0.12 (Indonesia), and 0.88 (Algeria) GDP/quality-adjusted life-year. Cost-effectiveness was maintained after conducting sensitivity analyses in the 30-year and 1-year analyses. A projected increase in treatment costs was partially offset by a reduction in complications. The difference in overall costs between insulin detemir and OGLDs alone was USD518, 1431, 3510, 15, and 5219, respectively.

CONCLUSION

Changes in clinical outcomes associated with starting insulin detemir in insulin-naïve individuals with T2D resulted in health gains that made the intervention cost-effective in five countries with distinct healthcare resources.

An analysis of the short- and long-term cost-effectiveness of starting biphasic insulin aspart 30 in insulin-naïve people with poorly controlled type 2 diabetes

AIM

This study aimed to assess the cost-effectiveness of starting insulin therapy with biphasic insulin aspart 30 (BIAsp 30) in people with type 2 diabetes inadequately controlled on oral glucose-lowering drugs in Saudi Arabia, India, Indonesia, and Algeria.

METHODS

The IMS CORE Diabetes Model was used to evaluate economic outcomes associated with starting BIAsp 30, using baseline characteristics and treatment outcomes from the A(1)chieve study. Time horizons of 1 and 30 years were applied, with country-specific costs for complications, therapies, and background mortality. Incremental cost-effectiveness ratios (ICERs) are expressed as cost per quality-adjusted life-year (QALY) in local currencies, USD, and fractions of local GDP per capita (GDPc). Cost-effectiveness was pre-defined using the World Health Organization definition of <3.0 times GDPc. Comprehensive sensitivity analyses were performed.

RESULTS

In the primary 30-year analyses, starting BIAsp 30 was associated with a projected increase in life expectancy of >1 year and was highly cost-effective, with ICERs of -0.03 (Saudi Arabia), 0.25 (India), 0.48 (India), 0.47 (Indonesia), and 0.46 (Algeria) GDPc/QALY. The relative risk of developing selected complications was reduced in all countries. Sensitivity analyses including cost of self-monitoring, treatment costs, and deterioration of glucose control with time showed the results to be robust. In a 1-year analysis, ICER per QALY gained was still cost-effective or highly cost-effective.

CONCLUSION

Starting BIAsp 30 in people with type 2 diabetes in the A(1)chieve study was found to be cost-effective across all country settings at 1- and 30-year time horizons, and usefully increased predicted life expectancy.