Preventing liver disease with policy measures to tackle alcohol consumption and obesity: The HEPAHEALTH II study.

BACKGROUND & AIMS: Chronic liver disease (CLD) causes 1.8% of all deaths in Europe, many of them from liver cancer. We estimated the impact of several policy interventions in France, the Netherlands, and Romania. METHODS: We used a validated microsimulation model to assess seven different policy scenarios in 2022-2030: a minimum unit price (MUP) of alcohol of €0.70 or €1, a volumetric alcohol tax, a sugar-sweetened beverage (SSB) tax, food marketing restrictions, plus two different combinations of these policies compared against current policies (the 'inaction' scenario). RESULTS: All policies reduced the burden of CLD and liver cancer. The largest impact was observed for a MUP of €1, which by 2030 would reduce the cumulative incidence of CLD by between 7.1% to 7.3% in France, the Netherlands, and Romania compared with inaction. For liver cancer, the corresponding reductions in cumulative incidence were between 4.8% to 5.8%. Implementing a package containing a MUP of €0.70, a volumetric alcohol tax, and an SSB tax would reduce the cumulative incidence of CLD by between 4.29% to 4.71% and of liver cancer by between 3.47% to 3.95% in France, the Netherlands, and Romania. The total predicted reduction in healthcare costs by 2030 was greatest with the €1 MUP scenario, with a reduction for liver cancer costs of €8.18M and €612.49M in the Netherlands and France, respectively. CONCLUSIONS: Policy measures tackling primary risk factors for CLD and liver cancer, such as the implementation of a MUP of €1 and/or a MUP of €0.70 plus SSB tax could markedly reduce the number of Europeans with CLD or liver cancer. IMPACT AND IMPLICATIONS: Policymakers must be aware that alcohol and obesity are the two leading risk factors for chronic liver disease and liver cancer in Europe and both are expected to increase in the future if no policy interventions are made. This study assessed the potential of different public health policy measures to mitigate the impact of alcohol consumption and obesity on the general population in three European countries: France, the Netherlands, and Romania. The findings support introducing a €1 minimum unit price for alcohol to reduce the burden of chronic liver disease. In addition, the study shows the importance of targeting multiple drivers of alcohol consumption and obesogenic products simultaneously via a harmonized fiscal policy framework, to complement efforts being made within health systems. These findings should encourage policymakers to introduce such policy measures across Europe to reduce the burden of liver disease. The modeling methods used in this study can assist in structuring similar modeling in other regions to expand on this study's findings.

The Clinical Impact and Cost-Effectiveness of Surveillance of Incidentally Detected Gastric Intestinal Metaplasia: A Microsimulation Analysis.

BACKGROUND & AIMS: Gastric intestinal metaplasia (GIM) is associated with a higher risk of noncardia intestinal gastric adenocarcinoma (GA). The aim of this study was to estimate lifetime benefits, complications, and cost-effectiveness of GIM surveillance using esophagogastroduodenoscopy (EGD). METHODS: We developed a semi-Markov microsimulation model of patients with incidentally detected GIM, to compare the effectiveness of EGD surveillance with no surveillance at 10-year, 5-year, 3-year, 2-year, and 1-year intervals. We modeled a simulated cohort of 1,000,000 US individuals aged 50 with incidental GIM. Outcome measures were lifetime GA incidence, mortality, number of EGDs, complications, undiscounted life-years gained, and incremental cost-effectiveness ratio with a willingness-to-pay threshold of $100,000/quality-adjusted life-year (QALY). RESULTS: In the absence of surveillance, the model simulated 32.0 lifetime GA cases and 23.0 lifetime GA deaths per 1000 individuals with GIM, respectively. Among surveilled individuals, simulated lifetime GA incidence (per 1000) decreased with shorter surveillance intervals (10-year to 1-year, 11.2-6.1) as did GA mortality (7.4-3.6). Compared with no surveillance, all modeled surveillance intervals yielded greater life expectancy (87-190 undiscounted life-years gained per 1000); 5-year surveillance provided the greatest number of life-years gained per EGD performed and was the cost-effective strategy ($40,706/QALY). In individuals with risk factors of family history of GA or anatomically extensive, incomplete-type GIM intensified 3-year surveillance was cost-effective (incremental cost-effectiveness ratio $28,156/QALY and $87,020/QALY, respectively). CONCLUSIONS: Using microsimulation modeling, surveillance of incidentally detected GIM every 5 years is associated with reduced GA incidence/mortality and is cost-effective from a health care sector perspective. Real-world studies evaluating the impact of GIM surveillance on GA incidence and mortality in the United States are needed.

Cost-effectiveness of romosozumab for the treatment of postmenopausal women with osteoporosis at high risk of fracture in Belgium.

This study evaluated the cost-effectiveness of sequential treatment with romosozumab-to-alendronate compared to alendronate monotherapy and teriparatide-to-alendronate, in postmenopausal osteoporotic women from a Belgian healthcare perspective. Romosozumab-to-alendronate was found to be cost-effective compared to alendronate monotherapy and dominant compared to teriparatide-to-alendronate for osteoporotic women at high risk of fracture in Belgium. PURPOSE: This study aimed to evaluate the cost-effectiveness of sequential treatment with romosozumab followed by alendronate compared to alendronate monotherapy and teriparatide followed by alendronate, in postmenopausal osteoporotic women at high risk of fracture, from a Belgian healthcare perspective. Romosozumab is reimbursed in Belgium since December 2021. METHODS: A Markov microsimulation model was used to evaluate the cost-effectiveness of romosozumab-to-alendronate compared to alendronate monotherapy and to teriparatide-to-alendronate over a lifetime horizon. Patients transition between five different health states every 6 months based on fracture risks or death. The model was populated with Belgium-specific epidemiological and cost data, where available. The fracture risk reduction of romosozumab treatment was collated from the ARCH study, and from a published network meta-analysis. Costs were included from a healthcare perspective (NIHDI). Cost-effectiveness was reported in terms of costs per quality-adjusted life year (QALY), reported in Euro (€) 2022. Deterministic (DSA) and probabilistic sensitivity analyses (PSA) were performed. RESULTS: Romosozumab-to-alendronate was associated with 0.12 additional QALYs at an additional cost of €2314 compared to alendronate monotherapy, resulting in an ICER of €19,978. Compared to teriparatide-to-alendronate, romosozumab-to-alendronate was found to be dominant, with higher QALYs and lower costs. The base-case results were robust to uncertainty in the input parameters when conducting the sensitivity analysis. CONCLUSION: Sequential treatment with romosozumab followed by alendronate was found to be cost-effective compared to alendronate monotherapy and dominant compared to teriparatide followed by alendronate for postmenopausal women with osteoporosis at high risk of fracture in Belgium.

An Economic Evaluation of Family-Based Versus Traditional Helicobacter pylori Screen-and-Treat Strategy: Based on Real-World Data and Microsimulation Model.

OBJECTIVE: There is an economic evaluation on the family-based Helicobacter pylori screen-and-treat strategy (FBHS) in China. This study aimed to compare the cost-effectiveness of the FBHS with the traditional H. pylori screen-and-treat strategy (TBHS). MATERIALS AND METHODS: A seven-state microsimulation model, including H. pylori infection and gastric cancer states, was constructed on the basis of the target family samples from 29 provinces in China. Taking a lifetime horizon from a healthcare system perspective, the long-term costs and health outcomes of the FBHS and TBHS screening strategies were simulated separately, and economic evaluations were performed. The model parameters were primarily derived from real-world data, published literature, and expert opinions. The primary outcome was the incremental cost-effectiveness ratio (ICER) expressed as cost/quality-adjusted life-year (QALY) gained. One-way sensitivity analysis, probabilistic sensitivity analysis, and scenario analysis were performed to assess the uncertainty of the results. RESULTS: The base-case analysis revealed that the average costs for FBHS and TBHS were 563.67 CNY and 574.08 CNY, respectively, with corresponding average QALYs of 14.83 and 14.79. The ICER for the comparison between the two strategies was -214.07, indicating that FBHS was an absolutely dominant strategy with better cost-effectiveness. The results of both one-way sensitivity analysis and probabilistic sensitivity analysis were robust. When taking into account the added benefit of the higher H. pylori eradication rate in FBHS, the average costs were further reduced, and the average QALYs were increased, solidifying its position as an unequivocally dominant strategy. CONCLUSION: The FBHS is an absolutely dominant and cost-effective strategy that enables an optimized allocation of screening resources. Decision-makers should prioritize FBHS when developing H. pylori prevention and control strategies.

Microsimulation Models on Mental Health: A Critical Review of the Literature.

OBJECTIVES: To retrieve and synthesize the literature on existing mental health-specific microsimulation models or generic microsimulation models used to examine mental health, and to critically appraise them. METHODS: All studies on microsimulation and mental health published in English in MEDLINE, Embase, PsycINFO, and EconLit between January 1, 2010, and September 30, 2022, were considered. Snowballing, Google searches, and searches on specific journal websites were also undertaken. Data extraction was done on all studies retrieved and the reporting quality of each model was assessed using the Quality Assessment Reporting for Microsimulation Models checklist, a checklist developed by the research team. A narrative synthesis approach was used to synthesize the evidence. RESULTS: Among 227 potential hits, 19 studies were found to be relevant. Some studies covered existing economic-demographic models, which included a component on mental health and were used to answer mental-health-related research questions. Other studies were focused solely on mental health and included models that were developed to examine the impact of specific policies or interventions on specific mental disorders or both. Most models examined were of medium quality. The main limitations included the use of model inputs based on self-reported and/or cross-sectional data, small and/or nonrepresentative samples and simplifying assumptions, and lack of model validation. CONCLUSIONS: This review found few high-quality microsimulation models on mental health. Microsimulation models developed specifically to examine mental health are important to guide healthcare delivery and service planning. Future research should focus on developing high-quality mental health-specific microsimulation models with wide applicability and multiple functionalities.

Modeling Thyroid Cancer Epidemiology in the United States Using Papillary Thyroid Carcinoma Microsimulation Model.

OBJECTIVES: Thyroid cancer incidence increased over 200% from 1992 to 2018, whereas mortality rates had not increased proportionately. The increased incidence has been attributed primarily to the detection of subclinical disease, raising important questions related to thyroid cancer control. We developed the Papillary Thyroid Carcinoma Microsimulation model (PATCAM) to answer them, including the impact of overdiagnosis on thyroid cancer incidence. METHODS: PATCAM simulates individuals from age 15 until death in birth cohorts starting from 1975 using 4 inter-related components, including natural history, detection, post-diagnosis, and other-cause mortality. PATCAM was built using high-quality data and calibrated against observed age-, sex-, and stage-specific incidence in the United States as reported by the Surveillance, Epidemiology, and End Results database. PATCAM was validated against US thyroid cancer mortality and 3 active surveillance studies, including the largest and longest running thyroid cancer active surveillance cohort in the world (from Japan) and 2 from the United States. RESULTS: PATCAM successfully replicated age- and stage-specific papillary thyroid cancers (PTC) incidence and mean tumor size at diagnosis and PTC mortality in the United States between 1975 and 2015. PATCAM accurately predicted the proportion of tumors that grew more than 3 mm and 5 mm in 5 years and 10 years, aligning with the 95% confidence intervals of the reported rates from active surveillance studies in most cases. CONCLUSIONS: PATCAM successfully reproduced observed US thyroid cancer incidence and mortality over time and was externally validated. PATCAM can be used to identify factors that influence the detection of subclinical PTCs.

Benefit-Harm Analysis for Informed Decision Making on Participating in Colorectal Cancer Screening: A Modeling Study.

OBJECTIVES: To facilitate informed decision making on participating in colorectal cancer (CRC) screening, we assessed the benefit-harm balance of CRC screening for a wide range of subgroups over different time horizons. METHODS: The study combined incidence proportions of benefits and harms of (not) participating in CRC screening estimated by the Adenoma and Serrated pathway to CAncer microsimulation model, a preference eliciting survey, and benefit-harm balance modeling combining all outcomes to determine the net health benefit of CRC screening over 10, 20, and 30 years. Probability of net health benefit was estimated for 210 different subgroups based on age, sex, previous participation in CRC screening, and lifestyle. RESULTS: CRC screening was net beneficial in 183 of 210 subgroups over 30 years (median probability [MP] of 0.79, interquartile range [IQR] of 0.69-0.85) across subgroups. Net health benefit was greater for men (MP 0.82; IQR 0.69-0.89) than women (MP 0.76; IQR 0.67-0.83) and for those without history of participation in previous screenings (MP 0.84; IQR 0.80-0.89) compared with those with (MP 0.69; IQR 0.59-0.75). Net health benefit decreased with increasing age, from MP of 0.84 (IQR 0.80-0.86) at age 55 to 0.61 (IQR 0.56-0.71) at age 75. Shorter time horizons led to lower benefit, with MP of 0.70 (IQR 0.62-0.80) over 20 years and 0.54 (IQR 0.48-0.67) over 10 years. CONCLUSIONS: Our benefit-harm analysis provides information about net health benefit of screening participation, based on important characteristics and preferences of individuals, which could assist screening invitees in making informed decisions on screening participation.

The Determination of Diabetes Utilities, Costs, and Effects Model: A Cost-Utility Tool Using Patient-Level Microsimulation to Evaluate Sensor-Based Glucose Monitoring Systems in Type 1 and Type 2 Diabetes: Comparative Validation.

OBJECTIVES: To assess the accuracy and validity of the Determination of Diabetes Utilities, Costs, and Effects (DEDUCE) model, a Microsoft-Excel-based tool for evaluating diabetes interventions for type 1 and type 2 diabetes. METHODS: The DEDUCE model is a patient-level microsimulation, with complications predicted based on the Sheffield and Risk Equations for Complications Of type 2 diabetes models for type 1 and type 2 diabetes, respectively. For this tool to be useful, it must be validated to ensure that its complication predictions are accurate. Internal, external, and cross-validation was assessed by populating the DEDUCE model with the baseline characteristics and treatment effects reported in clinical trials used in the Fourth, Fifth, and Ninth Mount Hood Diabetes Challenges. Results from the DEDUCE model were evaluated against clinical results and previously validated models via mean absolute percentage error or percentage error. RESULTS: The DEDUCE model performed favorably, predicting key outcomes, including cardiovascular disease in type 1 diabetes and all-cause mortality in type 2 diabetes. The model performed well against other models. In the Mount Hood 9 Challenge comparison, error was below the mean reported from comparator models for several outcomes, particularly for hazard ratios. CONCLUSIONS: The DEDUCE model predicts diabetes-related complications from trials and studies well when compared with previously validated models. The model may serve as a useful tool for evaluating the cost-effectiveness of diabetes technologies.

Flexible Approaches Based on Multistate Models and Microsimulation to Perform Real-World Cost-Effectiveness Analyses: An Application to Proprotein Convertase Subtilisin-Kexin Type 9 Inhibitors.

OBJECTIVES: This study aims to show the application of flexible statistical methods in real-world cost-effectiveness analyses applied in the cardiovascular field, focusing specifically on the use of proprotein convertase subtilisin-kexin type 9 inhibitors for hyperlipidemia. METHODS: The proposed method allowed us to use an electronic health database to emulate a target trial for cost-effectiveness analysis using multistate modeling and microsimulation. We formally established the study design and provided precise definitions of the causal measures of interest while also outlining the assumptions necessary for accurately estimating these measures using the available data. Additionally, we thoroughly considered goodness-of-fit assessments and sensitivity analyses of the decision model, which are crucial to capture the complexity of individuals' healthcare pathway and to enhance the validity of this type of health economic models. RESULTS: In the disease model, the Markov assumption was found to be inadequate, and a "time-reset" timescale was implemented together with the use of a time-dependent variable to incorporate past hospitalization history. Furthermore, the microsimulation decision model demonstrated a satisfying goodness of fit, as evidenced by the consistent results obtained in the short-term horizon compared with a nonmodel-based approach. Notably, proprotein convertase subtilisin-kexin type 9 inhibitors revealed their favorable cost-effectiveness only in the long-term follow-up, with a minimum willingness to pay of 39 000 Euro/life years gained. CONCLUSIONS: The approach demonstrated its significant utility in several ways. Unlike nonmodel-based or alternative model-based methods, it enabled to (1) investigate long-term cost-effectiveness comprehensively, (2) use an appropriate disease model that aligns with the specific problem under study, and (3) conduct subgroup-specific cost-effectiveness analyses to gain more targeted insights.

The future burden of type 2 diabetes in Belgium: a microsimulation model.

OBJECTIVE: To forecast the annual burden of type 2 diabetes and related socio-demographic disparities in Belgium until 2030. METHODS: This study utilized a discrete-event transition microsimulation model. A synthetic population was created using 2018 national register data of the Belgian population aged 0-80 years, along with the national representative prevalence of diabetes risk factors obtained from the latest (2018) Belgian Health Interview and Examination Surveys using Multiple Imputation by Chained Equations (MICE) as inputs to the Simulation of Synthetic Complex Data (simPop) model. Mortality information was obtained from the Belgian vital statistics and used to calculate annual death probabilities. From 2018 to 2030, synthetic individuals transitioned annually from health to death, with or without developing type 2 diabetes, as predicted by the Finnish Diabetes Risk Score, and risk factors were updated via strata-specific transition probabilities. RESULTS: A total of 6722 [95% UI 3421, 11,583] new cases of type 2 diabetes per 100,000 inhabitants are expected between 2018 and 2030 in Belgium, representing a 32.8% and 19.3% increase in T2D prevalence rate and DALYs rate, respectively. While T2D burden remained highest for lower-education subgroups across all three Belgian regions, the highest increases in incidence and prevalence rates by 2030 are observed for women in general, and particularly among Flemish women reporting higher-education levels with a 114.5% and 44.6% increase in prevalence and DALYs rates, respectively. Existing age- and education-related inequalities will remain apparent in 2030 across all three regions. CONCLUSIONS: The projected increase in the burden of T2D in Belgium highlights the urgent need for primary and secondary preventive strategies. While emphasis should be placed on the lower-education groups, it is also crucial to reinforce strategies for people of higher socioeconomic status as the burden of T2D is expected to increase significantly in this population segment.

Integrating decision modeling and machine learning to inform treatment stratification.

There is increasing interest in moving away from "one size fits all (OSFA)" approaches toward stratifying treatment decisions. Understanding how expected effectiveness and cost-effectiveness varies with patient covariates is a key aspect of stratified decision making. Recently proposed machine learning (ML) methods can learn heterogeneity in outcomes without pre-specifying subgroups or functional forms, enabling the construction of decision rules ('policies') that map individual covariates into a treatment decision. However, these methods do not yet integrate ML estimates into a decision modeling framework in order to reflect long-term policy-relevant outcomes and synthesize information from multiple sources. In this paper, we propose a method to integrate ML and decision modeling, when individual patient data is available to estimate treatment-specific survival time. We also propose a novel implementation of policy tree algorithms to define subgroups using decision model output. We demonstrate these methods using the SPRINT (Systolic Blood Pressure Intervention Trial), comparing outcomes for "standard" and "intensive" blood pressure targets. We find that including ML into a decision model can impact the estimate of incremental net health benefit (INHB) for OSFA policies. We also find evidence that stratifying treatment using subgroups defined by a tree-based algorithm can increase the estimates of the INHB.

Scenarios of Delayed First Births and Associated Cohort Fertility Levels.

Fertility rates among individuals in their 20s have fallen sharply across Europe over the past 50 years. The implications of delayed first births for fertility levels in modern family regimes remain little understood. Using microsimulation models of childbearing and partnership for the 1970-1979 birth cohorts in Italy, Great Britain, Sweden, and Norway, we implement fictive scenarios that reduce the risk of having a first child before age 30 and examine fertility recovery mechanisms for aggregate fertility indicators (the proportion of women with at least one, two, three, or four children; cohort completed fertility rate). Exposure to a first birth increases systematically in the ages following the simulated reduction in first-birth risks, leading to a structural recovery in childbearing that varies across countries according to their fertility and partnership regimes. Full recovery requires an increase in late first-birth risks, with greater increases in countries where late family formation is uncommon and average family sizes are larger: in scenarios where early fertility declines substantially (a linear decline from 50% at age 15 to 0% at age 30), first-birth risks above age 30 would have to increase by 54% in Great Britain, 40% in Norway and Sweden, and 20% in Italy to keep completed fertility constant.

Economic evaluation of hepatocellular carcinoma surveillance in chronic hepatitis B patients with virological remission.

BACKGROUND: Subsequent risk of hepatocellular carcinoma (HCC) persists in chronic hepatitis B (CHB) patients with virological remission. We aimed to assess the cost-effectiveness of HCC surveillance in those patients and determine appropriate age to commence or discontinue surveillance. METHODS: We developed an individual-based state transition model, simulating the advancement of HCC in CHB patients with virological remission. We used this model to compare the incremental cost-effectiveness ratio (ICER) and long-term health outcomes of biannual or annual HCC surveillance for varying durations with no surveillance. RESULTS: For compensated cirrhosis patients with CHB, biannual surveillance was not cost-effective for all age groups, while annual surveillance was cost-effective for patients aged 55 to 70 (ICER USD 28,076 / quality-adjusted life years [QALY] gained), which detected 176 additional early HCC cases in a 100,000-person cohort compared to no surveillance. In CHB patients with advanced fibrosis, annual surveillance for patients aged 40 to 75 was the most cost-effective strategy (ICER USD 4,984/QALY gained), which detected 289 additional early HCC per 100,000 patients. CONCLUSIONS: Annual surveillance for patients with compensated cirrhosis or advanced fibrosis was a more cost-effective option that demonstrated substantial economic benefits, being slightly less effective than biannual surveillance at a significantly lower cost, providing insights for professionals in evaluating HCC surveillance among high-risk patients in China.

The most cost-effective age group for surveillance of hepatocellular carcinoma (HCC) varied depending on the stage of the disease. Regular annual surveillance for patients with compensated cirrhosis or advanced fibrosis was more cost-effective option, showing great economic and clinical benefits with slightly less effective than biannual surveillance but significantly lower cost.

Efficient organized colorectal cancer screening in Shenzhen: a microsimulation modelling study.

BACKGROUND: Colorectal cancer (CRC) is a global health issue with noticeably high incidence and mortality. Microsimulation models offer a time-efficient method to dynamically analyze multiple screening strategies. The study aimed to identify the efficient organized CRC screening strategies for Shenzhen City. METHODS: A microsimulation model named CMOST was employed to simulate CRC screening among 1 million people without migration in Shenzhen, with two CRC developing pathways and real-world participation rates. Initial screening included the National Colorectal Polyp Care score (NCPCS), fecal immunochemical test (FIT), and risk-stratification model (RS model), followed by diagnostic colonoscopy for positive results. Several start-ages (40, 45, 50 years), stop-ages (70, 75, 80 years), and screening intervals (annual, biennial, triennial) were assessed for each strategy. The efficiency of CRC screening was assessed by number of colonoscopies versus life-years gained (LYG). RESULTS: The screening strategies reduced CRC lifetime incidence by 14-27 cases (30.9-59.0%) and mortality by 7-12 deaths (41.5-71.3%), yielded 83-155 LYG, while requiring 920 to 5901 colonoscopies per 1000 individuals. Out of 81 screening, 23 strategies were estimated efficient. Most of the efficient screening strategies started at age 40 (17 out of 23 strategies) and stopped at age 70 (13 out of 23 strategies). Predominant screening intervals identified were annual for NCPCS, biennial for FIT, and triennial for RS models. The incremental colonoscopies to LYG ratios of efficient screening increased with shorter intervals within the same test category. Compared with no screening, when screening at the same start-to-stop age and interval, the additional colonoscopies per LYG increased progressively for FIT, NCPCS and RS model. CONCLUSION: This study identifies efficient CRC screening strategies for the average-risk population in Shenzhen. Most efficient screening strategies indeed start at age 40, but the optimal starting age depends on the chosen willingness-to-pay threshold. Within insufficient colonoscopy resources, efficient FIT and NCPCS screening strategies might be CRC initial screening strategies. We acknowledged the age-dependency bias of the results with NCPCS and RS.

Cost-effectiveness of single-pill and separate-pill administration of antihypertensive triple combination therapy: a population-based microsimulation study.

BACKGROUND: Single-pill combination (SPC) of three antihypertensive drugs has been shown to improve adherence to therapy compared with free combinations, but little is known about its long-term costs and health consequences. This study aimed to evaluate the lifetime cost-effectiveness profile of a three-drug SPC of an angiotensin-converting enzyme inhibitor, a calcium-channel blocker, and a diuretic vs the corresponding two-pill administration (a two-drug SPC plus a third drug separately) from the Italian payer perspective. METHODS: A cost-effectiveness analysis was conducted using multi-state semi-Markov modeling and microsimulation. Using the healthcare utilization database of the Lombardy Region (Italy), 30,172 and 65,817 patients aged ≥ 40 years who initiated SPC and two-pill combination, respectively, between 2015 and 2018 were identified. The observation period extended from the date of the first drug dispensation until death, emigration, or December 31, 2019. Disease and cost models were parametrized using the study cohort, and a lifetime microsimulation was applied to project costs and life expectancy for the compared strategies, assigning each of them to each cohort member. Costs and life-years gained were discounted by 3%. Probabilistic sensitivity analysis with 1,000 samples was performed to address parameter uncertainty. RESULTS: Compared with the two-pill combination, the SPC increased life expectancy by 0.86 years (95% confidence interval [CI] 0.61-1.14), with a mean cost differential of -€12 (95% CI -9,719-8,131), making it the dominant strategy (ICER = -14, 95% CI -€15,871-€7,113). The cost reduction associated with the SPC was primarily driven by savings in hospitalization costs, amounting to €1,850 (95% CI 17-7,813) and €2,027 (95% CI 19-8,603) for patients treated with the SPC and two-pill combination, respectively. Conversely, drug costs were higher for the SPC (€3,848, 95% CI 574-10,640 vs. €3,710, 95% CI 263-11,955). The cost-effectiveness profile did not significantly change according to age, sex, and clinical status. CONCLUSIONS: The SPC was projected to be cost-effective compared with the two-pill combination at almost all reasonable willingness-to-pay thresholds. As it is currently prescribed to only a few patients, the widespread use of this strategy could result in benefits for both patients and the healthcare system.

Paediatric aortic valve replacement: a meta-analysis and microsimulation study.

AIMS: To support decision-making in children undergoing aortic valve replacement (AVR), by providing a comprehensive overview of published outcomes after paediatric AVR, and microsimulation-based age-specific estimates of outcome with different valve substitutes. METHODS AND RESULTS: A systematic review of published literature reporting clinical outcome after paediatric AVR (mean age <18 years) published between 1/1/1990 and 11/08/2021 was conducted. Publications reporting outcome after paediatric Ross procedure, mechanical AVR (mAVR), homograft AVR (hAVR), and/or bioprosthetic AVR were considered for inclusion. Early risks (<30d), late event rates (>30d) and time-to-event data were pooled and entered into a microsimulation model. Sixty-eight studies, of which one prospective and 67 retrospective cohort studies, were included, encompassing a total of 5259 patients (37 435 patient-years; median follow-up: 5.9 years; range 1-21 years). Pooled mean age for the Ross procedure, mAVR, and hAVR was 9.2 ± 5.6, 13.0 ± 3.4, and 8.4 ± 5.4 years, respectively. Pooled early mortality for the Ross procedure, mAVR, and hAVR was 3.7% (95% CI, 3.0%-4.7%), 7.0% (5.1%-9.6%), and 10.6% (6.6%-17.0%), respectively, and late mortality rate was 0.5%/year (0.4%-0.7%/year), 1.0%/year (0.6%-1.5%/year), and 1.4%/year (0.8%-2.5%/year), respectively. Microsimulation-based mean life-expectancy in the first 20 years was 18.9 years (18.6-19.1 years) after Ross (relative life-expectancy: 94.8%) and 17.0 years (16.5-17.6 years) after mAVR (relative life-expectancy: 86.3%). Microsimulation-based 20-year risk of aortic valve reintervention was 42.0% (95% CI: 39.6%-44.6%) after Ross and 17.8% (95% CI: 17.0%-19.4%) after mAVR. CONCLUSION: Results of paediatric AVR are currently suboptimal with substantial mortality especially in the very young with considerable reintervention hazards for all valve substitutes, but the Ross procedure provides a survival benefit over mAVR. Pros and cons of substitutes should be carefully weighed during paediatric valve selection.

Economic evaluation of the effect of needle and syringe programs on skin, soft tissue, and vascular infections in people who inject drugs: a microsimulation modelling approach.

BACKGROUND: Needle and syringe programs (NSP) are effective harm-reduction strategies against HIV and hepatitis C. Although skin, soft tissue, and vascular infections (SSTVI) are the most common morbidities in people who inject drugs (PWID), the extent to which NSP are clinically and cost-effective in relation to SSTVI in PWID remains unclear. The objective of this study was to model the clinical- and cost-effectiveness of NSP with respect to treatment of SSTVI in PWID. METHODS: We performed a model-based, economic evaluation comparing a scenario with NSP to a scenario without NSP. We developed a microsimulation model to generate two cohorts of 100,000 individuals corresponding to each NSP scenario and estimated quality-adjusted life-years (QALY) and cost (in 2022 Canadian dollars) over a 5-year time horizon (1.5% per annum for costs and outcomes). To assess the clinical effectiveness of NSP, we conducted survival analysis that accounted for the recurrent use of health care services for treating SSTVI and SSTVI mortality in the presence of competing risks. RESULTS: The incremental cost-effectiveness ratio associated with NSP was $70,278 per QALY, with incremental cost and QALY gains corresponding to $1207 and 0.017 QALY, respectively. Under the scenario with NSP, there were 788 fewer SSTVI deaths per 100,000 PWID, corresponding to 24% lower relative hazard of mortality from SSTVI (hazard ratio [HR] = 0.76; 95% confidence interval [CI] = 0.72-0.80). Health service utilization over the 5-year period remained lower under the scenario with NSP (outpatient: 66,511 vs. 86,879; emergency department: 9920 vs. 12,922; inpatient: 4282 vs. 5596). Relatedly, having NSP was associated with a modest reduction in the relative hazard of recurrent outpatient visits (HR = 0.96; 95% CI = 0.95-0.97) for purulent SSTVI as well as outpatient (HR = 0.88; 95% CI = 0.87-0.88) and emergency department visits (HR = 0.98; 95% CI = 0.97-0.99) for non-purulent SSTVI. CONCLUSIONS: Both the individuals and the healthcare system benefit from NSP through lower risk of SSTVI mortality and prevention of recurrent outpatient and emergency department visits to treat SSTVI. The microsimulation framework provides insights into clinical and economic implications of NSP, which can serve as valuable evidence that can aid decision-making in expansion of NSP services.

An individual-based dynamic model to assess interventions to mitigate opioid overdose risk.

BACKGROUND: Illicit opioid overdose continues to rise in North America and is a leading cause of death. Mathematical modeling is a valuable tool to investigate the epidemiology of this public health issue, as it can characterize key features of population outcomes and quantify the broader effect of structural and interventional changes on overdose mortality. The aim of this study is to quantify and predict the impact of key harm reduction strategies at differing levels of scale-up on fatal and nonfatal overdose among a population of people engaging in unregulated opioid use in Toronto. METHODS: An individual-based model for opioid overdose was built featuring demographic and behavioural variation among members of the population. Key individual attributes known to scale the risk of fatal and nonfatal overdose were identified and incorporated into a dynamic modeling framework, wherein every member of the simulated population encompasses a set of distinct characteristics that govern demographics, intervention usage, and overdose incidence. The model was parametrized to fatal and nonfatal overdose events reported in Toronto in 2019. The interventions considered were opioid agonist therapy (OAT), supervised consumption sites (SCS), take-home naloxone (THN), drug-checking, and reducing fentanyl in the drug supply. Harm reduction scenarios were explored relative to a baseline model to examine the impact of each intervention being scaled from 0% use to 100% use on overdose events. RESULTS: Model simulations resulted in 3690.6 nonfatal and 295.4 fatal overdoses, coinciding with 2019 data from Toronto. From this baseline, at full scale-up, 290 deaths were averted by THN, 248 from eliminating fentanyl from the drug supply, 124 from SCS use, 173 from OAT, and 100 by drug-checking services. Drug-checking and reducing fentanyl in the drug supply were the only harm reduction strategies that reduced the number of nonfatal overdoses. CONCLUSIONS: Within a multi-faceted harm reduction approach, scaling up take-home naloxone, and reducing fentanyl in the drug supply led to the largest reduction in opioid overdose fatality in Toronto. Detailed model simulation studies provide an additional tool to assess and inform public health policy on harm reduction.

Microfoundations of the weakening educational gradient in fertility.

The disappearance of the social gradient in fertility represents a paradigm shift that has called into question the validity of theories that predicted a decline in fertility with increased access to education and resources. Emerging theories have tried to explain this trend by highlighting a potential change in the fertility preferences of more educated couples. In this paper we add additional elements to this explanation. Using a computational modelling approach, we show that it is still possible to simulate the weakening social gradient in fertility, in the context of steady declines in family size preferences. Our results show that one of the key drivers of the change in the education-fertility relationship can be found in the transition to an increasingly regulated fertility regime. As the share of unplanned births decreases over time, the negative association between education and fertility weakens and the mechanisms that positively connect educational attainment with desired fertility become dominant.

Integrating LiDAR Sensor Data into Microsimulation Model Calibration for Proactive Safety Analysis.

Studies have shown that vehicle trajectory data are effective for calibrating microsimulation models. Light Detection and Ranging (LiDAR) technology offers high-resolution 3D data, allowing for detailed mapping of the surrounding environment, including road geometry, roadside infrastructures, and moving objects such as vehicles, cyclists, and pedestrians. Unlike other traditional methods of trajectory data collection, LiDAR's high-speed data processing, fine angular resolution, high measurement accuracy, and high performance in adverse weather and low-light conditions make it well suited for applications requiring real-time response, such as autonomous vehicles. This research presents a comprehensive framework for integrating LiDAR sensor data into simulation models and their accurate calibration strategies for proactive safety analysis. Vehicle trajectory data were extracted from LiDAR point clouds collected at six urban signalized intersections in Lubbock, Texas, in the USA. Each study intersection was modeled with PTV VISSIM and calibrated to replicate the observed field scenarios. The Directed Brute Force method was used to calibrate two car-following and two lane-change parameters of the Wiedemann 1999 model in VISSIM, resulting in an average accuracy of 92.7%. Rear-end conflicts extracted from the calibrated models combined with a ten-year historical crash dataset were fitted into a Negative Binomial (NB) model to estimate the model's parameters. In all the six intersections, rear-end conflict count is a statistically significant predictor (p-value < 0.05) of observed rear-end crash frequency. The outcome of this study provides a framework for the combined use of LiDAR-based vehicle trajectory data, microsimulation, and surrogate safety assessment tools to transportation professionals. This integration allows for more accurate and proactive safety evaluations, which are essential for designing safer transportation systems, effective traffic control strategies, and predicting future congestion problems.