Cost Value Research Articles

Pipe production cost management model based on graph theory

The pipe production process is a complex dynamical system with a significant number of production operations and interconnected cost localization centres. Purpose. To develop a mathematical model of the process of handling analytical information of a pipe enterprise using graph theory for the needs of cost management at each production stage. Methodology. Technological flow charts of the production job, where the list of mandatory activities and routing of the operating process are indicated, were used to organize cost accounting by operational centres of their localization with the help of computer modelling elements, namely the graph theory. The work used a complex of research methods, including analysis and scientific synthesis of scientific and technical information; theoretical studies; methods of mathematical and computer modelling, engineering developments. Findings. The cost accounting process is represented by a directed hypergraph. Each production operation is associated with a graph vertex. Each vertex is assigned to a series of interrelated marks: type of technological operation; weight factor; the value of direct costs for the operation; the value of indirect costs for the operation; the expense factor. The initial state of the hypergraph is specified by means of its initial marking, which corresponds to the set cipher of the batch of pipes and its weight. Further execution of the marked hypergraph is performed by running the allowed vertices. Marking of the graph ends if all the information from the technological flow charts of pipe products has been used. Originality. A model of cost management by operational centres is proposed which will allow dividing the prime cost of pipes which differ according to the production technology. It is recommended to rank pipe products within each technologically similar group for an economically feasible allocation of costs between batches of pipes. The proposed process model of processing analytical information of the pipe enterprise using graph theory will allow providing data governance as for the prime cost of each individual batch of pipe products, will contribute to the improvement in the order generation procedure taking into account the acquired information, and will allow making the appropriate adjustments when making management decisions. Practical value. Calculation of expenses for production operations allows one to identify the most cost-intensive of them. Relying on the results of the calculation, the enterprise management has the opportunity to manage costs at any stage of the production process. Moreover, the model allows determining the amount of consumed metal for each production operation, which is relevant for pipe enterprises. It is appropriate to focus further scientific developments in this direction on the possibility of managing non-manufacturing cost with the help of mathematical models in economics to optimize the supply and sales activities of the enterprise.

Cost-effectiveness analysis of atezolizumab plus bevacizumab and chemotherapy for the treatment of metastatic, persistent, or recurrent cervical cancer (BEATcc)

ABSTRACT Background The addition of atezolizumab to bevacizumab plus platinum regimen has demonstrated notable improvements in treating metastatic, persistent, or recurrent cervical cancer, but its cost-effectiveness requires further investigation. From a US payer perspective, we aimed to evaluate the cost-effectiveness of atezolizumab plus bevacizumab and chemotherapy vs. standard chemotherapy as a first-line treatment for metastatic, persistent, or recurrent cervical cancer. Methods A partitioned survival model based on the data from the BEATcc trial was used to calculate the incremental cost-effectiveness ratio (ICER), using cost and health utility information obtained from literature and publicly accessible databases. One-way and probabilistic sensitivity analyses were performed to evaluate the model’s responsiveness to variations in parameters. Results The addition of atezolizumab resulted in an additional 0.839 quality-adjusted life years (QALY) at an additional cost of $458,237, leading to an ICER of $545,943/QALY. One-way sensitivity analysis indicated that the cost of atezolizumab had the greatest impact on the ICER, followed by the utility value of progression-free survival (PFS) and follow-up costs. Probabilistic sensitivity analysis showed a 0% cost-effectiveness probability at the current willingness-to-pay (WTP) threshold of $150,000 per QALY. Conclusion Adding atezolizumab to chemotherapy is cost-prohibitive in the US and may not be cost-effective for patients.

Business AI for Oil and Gas: Unlocking Efficiency Across the Value Chain

This article explores the transformative impact of artificial intelligence (AI) on the oil and gas industry, focusing on its applications across the value chain from exploration to end-user delivery. It examines the potential of AI, particularly generative AI, to optimize various aspects of the sector, including exploration, development, production, transportation, refining, and sales. The article discusses specific AI applications in refinery processes. It highlights the significant benefits of AI implementation, such as improved operational efficiency, reduced downtime, enhanced decision-making, cost reduction, and increased safety. Drawing on industry studies and research, the article presents quantitative data on the potential cost savings, productivity improvements, and value creation that AI technologies can bring to the oil and gas sector.

Impact of Skidding and Slope on Grapple Skidder Productivity and Costs: A Monte Carlo Simulation in Eucalyptus Plantations

Background: In the context of mechanized timber harvesting, alterations in technical parameters, such as skidding distance and terrain slope, have the potential to influence the productivity and production costs associated with the self-propelled grapple skidder. Furthermore, these variables are inherently uncertain, which could potentially cause forest managers to make inaccurate decisions. The objective was to analyze whether four skidding distances and two slope classes influence the productivity and production costs of the grapple skidder in Eucalyptus planted forests from a stochastic perspective using the Monte Carlo method. Methods: Productivity was estimated using the time study protocol. To calculate the cost per scheduled hour of the grapple skidder, both fixed and variable costs were considered, and subsequently, the production cost was determined. Results: The mean productivity of the grapple skidder on flat slopes was 114.35 m3 h−1, while on wavy to strong wavy slopes it was 80.43 m3 h−1. In flat slopes, considering all skid distance ranges, the mean production cost was 0.82 USD m−3, while in wavy to strong wavy slopes it was 1.48 USD m−3. The mean values for operator labor costs and fuel account for 58.1% of the cost per scheduled hour of the grapple skidder. Conclusions: The mean productivity of the grapple skidder in Eucalyptus planted forests decreased with increasing skidding distance in both slope classes but was 29.7% lower on wavy to strong wavy slopes compared to flat slopes. The mean production cost of the grapple skidder during timber skidding on flat slopes is 80.0% lower than on wavy to strong wavy slopes. For future investigations, the impact of other slope classes, skid distances, and silvicultural aspects on productivity and production costs can be considered from a stochastic perspective using the Monte Carlo method.

An analytical approach for evaluation of conveyor exit strategies in open-pit mines

Transportation is the most expensive task in deep open-pit mining operations. An In-Pit Crushing and Conveying (IPCC) system, as an alternative to the conventional shovel-truck system, requires precise planning to avoid wasting high capital expenditures on trucks. The decision to fit a conveyor system into the pit design is challenging and needs to be addressed in the literature. Further optimisation of the IPCC system requires choosing an appropriate conveyor exit strategy. Conveyor exit schemes include a Dedicated Ramp Slot (DRS), an Existing Ramping System, an inclined tunnel and High-Angle Conveyors (HAC). This paper provides an analytical approach to compare the cost of different conveyor exit strategies in open-pit mines. The results indicate that for a depth up to 100 m, the Present Value of Cost (PVC) for the DRS is the least. For the cases deeper than 300 m, the HAC has the least PVC. Sensitivity analysis showed that for the depths between 100 and 300 m, a more accurate and detailed definition of parameters is needed. Besides, in most cases, the HAC provides the lowest payback period and the highest internal rate of return among the alternatives.

Electro-mobility – an Opportunity to Develop a More Sustainable Transport System

The future of transport is electro-mobility, a technology that ensures environmentally friendly and energy efficient vehicles on the road. But to exploit the full benefits of electric propulsion there are still many challenges to overcome. These challenges are related to the cost and residual value (aftermarket) of the vehicles, battery life and cost, charging and range. This article discusses these challenges as well as the state of the electric vehicle market. The aim is to present to what extent the development of electric mobility in Europe and in Bulgaria will outline a more sustainable transport system and to outline what the opportunities for its development are. Decarburization of transport is key to achieving sustainable mobility ensuring transport connectivity across the continent.

The cost of obesity and related NCDs in Brazil: An analysis of hospital admissions, disability retirement benefits, and statutory sick pay

ObjectivesThis study analyses the prevalence of overweight/obesity in Brazil, and its costs regarding hospital admissions (HA), disability retirement benefits (DRB), and statutory sick pay (SSP) associated with obesity-related non-communicable diseases (NCDs). Study designTime-series study. MethodsThis study analyses data from the VIGITEL system (2010–2019) to calculate the body-mass index (BMI) of adult residents in Brazil's state capitals. Data on HA, DRB, and SSP were obtained from Brazil's SIH/SUS and AEPS Infologo systems. Pearson's correlation and linear regression models were applied. The study selected 23 diseases of the International Classification of Disease (ICDs) belonging to chapters C; E; I; and K. Cost values in BRL were deflated using IPCA. ResultsThe results showed a significant increase in overweight and obesity rates in Brazil, with BMI rising by 0.09 kg/m2 annually. Regression analysis revealed that each 1-point increase in the average BMI of the population is associated with an increase of 81,772 (BRL 237.51 million/year) new HA per year, 5541 (BRL 18.8 million/year) new DRB granted per year, and 42,360 (BRL 131 million/year) new SSP per year. Also, every 1 % increase in the share of the Brazilian population with obesity is associated with an increase of 16,973 (BRL 48.8 million/year) new HA per year, 1202 (BRL 3.97 million/year) new DRB granted per year, and 8686 (BRL 26.8 million/year) new SSP per year. Regressions for deflated values showed lower significance, suggesting a strong impact of inflation on health costs in Brazil. ConclusionsObesity prevalence in Brazil implies high direct and indirect costs for the Brazilian government, especially considering circulatory system diseases.

Pre-referral ultrasound for cryptorchidism: Still common, still not necessary.

Evidence-based guidelines do not recommend imaging in cryptorchidism, but anecdotally most referrals include an ultrasound report. We aimed to assess the frequency, utility and burden of imaging in children referred with presumptive disorders of testicular descent, and to assess trends over a 7-year period before and after local and international guidelines have been introduced. This was a prospective cohort study of children referred to the Queensland Children'sHospital for anomalies of testicular descent between 2015-2017 and 2023-2024. Data were collected regarding demographics, referral details, imaging performed and surgical diagnosis. A total of 268 children were recruited. Ultrasound frequency has not significantly changed over time (72.8%, 2015-2017; 63.6% 2023-2024; P = 0.11). Currently, 17.6% of families are charged, and 31.9% need to take time off work, for the ultrasound. This is a significant increase from the 2015-2017 cohort. Parents report concern and anxiety, and find it traumatic for their child. Following review, the majority (65.7%) had physiologically normal testes, while 4.9% and 22.4% were diagnosed with bilateral or unilateral cryptorchidism, respectively, and 7.0% had other diagnoses. Ultrasound was concordant with the surgical diagnosis in 25.0% (2015-2017) and 30.7% (2023-2024). Ultrasound did not contribute to diagnosis nor management in any patient. Despite international and local guidelines, cryptorchid children continue to undergo ultrasound prior to referral. Such ultrasounds do not provide utility, or value for cost. We recommend avoiding their routine use for suspicion of testicular maldescent and working together to improve strategies for translating evidence-based guidelines into clinical practice.

What can optimized cost distances based on genetic distances offer? A simulation study on the use and misuse of ResistanceGA.

Modelling population connectivity is central to biodiversity conservation and often relies on resistance surfaces reflecting multi-generational gene flow. ResistanceGA (RGA) is a common optimization framework for parameterizing these surfaces by maximizing the fit between genetic distances and cost distances using maximum likelihood population effect models. As the reliability of this framework has rarely been studied, we investigated the conditions maximizing its accuracy for both prediction and interpretation of landscape features' permeability. We ran demo-genetic simulations in contrasted landscapes for species with distinct dispersal capacities and specialization levels, using corresponding reference cost scenarios. We then optimized resistance surfaces from the simulated genetic distances using RGA. First, we evaluated whether RGA identified the drivers of the genetic patterns, that is, distinguished Isolation-by-Resistance (IBR) patterns from either Isolation-by-Distance or patterns unrelated to ecological distances. We then assessed RGA predictive performance using a cross-validation method, and its ability to recover the reference cost scenarios shaping genetic structure in simulations. IBR patterns were well detected and genetic distances were predicted with great accuracy. This performance depended on the strength of the genetic structuring, sampling design and landscape structure. Matching the scale of the genetic pattern by focusing on population pairs connected through gene flow and limiting overfitting through cross-validation further enhanced inference reliability. Yet, the optimized cost values often departed from the reference values, making their interpretation and extrapolation potentially dubious. While demonstrating the value of RGA for predictive modelling, we call for caution and provide additional guidance for its optimal use.

Explanatory Factors of the Accounting Choices for Investments Under IAS 27 of Listed European Union Entities

ABSTRACTThis study aims to analyze the explanatory factors of the accounting choices for investments of entities with securities traded on regulated markets from the European Union (EU) under International Accounting Standards (IAS) 27—Separate Financial Statements (SFS). According to IAS 27, investments in their scope can be accounted for by using the cost, equity method, or fair value, which represents alternative accounting methods commonly known in the literature as accounting choices. To identify the factors that may explain the accounting choices for investments under IAS 27, a logistic regression model is used. The research covers listed entities from 19 out of the 21 EU countries where IAS 27 is required or permitted. The findings highlight that the entities’ size and investment weight likely explain the adoption of the cost method, conversely to the size of the board of directors, which negatively explains its use. Accounting choices for investments under SFS are not yet explored in the literature. Moreover, this research also proposes further explanatory factors in the scope of the literature on accounting choices. This paper can potentially benefit a diverse set of stakeholders, namely the accounting standard‐setters, as they can draw attention to the comparability issues from the use of accounting choices, which may mitigate the financial information usefulness for decision‐making. Furthermore, auditors, supervisors, as well as investors and other users, can have a more comprehensive perspective of the reasons behind the method chosen by entities for accounting for their financial investments.

Life cycle management of critical refurbishable parts of ship equipment

To ensure the product life cycle (PLC), foreign and domestic information technologies have been developed that mainly ensure the stages of design and manufacture of products, but they do not allow for automation of the design of technologies for restoration and strengthening of parts. The relevance of restoration of critical parts of ship equipment is due to dependence on foreign supplies of equipment and spare parts (SP), as well as sanctions from unfriendly states, which complicated the acquisition of SP, and the need for import independence arose. The paper shows that life cycle management of a restored part has a significant impact on the efficiency of marine fleet operation, and provides stages and main sub-stages of the life cycle of restored parts of ship equipment. Restoration of parts is considered appropriate if the required durability and savings are ensured compared to manufacturing or purchasing a new part. The concept of life cycle management of restored parts is provided. Life cycle management of restored parts includes planning, control and management of all stages, as well as decision-making to ensure the durability of the part through the use of advanced materials and coating formation technologies. The stage of the life cycle of the restored part, determining the service life of the part, the economic efficiency of its restoration and subsequent operation, is the technological process that ensures the optimal chemical composition, mechanical and structural parameters of the coating. All the properties of the restored part are laid down at the stage of designing the technological process. The prospects of using the life cycle management of the restored part are shown using the example of restoring precision parts of the fuel equipment of marine diesel engines. The use of various technologies for the same type of restored precision parts allows obtaining coatings with different chemical composition, mechanical properties, structure and, accordingly, different values of durability and cost price to ensure the specified service life of the tribological unit at an acceptable price.

Cost-effective reliability level in 100% renewables-based standalone microgrids considering investment and expected energy not served costs

Loss of load probability (LOLP) and expected energy not served (EENS) are commonly used in electrical power systems to evaluate reliability. LOLP defined as the probability that available generation capacity will be inadequate to supply customer demand. EENS defined as the expected amount of energy not being served to consumers by the system during the period considered due to system capacity shortages or unexpected power outages. Loss of Load Frequency (LOLF) is referred to a number of loss of load (LOL) event happened in the operation life span of the SMG. Loss of Load Reduction (LOLR) is defined as the required reduction in LOLF to obtain a specific reliability level. While power systems are designed to minimize LOLP and EENS, this is constrained by the total cost: investment cost, operation and maintenance cost, and cost of customer interruption (CCI). This research considers Standalone Microgrid (SMG), also known as Autonomous Microgrid which only operates in off-grid mode and cannot be connected to wider electrical power system. When designing a 100 % renewable energy integrated SMGs, it is crucial to determine the cost-effective reliability level (CERL). The CERL occurs when the total cost is minimum. This research proposes an approach to calculate the CERL for a fully renewable SMG. An analytical formulation is proposed to represent the LOLR needed to obtain a specific reliability level as a function of the required size of reliability improvement alternatives. The CCI is evaluated using LOLF and EENS indices. Finally, the total cost of the SMG system is evaluated for each reliability level. Consequently, the total cost of the SMG system is expressed as a function of reliability levels, and the minimum value of total cost and the corresponding reliability level are evaluated. In this research, a Monte Carlo Simulation (MCS) approach is used to find hourly LOLF, considering 25 years (219,000 h) of SMG lifespan, regression analysis is used for an analytical formulation, and mixed integer linear programming (MILP) is used for the investment decision making based on a cost minimisation approach. The result demonstrates that the CERL of the SMG system evaluated in the case study is 98.71 %.

Challenges and recommendations for collecting and quantifying implementation costs in practice: a qualitative interview study

BackgroundThe cost of implementation is typically not accounted for in published economic evaluations, which determine the relative value for money of health innovations and are important for allocating scarce resources. Despite key papers outlining relevant implementation costs, they continue to be under reported in the literature and often not considered in practice. This study sought to understand and outline current practices for capturing the costs associated with implementation efforts, with examples from the digital health setting.MethodsA qualitative study of semi-structured interviews with purposefully sampled experts in implementation science, health economics and/or digital health was conducted. The interview guide was informed by a literature review and was pilot tested. Interviews were digitally recorded and transcribed. A hybrid inductive/deductive framework analysis was conducted using thematic analysis to elicit key concepts related to the research question.ResultsInterviews were conducted with sixteen participants with specialist expertise in implementation science (n = 8), health economics (n = 6), and/or digital health (n = 8). Five participants were experienced in more than one field. Four key themes were elicited from the data: difficulty identifying and collecting implementation cost data; variation in approaches for collecting implementation cost data; the value of implementation costs; and collaboration enables implementation costing. Broadly, while interviewees recognised implementation costs as important, only some costs were considered in practice likely due to the perceived ill-defined boundaries and inconsistencies in terminology. A variety of methods were used to collect and estimate implementation costs; the most frequent approach was staff time tracking. Multidisciplinary collaboration facilitated this process, but the burden of collecting the necessary data was also highlighted.ConclusionsIn current practice, standardised methods are not commonly used for data collection or estimation of implementation costs. Improved data collection through standardised practices may support greater transparency and confidence in implementation cost estimates. Although participants had industry exposure, most were also academic researchers and findings may not be representative of non-academic industry settings.

Current state and open issues of priming onion seeds

Relevance. In the context of climate change, onion cultivation has become a challenge and innovative solutions are needed to support breeders and seed producers as well as farmers, starting with critical issues of seed quality. Seed priming successfully improves seed viability, which leads to rapid and uniform germination and emergence of onion seedlings.Results. Priming onion seeds can improve viability, especially under unfavorable conditions such as low/high temperatures, reduced water availability and salinity. It is a simple, low-cost and low-risk intervention that can be a useful technology for farmers and have a positive impact on their livelihoods by increasing the rate of seed germination, increasing the rate of plant development, reducing harvest time and increasing yields. Although this method is common for radish, tomato, carrot and cabbage seeds, this method is less popular for onions. This review provides an up-to-date picture of the scientific and technological advances that have contributed to increasing seed germination and vigor in onion plants to date. For large-scale commercial use, optimal priming methods and conditions tailored to different varieties or seed lots will require further extensive experimental work. It cannot be denied that seed priming technology is characterized by ease of operation, low cost and high practical value in industrial and market contexts. It can be foreseen that this technology will have wider prospects in agricultural production and green building. In addition, seed priming can effectively restore or enhance seed viability and ensure successful retention of germplasm resources and subsequent development, especially for onion seeds that rapidly lose viability.

ANALISIS PENGENDALIAN PERSEDIAAN SIMPLISIA PRODUK WEDANG UWUH (STUDI KASUS: CV SALAMA NUSANTARA)

CV Salama Nusantara had not conducted calculations regarding inventory, and there were still raw materials accumulating in the warehouse (overstock), which could result in a reduction in profit and an increase in company expenses. Additionally, it was observed that there was a shortage of raw materials (stockout), leading to production interruptions and the company incurring higher costs for reordering in smaller quantities. This research aimed to understand the inventory system when using ABC and EOQ methods and the difference in Total Inventory Cost (TIC) values between the company’s and EOQ methods The study showed that the ABC method in the simplisia inventory system classified category A with 66.58% of the investment value for one type of simplisia, requiring greater control compared to categories B and C. The use of EOQ for ginger simplisia resulted in the highest EOQ value of 134.72 kg with an ordering frequency of 7 times. The comparison of Total Inventory Cost (TIC) for simplisia such as red ginger, cardamom, sappanwood, cinnamon, cloves, and nutmeg showed that the EOQ method resulted in a lower TIC compared to the company’s policy, with differences of Rp2,365, Rp12,973, Rp14,116, Rp65,494, Rp4,768, Rp16,055, and Rp66,048, respectively.

Cost-effectiveness of finerenone added to standard of care for patients with type 2 diabetes-related chronic kidney disease in the United States.

To examine the cost-effectiveness of adding finerenone to standard of care (SoC) for treating type 2 diabetes mellitus (T2DM)-related chronic kidney disease (CKD) in the United States. Based on the clinical data analysed by FIDELITY, we referenced the validated FINE-CKD model (Markov model) to evaluate the cost-effectiveness of SoC versus SoC + finerenone from the perspective of US payers. The model was cycled for 35 years in 4-month cycles, with cost and utility values derived from the published literature. The primary outcomes were incremental cost-effectiveness ratio (ICER) and quality-adjusted life years (QALYs). Deterministic and probabilistic sensitivity analyses were conducted to assess the robustness of the base-case results. The treatment strategy of finerenone plus SoC led to gains of 6.95 QALYs and had a lifetime cost of $491 745.31. Compared to SoC, that strategy yielded 0.48 more QALYs at an added cost of $65 305.72. The ICER for finerenone was $135 257.06 per QALY, which is below the willingness-to-pay threshold of United States ($150 000/QALY). The results were sensitive to the hazard ratios associated with the efficacy of finerenone and its cost. Probabilistic sensitivity analyses showed that the probability that finerenone plus SoC would be cost-effective was 57.6%. For patients with T2DM-related CKD, adding finerenone to SoC may be a cost-effective option in the United States. Reasonable price reductions for finerenone could potentially benefit more patients.

Emerging cost-time Pareto front for diffusion with stochastic return

Abstract Resetting, in which a system is regularly returned to a given state after a fixed or random duration, has become a useful strategy to optimize the search performance of a system. While earlier theoretical frameworks focused on instantaneous resetting, wherein the system is directly teleported to a given state, there is a growing interest in physical resetting mechanisms that involve a finite return time. However employing such a mechanism involves cost and the effect of this cost on the search time remains largely unexplored. Yet answering this is important in order to design cost-efficient resetting strategies. Motivated from this, we present a thermodynamic analysis of a diffusing particle whose position is intermittently reset to a specific site by employing a stochastic return protocol with external confining trap. We show for a family of potentials U R ( x ) ∼ | x | m with m > 0, it is possible to find optimal potential shape that minimises the expected first-passage time for a given value of the thermodynamic cost, i.e. mean work. By varying this value, we then obtain the Pareto optimal front, and demonstrate a trade-off relation between the first-passage time and the work done.

Investigating the Future of Freight Transport Low Carbon Technologies Market Acceptance across Different Regions

Fighting climate change has become a major task worldwide. One of the key energy sectors to emit greenhouse gases is transportation. Therefore, long term strategies all over the world have been set up to reduce on-road combustion emissions. In this context, the road freight sector faces significant challenges in decarbonization, driven by its limited availability of low-emission fuels and commercialized zero-emission vehicles compared with its high energy demand. In this work, we develop the Mobility and Energy Transportation Analysis (META) Model, a python-based optimization model to quantify the impact of transportation projected policies on freight transport by projecting conventional and alternative fuel technologies market acceptance as well as greenhouse gas (GHG) emissions. Along with introducing e-fuels as an alternative refueling option for conventional vehicles, META investigates the market opportunities of Mobile Carbon Capture (MCC) until 2050. To accurately assess this technology, a techno-economic analysis is essential to compare MCC abatement cost to alternative decarbonization technologies such as electric trucks. The novelty of this work comes from the detailed cost categories taken into consideration in the analysis, including intangible costs associated with heavy-duty technologies, such as recharging/refueling time, cargo capacity limitations, and consumer acceptance towards emerging technologies across different regions. Based on the study results, the competitive total cost of ownership (TCO) and marginal abatement cost (MAC) values of MCC make it an economically promising alternative option to decarbonize the freight transport sector. Both in the KSA and EU, MCC options could reach greater than 50% market shares of all ICE vehicle sales, equivalent to a combined 35% of all new sales shares by 2035.

Cost-effectiveness analysis of selpercatinib versus chemotherapy and pembrolizumab in the first-line treatment of rearranged during transfection fusion-positive non-small cell lung cancer in the United States.

Although selpercatinib has shown clinical benefits for rearranged during transfection (RET) fusion-positive non-small cell lung cancer (NSCLC), its cost-effectiveness requires further evaluation. This study aimed to evaluate the cost-effectiveness of selpercatinib versus chemotherapy and pembrolizumab in the first-line treatment of RET fusion-positive NSCLC from the perspective of the United States (US) payer. A partitioned survival model was developed based on data from the LIBRETTO-431 trial. Cost and utility values for the health state were obtained from database data or published literature. The measured outcomes included quality-adjusted life-years (QALYs) and the incremental cost-effectiveness ratio (ICER). One-way sensitivity analysis and probabilistic sensitivity analyses (PSA) were conducted to assess the uncertainty of the model. Selpercatinib increased QALYs in patients with RET fusion-positive NSCLC by 0.90 compared to chemotherapy plus pembrolizumab, with an additional cost of $542,517.45, resulting in an ICER of $603,286.49/QALY, which exceeded the willingness-to-pay (WTP) threshold ($150,000) in the US. One-way sensitivity analysis suggested that the utility of progressed disease, the utility of progression-free survival, the price of selpercatinib, the discount, the price of pemetrexed, and the price of pembrolizumab had the greatest influence on the cost- effectiveness analysis process. In the PSA, 99.9% of the scatter points were distributed above the US WTP threshold of $150,000. From the perspective of the US payer, selpercatinib is not cost-effective compared to chemotherapy and pembrolizumab for first-line treatment in patients with RET fusion-positive NSCLC.

Optimizing a Hybrid Wind-Solar-Biomass System with Battery and Hydrogen Storage Using Generic Algorithm-Particle Swarm Optimization for Performance Assessment

This paper investigates the optimal design of a hybrid renewable energy system, integrating wind turbines, solar photovoltaic systems, biomass, and battery and hydrogen storage to ensure a reliable energy supply at the lowest annual cost for a residential load in Kern County, USA. The hybrid generic algorithm particle swarm optimization (GAPSO) algorithm was adopted to determine the optimal configuration of parameters and cost-effectiveness, considering technical, economic, environmental, and social performance indicators. The generic algorithm (GA) and particle swarm optimization (PSO) validate the effectiveness of the proposed technique, showcasing its efficiency in system optimization. The findings indicate that GAPSO outperforms GA and PSO due to its rapid convergence, lowest final fitness value, and stable optimization process. The hybrid GAPSO's performance, combined with the different capacities of wind turbines (4,561 kW), solar PV (8,480 kW), biomass (2,261 kW), battery banks (8,000 kWh), and fuel cells (2,392 kW), resulted in an annual cost of $6,239,193; energy cost and net present value of $0.48/kWh and $101,333,937. The system maintained a supply loss of 0.8%, achieved an availability index of 99.2%, a renewable energy fraction of 88.87%, GHGs emission of 953615 kg, land use of 3842875 m2, and water consumption 528678 L respectively. GAPSO achieved a 2.17% and 0.01% improvement in cost-effectiveness and 11.11% increase in reliability compared to GA and PSO.