Decision models in type 2 diabetes mellitus: A systematic review

Cost-Effectiveness of Routine Monitoring of Long-Term Conditions in Primary Care: Informing Decision Modelling with a Systematic Review in Hypertension, Type 2 Diabetes and Chronic Kidney Disease

BACKGROUND

Long-term conditions (LTCs) are major public health problems with a considerable health-related and economic burden. Modelling is key in assessing costs and benefits of different disease management strategies, including routine monitoring, in the conditions of hypertension, type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD) in primary care.

OBJECTIVE

This review aimed to identify published model-based cost-effectiveness studies of routine laboratory testing strategies in these LTCs to inform a model evaluating the cost effectiveness of testing strategies in the UK.

METHODS

We searched the Medline and Embase databases from inception to July 2023; the National Institute for Health and Care Institute (NICE) website was also searched. Studies were included if they were model-based economic evaluations, evaluated testing strategies, assessed regular testing, and considered adults aged >16 years. Studies identified were summarised by testing strategies, model type, structure, inputs, assessment of uncertainty, and conclusions drawn.

RESULTS

Five studies were included in the review, i.e. Markov (n = 3) and microsimulation (n = 2) models. Models were applied within T2DM (n = 2), hypertension (n = 1), T2DM/hypertension (n = 1) and CKD (n = 1). Comorbidity between all three LTCs was modelled to varying extents. All studies used a lifetime horizon, except for a 10-year horizon T2DM model, and all used quality-adjusted life-years as the effectiveness outcome, except a TD2M model that used glycaemic control. No studies explicitly provided a rationale for their selected modelling approach. UK models were available for diabetes and CKD, but these compared only a limited set of routine monitoring tests and frequencies.

CONCLUSIONS

There were few studies comparing routine testing strategies in the UK, indicating a need to develop a novel model in all three LTCs. Justification for the modelling technique of the identified studies was lacking. Markov and microsimulation models, with and without comorbidities, were used; however, the findings of this review can provide data sources and inform modelling approaches for evaluating the cost effectiveness of testing strategies in all three LTCs.

Cost-Effectiveness Analysis of a Prescription Digital Therapeutic in Type 2 Diabetes

INTRODUCTION

BT-001 (AspyreRx™) prescription digital therapy, a form of personalized cognitive behavioral therapy, has demonstrated clinically meaningful and durable hemoglobin A1c reductions in patients with type 2 diabetes (T2D). The current study examined the cost-effectiveness of BT-001 plus standard of care (SoC) versus SoC alone in T2D over a lifetime horizon from a healthcare payer perspective.

METHODS

We modeled the T2D pathway using an individual patient-level simulation; clinical data were sourced from the intention-to-treat subset of the BT-001 randomized clinical trial (RCT). SoC across both arms included the composition of oral and injectable treatments for T2D. Events were simulated using the United Kingdom Prospective Diabetes Study Outcomes Model 2 risk equation. A 3-month model cycle length was used in the first year, then annual model cycles were used in line with the original risk engine specifications. Patient characteristics informed event equations and Monte Carlo random sampling was used to assess the occurrence of events within each model cycle. Incidence of hypoglycemic events, drug discontinuation, costs, and health utilities and disutility values were sourced from the literature.

RESULTS

From a payer perspective, BT-001 plus SoC versus SoC alone was dominant with a gain in quality-adjusted life years (QALYs) of 0.101 and cost savings of $7343 per patient over the lifetime horizon (i.e., more effective and less costly). BT-001 plus SoC was cost-effective at a willingness-to-pay of $100,000 per QALY (incremental net monetary benefit was $17,443). Savings with BT-001 were primarily driven by a reduction in drug acquisition costs. The reduction in hemoglobin A1c with BT-001 was associated with fewer T2D complications.

CONCLUSIONS

BT-001 plus SoC was estimated to dominate SoC alone over the lifetime horizon from a payer perspective, suggesting that using BT-001 can empower patients to better manage their diabetes with the potential for lifelong advantages.

A Systematic Review of Methodologies Used in Models of the Treatment of Diabetes Mellitus

BACKGROUND

Diabetes mellitus is a chronic and complex disease, increasing in prevalence and consequent health expenditure. Cost-effectiveness models with long time horizons are commonly used to perform economic evaluations of diabetes' treatments. As such, prediction accuracy and structural uncertainty are important features in cost-effectiveness models of chronic conditions.

OBJECTIVES

The aim of this systematic review is to identify and review published cost-effectiveness models of diabetes treatments developed between 2011 and 2022 regarding their methodological characteristics. Further, it also appraises the quality of the methods used, and discusses opportunities for further methodological research.

METHODS

A systematic literature review was conducted in MEDLINE and Embase to identify peer-reviewed papers reporting cost-effectiveness models of diabetes treatments, with time horizons of more than 5 years, published in English between 1 January 2011 and 31 of December 2022. Screening, full-text inclusion, data extraction, quality assessment and data synthesis using narrative synthesis were performed. The Philips checklist was used for quality assessment of the included studies. The study was registered in PROSPERO (CRD42021248999).

RESULTS

The literature search identified 30 studies presenting 29 unique cost-effectiveness models of type 1 and/or type 2 diabetes treatments. The review identified 26 type 2 diabetes mellitus (T2DM) models, 3 type 1 DM (T1DM) models and one model for both types of diabetes. Fifteen models were patient-level models, whereas 14 were at cohort level. Parameter uncertainty was assessed thoroughly in most of the models, whereas structural uncertainty was seldom addressed. All the models where validation was conducted performed well. The methodological quality of the models with respect to structure was high, whereas with respect to data modelling it was moderate.

CONCLUSIONS

Models developed in the past 12 years for health economic evaluations of diabetes treatments are of high-quality and make use of advanced methods. However, further developments are needed to improve the statistical modelling component of cost-effectiveness models and to provide better assessment of structural uncertainty.

Cost-Effectiveness of Pharmacist Care in Diabetes Management: A Systematic Review

INTRODUCTION

In recent years, the role of pharmacists has undergone significant transformation to become more patient-centered and involved in managing chronic diseases. Nonetheless, it remains unclear whether pharmacist involvement in diabetes management is cost-effective. This study aimed to systematically review the cost-effectiveness and reporting quality in comprehensive economic evaluations of pharmacist management compared to standard care in diabetes.

METHODS

Eligible studies included cost-effectiveness analyses employing pharmacist professional services as the intervention for diabetes. A literature search was conducted in the bibliographic databases Pubmed, Scopus, China National Knowledge Infrastructure (CNKI), and the International Health Technology Assessment (HTA) database from their inception until July 2023. Two independent reviewers performed title, abstract, full-text screening, and data abstraction and assessed the quality of reporting and methodological approaches using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) checklists.

RESULTS

Twelve studies were identified with an average research quality score of 19.8, including cost-utility (n = 5) and cost-effectiveness (n = 7) analyses, with only four studies rated as high quality. The efficacy data were derived from randomized controlled trials (n = 7), retrospective studies (n = 2), and published literature sources (n = 2). Half of the included studies were conducted in high-income countries, while the other half was in upper-middle and lower-middle-income countries, respectively. Despite significant variations in the cost of pharmacist intervention, consistent findings demonstrate that pharmacist involvement in diabetes management is more cost-effective or even cost-saving than standard care, primarily attributed to better glycemic control, enhanced patient compliance, and reduced risks of medication-related problems.

CONCLUSION

This systematic review substantiates that pharmacist involvement in diabetes management is cost-effective compared with standard care. However, the overall quality of reporting needs to be improved, and high-quality evidence is urgently needed to support healthcare decision-making in pharmacy practice.

Prediction of complications in health economic models of type 2 diabetes: a review of methods used

AIM

Diabetes health economic (HE) models play important roles in decision making. For most HE models of diabetes 2 diabetes (T2D), the core model concerns the prediction of complications. However, reviews of HE models pay little attention to the incorporation of prediction models. The objective of the current review is to investigate how prediction models have been incorporated into HE models of T2D and to identify challenges and possible solutions.

METHODS

PubMed, Web of Science, Embase, and Cochrane were searched from January 1, 1997, to November 15, 2022, to identify published HE models for T2D. All models that participated in The Mount Hood Diabetes Simulation Modeling Database or previous challenges were manually searched. Data extraction was performed by two independent authors. Characteristics of HE models, their underlying prediction models, and methods of incorporating prediction models were investigated.

RESULTS

The scoping review identified 34 HE models, including a continuous-time object-oriented model (n = 1), discrete-time state transition models (n = 18), and discrete-time discrete event simulation models (n = 15). Published prediction models were often applied to simulate complication risks, such as the UKPDS (n = 20), Framingham (n = 7), BRAVO (n = 2), NDR (n = 2), and RECODe (n = 2). Four methods were identified to combine interdependent prediction models for different complications, including random order evaluation (n = 12), simultaneous evaluation (n = 4), the 'sunflower method' (n = 3), and pre-defined order (n = 1). The remaining studies did not consider interdependency or reported unclearly.

CONCLUSIONS

The methodology of integrating prediction models in HE models requires further attention, especially regarding how prediction models are selected, adjusted, and ordered.

MATHEMATICAL MODEL FOR PREDICTING FASTING BLOOD GLUCOSE LEVEL IN DIABETES MELLITUS PATIENTS

OBJECTIVE

The aim: To substantiate the use of data on patients' lifestyle, parameters of blood glucose, heart rate, blood pressure and bread units to build a mathematical model for predicting fasting blood glucose level in diabetes mellitus patients to improve existing measures for diabetes prevention.

PATIENTS AND METHODS

Materials and methods: An open database consisting of the studied parameters of 359 people was used in the research. The linear regression method was used to predict fasting blood glucose level in diabetes mellitus patients. The statistical software IBM SPSS Statistics Version 23 was chosen for calculations.

RESULTS

Results: To calculate the coefficients of the linear regression equation, stepwise elimination of parameters was chosen. The analysis of the coefficients of influence of independent variables on dependent showed that the greatest effect on the change in glucose level had value of consumed bread units. The model for women diagnosed with type 2 diabetes showed the highest accuracy.

CONCLUSION

Conclusions: Mathematical modeling made it clear that any malnutrition or health disorders can lead to a significant change in glucose levels. The obtained models consist of a number of parameters, some of which might depend on the presence of concomitant diseases. Further studies should focus on the optimal combination of various parameters taking into account methods of treating comorbidities.

The transferability and validity of a population-level simulation model for the economic evaluation of interventions in diabetes: the MICADO model

AIMS

Valid health economic models are essential to inform the adoption and reimbursement of therapies for diabetes mellitus. Often existing health economic models are applied in other countries and settings than those where they were developed. This practice requires assessing the transferability of a model developed from one setting to another. We evaluate the transferability of the MICADO model, developed for the Dutch 2007 setting, in two different settings using a range of adjustment steps. MICADO predicts micro- and macrovascular events at the population level.

METHODS

MICADO simulation results were compared to observed events in an Italian 2000-2015 cohort (Casale Monferrato Survey [CMS]) and in a Dutch 2008-2019 (Hoorn Diabetes Care Center [DCS]) cohort after adjusting the demographic characteristics. Additional adjustments were performed to: (1) risk factors prevalence at baseline, (2) prevalence of complications, and (3) all-cause mortality risks by age and sex. Model validity was assessed by mean average percentage error (MAPE) of cumulative incidences over 10 years of follow-up, where lower values mean better accuracy.

RESULTS

For mortality, MAPE was lower for CMS compared to DCS (0.38 vs. 0.70 following demographic adjustment) and adjustment step 3 improved it to 0.20 in CMS, whereas step 2 showed best results in DCS (0.65). MAPE for heart failure and stroke in DCS were 0.11 and 0.22, respectively, while for CMS was 0.42 and 0.41.

CONCLUSIONS

The transferability of the MICADO model varied by event and per cohort. Additional adjustments improved prediction of events for MICADO. To ensure a valid model in a new setting it is imperative to assess the impact of adjustments in terms of model accuracy, even when this involves the same country, but a new time period.

Role of mesenchymal stromal cells derivatives in diabetic foot ulcers: a controlled randomized phase 1/2 clinical trial

BACKGROUND

Diabetes-related foot complications have been identified as the most common isolated cause of morbidity among patients with diabetes and the leading cause of amputation. Therefore, new strategies to stimulate skin regeneration may provide a novel therapeutic approach to reduce non-healing ulcer disease. Recently, we demonstrated in proof-of-concept in humans that administration of allogeneic bone marrow mesenchymal stromal cellss derivatives (allo-hBM-MSCDs) is effective in a similar way to the use of allogeneic bone marrow mesenchymal stromal cellss (allo-hBM-MSCs) in grade 2 diabetic foot ulcers (DFUs).

AIM

To assess the safety and efficacy profile of the allo-hBM-MSCDs relative to the conventional approach (PolyMen® dressing) in 1/2 clinical trial phases in patients with grade 1 and 2 DFUs.

METHODS

In the present study, we used 2 doses of allo-hBM-MSCDs (1 mL) or 1 dose of allo-hBM-MSCs (1 × 106 cells) intradermally injected around wounds and assessed their safety and effectiveness, relative to the conventional approach (PolyMem dressing). Allo-hBM-MSCDs and allo-hBM-MSCs were produced in a certified Good Manufacturing Practice-type Laboratory. Patients with grade 1 and 2 DFUs were randomized to receive allo-hBM-MSCDs (n=12), allo-hBM-MSCs (n=6) or conventional treatment (PolyMem dressing) (n=10). The wound-healing process was macroscopically evaluated until the complete closure of the ulcers.

RESULTS

No adverse events were reported. Patients with grade 1 and 2 DFUs treated with either allo-hBM-MSCDs or allo-hBM-MSCs, achieved greater percentages of wound closure, enhanced skin regeneration in shorter times and a greater ulcer-free survival relative to the patients who received conventional treatment. Finally, through proteomic analysis, we elucidated the proteins and growth factors that are secreted by allo-hBM-MSCs and relevant to the wound-healing process. In addition, by combining proteomics with Gene Ontology analysis, we comprehensively classified secreted proteins on both biological process and molecular function.

CONCLUSIONS

In this phase 1/2 trial, our cumulative results suggest that 2 doses of allo-hBM-MSCDs combined with a wound dressing are a safe and effective treatment for grade 1 and 2 DFUs.

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.