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Background and Objective: Half of patients with gastroesophageal reflux disease (GERD) experience persistent symptoms while on proton pump inhibitors (PPIs), thus driving efforts to develop novel adjunctive therapies for PPI-refractory GERD. An economic analysis was performed to establish at what cost and efficacy such potential medications are likely to become cost effective in clinical practice., Methods: A Markov decision model was used to examine a hypothetical cohort of patients being evaluated for PPI-refractory GERD in the USA. The model compared 3 strategies: (1) usual care (i.e., upfront diagnostic testing with upper endoscopy ± ambulatory pH testing); (2) use of a PPI-adjunctive therapy after positive ambulatory pH testing; and (3) empiric use of a PPI-adjunctive therapy (i.e., diagnostic testing only after failing empiric treatment). The primary outcome was incremental cost per quality-adjusted life year (QALY) gained (third-party payer perspective) over a 10-year time horizon using a willingness to pay threshold of $100,000/QALY., Results: In two-way sensitivity analyses varying the cost and effectiveness of the PPI-adjunctive therapy, most combinations revealed that use of the medication after positive pH testing was the most cost-effective approach. Empiric treatment was the preferred strategy only when the therapy was highly efficacious (≥ 87.5% response rate) and low cost (≤ $109/month). Use of PPI-adjunctive treatments were not cost effective when the cost exceeded $1150/month., Conclusion: Use of PPI-adjunctive therapies in those with persistent GERD symptoms may become cost effective when guided by ambulatory pH tests. These data can guide investigators, industry, and payers as they develop, validate, and price new treatments for PPI-refractory GERD., (© 2024. The Author(s).)

Background: Budget impact models (BIMs) forecast the financial implications of adopting new technologies and the potential need for budget reallocation, thus playing a crucial role in reimbursement decisions. Despite the importance of accurate forecasts, studies indicate large discrepancies between estimates and reality. We are developing an artificial intelligence-based clinical decision tool to identify patients with non-small cell lung cancer who are most likely to benefit from immunotherapy., Objective: To evaluate the budgetary implications and describe a systematic literature review of published lung cancer BIMs., Methods: We searched PubMed and EMBASE for studies published between 2010 and 2023 that include BIMs that describe lung cancer interventions. Forward and backward reference searches were performed for all qualifying studies. We extracted author and publication year, country, interventions, disease stages, time horizon, analytical perspective, modeling methods used, types of costs included, sensitivity analyses conducted, and data sources used. We then evaluated adherence to the Professional Society for Health Economics and Pharmacoeconomics Research best-practice guidelines., Results: A total of 25 BIMs were identified, spanning 14 different countries. Model structure could not be ascertained definitively for nearly half of the models. The cost calculator approach was most common among the others. Time horizons ranged from 1 to 5 years, in line with recommendations. Most models compared drugs, 4 compared nondrug interventions, and 7 compared diagnostic technologies. Assumptions about market uptake were poorly documented and poorly motivated. Inclusion of cancer-related costs was rare. Adherence to best practices was variable and did not appear to improve over time., Conclusions: The number of published BIMs for lung cancer exceeded expectations. There were modest trends toward publication frequency and model quality over time. Our analysis revealed variability across the models, as well as their adherence to best practices, indicating substantial room for improvement. Although none of the models were individually suitable for the purpose of evaluating an artificial intelligence-based treatment selection tool, some models provided valuable insights.

Background: Heavily treatment-experienced (HTE) people with HIV (PWH) have limited treatment options owing to multidrug resistance (MDR). Lenacapavir (LEN) is indicated, in combination with other antiretrovirals, for the treatment of adults with MDR HIV-1 experiencing failure of their current antiretroviral regimen because of resistance, intolerance, or safety considerations., Objective: To evaluate the cost-utility of LEN in combination with an optimized background regimen (OBR) vs alternative recently approved treatments for HTE PWH, fostemsavir (FTR)+OBR and ibalizumab (IBA)+OBR, for the treatment of PWH with MDR, from a mixed US health care payer perspective., Methods: A Markov state-transition model with a lifetime time horizon was developed. Transition probabilities between viral load categories were based on individual participant data from the CAPELLA trial for LEN+OBR and on relative efficacy parameters obtained from indirect treatment comparisons for comparators. Health state utilities were sourced from the literature. Costs included drug acquisition costs, drug administration costs, disease management costs, adverse event costs, AIDS-related event costs, and treatment switching costs and were sourced from red book costs, Medicare and Medicaid fees, and the literature. Costs and outcomes were discounted at 3% annually. The model was used to estimate total and incremental costs, life-years (LYs), quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios. A deterministic and a probabilistic sensitivity analysis, as well as scenario analyses, were performed to address elements of uncertainty in the model and to explore the robustness of the results., Results: Over a lifetime time horizon, LEN+OBR was associated with the highest absolute QALYs (9.41) and the greatest number of LYs (12.09) compared with FTR+OBR (QALYs: 8.75; LYs: 11.26) and IBA+OBR (QALYs: 8.36; LYs: 10.78). LEN+OBR was also associated with the lowest total lifetime costs of the 3 interventions (LEN+OBR: $1,441,122 [US dollars]; FTR+OBR: $1,504,986; IBA+OBR: $1,524,396) and therefore was dominant over both comparators in the base case. LEN+OBR remained dominant vs FTR+OBR and IBA+OBR across the range of scenarios tested and LEN+OBR had a 99% probability of being cost-effective compared with FTR+OBR and IBA+OBR in the probabilistic sensitivity analysis at a willingness-to-pay threshold of $50,000/QALY., Conclusions: This economic evaluation demonstrated that LEN+OBR provides meaningful increases in QALYs and LYs, and is dominant over a lifetime time horizon, compared with FTR+OBR and IBA+OBR for the treatment of PWH with MDR in the United States.

Background: Individual-level interventions for dementia risk factors could reduce costs associated with dementia and some are cost-effective. We aimed to estimate the cost-effectiveness of population-level interventions for tackling dementia risk factors., Methods: In this economic modelling study, we included recommended population-based interventions from a previously published review article for which there was consistent and robust evidence of effectiveness in tackling a dementia risk factor (tobacco smoking, excess alcohol use, hypertension, obesity, air pollution, and head injury). We only included interventions if they had not been introduced in England or were in place but could be extended. The interventions studied were increases in tobacco pricing, minimum pricing for alcohol, raising alcohol price, salt reduction policies, sugar reduction policies, low emission zones, and compulsory helmet use for cycling by children (aged 5-18 years). We used published intervention effect sizes and relative risks for each risk factor and a Markov model to estimate progression to dementia in populations with and without the intervention, looking at lifetime risk, in the population of England., Findings: We estimated that reductions in excess alcohol use through minimum unit pricing would lead to cost-savings of £280 million and 4767 quality-adjusted life-years (QALYs) gained over an indefinite succession of age cohorts. Reformulation of food products to reduce salt would lead to cost-savings of £2·4 billion and 39 433 QALYs gained and reformulation to reduce sugar would lead to cost-savings of £1·046 billion and 17 985 QALYs gained. Reducing dementia risk from air pollution by introducing low emission zones in English cities with a population of 100 000 or more (that do not already impose restrictions) would lead to £260 million cost-savings and 5119 QALYs gained. Raising cigarette prices by 10% to reduce dementia risk from smoking would lead to 2277 QALYs gained and cost-savings of £157 million. Making bicycle helmets compulsory for children (aged 5-18 years) to reduce dementia risk from head injury would lead to cost-savings of £91 million and 1554 QALYs gained., Interpretation: Population-level interventions could help tackle life course dementia risk and save costs., Funding: UK National Institute for Health and Care Research Three Schools dementia research programme., Competing Interests: Declaration of interests GL is supported by grants from the UK National Institute for Health and Care Research (NIHR) Applied Research Collaborations, NIHR Biomedical Research Centre, NIHR Health Technology Assessment, NIHR programme grants, North Thames Applied Research Collaborations, Alzheimer’s Association, Norwegian Research Council, and Wellcome Trust. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The characteristics and relative strengths and weaknesses of partitioned survival models (PSMs) and state transition models (STMs) for three state oncology cost-effectiveness models have previously been studied. Despite clear and longstanding economic modeling guidelines, more than one structure is rarely presented, and the choice of structure appears correlated more with audience or precedent than disease, decision problem, or available data. One reason may be a lack of guidance and tools available to readily compare measures of internal validity such as the model fit and efficiency of different structures, or sensitivity of results to those choices. To address this gap, methods are presented to evaluate the fit and efficiency of three structures, with an accompanying R software package, psm3mkv. The methods are illustrated by analyzing interim and final analysis datasets of the KEYNOTE-826 randomized controlled trial. At both interim and final analyses, the STM Clock Reset structure provided the best and most efficient fit. Structural uncertainties had been reduced from interim to final analysis. Beyond measures of internal validity, guidelines highlight the importance of reflecting all available data, avoiding model selection purely on the basis of goodness of fit and strongly considering external validity. The method and software allow modelers to more easily evaluate and report model fit and efficiency, examine implicit assumptions, and reveal sensitivities to structural choices., (© 2024. Merck & Co., Inc., Rahway, NJ, USA and its affiliates under exclusive licence to Springer Nature Switzerland AG.)

Aims: The direct cost of diabetes to the UK health system was estimated at around £10 billion in 2012. This analysis updates that estimate using more recent and accurate data sources., Methods: A pragmatic review of relevant data sources for UK nations was conducted, including population-level data sets and published literature, to generate estimates of costs separately for Type 1, Type 2 and gestational diabetes. A comprehensive cost framework, developed in collaboration with experts, was used to create a population-based cost of illness model. The key driver of the analysis was prevalence of diabetes and its complications. Estimates were made of the excess costs of diagnosis, treatment and diabetes-related complications compared with the general UK population. Estimates of the indirect costs of diabetes focused on productivity losses due to absenteeism and premature mortality., Results: The direct costs of diabetes in 2021/22 for the UK were estimated at £10.7 billion, of which just over 40% related to diagnosis and treatment, with the rest relating to the excess costs of complications. Indirect costs were estimated at £3.3 billion., Conclusions: Diabetes remains a considerable cost burden in the UK, and the majority of those costs are still spent on potentially preventable complications. Although rates of some complications are reducing, prevalence continues to increase and effective approaches to primary and secondary prevention continue to be needed. Improvements in data capture, data quality and reporting, and further research on the human and financial implications of increasing incidence of Type 2 diabetes in younger people are recommended., (© 2024 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.)

Objectives: Novel interventions (axicabtagene ciloleucel [axi-cel], lisocabtagene maraleucel [liso-cel], tafasitamab-lenalidomide [Tafa-L], polatuzumab-rituximab-bendamustine [pola-BR]) improve clinical outcomes in second-line (2 L) treatment of transplant-ineligible patients with early relapse or refractory (R/R) diffuse large B cell lymphoma (DLBCL). The costs vary depending on the respective treatment regimen and the treatment duration, difficult comparability in reimbursement decisions. The objective was to analyze the health economic impacts of novel 2 L interventions and conventional immunochemotherapies (bendamustine-rituximab [BR], rituximab-gemcitabine-oxaliplatin [R-GemOx]) from a German healthcare payer's perspective as a function of treatment duration., Methods: An economic model was developed to compare treatment costs of 2 L interventions depending on the treatment duration. Treatment duration was measured by progression-free survival (PFS), identified based on a systematic review. Total and average costs were calculated over 5 years to evaluate incremental costs at median PFS for each intervention., Results: Average costs per month at median PFS ranged from €2846 (95% CI: 5067-1641) to €40 535 (95% CI: 91180-N/A) for BR and liso-cel, respectively. Incremental costs at the lowest median PFS (R-GemOx: 5.3 months) revealed -€664, €5560, €11 817, €53 145, and €67 745 for BR, Tafa-L, pola-BR, axi-cel, and liso-cel as compared to R-GemOx, respectively., Conclusions: Analyses uncovered a variation of incremental costs of 2 L transplant-ineligible DLBCL interventions as a function of time leading to amortization of high-priced interventions., (© 2024 The Author(s). European Journal of Haematology published by John Wiley & Sons Ltd.)

Background and Purpose: To simulate patient-level costs, analyze the economic potential of telemedicine-based mobile stroke units for acute prehospital stroke care, and identify major determinants of cost-effectiveness, based on two recent prospective trials from the United States and Germany., Methods: A Markov decision model was developed to simulate lifetime costs and outcomes of mobile stroke unit. The model compares diagnostic and therapeutic pathways of ischemic stroke, hemorrhagic stroke, and stroke mimic patients by conventional care or by mobile stroke units. The treatment outcomes were derived from the B_PROUD and the BEST-mobile stroke unit trials and further input parameters were derived from recent literature. Uncertainty was addressed by deterministic and probabilistic sensitivity analyses. A lifetime horizon based on the US healthcare system was adopted to evaluate different cost thresholds for mobile stroke unit and the resulting cost-effectiveness. Willingness-to-pay thresholds were set at 1x and 3x gross domestic product per capita, as recommended by the World Health Organization., Results: In the base case scenario, mobile stroke unit care yielded an incremental gain of 0.591 quality-adjusted life years per dispatch. Mobile stroke unit was highly cost-effective up to a maximum average cost of 43,067 US dollars per patient. Sensitivity analyses revealed that MSU cost-effectiveness is mainly affected by reduction of long-term disability costs. Also, among other parameters, the rate of stroke mimics patients diagnosed by MSU plays an important role., Conclusion: This study demonstrated that mobile stroke unit can possibly be operated on an excellent level of cost-effectiveness in urban areas in North America with number of stroke mimic patients and long-term stroke survivor costs as major determinants of lifetime cost-effectiveness., Competing Interests: Declaration of conflicting interestsThe authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: JSR, MFF, SOS, and FT: The Department of Radiology and Nuclear Medicine has research agreements with Siemens Healthineers. KS, CH, MN, and KCF: The authors declare that there is no conflict of interest.JLS: Contracted hourly payments from Medtronic, Cerenovus, Phillips, Neurovasc, Boehringer Ingelheim (prevention only), and Rapid Medical for service on Trial Steering Committee/DSMBs advising on rigorous study design and conduct.

This study considers a hypothetical global pediatric vaccine market where multiple coordinating entities make optimal procurement decisions on behalf of countries with different purchasing power. Each entity aims to improve affordability for its countries while maintaining a profitable market for vaccine producers. This study analyzes the effect of several factors on affordability and profitability, including the number of non-cooperative coordinating entities making procuring decisions, the number of market segments in which countries are grouped for tiered pricing purposes, how producers recover fixed production costs, and the procuring order of the coordinating entities. The study relies on a framework where entities negotiate sequentially with vaccine producers using a three-stage optimization process that solves a MIP and two LP problems to determine the optimal procurement plans and prices per dose that maximize savings for the entities' countries and profit for the vaccine producers. The study's results challenge current vaccine market dynamics and contribute novel alternative strategies to orchestrate the interaction of buyers, producers, and coordinating entities for enhancing affordability in a non-cooperative market. Key results show that the order in which the coordinating entities negotiate with vaccine producers and how the latter recuperate their fixed cost investments can significantly affect profitability and affordability. Furthermore, low-income countries can meet their demands more affordably by procuring vaccines through tiered pricing via entities coordinating many market segments. In contrast, upper-middle and high-income countries increase their affordability by procuring through entities with fewer and more extensive market segments. A procurement order that prioritizes entities based on the descending income level of their countries offers higher opportunities to increase affordability and profit when producers offer volume discounts., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Introduction: This review presents a critical appraisal of differences in the methodologies and quality of model-based and empirical data-based cost-utility studies on continuous glucose monitoring (CGM) in type 1 diabetes (T1D) populations. It identifies key limitations and challenges in health economic evaluations on CGM and opportunities for their improvement., Methods: The review and its documentation adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. Searches for articles published between January 2000 and January 2023 were conducted using the MEDLINE, Embase, Web of Science, Cochrane Library, and Econlit databases. Published studies using models and empirical data to evaluate the cost utility of all CGM devices used by T1D patients were included in the search. Two authors independently extracted data on interventions, populations, model settings (e.g., perspectives and time horizons), model types and structures, clinical outcomes used to populate the model, validation, and uncertainty analyses. They subsequently met to confirm consensus. Quality was assessed using the Philips checklist for model-based studies and the Consensus Health Economic Criteria (CHEC) checklist for empirical studies. Model validation was assessed using the Assessment of the Validation Status of Health-Economic decision models (AdViSHE) checklist. The extracted data were used to generate summary tables and figures. The study protocol is registered with PROSPERO (CRD42023391284)., Results: In total, 34 studies satisfied the selection criteria, two of which only used empirical data. The remaining 32 studies applied 10 different models, with a substantial majority adopting the CORE Diabetes Model. Model-based studies often lacked transparency, as their assumptions regarding the extrapolation of treatment effects beyond available evidence from clinical studies and the selection and processing of the input data were not explicitly stated. Initial scores for disagreements concerning checklists were relatively high, especially for the Philips checklist. Following their resolution, overall quality scores were moderate at 56%, whereas model validation scores were mixed. Strikingly, costing approaches differed widely across studies, resulting in little consistency in the elements included in intervention costs., Discussion and Conclusion: The overall quality of studies evaluating CGM was moderate. Potential areas of improvement include developing systematic approaches for data selection, improving uncertainty analyses, clearer reporting, and explaining choices for particular modeling approaches. Few studies provided the assurance that all relevant and feasible options had been compared, which is required by decision makers, especially for rapidly evolving technologies such as CGM and insulin administration. High scores for disagreements indicated that several checklists contained questions that were difficult to interpret consistently for quality assessment. Therefore, simpler but comprehensive quality checklists may be needed for model-based health economic evaluation studies., (© 2024. The Author(s).)

Background: Amyotrophic lateral sclerosis (ALS) is a devastating disease which leads to loss of muscle function and paralysis. Historically, clinical drug development has been unsuccessful, but promising disease-modifying therapies (DMTs) may be on the horizon., Objectives: The aims of this study were to estimate survival, quality-adjusted life-years (QALYs) and costs under current care, and to explore the conditions under which new therapies might be considered cost effective., Methods: We developed a health economic model to evaluate the cost effectiveness of future ALS treatments from a UK National Health Service and Personal Social Services perspective over a lifetime horizon using data from the ALS-CarE study. Costs were valued at 2021/22 prices. Two hypothetical interventions were evaluated: a DMT which delays progression and mortality, and a symptomatic therapy which improves utility only. Sensitivity analysis was conducted to identify key drivers of cost effectiveness., Results: Starting from King's stage 2, patients receiving current care accrue an estimated 2.27 life-years, 0.75 QALYs and lifetime costs of £68,047. Assuming a 50% reduction in progression rates and a UK-converted estimate of the price of edaravone, the incremental cost-effectiveness ratio for a new DMT versus current care is likely to exceed £735,000 per QALY gained. Symptomatic therapies may be more likely to achieve acceptable levels of cost effectiveness., Conclusions: Regardless of efficacy, DMTs may struggle to demonstrate cost effectiveness, even at a low price. The cost effectiveness of DMTs is likely to be strongly influenced by drug price, the magnitude and durability of relative treatment effects, treatment starting/stopping rules and any additional utility benefits over current care., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: In patients with a degenerative tear of the medial meniscus, recent meta-analyses and systematic reviews have shown no treatment benefit of arthroscopic partial meniscectomy (APM) over conservative treatment or placebo surgery. Yet, advocates of APM still argue that APM is cost effective. Giving advocates of APM their due, we note that there is evidence from the treatment of other musculoskeletal complaints to suggest that a treatment may prove cost effective even in the absence of improvements in efficacy outcomes, as it may lead to other benefits, such as diminished productivity loss and reduced costs, and so the question of cost effectiveness needs to be answered for APM., Questions/purposes: (1) Does APM result in lower postoperative costs compared with placebo surgery? (2) Is APM cost-effective compared with placebo surgery?, Methods: One hundred forty-six adults aged 35 to 65 years with knee symptoms consistent with a degenerative medial meniscus tear and no knee osteoarthritis according to the American College of Rheumatology clinical criteria were randomized to APM (n = 70) or placebo surgery (n = 76). In the APM and placebo surgery groups, mean age was 52 ± 7 years and 52 ± 7 years, and 60% (42 of 70) and 62% (47 of 76) of participants were men, respectively. There were no between-group differences in baseline characteristics. In both groups, a standard diagnostic arthroscopy was first performed. Thereafter, in the APM group, the torn meniscus was trimmed to solid meniscus tissue, whereas in the placebo surgery group, APM was carefully mimicked but no resection of meniscal tissue was performed; as such, surgical costs were the same in both arms and were not included in the analyses. All patients received identical postoperative care including a graduated home-based exercise program. At the 2-year follow-up, two patients were lost to follow-up, both in the placebo surgery group. Cost effectiveness over the 2-year trial period was computed as incremental net monetary benefit (INMB) for improvements in quality-adjusted life years (QALY), using both the societal (primary) and healthcare system (secondary) perspectives. To be able to consider APM cost effective, the CEA analysis should yield a positive INMB value. Nonparametric bootstrapping was used to assess uncertainty. Several one-way sensitivity analyses were also performed., Results: APM did not deliver lower postoperative costs, nor did it convincingly improve quality of life scores when compared with placebo surgery. From a societal perspective, APM was associated with € 971 (95% CI -2013 to 4017) higher costs and 0.015 (95% CI -0.011 to 0.041) improved QALYs over 2-year follow-up compared with placebo surgery. Both differences were statistically inconclusive (a wide 95% CI that crossed the line of no difference). Using the conventional willingness to pay (WTP) threshold of € 35,000 per QALY, APM resulted in a negative INMB of € -460 (95% CI -3757 to 2698). In our analysis, APM would result in a positive INMB only when the WTP threshold rises to about € 65,000 per QALY. The wide 95% CIs suggests uncertain cost effectiveness irrespective of chosen WTP threshold., Conclusion: The results of this study lend further support to clinical practice guidelines recommending against the use of APM in patients with a degenerative meniscus tear. Given the robustness of existing evidence demonstrating no benefit or cost effectiveness of APM over nonsurgical treatment or placebo surgery, future research is unlikely to alter this conclusion.Level of Evidence Level III, economic analysis., Competing Interests: Each author certifies that there are no funding or commercial associations (consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article related to the author or any immediate family members. All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research ® editors and board members are on file with the publication and can be viewed on request., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Association of Bone and Joint Surgeons.)

Purpose: To analyze the cost effectiveness of performing a renal mass biopsy in advance of ablation or concurrently with a percutaneous ablation procedure for the management of small renal masses (SRMs)., Materials and Methods: A decision-analytic model was developed with a cohort of 65-year-old male patients with an incidental, unilateral 1-3 cm SRM. A decision tree modeled the first year of clinical intervention, after which patients entered a Markov model with a lifetime horizon. Patients were assumed to be treated in accordance with established clinical practice guidelines, including surveillance, repeat ablation for recurrence, and systemic therapy for metastasis. Healthcare cost and utility values were determined from published literature or local hospital estimates, discounted at 1.5%. Total lifetime costs were calculated from the perspective of a Canadian healthcare payer and converted to 2022 Canadian dollars (C$). The primary outcome was incremental cost-effectiveness ratio (ICER) at a willingness-to-pay threshold of C$50,000 per quality-adjusted life year (QALY) gained. The secondary outcome was ICER at a willingness-to-pay threshold of C$50,000 per life year (LY) gained., Results: Concurrent biopsy and ablation resulted in a gain of 16.4 quality-adjusted days, at an incremental cost of $386, with an ICER of C$8,494/QALY. The concurrent strategy was the dominant strategy for a prevalence of benign mass of <5%. Sequential biopsy and ablation was only cost-effective when LYs were not quality-adjusted and ablation cost was >C$4,300 or benign mass prevalence was >28%., Conclusions: Concurrent biopsy and ablation is cost-effective relative to pretreatment diagnostic biopsy for management of incidental SRMs., (Copyright © 2024 SIR. Published by Elsevier Inc. All rights reserved.)

Background and Objective: Multiple myeloma is a rare incurable hematological cancer in which most patients relapse or become refractory to treatment. This systematic literature review aimed to critically review the existing economic models used in economic evaluations of systemic treatments for relapsed/refractory multiple myeloma and to summarize how the models addressed differences in the line of therapy and exposure to prior treatment., Methods: Following a pre-approved protocol, literature searches were conducted on 17 February, 2023, in relevant databases for models published since 2014. Additionally, key health technology assessment agency websites were manually searched for models published as part of submission dossiers since 2018. Reported information related to model conceptualization, structure, uncertainty, validation, and transparency were extracted into a pre-defined extraction sheet., Results: In total, 49 models assessing a wide range of interventions across multiple lines of therapy were included. Only five models specific to heavily pre-treated patients and/or those who were refractory to multiple treatment classes were identified. Most models followed a conventional simple methodology, such as partitioned survival (n = 28) or Markov models (n = 9). All included models evaluated specific interventions rather than the whole treatment sequence. Where subsequent therapies were included in the model, these were generally only considered from a cost and resource use perspective. The models generally used overall and progression-free survival as model inputs, although data were often immature. Sensitivity analyses were frequently reported (n = 41) whereas validation was only considered in less than half (n = 19) of the models., Conclusions: Published economic models in relapsed/refractory multiple myeloma rarely followed an individual patient approach, mainly owing to the higher need for complex data assumptions compared with simpler modeling approaches. As many patients experience disease progression on multiple treatment lines, there is a growing need for modeling complex treatment strategies, leading to more sophisticated approaches in the future. Maintaining transparency, high reporting standards, and thorough analyses of uncertainty are crucial to support these advancements., (© 2024. The Author(s).)

Background: This research was conducted with the aim of investigating the effects of green tax on Iran's economy. Methods: This was analytical research using the Nordhaus economic model. The data relating to torques and statistical tests were used to compare actual and model data to determine how well the designed Nordhaus model corresponds to the data on Iran's economy, t and f statistical tests were designed to determine the degree of conformity of the Nordhaus model, and the first and second-order coefficients were used for the variables. Data analysis of the gross domestic product, investment, government spending and oil revenue was used with GAMS software. Results: The values of the simulated and real characteristics did not differ significantly at the 95% confidence level(P-value=0.05), which shows the high compliance of the Nordhaus model with the real data of these variables. According to the Nordhaus model, green tax affects economic welfare. It reduces economic growth in the short term and increases it in the long term. By reducing production, the level of leisure increases and leads to compensate for the reduction in consumption due to reduced production and increased economic welfare. Conclusion: One percentage of increase in the rate of tax on return of capital leads to a reduction in consumption and a reduction in capital. Increasing the rate of tax on return of capital leads to increased tax revenues and helps governments to compensate for pollution costs and improve the quality of the environment.

This research aims to investigate information asymmetry in e-commerce supply chain channels and the impact of the fair preference model on the behavior and returns of channel members. Therefore, by contrasting it with the model in the completely rational case, this research establishes a more realistic principal-agent model and incorporates the fair preference model into the e-commerce supply chain channel. According to the model's analysis, the effort level of the retailer at each stage is positively correlated with the e-commerce efficiency coefficient, and the incentive coefficient of manufacturers is positively correlated with the e-commerce efficiency coefficient in the case where all rationality is assumed. Manufacturing companies' anticipated profits are positively correlated with the e-commerce efficiency coefficient. According to the fair preference model, retailers will put forth more effort to sell products when their fixed income from manufacturers is higher and their optimal effort level is positively correlated with that income. When e-commerce's efficiency coefficient is higher than 1, the retailer's revenue and effort exceeded those of traditional channels. Manufacturers and retailers both experience Pareto improvements in their earnings after the fair preference model is introduced., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Abstract Background Due to the SARS-CoV-2 pandemic, public health interventions have been introduced globally in order to prevent the spread of the virus and avoid the overload of health care systems, especially for the most severely affected patients. Scientific studies to date have focused primarily on describing the clinical course of patients, identifying treatment options and developing vaccines. In Germany, as in many other regions, current tests for SARS-CoV2 are not conducted on a representative basis and in a longitudinal design. Furthermore, knowledge about the immune status of the population is lacking. Nonetheless, these data are needed to understand the dynamics of the pandemic and hence to appropriately design and evaluate interventions. For this purpose, we recently started a prospective population-based cohort in Munich, Germany, with the aim to develop a better understanding of the state and dynamics of the pandemic. Methods In 100 out of 755 randomly selected constituencies, 3000 Munich households are identified via random route and offered enrollment into the study. All household members are asked to complete a baseline questionnaire and subjects ≥14 years of age are asked to provide a venous blood sample of ≤3 ml for the determination of SARS-CoV-2 IgG/IgA status. The residual plasma and the blood pellet are preserved for later genetic and molecular biological investigations. For twelve months, each household member is asked to keep a diary of daily symptoms, whereabouts and contacts via WebApp. If symptoms suggestive for COVID-19 are reported, family members, including children

In the era of the digital economy, the data element investment strategy decisions and game mechanisms of leaders and followers are crucial issues to be studied. To explore the environment in which digital collaboration between enterprises benefits both parties, this study initially proposes a three-stage game model of leaders and followers based on the sequential game method. Subsequently, we analyze the investment strategy choices for leading and following enterprises across six scenarios within dynamic market environments. Finally, numerical simulations are employed to examine the effect of both strategies on the industry and society as a whole. The simulation shows that (1) The cooperation strategy is a more effective approach for enhancing data-driven innovation performance, but when it comes to mature markets, this strategy may conflict with the interests of followers. (2) Followers can benefit from the cooperation strategy by significantly boosting the growth rate of data elements, but it may cause enterprises to lose their original market scale. (3) Excessively high initial production costs can negatively affect the innovative performance of the industry and social wealth, whereas mature industries can achieve greater industry performance and social welfare through investment in data elements. Considering the environmental characteristics of the digital economy, the findings of this study elucidate the ramifications of innovation strategies on enterprises, industries, and society, providing positive insights for two types of enterprises with different strengths to make apt decisions regarding digital cooperation., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Fang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Investigating novel collaboration modes is imperative for enhancing the cooperative ties between brand retailers and anchors as live streaming commerce moves progressively towards standardization. In this paper, we study a live streaming commerce supply chain system composed of a brand retailer and an Internet celebrity anchor. We also develop the pricing and live streaming service effort decision models under the equal proportion settlement mode of pit fee for the brand retailer and anchor. The research results show that under certain conditions, there is an optimal joint decision on price discount and live streaming service effort. In addition, the equal proportion settlement mode provides security for brand retailers but tends to expose the anchor's capabilities of live streaming sales. Consequently, anchors can only obtain a higher proportion of the pit fee by putting in more effort. Finally, through numerical analysis, we presented the impact of key parameters on the optimal decisions, demand, and profits of brand retailers and anchors. Based on these findings, we provided relevant managerial insights, offering valuable guidance and reference for the live streaming commerce industry., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Research on small and medium-sized enterprises (SMEs) access to bank finance is vital for the euro area economy. SMEs heavily represent the European business sector, employing around 100 million people and accounting for more than half of the Gross Domestic Product. Research studies in the field often rely on the ECB/EC Survey on the Access to Finance of Enterprises (SAFE). Many studies employ probit or logit models with categorical dependent variables derived from SAFE. The research findings show that hardly any study employs the simpler linear probability model (LPM), with a dominant lack of research providing evidence that justifies the model selection process and suitability. However, it is well known that different econometrics models can lack consistency and frequently yield different results. Yet, the literature has no consensus on the best econometric approach. In addition, there is a lack of robustness tests in the literature to ensure model validity, underlining the need for a comprehensive review of the methodological framework that dominates SAFE data use. This paper addresses the identified research gap by introducing a robust methodological framework that helps researchers identify and choose an appropriate categorical model when using SAFE data. The study adds significant value to the extant literature by identifying four criteria that need to be considered when selecting the appropriate model among three common binary dependent models: LPM, probit and logit models. The findings show that the probit model was appropriate is all cases but that the LPM should not be disregarded, as it can be used in two cases: when considering the interaction between monetary policy and debt to assets and monetary policy and innovation. The use of the LPM is justified as a less complex econometric model, allowing for clearer communication of the results. This innovative, robust approach to choosing the appropriate econometric categorical dependent model when employing SAFE data contributes to support policy effectively., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Finnegan, Morales. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Exchange rate pass-through (ERPT) represents a degree to which changes in nominal exchange rates are transmitted into domestic prices. European Union (EU) countries have experienced the unprecedented inflationary pressure due to high geopolitical risk events. As such, understanding the ERPT plays a crucial role. This study provides a comprehensive and up-to-date analysis of ERPT to import prices for 16 EU countries from January 2006 to December 2022. Using the panel autoregressive distributed lag (ARDL) model, our findings confirm the linear, rather than nonlinear, ERPT pattern characterized by a diminishing trend over time in the EU countries. However, the degree of pass-through varies depending on country characteristics. Specifically, countries that are highly dependent on imports experience a larger ERPT. Furthermore, the degree of pass-through to import prices is more significant and persistent during periods of high uncertainty. These findings are robust across various robust analyses including sub periods. Our findings provide that help policymakers evaluate the trade-offs between exchange rate risks and macroeconomic stability during times of high uncertainty., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Vo, Vu. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objectives: This analysis aims to better reflect the value of new antibiotic treatment strategies, thereby informing clinical antibiotic use, antimicrobial reimbursement and/or hospital formulary decision-making in China., Design: We adapted a published and validated dynamic disease transmission and cost-effectiveness model to evaluate the clinical and economic outcomes of introducing a new antibiotic, ceftazidime/avibactam (CAZ-AVI) for treating resistant infections in Zhejiang province, China. Outcomes were assessed over a 10-year infectious period and an annual discount rate of 5%. Costs were extracted from the hospital's Health Information System (HIS) and obtained after data cleaning, aggregation and discounting., Setting: The Chinese healthcare system perspective., Participants: 10 905 patients in a Chinese tier-3 hospital from 2018 to 2021 with any of the three common infections (complicated intra-abdominal infection (cIAI), hospital-acquired/ventilator-associated pneumonia (HAP/VAP) and infections with limited treatment options (LTO)) caused by three common resistant pathogens ( Escherichia coli, Klebsiella spp. and Pseudomonas aeruginosa )., Interventions: (1) Current treatment strategy (piperacillin-tazobactam (pip/taz) and meropenem); (2) CAZ-AVI at the third line; (3) CAZ-AVI at the second line; (4) CAZ-AVI at the first line; (5) CAZ/AVI first line, two lines diversified (i.e., equal pip/taz and CAZ-AVI at the first line; meropenem at the last line) and (6) CAZ/AVI first line, all-lines diversified., Primary Outcome Measures: Quality-adjusted life years (QALYs) lost, hospitalisation costs and incremental net monetary benefit (INMB) were used to assess cost-effectiveness., Results: Over 10 years, the introduction of CAZ-AVI to the current treatment strategy led to lower hospitalisation costs and more QALYs across all five treatment strategies, with between 68 284 and 78 571 QALYs gained whilst saving up to US$236.37 for each additional QALY gained. The INMB of introducing CAZ-AVI is estimated up to US$3 550 811 878., Conclusions: Introducing CAZ-AVI had a positive impact on clinical and economic outcomes for treating antimicrobial resistance, and diversifying the antibiotics use early in the treatment might yield the best benefits., Competing Interests: Competing interests: YC, PD and AA-T are employees of Pfizer. JG is an employee of Health Economics and Outcomes Research Ltd.; Health Economics and Outcomes Research Ltd. received fees from Pfizer in relation to this study. HD and XZ are paid consultants to Pfizer from Zhejiang University and Shandong University, respectively., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

This study estimates the monetary policy reaction function (MPRF) in a Dynamic Stochastic General Equilibrium (DSGE) framework using Bayesian analysis for the emerging economies. DSGE models are suitable for the policy analysis because of their simplicity and prominent role of forward-looking variables. This is a pioneer study investigating the combined effects of credit spreads, fiscal imbalances, and monetary autonomy on interest rates for BRICS member countries. Using real data for the period 1970-2021, the posterior estimates confirm that both credit spread and fiscal imbalance significantly contribute to fluctuations in output, inflation, and interest rates in all the sample economies. The estimates show that fluctuations in the inflation rate are due to supply shocks. The empirical estimates also reveal that fiscal imbalances shock significantly affect output in Brazil, India, and South Africa, whereas, based on real data inflation and interest rate are significantly affected by fiscal imbalance shocks in China and South Africa. Yet, the findings suggest that the effects of various shocks on output and interest rates vary across countries., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Waheed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

With the gradual rise of the supply chain financial model and the expansion of scale, credit risk and contagion effects are gradually strengthened as business and financial links between upstream and downstream enterprises in the supply chain. The traditional credit risk contagion assessment model based on the financial status of an enterprise and the pledging of fixed assets has been unable to meet the basic needs of modern supply chain companies and financial institutions for risk control. Therefore, this paper introduces the Cox-Copula model to comprehensively assess a company's financial situation and the business health of upstream and downstream companies in the supply chain from the perspective of actual transactions between companies and fixed asset pledges. The study found that credit risk has a contagion effect in supply chain enterprises, and this contagion effect of credit risk has certain dynamic characteristics. At the same time, it was found that the impacts of macroeconomic factors and microfinance factors on credit risk contagion of supply chain finance have differences in the two dimensions of degree and direction of action., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Geng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

We make a novel investigation of welfare costs associated with various suboptimal decisions made by retirees, both analytically and numerically. We utilize a unique framework that incorporates recursive utility with housing, and also encompasses expected utility and recursive utility without housing as special cases. Our findings indicate that under-investment in stocks incurs lower welfare costs compared to an equivalent over-investment. Suboptimal allocations in bond holdings result in higher costs than similar misallocations in stocks. Choosing not to participate in the stock market is less detrimental than avoiding the bond market. Should retirees opt to simplify their decision-making by investing solely in one type of asset, it is less costly for them to invest exclusively in bonds. Overconsumption of housing is less costly than an equivalent underconsumption. Suboptimal consumption imposes the highest welfare cost. Decisions regarding consumption, housing, and savings are found to be more crucial than the choice of how to distribute liquid savings between stocks and bonds. Additionally, recursive utility model better captures retirees' preference for bonds over stocks than expected utility model. Our results, which are consistent across various parameter settings, provide valuable insights for academics and policymakers aiming to enhance retiree welfare., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Aydilek, Aydilek. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The use of digital technology by banks and other financial institutions to facilitate financial inclusion is referred to as digital financial inclusion. This fusion of digital finance and traditional banking methods has the potential to impact banks' operational effectiveness. This study uses the panel effects model to examine the link between digital financial inclusion and bank performance in 30 Chinese provinces from 2012 to 2021. This research uses kernel density estimation to examine the spatial-temporal growth patterns of both variables. The mediator variable in examining how digital financial inclusion affects bank performance is risk-taking. Finally, the paper analyses the regional heterogeneity of the impact. It presents the following conclusions: (1) In China, digital financial inclusion and bank performance have constantly increased, with noticeable regional variances in their development levels. This regional inequality has widened gradually since 2018, yet it has not resulted in polarization. (2) The significant positive correlation between digital inclusive finance and banking performance indicates that banking performance tends to increase with the enhancement of digital inclusive finance. (3) Digital financial inclusion impacts bank performance, with risk-taking as a moderator. The spread of digital financial inclusion services enhances banks' willingness to take risks, enhancing overall efficiency. (4) Digital financial inclusion boosts bank performance in the Northwest, South, North, and East regions while lightly inhibiting it in the Central region. Based on the findings, this study makes bank and government suggestions., Competing Interests: The authors declare no conflict of interest., (Copyright: © 2024 Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: This paper uses health economics methods to discuss the cost-effectiveness value of long protocol and antagonist protocol for in vitro fertilisation and embryo transfer (ET) in the Chinese population., Design: Health economic evaluation study., Setting: The data needed to construct the model for this study were derived from published studies and other secondary sources in China., Participants: No patients participated in the study., Measures: The main outcomes were live birth rate (LBR) and cost. From the societal perspective, we considered the direct and indirect costs over the course of the treatment cycles. A cost-effectiveness was measured using the incremental cost-effectiveness ratio and the probability that a protocol has higher net monetary benefit. Sensitivity analysis was carried out to verify the reliability of the simulation results., Results: For the Chinese population, the long protocol resulted in a higher LBR than the antagonist protocol (29.33% vs 20.39%), but at the same time, it was more expensive (￥29 146.26 (US$4333.17) vs ￥23 343.70 (US$3470.51)), in the case of considering only one fresh ET cycle. It was the same when considering subsequent frozen ET (FET) cycles (51.78% vs 42.81%; ￥30 703.02 (US$4564.62) vs ￥24 740.95 (US$3678.24)). The results of most subgroups were consistent with the results of the basic analysis. However, for certain populations, the long protocol was the inferior protocol (less effective and more expensive)., Conclusion: For the Chinese population, when the monetary value per live birth was greater than ￥65 420 (US$9726) and ￥66 400 (US$9872), respectively, considering only one fresh cycle and considering subsequent frozen cycles, the long protocol is the preferred protocol. This threshold also varies for women of different ages and ovarian response capacities. For women in POSEIDON (Patient-Oriented Strategies Encompassing IndividualizeD Oocyte Number) group 2, group 3 and group 4, antagonist protocol is recommended as the preferred protocol. The results of this study need to be verified by further large-scale randomised controlled trials., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Using a multi-product trade model, this study investigates the impact of temperature on firms' diversification in the export market. Using export and meteorological data of Chinese firms from 2000 to 2016, the empirical results confirm an inverted U-shaped relationship, implying that extreme temperatures significantly reduce firms' export product diversification. The analysis shows that extreme temperatures primarily reduce the variety of both new and existing products, with a less robust effect on product exit strategies. General trade firms are more adaptable to extreme temperatures than processing trade firms, and are likely to maintain diversified strategies. Stronger regional financial markets and higher energy consumption increase the adaptability of local firms to extreme temperatures. Firms have not yet adapted to local climatic norms. Furthermore, extreme temperatures also partly inhibit diversification of export destinations and relationships. The results of the study show that as climate change intensifies, leading to more frequent extreme temperatures, firms will face significant hurdles in pursuing diversified development strategies, pointing to increasing challenges ahead., Competing Interests: The authors have declared that no competing interests exist, (Copyright: © 2024 Zhang, Yao. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Scientific research requires taking risks, as the most cautious approaches are unlikely to lead to the most rapid progress. Yet, much funded scientific research plays it safe and funding agencies bemoan the difficulty of attracting high-risk, high-return research projects. Why don't the incentives for scientific discovery adequately impel researchers toward such projects? Here, we adapt an economic contracting model to explore how the unobservability of risk and effort discourages risky research. The model considers a hidden-action problem, in which the scientific community must reward discoveries in a way that encourages effort and risk-taking while simultaneously protecting researchers' livelihoods against the vicissitudes of scientific chance. Its challenge when doing so is that incentives to motivate effort clash with incentives to motivate risk-taking, because a failed project may be evidence of a risky undertaking but could also be the result of simple sloth. As a result, the incentives needed to encourage effort actively discourage risk-taking. Scientists respond by working on safe projects that generate evidence of effort but that don't move science forward as rapidly as riskier projects would. A social planner who prizes scientific productivity above researchers' well-being could remedy the problem by rewarding major discoveries richly enough to induce high-risk research, but in doing so would expose scientists to a degree of livelihood risk that ultimately leaves them worse off. Because the scientific community is approximately self-governing and constructs its own reward schedule, the incentives that researchers are willing to impose on themselves are inadequate to motivate the scientific risks that would best expedite scientific progress., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Gross, Bergstrom. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Physical capital stock is the basic indicator of macroeconomic empirical studies and also an important manifestation of macroeconomic activity capacity. When measuring China's provincial physical capital stock by the perpetual inventory method, the treatment for the depreciation rate and the initial physical capital stock in the existing literature has some defects in reflecting the economic performance. The purpose of this paper is to build the most reliable and reasonable statistical series of China's provincial physical capital stock. We establish a measurement formula in form of the variable depreciation rate and improve the treatment for the depreciation rate and the initial physical capital stock. For the depreciation rate, we measure the benchmark depreciation rate of physical capital and determine the variable depreciation rate according to the economic growth rate, which makes the variable depreciation rate reflect the economic growth. For the initial physical capital stock, we measure the initial physical capital stock according to the capital output ratio, which makes the initial physical capital stock reflect the economic aggregate. Based on these improvements, we measure China's provincial physical capital stock from 1952 to 2022 by the perpetual inventory method. Through analyzing the measurement results, we have a more distinct insight into the temporal and spatial characteristics of China's provincial physical capital stock: The growth rate of physical capital stock at the provincial level has slowed in spite of remaining high; The eastern region is much higher than the central and western regions. According to these two characteristics, it is suggested that policymakers need to improve market mechanisms and adjust investment policies to promote a benign profile of economic growth and a regional optimization of capital formation., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Wang, Ma. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The purpose of this study is to explore the trends and causes of established and emerging nations' stock market integration with India. The National Stock Exchange (NSE) indices act as a counterweight to international market indices. This study investigates the sustained interest of foreign investors in the Indian stock market in the wake of capital market reforms, as well as whether it moves in tandem with other markets in Asia and the United States. Methods: Our study examined the possibility of cross-country cointegration between the largest economies and indices around the world using multiple financial econometric models, such as Augmented Dickey-Fuller, Unit Root, Correlation, and Johansen Cointegration. Results: The findings of this study significantly support the notion that Indian and international financial markets are highly integrated. Vector error correction model indicates that the Indian market (NSE) is highly cointegrated with the US market (National Association of Securities Dealers Automated Quotations) and increased volatility signifies global contagion. Conclusion: A cursory examination of the data reveals distinct investment and portfolio diversification options for global investors. This could assist regulators in formulating more effective rules regarding price discovery processes., Competing Interests: No competing interests were disclosed., (Copyright: © 2024 Ali F et al.)

Objective: To assess the cost-effectiveness of using cheaper-but-noisier outcome measures, such as a short questionnaire, for large simple clinical trials., Background: To detect associations reliably, trials must avoid bias and random error. To reduce random error, we can increase the size of the trial and increase the accuracy of the outcome measurement process. However, with fixed resources, there is a trade-off between the number of participants a trial can enrol and the amount of information that can be collected on each participant during data collection., Methods: To consider the effect on measurement error of using outcome scales with varying numbers of categories, we define and calculate the variance from categorisation that would be expected from using a category midpoint; define the analytic conditions under which such a measure is cost-effective; use meta-regression to estimate the impact of participant burden, defined as questionnaire length, on response rates; and develop an interactive web-app to allow researchers to explore the cost-effectiveness of using such a measure under plausible assumptions., Results: An outcome scale with only a few categories greatly reduced the variance of non-measurement. For example, a scale with five categories reduced the variance of non-measurement by 96% for a uniform distribution. We show that a simple measure will be more cost-effective than a gold-standard measure if the relative increase in variance due to using it is less than the relative increase in cost from the gold standard, assuming it does not introduce bias in the measurement. We found an inverse power law relationship between participant burden and response rates such that a doubling the burden on participants reduces the response rate by around one third. Finally, we created an interactive web-app ( https://benjiwoolf.shinyapps.io/cheapbutnoisymeasures/ ) to allow exploration of when using a cheap-but-noisy measure will be more cost-effective using realistic parameters., Conclusion: Cheaper-but-noisier questionnaires containing just a few questions can be a cost-effective way of maximising power. However, their use requires a judgement on the trade-off between the potential increase in risk of information bias and the reduction in the potential of selection bias due to the expected higher response rates., (© 2024. The Author(s).)

Fluctuations in the financial market are influenced by various driving forces and numerous factors. Traditional financial research aims to identify the factors influencing stock prices, and existing works construct a common neural network learning framework that learns temporal dependency using a fixed time window of historical information, such as RNN and LSTM models. However, these models only consider the short-term and point-to-point relationships within stock series. The financial market is a complex and dynamic system with many unobservable temporal patterns. Therefore, we propose an adaptive period-aggregation model called the Latent Period-Aggregated Stock Transformer (LPAST). The model integrates a variational autoencoder (VAE) with a period-to-period attention mechanism for multistep prediction in the financial time series. Additionally, we introduce a self-correlation learning method and routing mechanism to handle complex multi-period aggregations and information distribution. Main contributions include proposing a novel period-aggregation representation scheme, introducing a new attention mechanism, and validating the model's superiority in long-horizon prediction tasks. The LPAST model demonstrates its potential and effectiveness in financial market prediction, highlighting its relevance in financial research and predictive analytics., Competing Interests: NO authors have competing interests., (Copyright: © 2024 Tang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In the digital era, digital economy has a far-reaching impact on the collaborative agglomeration of manufacturing and service industries. This research aims to examine the economic relationship between digital economy and industrial collaborative agglomeration. Based on a panel data set of 286 Chinese cities, this research employs Tobit model, moderating effect model, and mediating effect model to conduct data analysis. It is found that digital economy has a nonlinear relationship with industrial collaborative agglomeration, and this relationship is a U-shape. Moderating effect analysis reveals that government intervention significantly regulates the role of digital economy in industrial collaborative agglomeration. Mediating effect analysis indicates that digital economy promotes industrial collaborative agglomeration through entrepreneurial activity. Heterogeneity analysis shows that the facilitating effect of digital economy on collaborative agglomeration in high-end industries comes earlier than in middle- and low-end industries. Moreover, this research finds that digital economy plays a significant role in industrial collaborative agglomeration in central and western regions of China but not in the eastern region. To enhance the impact of digital economy on industrial collaborative agglomeration, it is crucial to strengthen the engagement of the government and ensure the availability of digital technology., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Lei et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Small and medium-sized enterprises (SMEs) were an important part of China's economy, but they faced challenges to growth due to financing difficulties. Government subsidies are considered as a potential way to address this problem. This study aims to assess the effectiveness of the Chinese government's subsidy program aimed at improving the accessibility of financing for SMEs. We analyze a comprehensive dataset of Chinese firms' subsidy programs from 2011 to 2020. We classify subsidies into unconditional and conditional categories and use fixed-effects regression models to control for the effects of time and between-group variation to more accurately assess the effectiveness of government subsidies. In addition, we use a PSM-DID model to reduce the effect of selectivity bias to more accurately estimate the causal effect of subsidies on financing strategies. We also use a mediated effects model to help understand the mechanisms by which different types of subsidies affect financing strategies. The results show that government subsidies can significantly improve SMEs' financing ability, but different types of subsidies produce subtle differences. Conditional subsidies support debt financing mainly through incentives, while unconditional subsidies help SMEs improve their equity financing ability through information effects. Furthermore, we find that over-reliance on a single subsidy type may reduce its effectiveness, suggesting a complex relationship between government intervention and SME financing. Thus, well-designed policies are crucial for promoting SMEs and fostering economic growth., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Sun et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Innovative products entering the market will cause dynamic changes in market demand, and consumers' purchase regret and their return behavior make the market environment more and more complex, which in turn affects the dynamic decision-making in the supply chain. In this paper, under the situation of discrete decision time, combining with the objective reality, we make discrete modification to the classical Bass diffusion model (Bass model), construct a manufacturer-led, retailer-followed supply chain differential game model, analyze the optimal decision-making of the manufacturer and the retailer by combining with the theory of discrete optimal control, and then verify the conclusions by numerical simulation. The results show that: when retailers purchase directly from the manufacturer and sell in the market, the optimal pricing of the innovative product can make the supply chain as a whole, realizing Pareto optimality; consumer's purchase regret will increase the amount of returns, which will lead to the decrease of product sales and the profits of the manufacturer and the retailer; when the innovative product accounts for a different share of the market, the impact of purchase regret on the wholesale price and the retail price are also different. Therefore, manufacturers need to have an extensive comprehension of the market to minimize the negative effects of consumer regret and returns, and to formulate a reasonable pricing strategy for their products to gain as much profit as possible., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Mu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: In the United States, approximately 1% of pregnancies are complicated by pregestational diabetes. Individuals with type 1 diabetes have an increased risk of adverse maternal and neonatal outcomes. While continuous glucose monitoring has demonstrated benefits for patients with type 1 diabetes, its cost is higher than traditional intermittent fingerstick monitoring, particularly if used only during pregnancy., Objective: To develop an economic analysis model to compare in silico the cost of continuous glucose monitoring and self-monitoring of blood glucose in a cohort of pregnant individuals with type 1 diabetes mellitus., Study Design: We developed an economic analysis model to compare two glucose monitoring strategies in pregnant individuals with type 1 diabetes: continuous glucose monitoring and self-monitoring. The model considered hypertensive disorders of pregnancy, large for gestational age, cesarean delivery, neonatal intensive care unit (NICU) admission, and neonatal hypoglycemia. The primary outcome was the total cost per strategy in 2022 USD from a health system perspective, with self-monitoring as the reference group. Probabilities, relative risks, and costs were extracted from the literature, and the costs were adjusted to 2022 US dollars. Sensitivity analyses were conducted by varying parameters based on the probability, relative risk, and cost distributions. The robustness of the results was tested through 1000 Monte Carlo simulations., Results: In the base-case analysis, the cost of pregnancy using continuous glucose monitoring was $26,837 compared to $29,039 for self-monitoring, resulting in a cost reduction of $2,202 per individual. The parameters with the greatest effect on the incremental cost included the relative risk of NICU admission, cost of NICU admission, continuous glucose monitoring costs, and usual care costs. Monte Carlo simulations indicated that continuous glucose monitoring was the optimal strategy 98.7% of the time. One-way sensitivity analysis showed that continuous glucose monitoring was more economical if the relative risk of NICU admission with continuous glucose monitoring vs. self-monitoring was below 1.15., Conclusion: Compared to self-monitoring, continuous glucose monitoring is an economical strategy for pregnant individuals with type 1 diabetes mellitus., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: The health and economic consequences of artificial intelligence (AI) systems for mechanically ventilated intensive care unit patients often remain unstudied. Early health technology assessments (HTA) can examine the potential impact of AI systems by using available data and simulations. Therefore, we developed a generic health-economic model suitable for early HTA of AI systems for mechanically ventilated patients., Materials and Methods: Our generic health-economic model simulates mechanically ventilated patients from their hospitalisation until their death. The model simulates two scenarios, care as usual and care with the AI system, and compares these scenarios to estimate their cost-effectiveness., Results: The generic health-economic model we developed is suitable for estimating the cost-effectiveness of various AI systems. By varying input parameters and assumptions, the model can examine the cost-effectiveness of AI systems across a wide range of different clinical settings., Conclusions: Using the proposed generic health-economic model, investors and innovators can easily assess whether implementing a certain AI system is likely to be cost-effective before an exact clinical impact is determined. The results of the early HTA can aid investors and innovators in deployment of AI systems by supporting development decisions, informing value-based pricing, clinical trial design, and selection of target patient groups., Competing Interests: Declaration of competing interest Authors LRZ, JK, SvdP, ADIvA and BF have no competing interests to declare that are relevant to the content of this article. MJP reports grants and personal fees from various pharmaceutical industries, all outside the submitted work. He holds stocks in Pharmacoeconomics Advice Groningen (PAG Ltd.; Groningen, Netherlands) and Health-Ecore Ltd. (Zeist/Groningen, Netherlands) and is advisor to Asc Academics (Groningen/Utrecht, Netherlands), all pharmacoeconomic consultancy companies. The Department of Anaesthesiology, Intensive Care Medicine & Pain Therapy of the University Hospital Frankfurt, Goethe University received support from B. Braun Melsungen, CSL Behring, Fresenius Kabi, and Vifor Pharma for the implementation of Frankfurt‘s Patient Blood Management program. KZ has received honoraria for participation in advisory board meetings for Haemonetics and Vifor and received speaker fees from CSL Behring, Masimo, Pharmacosmos, Boston Scientific, Salus, iSEP, Edwards and GE Healthcare. He is the Principal Investigator of the EU-Horizon 2020 project ENVISION (Intelligent plug-and-play digital tool for real-time surveillance of COVID-19 patients and smart decision-making in Intensive Care Units) and Horizon Europe 2021 project COVend (Biomarker and AI-supported FX06 therapy to prevent progression from mild and moderate to severe stages of COVID-19)., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

In the last few decades, developers of new drugs, biologics, and devices have increasingly leveraged digital health technologies (DHTs) to assess clinical trial digital endpoints. To our knowledge, a comprehensive assessment of the financial net benefits of digital endpoints in clinical trials has not been conducted. We obtained data from the Digital Medicine Society (DiMe) Library of Digital Endpoints and the US clinical trials registry, ClinicalTrials.gov. The benefit metrics are changes in trial phase duration and enrollment associated with the use of digital endpoints. The cost metric was obtained from an industry survey of the costs of including digital endpoints in clinical trials. We developed an expected net present value (eNPV) model of the cash flows for new drug development and commercialization to assess financial value. The value measure is the increment in eNPV that occurs when digital endpoints are employed. We also calculated a return on investment (ROI) as the ratio of the estimated increment in eNPV to the mean digital endpoint implementation cost. For phase II trials, the increase in eNPV varied from $2.2 million to $3.3 million, with ROIs between 32% and 48% per indication. The net benefits were substantially higher for phase III trials, with the increase in eNPV varying from $27 million to $40 million, with ROIs that were four to six times the investment. The use of digital endpoints in clinical trials can provide substantial extra value to sponsors developing new drugs, with high ROIs., (© 2024 The Author(s). Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

We are developing an economic model to explore multiple topics in Australian youth mental health policy. To help make that model more readily transferable to other jurisdictions, we developed a software framework for authoring modular computational health economic models (CHEMs) (the software files that implement health economic models). We specified framework user requirements for: a simple programming syntax; a template CHEM module; tools for authoring new CHEM modules; search tools for finding existing CHEM modules; tools for supplying CHEM modules with data; reproducible analysis and reporting tools; and tools to help maintain a CHEM project website. We implemented the framework as six development version code libraries in the programming language R that integrate with online services for software development and research data archiving. We used the framework to author five development version R libraries of CHEM modules focussed on utility mapping in youth mental health. These modules provide tools for variable validation, dataset description, multi-attribute instrument scoring, construction of mapping models, reporting of mapping studies and making out of sample predictions. We assessed these CHEM module libraries as mostly meeting transparency, reusability and updatability criteria that we have previously developed, but requiring more detailed documentation and unit testing of individual modules. Our software framework has potential value as a prototype for future tools to support the development of transferable CHEMs.Code: Visit https://www.ready4-dev.com for more information about how to find, install and apply the prototype software framework., (© 2024. The Author(s).)

Purpose: The optimal adjuvant therapy (antiestrogen therapy [ET] + radiation therapy or ET alone, or in some reports radiation therapy alone) in older women with early-stage breast cancer has been highly debated. However, granular details on the role of insurance in the out-of-pocket cost for patients receiving ET with or without radiation therapy are lacking. This project disaggregates out-of-pocket costs by insurance plans to increase treatment cost transparency., Methods and Materials: Several radiation therapy schedules are accepted standards as per the National Comprehensive Cancer Network guidelines. For our financial estimate model, we used the 5-fraction and 15-fraction radiation therapy and ET prescribed over a 5-year duration. The total aggregate out-of-pocket costs were determined from the sum of treatment costs, deductibles, and copays/coinsurance based on Medicaid, Original Medicare, Medigap Plan G, and Medicare Part D Rx plans. The model assumes a Medicare- and/or Medicaid-eligible patient ≥70 years of age with node-negative, early-stage estrogen-receptor-positive breast cancer. Patient out-of-pocket costs were estimated from publicly available insurance data from plan-specific benefit coverage materials using a 5-year time horizon., Results: Original Medicare beneficiaries face a total out-of-pocket treatment charge of $2738.52 for ET alone, $2221.26 for 5-fraction radiation therapy alone, $2573.92 for 15-fraction radiation therapy alone, $3361.26 for combined ET+ 5-fraction radiation therapy, and $3713.92 for combined ET + 15-fraction radiation therapy. Medigap Plan G beneficiaries have an out-of-pocket charge of $1130.00 with radiation therapy alone and face an out-of-pocket of $2270.00 for ET alone and combined ET+ radiation therapy. For Medicaid beneficiaries, all treatments approved by Medicaid are covered without limit, resulting in no out-of-pocket expense for either adjuvant treatment option., Conclusions: This model (based on actual cost estimates per insurance plan rather than claims data), by estimating expenses within Medicare and Medicaid plans, provides a level of transparency to patient cost. With knowledge of the costs borne by patients themselves, treatment decisions informed by patients' individual priorities and preferences may be further enhanced., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objectives: The results of a recent single-arm trial (ZUMA-5) of axicabtagene ciloleucel (axi-cel) for relapsed/refractory (r/r) follicular lymphoma (FL) demonstrated high rates of durable response and tolerable toxicity among treated patients. To quantify the value of axi-cel compared with standard of care (SOC) to manage r/r FL patients who have had at least 2 prior lines of systemic therapy (3L+), a cost-effectiveness model was developed from a US third-party payer perspective., Methods: A 3-state partitioned-survival cost-effectiveness model was developed with a lifetime horizon. Patient-level analyses of the 36-month ZUMA-5 (axi-cel) and SCHOLAR-5 (SOC) studies were used to extrapolate progression-free and overall survivals. After 5 years of survival, an estimated 40% of the modeled population was assumed to experience long-term remission based on literature. Results include the incremental cost-effectiveness ratio (ICER) measured as incremental cost per quality-adjusted life year (QALY) gained. One-way sensitivity analysis, probabilistic sensitivity analysis, and scenario analyses were performed. All outcomes were discounted 3% per year., Results: Axi-cel led to an increase of 4.28 life-years, 3.64 QALYs, and a total cost increase of $321 192 relative to SOC, resulting in an ICER of $88 300 per QALY. Across all parameters varied in the one-way sensitivity analysis, the ICER varied between $133 030 and $67 277. In the probabilistic sensitivity analysis, axi-cel had a 99% probability of being cost-effective across 5000 iterations using a $150 000 willingness-to-pay threshold., Conclusions: Given the robustness of the model results and sensitivity analyses, axi-cel is expected to be a cost-effective treatment in 3L+ r/r FL., Competing Interests: Author Disclosures Author disclosure forms can be accessed below in the Supplemental Material section., (Copyright © 2024. Published by Elsevier Inc.)

Objectives: Health economic (HE) models are often considered as "black boxes" because they are not publicly available and lack transparency, which prevents independent scrutiny of HE models. Additionally, validation efforts and validation status of HE models are not systematically reported. Methods to validate HE models in absence of their full underlying code are therefore urgently needed to improve health policy making. This study aimed to develop and test a generic dashboard to systematically explore the workings of HE models and validate their model parameters and outcomes., Methods: The Probabilistic Analysis Check dashBOARD (PACBOARD) was developed using insights from literature, health economists, and a data scientist. Functionalities of PACBOARD are (1) exploring and validating model parameters and outcomes using standardized validation tests and interactive plots, (2) visualizing and investigating the relationship between model parameters and outcomes using metamodeling, and (3) predicting HE outcomes using the fitted metamodel. To test PACBOARD, 2 mock HE models were developed, and errors were introduced in these models, eg, negative costs inputs, utility values exceeding 1. PACBOARD metamodeling predictions of incremental net monetary benefit were validated against the original model's outcomes., Results: PACBOARD automatically identified all errors introduced in the erroneous HE models. Metamodel predictions were accurate compared with the original model outcomes., Conclusions: PACBOARD is a unique dashboard aiming at improving the feasibility and transparency of validation efforts of HE models. PACBOARD allows users to explore the working of HE models using metamodeling based on HE models' parameters and outcomes., Competing Interests: Author Disclosures Author disclosure forms can be accessed below in the Supplemental Material section., (Copyright © 2024. Published by Elsevier Inc.)

Background: The disparity between the demand for and supply of kidney transplants has resulted in prolonged waiting times for patients with kidney failure. A potential approach to address this shortage is to consider kidneys from donors with a history of common cancers, such as breast, prostate, and colorectal cancers., Methods: We used a patient-level Markov model to evaluate the outcomes of accepting kidneys from deceased donors with a perceived history of breast, prostate, or colorectal cancer characterized by minimal to intermediate transmission risk. Data from the Australian transplant registry were used in this analysis. The study compared the costs and quality-adjusted life years (QALYs) from the perspective of the Australian healthcare system between the proposed practice of accepting these donors and the conservative practice of declining them. The model simulated outcomes for 1500 individuals waitlisted for a deceased donor kidney transplant for a 25-y horizon., Results: Under the proposed practice, when an additional 15 donors with minimal to intermediate cancer transmission risk were accepted, QALY gains ranged from 7.32 to 20.12. This translates to an approximate increase of 7 to 20 additional years of perfect health. The shift in practice also led to substantial cost savings, ranging between $1.06 and $2.3 million., Conclusions: The proposed practice of accepting kidneys from deceased donors with a history of common cancers with minimal to intermediate transmission risk offers a promising solution to bridge the gap between demand and supply. This approach likely results in QALY gains for recipients and significant cost savings for the health system., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background and Objective: In Italy, the management of metastatic non-small cell lung cancer and melanoma leads to significant healthcare challenges, necessitating cost-effective treatment strategies and offering valuable insights for healthcare policymakers and stakeholders. This study was designed to assess the costs, quality-adjusted life-years (QALYs) and disability-adjusted life-years (DALYs) associated with the health and economic outcomes of (1) pembrolizumab-combined chemotherapy administered as a first-line treatment for metastatic non-squamous and squamous non-small cell lung cancer (NSCLC) where the tumour presents with a programmed death-ligand 1 expression level < 50% and of (2) adjuvant pembrolizumab treatment for stage III melanoma., Methods: Three cost-effectiveness models developed by MSD were investigated for each treatment indication. A unique model was built to assess the overall effect of pembrolizumab versus chemotherapy or watchful waiting in patients with lung cancer or melanoma, respectively. Theoretical cohorts of patients with metastatic squamous and non-squamous NSCLC were followed over time using a partitioned survival model with weekly cycles. A weekly cycle Markov model was employed for melanoma. The analysis was conducted from the Italian National Health Service perspective, considering a time horizon of 40 years (lifetime). A single closed cohort of treatable patients was followed over time for each indication (4000, 7000 and 900 for NSCLC squamous, non-squamous and melanoma, respectively). The costs evaluated included those for adverse drug events, non-drug disease management, subsequent treatment and terminal care. Drug acquisition and administration costs were excluded., Results: For each treatment indication assessed, pembrolizumab produced downstream direct cost offsets (- €122,498,568, - €133,369,076 and - €32,993,242 for NSCLC squamous, non-squamous and melanoma indications, respectively), increased quality of life (+2088, +5317 and +2307 QALYs for NSCLC squamous, non-squamous and melanoma indications, respectively) and reduced disability (- 2658, - 7202 and - 3029 DALYs for NSCLC squamous, non-squamous and melanoma indications, respectively). Across indications, the total cost offsets of pembrolizumab were - €288,860,885, with 9712 QALYs gained and 12,889 DALYs avoided., Conclusions: The analysis demonstrated that, compared with chemotherapy, pembrolizumab is more cost effective in Italy as a first-line treatment in patients with metastatic squamous or non-squamous NSCLC and, if compared with watchful waiting, as adjuvant treatment in patients with stage III melanoma. The present analysis suggested that pembrolizumab use could lead to important health benefits for patients while offsetting a portion of cancer care costs., (© 2024. Merck & Co., Inc., Rahway, NJ, USA and its affiliates.)

Objectives: To illustrate the financial consequences of implementing different managed entry agreements (managed entry agreements for the Dutch healthcare system for autologous gene therapy atidarsagene autotemcel [Libmeldy]), while also providing a first systematic guidance on how to construct managed entry agreements to aid future reimbursement decision making and create patient access to high-cost, one-off potentially curative therapies., Methods: Three payment models were compared: (1) an arbitrary 60% price discount, (2) an outcome-based spread payment with discounts, and (3) an outcome-based spread payment linked to a willingness to pay model with discounts. Financial consequences were estimated for full responders (A), patients responding according to the predicted clinical pathway presented in health technology assessment reports (B), and unstable responders (C). The associated costs for an average patient during the time frame of the payment agreement, the total budget impact, and associated benefits expressed in quality-adjusted life-years of the patient population were calculated., Results: When patients responded according to the predicted clinical pathway presented in health technology assessment reports (scenario B), implementing outcome-based reimbursement models (models 2 and 3) had lower associated budget impacts while gaining similar benefits compared with the discount (scenario 1, €8.9 million to €6.6 million vs €9.2 million). In the case of unstable responders (scenario C), costs for payers are lower in the outcome-based scenarios (€4.1 million and €3.0 million, scenario 2C and 3C, respectively) compared with implementing the discount (€9.2 million, scenario 1C)., Conclusions: Outcome-based models can mitigate the financial risk of reimbursing atidarsagene autotemcel. This can be considerably beneficial over simple discounts when clinical performance was similar to or worse than predicted., Competing Interests: Author Disclosures Author disclosure forms can be accessed below in the Supplemental Material section. The views expressed in this article are the personal views of the authors. They may not be understood or quoted as being made on behalf of or reflecting the position of the agencies or organizations with which the authors are affiliated., (Copyright © 2024. Published by Elsevier Inc.)

Background: Heart failure (HF) is among the leading causes of death in the United States. Further, patients hospitalized because of HF with comorbid diabetes mellitus (DM) are at a significantly increased risk of death and rehospitalization. Results from the SOLOIST-WHF trial show that sotagliflozin lowered rates of readmission among hospitalized patients with HF and comorbid DM. However, it is unclear what the economic impact of the use of sotagliflozin would be on hospitals and health systems, particularly in an age where provider reimbursement is increasingly tied to value., Objective: To quantify the 1-year financial impact on US provider health systems of adopting sotagliflozin relative to standard of care (SoC) across different alternative payment models., Methods: This study created a 3-part decision tree model to quantify the financial impact of using sotagliflozin to treat patients hospitalized with HF in a US hospital setting. The model first estimated the clinical and economic outcomes of health systems with current SoC (no sotagliflozin) to treat US patients hospitalized for HF with comorbid DM. Then, using the results from the SOLOIST trial, the changes in clinical and economic outcomes with sotagliflozin adoption were modeled. Finally, the differences in health care utilization between sotagliflozin and SoC arms were translated to differences in health system reimbursement in the context of 3 common alternative payment models (APMs) in addition to the baseline fee-for-service (FFS) model: FFS with the Hospital Readmissions Reduction Program, the Bundled Payments for Care Improvement-Advanced program, and Accountable Care Organizations., Results: A typical community hospital would have 83.4 patients per year on average with an index HF hospitalization with comorbid DM. The model predicted that sotagliflozin would reduce the probability of hospitalization, emergency department visits, and deaths by 29.3%, 38.5%, and 17.8%, respectively, compared with SoC. For hospitals not participating in APM programs, sotagliflozin resulted in a net loss of $92.94 per person ($7,754 per health system). Conversely, when accounting for provider health system participation in APMs, sotagliflozin adoption increased financial returns by $4,720 per person ($305,604 per health system) under the Hospital Readmissions Reduction Program, $1,200 per person ($100,106 per health system) for the Bundled Payments for Care Improvement-Advanced program, and $1,078 per person ($31,029 per health system) for Accountable Care Organizations. Based on the national average composition of APM reimbursement, sotagliflozin adoption resulted in a $1,576 increase in margin per patient with HF ($105,454 per health system)., Conclusions: Although sotagliflozin adoption reduced health system revenue in an FFS payment model, it led to a net positive financial impact after accounting for APM bonus payments.

Background: Initiatives in perioperative care warrant robust cost-effectiveness analysis in a cost-constrained era when high-value care is a priority. A model of anesthesia-led early high-acuity postoperative care, advanced recovery room care (ARRC), has shown benefit in terms of hospital and patient outcomes, but its cost-effectiveness has not yet been formally determined., Methods: Data from a previously published single-center prospective cohort study of ARRC in medium-risk patients were used to generate a Markov model, which described patient transition between care locations, each with different characteristics and costs. The incremental cost-effectiveness ratio (ICER), using days at home (DAH) and hospital costs, was calculated for ARRC compared to usual ward care using deterministic and probabilistic sensitivity analysis., Results: The Markov model accurately described patient disposition after surgery. For each patient, ARRC provided 4.3 more DAH within the first 90 days after surgery and decreased overall hospital costs by $1081 per patient. Probabilistic sensitivity analysis revealed that ARRC had a 99.3% probability of increased DAH and a 77.4% probability that ARRC was dominant from the perspective of the hospital, with improved outcomes and decreased costs., Conclusions: Early high-acuity care for approximately 24 hours after surgery in medium-risk patients provides highly cost-effective improvements in outcomes when compared to usual ward care., Competing Interests: Conflicts of Interest: See Disclosures at the end of the article., (Copyright © 2023 International Anesthesia Research Society.)

Aim: The objective of this study was to compare adverse event (AE) management costs for fruquintinib, regorafenib, trifluridine/tipiracil (T/T) and trifluridine/tipiracil+bevacizumab (T/T+bev) for patients with metastatic colorectal cancer (mCRC) previously treated with at least two prior lines of therapy from the US commercial and Medicare payer perspectives. Materials & methods: A cost-consequence model was developed to calculate the per-patient and per-patient-per-month (PPPM) AE costs using rates of grade 3/4 AEs with incidence ≥5% in clinical trials, event-specific management costs and duration treatment. Anchored comparisons of AE costs were calculated using a difference-in-differences approach with best supportive care (BSC) as a common reference. AE rates and treatment duration were obtained from clinical trials: FRESCO and FRESCO-2 (fruquintinib), RECOURSE (T/T), CORRECT (regorafenib) and SUNLIGHT (T/T, T/T+bev). AE management costs for the commercial and Medicare perspectives were obtained from publicly available sources. Results: From the commercial perspective, the AE costs (presented as per-patient, PPPM) were: $4015, $1091 for fruquintinib (FRESCO); $4253, $1390 for fruquintinib (FRESCO-2); $17,110, $11,104 for T/T (RECOURSE); $9851, $4691 for T/T (SUNLIGHT); $8199, $4823 for regorafenib; and $11,620, $2324 for T/T+bev. These results were consistent in anchored comparisons: the difference-in-difference for fruquintinib based on FRESCO was -$1929 versus regorafenib and -$11,427 versus T/T; for fruquintinib based on FRESCO-2 was -$2257 versus regorafenib and -$11,756 versus T/T. Across all analyses, results were consistent from the Medicare perspective. Conclusion: Fruquintinib was associated with lower AE management costs compared with regorafenib, T/T and T/T+bev for patients with previously treated mCRC. This evidence has direct implications for treatment, formulary and pathways decision-making in this patient population.