Microsimulation Model Research Articles

Addition of continuous glucose monitoring to glucagon-like peptide 1 receptor agonist treatment for type 2 diabetes mellitus - An economic evaluation.

Both glucagon-like peptide 1 receptor agonists (GLP-1 RAs) and continuous glucose monitoring (CGM) have been shown to improve glycated hemoglobin A1c (A1c) levels among patients with type 2 diabetes mellitus (T2DM). Recently, a US real-world study found statistically significant improvements in A1c levels among patients using GLP-1 RA and a CGM device, compared with a matched cohort receiving only GLP-1 RA. To assess the cost-effectiveness from a US payer perspective of initiating CGM (FreeStyle Libre Systems) in people living with T2DM using a GLP-1 RA therapy, compared with GLP-1 RA alone. A patient-level microsimulation model was run for 10,000 patients over a lifetime horizon with 3.0% discounting for costs and utilities. Patient characteristics were based on the overall population of the US real-world study and the subgroup of patients not using intensive insulin. The effect of CGM was modeled as a persistent reduction in A1c compared with GLP-1 RA alone (overall = 0.37%; patients not using intensive insulin = 0.34%). Costs ($2,023) and disutilities were applied to diabetes complications and acute diabetic events. Outcomes were assessed as quality-adjusted life years (QALYs). The base-case incremental cost-effectiveness ratio (incremental costs/incremental QALYs) for GLP-1 RA plus CGM vs GLP-1 RA alone was $40,968/QALY in the overall cohort (cost = $484,180 vs $473,938; QALYs = 13.37 vs 13.12). Among patients not using intensive insulin, the incremental cost-effectiveness ratio was $43,095/QALY. Scenario analysis showed that the model results were robust to changing assumptions. Probabilistic sensitivity analysis showed that GLP-1 RA plus CGM had a 64% probability of being cost-effective at a willingness-to-pay threshold of $100,000 per QALY. From a US payer perspective, CGM is cost-effective when added to GLP-1 RA therapies for the treatment of T2DM, including for patients not using intensive insulin.

Evaluating strategies for global respiratory pandemic control at ports: a modelling study

BackgroundHeavy reliance on container shipping during the COVID-19 pandemic with lockdown implementation and air travel bans placed substantial pressure on shipping crews and ports. Long waiting times at ports, substantial...

Optimal allocation of antenatal and young child nutrition interventions: an individual-based global burden of disease calibrated microsimulation

BackgroundUndernutrition remains a global crisis and is a focus of Sustainable Development Goals. While there are multiple known, effective interventions, complex interactions between prevention and treatment and resource constraints can lead to difficulties in allocating funding. Simulation studies that use in silico simulation can help illuminate the interactions between interventions and provide insight into the cost-effectiveness of alternative packages of options.MethodsWe developed an individual-based microsimulation model based on the Global Burden of Disease (GBD) 2021 study data to test a range of nutrition interventions, including antenatal interventions (iron and folic acid, multiple micronutrients, and balanced energy protein supplementation) and child interventions (treatment for severe acute malnutrition, treatment for moderate acute malnutrition, and wasting prevention with small-quantity lipid-based nutrient supplements). We also developed an analytic approach to process the results of the microsimulation and identify the optimal intervention funding allocation for a given budget size. We use Ethiopia as an example in this paper.ResultsIn our illustrative example of Ethiopia, the reallocation of the baseline budget to minimize disability-adjusted life years (DALYs) resulted in first funding the antenatal multiple micronutrients to their maximum coverage and then funding treatment for severe child acute malnutrition. Relative to the baseline allocation, the reallocation optimized to minimizing DALYs resulted in 592,000 fewer annual DALYs, constituting an 8.3% reduction in total DALYs in Ethiopia.For budgets larger than the baseline, our model recommended funding first targeted moderate acute malnutrition treatment, second universal moderate acute malnutrition treatment, third wasting prevention with small-quantity lipid-based nutrient supplements, and fourth balanced energy protein supplementation.ConclusionsOur simulation is a novel model for estimating optimal allocation of spending on antenatal and child health nutrition interventions which accounts for the interaction between preventive and therapeutic approaches. Our illustrative results show that an optimized reallocation of current spending can substantially improve pregnancy-related and child health without additional funding. We hope this model can add validity and confidence to prior results to aid stakeholders in funding decisions.

Long-term health consequences and costs of changes in alcohol consumption in England during the COVID-19 pandemic.

The COVID-19 pandemic led to changes in alcohol consumption in England. Evidence suggests that one-fifth to one-third of adults increased their alcohol consumption, while a similar proportion reported consuming less. Heavier drinkers increased their consumption the most and there was a 20% increase in alcohol-specific deaths in England in 2020 compared with 2019, a trend continuing through 2021 and 2022. This study aimed to quantify future health, healthcare, and economic impacts of changes in alcohol consumption observed during the COVID-19 pandemic. This study used a validated microsimulation model of alcohol consumption and health outcomes. Inputted data were obtained from the Alcohol Toolkit Study, and demographic, health and cost data from published literature and publicly available datasets. Three scenarios were modelled: short, medium, and long-term, where 2020 drinking patterns continue until the end of 2022, 2024, and 2035, respectively. Disease incidence, mortality, and healthcare costs were modelled for nine alcohol-related health conditions. The model was run from 2020 to 2035 for the population of England and different occupational social grade groups. In all scenarios, the microsimulation projected significant increases in incident cases of disease, premature mortality, and healthcare costs, compared with the continuation of pre-COVID-19 trends. If COVID-19 drinking patterns continue to 2035, we projected 147,892 excess cases of diseases, 9,914 additional premature deaths, and £1.2 billion in excess healthcare costs in England. The projections show that the more disadvantaged (C2DE) occupational social grade groups will experience 36% more excess premature mortality than the least disadvantaged social group (ABC1) under the long-term scenario. Alcohol harm is projected to worsen as an indirect result of the COVID-19 pandemic and inequalities are projected to widen. Early real-world data corroborate the findings of the modelling study. Increased rates of alcohol harm and healthcare costs are not inevitable but evidence-based policies and interventions are required to reverse the impacts of the pandemic on alcohol consumption in England.

Subgroups varying in risk and density highlight the potential for stratified breast cancer screening.

Most breast cancer screening programs rely only on demographic data without considering individual risk factors of the population, which might limit their effectiveness by over- and underscreening specific subgroups. Therefore, the aim of this study is to highlight health and economic disparities in outcomes from such a uniform screening strategy. With the microsimulation model MISCAN, we simulated outcomes of the Dutch screening program considering 16 subgroups varying by their 5-year breast cancer risk and breast density. All outcomes showed significant disparities across risk-density subgroups. Notably, women with extremely dense breasts showed a mortality reduction from the current screening of 16-17 % compared to 25-29 % in other groups. Absolute benefits (breast cancer deaths averted, and life-years gained) increased with risk and varied independently by density. The range of false-positive rates varied almost twofold across the span of subgroups and nearly a ninefold difference in the medical costs incurred with lifelong follow-up. These findings emphasize the potential for stratified screening strategies to improve equity in health outcomes and reduce the burden of breast cancer.

Development of Mixed Traffic Microsimulation Model Calibration for Signalized Intersections

Development of Mixed Traffic Microsimulation Model Calibration for Signalized Intersections

Cost-effectiveness of FRAX®-based intervention thresholds for management of osteoporosis in Indian women: a Markov microsimulation model analysis.

Osteoporosis represents a significant public health challenge in India, with an increasing economic burden due to the aging population. This study evaluated the cost-effectiveness of using fracture risk assessment tool (FRAX®)-based intervention thresholds (ITs) for managing osteoporosis with generic alendronate in Indian women. A Markov microsimulation model, adapted to the Indian healthcare context, was used to simulate the costs and quality-adjusted life years (QALYs) associated with different treatment strategies. The one-time gross domestic product (GDP) per capita (estimated at INR 1,97,468/QALY gained) was used as the cost-effectiveness threshold. The model revealed that generic alendronate is cost-effective for major osteoporotic fracture (MOF) ITs beginning at age 60years with full adherence-incremental cost-effectiveness ratio (ICER) of INR 102,151 per QALY gained, and age 65 with real-world adherence-ICER of INR 28,203 per QALY gained (conversion rate used is 1 US dollar (USD) = INR 83.97 and 1 EURO = INR 92.70). Hip fracture (HF) ITs showed similar cost-effectiveness at ages 60 (ICER of INR 67,144) and was the dominant strategy (i.e., more QALYs for lower costs) at ≥ 65years. Fixed ITs of 14% for MOF and 3.5% for HF proved cost-effective across all age groups (dominant strategy for ages ≥ 65years). Limitations of our study include the reliance on fracture incidence data from Singaporean Indians and variability in fracture prevalence across India. The results support the integration of FRAX®-based fixed ITs from the age of 50years and age-based ones from the age of 65years in India to optimize resource allocation and improve osteoporosis management.

The Clinical and Economic Burden of Chronic Kidney Disease in Poland: Inside Patient-Level Microsimulation Modelling of CKD.

Background/Objectives: Chronic kidney disease (CKD) is associated with increased annual costs, with the highest costs attributable to renal replacement therapy (RRT). These costs will rise as prevalence increases. Therefore, forecasting the future prevalence and economic burden of CKD, particularly in underdiagnosed populations, may provide valuable insights to policymakers looking at strategies to implement interventions to delay CKD progression. Methods: As part of the Inside CKD study, this work used epidemiological data to generate a virtual population representative of Poland that progressed through a microsimulation in 1-year increments between 2022 and 2027. This microsimulation was used to assess the clinical and economic burdens of CKD in Poland. Results: Between 2022 and 2027, the percentage of individuals with CKD is projected to increase from 10.7% to 11.3%. Only 30.1% of individuals with CKD will be diagnosed in 2027. During this time, the total healthcare cost of individuals with diagnosed CKD pre-RRT is predicted to decrease slightly from $73 million to $62 million. However, the total healthcare cost of individuals with diagnosed CKD is projected to increase by 23.1% when including RRT. Conclusions: This study shows that the clinical and economic burdens of individuals with CKD will worsen in the upcoming years. The implementation of policies to enhance the early detection of CKD and the initiation of treatments to slow disease progression should be implemented to reduce the number of individuals requiring RRT.

Microsimulation Estimates of Decision Uncertainty and Value of Information Are Biased but Consistent.

Individual-level state-transition microsimulations (iSTMs) have proliferated for economic evaluations in place of cohort state transition models (cSTMs). Probabilistic economic evaluations quantify decision uncertainty and value of information (VOI). Previous studies show that iSTMs provide unbiased estimates of expected incremental net monetary benefits (EINMB), but statistical properties of iSTM-produced estimates of decision uncertainty and VOI remain uncharacterized. We compare iSTM-produced estimates of decision uncertainty and VOI to corresponding cSTMs. For a 2-alternative decision and normally distributed incremental costs and benefits, we derive analytical expressions for the probability of being cost-effective and the expected value of perfect information (EVPI) for cSTMs and iSTMs, accounting for correlations in incremental outcomes at the population and individual levels. We use numerical simulations to illustrate our findings and explore the impact of relaxing normality assumptions or having >2 decision alternatives. iSTM estimates of decision uncertainty and VOI are biased but asymptotically consistent (i.e., bias approaches 0 as number of microsimulated individuals approaches infinity). Decision uncertainty depends on 1 tail of the INMB distribution (e.g., P[INMB <0]), which depends on estimated variance (larger with iSTMs given first-order noise). While iSTMs overestimate EVPI, their direction of bias for the probability of being cost-effective is ambiguous. Bias is larger when uncertainties in incremental costs and effects are negatively correlated since this increases INMB variance. iSTMs are useful for probabilistic economic evaluations. While more samples at the population uncertainty level are interchangeable with more microsimulations for estimating EINMB, minimizing iSTM bias in estimating decision uncertainty and VOI depends on sufficient microsimulations. Analysts should account for this when allocating their computational budgets and, at minimum, characterize such bias in their reported results. Individual-level state-transition microsimulation models (iSTMs) produce biased but consistent estimates of the probability that interventions are cost-effective.iSTMs also produce biased but consistent estimates of the expected value of perfect information.The biases in these decision uncertainty and value-of-information measures are not reduced by more parameter sets being sampled from their population-level uncertainty distribution but rather by more individuals being microsimulated for each parameter set sampled.Analysts using iSTMs to quantify decision uncertainty and value of information should account for these biases when allocating their computational budgets and, at minimum, characterize such bias in their reported results.

Impact analysis of infant antibiotic exposure on the burden of asthma: a simulation modeling study

BackgroundInfant antibiotic use is associated with increased risk of asthma. We examined the population impact of antibiotic exposure in the first year of life on the burden of pediatric asthma in British Columbia, Canada, using simulation modeling.MethodsWe performed a Bayesian meta-analysis of empirical studies to construct dose-response equations between antibiotic exposure in the first year of life and pediatric (&amp;lt;19 years of age) asthma. We used administrative health data to document trends in infant (&amp;lt;1 year of age) antibiotic use in British Columbia during 2001 and 2018 (the study period). An independently developed microsimulation model of asthma was utilized to estimate asthma-related outcomes under three scenarios pertaining to the trends in antibiotic use during the study period: (1) observed trends, (2) flat trend in which the prescription rate remained at the 2001 value, and (3) intermediate trends midway between these two. We reported cumulative person-years with asthma, cumulative asthma incidence, and cumulative asthma exacerbations among the pediatric population during the study period.ResultsThere were 773,160 live births during the study period, with an average antibiotic prescription rate of 523 per 1,000 infants in the first year of life. The prescription rate decreased by 71.5% during the study period. In Scenario 1, there were 1,982,861 person-years with asthma, 183,392 asthma incident cases, and 383,072 exacerbations. Had the antibiotic exposure remained at the 2001 values (Scenario 2), there would have been additional 37,213 person-years with asthma, 10,053 asthma incident cases, and 23,280 exacerbations. Had the decline been half of the observed trend (Scenario 3), there would have been additional 20,318 person-years with asthma, 5,486 asthma incident cases, and 12,728 exacerbations. At least 80% of the excess burden in each outcome was attributable to the younger pediatric population of &amp;lt;10 years of age.ConclusionsThe decline in infant antibiotic exposure has resulted in a substantial reduction in the burden of asthma in British Columbia. Such benefits should be considered when evaluating the value proposition of initiatives aimed at reducing unnecessary antibiotic exposure in early life.

Estimating the effects of Basic Income schemes on mental and physical health among adults aged 18 and above in the UK: A microsimulation study

Basic Income is a largely unconditional, regular payment to all permanent residents to support basic needs. It has been proposed as an upstream health intervention by increasing income size and security. Modelling has quantified prospective effects on UK young people’s mental health. This paper extends this analysis to mental and physical health among adults aged 18+ using data from the 2021/22 Family Resources Survey and 12 waves (2009/11-2020/22) of Understanding Society to model the effects of three prospective schemes: 1) (£ per week) £50 per under-18, £75 per 18–64, £205 per 65+; 2) £75, £185, £205; 3) £100, £295, £295. We estimated effects on cases of depressive disorders (SF-12 MCS ≤45.6) and physical health problems (SF-12 PCS ≤50), quality-adjusted life years (QALYs) and willingness-to-pay value gained, as well as direct NHS, personal social services and patients’ associated costs savings regarding depressive disorders. Between 124,000 (95% CI: 86,000–150,000) and 1.005m (95% CI: 845,000–1.402m) cases of depressive disorders and 118,000 (70,000–156,000) to 1.042m (881,000–1.612m) cases of physical health problems could be prevented or postponed each year depending on the scheme. 129,000 (86,000–172,000) to 655,000 (440,000–870,000) QALYs could be gained, valued at £3.87bn (£2.58bn–£5.16bn) to £19.65bn (£13.21bn–£26.10bn). Estimated 2023 NHS and personal social services cost savings are between £126m (£88m–£154m) and £1.026bn (£872m–£1.432bn) assuming 50% of depressive disorders cases are diagnosed and treated at baseline. Estimating savings based on physical health problems is more difficult, but may reflect far greater related NHS and social care spend. Although non-income change impacts are not microsimulated, these findings indicate that Basic Income could provide substantial population health benefits, social return on investment and health and social care system savings. This gives policymakers and researchers an evidence base on which to base trial and policy design. Basic Income; Social determinants; Prevention; Upstream interventions; Microsimulation modelling.

A mobile-based randomized controlled trial on the feasibility and effectiveness of screening for major depressive disorder: study protocol

BackgroundMobile-based screening interventions to detect and treat Major Depressive Disorder (MDD) at an early stage might be a promising approach for reducing its societal burden. In the present study, we will evaluate the feasibility and effectiveness of screening for MDD using a mobile-based screening protocol.MethodsThis study will be a three-arm, parallel randomized control trial (RCT) performed in a multi-ethnic population within the municipality of Rotterdam (the Netherlands). The trial includes two intervention groups that will be screened 4-weekly for MDD for 12 months using the Patient Health Questionnaire (PHQ-9) and a control group who does not receive mobile-based screening for MDD. Participants in the one-test intervention arm will be referred for further diagnosis and treatment, if necessary, after a single positive test score for moderate-severe major depression symptoms (PHQ-9 > 10). Participants in the multiple-test intervention arm will only be referred after three consecutive positive test scores. 1786 eligible participants will be included in the RCT, with 446 and 447 in the one-test and multiple-test referral arms, respectively, and 893 in the control arm. Primary outcome is participants’ QoL after 12 months (EQ-5D-5L). Secondary outcomes include participants’ QoL after 24 months (EQ-5D-5L), evaluating the occurrence and severity of MDD symptoms (PHQ-9), intervention engagement, and identifying public mental health differences based on sociodemographic characteristics, including age, gender, ethnicity, financial situation, educational background, and living area. Long-term results of the RCT will be incorporated into a microsimulation model to determine the long-term benefits, harms, and costs of MDD screening.DiscussionThe information gained from examining the feasibility and (cost-) effectiveness of mobile-based screening for MDD could be of guidance for mental health policy implementations and support the introduction of mobile-based screening for MDD in the Netherlands and/or other nations.Trial registrationClinicalTrials.gov: NL84280.078.23, NCT05989412, August 8, 2024.

Cost-Effectiveness of FreeStyle Libre for Glucose Self-Management Among People with Diabetes Mellitus: A Canadian Private Payer Perspective.

For people living with diabetes, effective glucose monitoring is a key component in diabetes care, helping to reduce disease burden, complications, and healthcare utilization. Sensor-based glucose monitoring systems, which can provide more comprehensive information about glucose levels than capillary-based self-monitoring of blood glucose (SMBG), are becoming established among people living with diabetes. The objective of this study was to assess the cost-effectiveness of glucose monitoring with FreeStyle Libre systems, compared with SMBG, from the perspective of a Canadian private payer. The analysis used the validated, person-level microsimulation model DEDUCE (Determination of Diabetes Utilities, Costs, and Effects). Analyses were conducted separately for populations of people with type 1 and type 2 diabetes mellitus (T1DM; T2DM), with time horizons of 40 and 25years, respectively. T2DM treatment was assumed to be 84% non-insulin, 10% basal insulin, and 6% multiple daily injections of insulin. The effect of FreeStyle Libre was modeled as reductions versus SMBG in glycated hemoglobin level (T1DM, - 0.42%; insulin-treated T2DM, - 0.59%; non-insulin-treated T2DM, - 0.3%) and in acute diabetic events (hypoglycemia and diabetic ketoacidosis). Costs (in 2023Canadian dollars (Can$)) and utilities were discounted at 1.5%. Outcomes were assessed as costs andquality-adjusted life years (QALYs). In both populations, FreeStyle Libre was dominant to SMBG, providing more QALYs at a lower cost (T1DM: + 1.25 QALYs, - Can$32,287 costs; T2DM: + 0.48 QALYs, - Can$8091 costs). Reductions were seen in the cumulative incidence of all complications (except blindness in the T1DM analysis). FreeStyle Libre was dominant to SMBG in all scenarios tested. Probabilistic sensitivity analysis showed that FreeStyle Libre had a 100% probability of being dominant to SMBG for T1DM and a 91% probability of being dominant for T2DM. This economic analysis shows that, from a Canadian private payer perspective, FreeStyle Libre is cost-effective compared with SMBG for all people living with diabetes.

Microsimulation Analysis of COVID-19 and Inflation Effects on Romanian Household Income Dynamics

In recent years, EU member states have faced two significant crises: the COVID-19 pandemic and high inflation, exacerbated by geopolitical instability. These events have led to a decline in household purchasing power. Our study aims to quantify the impact of these crises on household income dynamics in Romania, using data from the EU Survey on Income and Living Conditions and the EUROMOD tax-benefit microsimulation model. We analyze income changes across demographic segments from 2019 to 2021 (COVID-19 period) and 2021 to 2023 (inflation crisis), focusing on household characteristics such as the presence and number of children, the gender of the household head, and the presence of elderly members. Our findings reveal that while disposable income increased from 2019 to 2021, the poorest 10% experienced the smallest gains. In 2022–2023, inflation eroded these increases, and the lower half of the income distribution struggled with reduced earnings and pensions. Despite this, the Gini coefficient for disposable income decreased from 2019 to 2023, indicating a reduced inequality. Our study highlighted that targeted public policy interventions are essential to support vulnerable households and mitigate the effects of economic shocks.

Reduced Breast and Ovarian Cancer Through Targeted Genetic Testing: Estimates Using the NEEMO Microsimulation Model.

Background: The effectiveness and cost-effectiveness of genetic testing for hereditary breast and ovarian cancer largely rely on the identification and clinical management of individuals with a pathogenic variant prior to developing cancer. Simulation modelling is commonly utilised to evaluate genetic testing strategies due to its ability to synthesise collections of data and extrapolate over long time periods and large populations. Existing genetic testing simulation models use simplifying assumptions for predictive genetic testing and risk management uptake, which could impact the reliability of their estimates. Our objective was to develop a microsimulation model that accurately reflects current genetic testing and subsequent care in Australia, directly incorporating the dynamic nature of predictive genetic testing within families and adherence to cancer risk management recommendations. Methods: The populatioN gEnEtic testing MOdel (NEEMO) is a population-level microsimulation that incorporates a detailed simulation of individuals linked within five-generation family units. The genetic component includes heritable high- and moderate-risk monogenic gene variants, as well as polygenic risk. Interventions include clinical genetic services, breast screening, and risk-reducing surgery. Model validation is described, and then to illustrate a practical application, NEEMO was used to compare clinical outcomes for four genetic testing scenarios in patients newly diagnosed with breast cancer (BC) and their relatives: (1) no genetic testing, (2) current practice, (3) optimised referral for genetic testing, and (4) genetic testing for all BC. Results: NEEMO accurately estimated genetic testing utilisation according to current practice and associated cancer incidence, pathology, and survival. Predictive testing uptake in first- and second-degree relatives was consistent with known prospective genetic testing data. Optimised genetic referral and expanded testing prevented up to 9.3% of BC and 4.1% of ovarian cancers in relatives of patients with BC. Expanding genetic testing eligibility to all BC patients did not lead to improvement in life-years saved in at-risk relatives compared to optimised referral of patients eligible for testing under current criteria. Conclusions: NEEMO is an adaptable and validated microsimulation model for evaluating genetic testing strategies. It captures the real-world uptake of clinical and predictive genetic testing and recommended cancer risk management, which are important considerations when considering real-world clinical and cost-effectiveness.

Cost effectiveness of empagliflozin in adult patients with chronic kidney disease in the Netherlands.

The recent EMPA-KIDNEY trial showed evidence for preventing disease progression in adult patients with chronic kidney disease (CKD) treated with empagliflozin. It is however yet unknown if use of empagliflozin is cost effective in the Netherlands. We aimed to evaluate the cost effectiveness of empagliflozin in adult patients with CKD in the Netherlands. A cost-effectiveness analysis was conducted using a Markov state microsimulation model, simulating kidney progression of CKD patients with eGFR <90 ml/min per 1.73 m2 comparing empagliflozin plus standard of care (SoC) and SoC alone. KDIGO classification was used to describe the risk of CKD progression. The input data were taken from the EMPA-KIDNEY trial (baseline characteristics, treatment effect, and utilities), and published data and national sources were used for general population mortality, treatment and event costs. The analyses were performed from a societal perspective with applying a lifetime horizon. Discounting was done according to the Dutch pharmacoeconomic guidelines. The incremental cost-effectiveness ratio (ICER) was compared to a willingness-to-pay threshold of €50,000/QALY. Deterministic and probabilistic sensitivity analyses were performed to explore the impact of uncertainty around the input parameters. The base-case results showed total discounted costs for empagliflozin plus SoC and SoC alone of €200,193 and €234,574 respectively, indicating total savings of €34,380. Empagliflozin plus SoC was associated with higher total discounted health benefits of 11.06 life years (LYs) and 9.01 quality-adjusted life years (QALYs), compared with 9.74 LYs and 7.79 QALYs for SoC alone, resulting in an additional 1.31 LYs and 1.22 QALYs for empagliflozin plus SoC. Empagliflozin plus SoC is a dominant alternative compared to SoC alone. Sensitivity analyses confirmed the robustness of the findings and conclusion. Using empagliflozin in addition to SoC in adult patients with CKD is likely to be cost saving compared to the current SoC in the Netherlands, irrespective of diabetes status and albuminuria.

A calibrated model for lung cancer natural history: the case for New Zealand

ABSTRACT A microsimulation model is an ideal tool to evaluate the impact of the new health screening programme. Health policymakers in New Zealand are reviewing international evidence on lung cancer screening with the aim of reducing lung cancer mortality through early detection. In this study, we developed and calibrated a New Zealand specific microsimulation model for the natural history of lung cancer. This is the first time a lung cancer microsimulation model has been developed for New Zealand. We adapted simulation steps devised for the MIcrosimulation Lung Cancer (MILC) model (Chrysanthopoulou, 2017). The simulation steps include a Gompertz tumour growth component, disease progression based on log-normal distributions and a survival component. Simulated lung cancer rates at different disease stages (i.e. local, regional, and distant) and at diagnosis were used to calibrate and validate model parameters to data from the New Zealand (NZ) lung cancer registry. We used the Bayesian approach to calibrate the model parameters using the Hamiltonian Monte Carlo (HMC) approach, which is not commonly employed in the field of cancer modelling. The calibrated model was able to predict general trends in lung cancer incidence by age group when compared to lung cancer incidence in NZ.

Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review

BackgroundTraditional epidemiological models tend to oversimplify the transmission dynamics of Mycobacterium tuberculosis (M.tb) to replicate observed tuberculosis (TB) epidemic patterns. This has led to growing interest in advanced methodologies like agent-based modelling (ABM), which can more accurately represent the complex heterogeneity of TB transmission.ObjectivesTo better understand the use of agent-based models (ABMs) in this context, we conducted a systematic review with two main objectives: (1) to examine how ABMs have been employed to model the intricate heterogeneity of M.tb transmission, and (2) to identify the challenges and opportunities associated with implementing ABMs for M.tb.Search methodsWe conducted a systematic search following PRISMA guidelines across four databases (MEDLINE, EMBASE, Global Health, and Scopus), limiting our review to peer-reviewed articles published in English up to December 2022. Data were extracted by two investigators using a standardized extraction tool. Prospero registration: CRD42022380580.Selection criteriaOur review included peer-reviewed articles in English that implement agent-based, individual-based, or microsimulation models of M.tb transmission. Models focusing solely on in-vitro or within-host dynamics were excluded. Data extraction targeted the methodological, epidemiological, and computational characteristics of ABMs used for TB transmission. A risk of bias assessment was not conducted as the review synthesized modelling studies without pooling epidemiological data.ResultsOur search initially identified 5,077 studies, from which we ultimately included 26 in our final review after exclusions. These studies varied in population settings, time horizons, and model complexity. While many incorporated population heterogeneity and household structures, some lacked essential features like spatial structures or economic evaluations. Only eight studies provided publicly accessible code, highlighting the need for improved transparency.Authors’ conclusionsABMs are a versatile approach for representing complex disease dynamics, particularly in cases like TB, where they address heterogeneous mixing and household transmission often overlooked by traditional models. However, their advanced capabilities come with challenges, including those arising from their stochastic nature, such as parameter tuning and high computational expense. To improve transparency and reproducibility, open-source code sharing, and standardised reporting are recommended to enhance ABM reliability in studying epidemiologically complex diseases like TB.

Economic impact of dapagliflozin in the management of chronic kidney disease in Italy: results from a micro-simulation model

Background: Dapagliflozin, approved in the treatment of patients with chronic kidney disease (CKD), has demonstrated attenuation of CKD progression and a reduced risk of cardio-renal outcomes and all-cause mortality (ACM) versus placebo, in addition to standard of care (SoC). The aim of this economic evaluation was to assess the potential medical care cost offsets associated with reduced rates of cardio-renal outcomes in Italy. Methods: A comparative micro-simulation model estimated the outcome-related costs of dapagliflozin plus SoC versus SoC alone over a 3-year horizon based on the DAPA-CKD trial. Incidence rates of end-stage kidney disease (ESKD), hospitalizations for heart failure (hHF), acute kidney injury (AKI) and ACM were estimated for a treated population of 90,564 patients. Associated direct medical costs for non-fatal events (ESKD, hHF and AKI) were calculated using available literature and national tariffs. The analysis was restricted to outcome-associated costs and did not consider the cost of drug treatments and disease management. Results: Patients treated with dapagliflozin plus SoC experienced fewer incident events of ESKD (6,540 vs 9,751), hHF (2,146 vs 4,242), AKI (3,772 vs. 5,271) and ACM (5,780 vs 8,037) per 90,564 treated patients versus those treated with SoC alone. Reductions (–35,6%) in clinical events (ESKD, hHF and AKI) were associated with a 34.4% reduction in total costs (€ 170 million) over 3 years. The clinical effect of dapagliflozin on ESKD management accounted for a € 134.5 million reduction in total costs. Conclusion: Based on the DAPA-CKD trial, dapagliflozin may prevent cardio-renal event incidence with a positive effect upon the Italian National Healthcare Service (NHS). Over three years, we estimated that dapagliflozin can reduce the Italian NHS expenditure associated with the management of ESKD, hHF and AKI events by 34.4% (€ 170 million).

Immediate Versus 5-Year Risk-Guided Initiation of Treatment for Primary Prevention of Cardiovascular Disease for Australians Aged 40 Years: A Health Economic Analysis.

Current Australian cardiovascular disease (CVD) prevention guidelines calculate 5-year CVD risk and recommend treatment when risk crosses specific thresholds. This may leave risk factors untreated for people with a low short-term (i.e. 5 years), but high long-term (i.e. lifetime), risk of CVD. We aimed to evaluate the cost effectiveness of intervention for risk factor control at age 40 years (regardless of calculated risk) compared to intervention for risk factor control at the age recommended by contemporary Australian CVD prevention guidelines (when the 5-year CVD risk reaches 10%) across a range of individual risk factor profiles. We used a causal microsimulation model populated with 108 different risk factor profiles, each replicated 10,000 times. Model data were derived from the UK Biobank study and published sources. The primary causal relationships factored in were those of low-density lipoprotein-cholesterol and systolic blood pressure with CVD (defined as myocardial infarction or stroke). The model simulated the ageing of individuals from 40 to 85 years. We calculated years of life lived, quality-adjusted life-years gained, incremental healthcare costs and the incremental cost-effectiveness ratio when low-density lipoprotein-cholesterol and blood pressure were controlled from age 40 years compared to initiation of treatment as recommended by Australian guidelines. The main side effect in the model was an increased risk of type 2 diabetes mellitus from statin use. The trade-off between reduced CVD and increased type 2 diabetes was summarised via quality-adjust life-years. Incremental cost-effectiveness ratios were compared to the Australian willingness-to-pay threshold of AU$28,000 per quality-adjust life-year gained. We adopted a healthcare perspective (2022 AUD) and discounted results at 3% annually. An earlier intervention meaningfully prevented CVD in all but the lowest risk individuals. Intervention at age 40 years versus age when the 5-year CVD risk reaches 10% led to an increase in quality-adjust life-years for 37/54 female individuals and 44/54 male individuals simulated and an increase in years of life lived (i.e. life expectancy) for 46/54 female individuals and 47/54 male individuals simulated. Earlier intervention was also cost effective in 5/54 female individuals and 17/54 male individuals. Current guidelines may result in certain individuals with a lower 5-year, but higher lifetime, risk of CVD being overlooked for earlier cost-effective interventions to prevent CVD.