A multi-criteria decision analysis approach for ranking the performance of CMIP6 models in reproducing precipitation patterns over Abaya-Chamo sub-basin, Ethiopia.

The most suitable multi-model ensemble set of general circulation models is used to reduce the uncertainty associated with GCM selection and improve the accuracy of the model simulations. This study evaluated the performance of 20 global climate models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in reproducing precipitation patterns over the Abaya-Chamo Sub-basin, Ethiopia. For the validation and selection of the models' capabilities, datasets from the Climate Hazards Infrared Precipitation with Stations (CHIRPS) were used after comparing them with ground observational datasets. The objective was to identify the most suitable multi-model ensemble (MME) of a subset of CMIP6 GCMs to capture the rainfall for the 1981-2014 period over the region. Climate Data Operators (CDOs) were used in climate data processing and extraction, and the Mann-Kendall test and Theil-Sen slope estimator methods were utilized to analyze the trends of the CMIP6 simulations. Four statistical metrics (Nash-Sutcliffe coefficient, percent bias, normalized root mean square error, and Kling-Gupta efficiency) were used to further assess the performance of the models. A multi-criteria decision analysis approach, namely, the technique for order preferences by similarity to an ideal solution (TOPSIS) method, was used to obtain the overall ranks of CMIP6 models and to select the best-performing CMIP6 model in the region. The results indicated that CHIRPS and most of the CMIP6 simulations generally reproduced bimodal precipitation patterns over the region. The CESM2-WACCM, NorESM2-MM, NorESM2-LM, and NorESM2-LM models performed better than the other models in reproducing seasonal patterns for the winter, spring, summer, and autumn seasons, respectively. On the other hand, FGOALS-f3-L revealed the trends of the reference datasets for all seasons. In terms of the NSE, PB, NRMSE, and KGE metrics, EC-Earth3-C, EC-Earth3, EC-Earth3-C, and EC-Earth-C, respectively, were considered good at representing the observed features of precipitation over the region. EC-Earth3-C,EC-Earth3, EC-Earth3-Veg-LR, ACCESS-CM2, MPI-ESM1-2-HR, and CNRM-CM6-1-HR exhibited the best performances in the Abaya-Chamo Sub-basin.

Uncertainty management for In Silico screening of reversed-phase liquid chromatography methods for small compounds.

The process of developing new reversed-phase liquid chromatography methods can be both time-consuming and challenging. To meet this challenge, statistics-based strategies have emerged as cost-effective, efficient and flexible solutions. In the present study, we use a Bayesian response surface methodology, which takes advantage of the knowledge of the pKa values of the compounds present in the analyzed sample to model their retention behavior. A multi-criteria decision analysis (MCDA) was then developed to exploit the uncertainty information inherent in the model distributions. This strategic approach is designed to integrate seamlessly with quantitative structure retention relationship (QSRR) models, forming an initial in-silico screening phase. Of the two methods presented for MCDA, one showed promising results. The method development process was carried out with the optimization phase, generating a design space that corroborates the results of the selection phase.

[Benefit-risk assessment of three oral Chinese patent medicines for activating blood and eliminating mass in treating primary liver cancer based on network Meta-analysis and multi-criteria decision analysis].

Network Meta-analysis and multi-criteria decision analysis(MCDA) model were performed to evaluate the benefit-risk of Compound Cantharis Capsules, Huisheng Oral Solution, and Jinlong Capsules in the adjuvant treatment of primary liver cancer(PLC). The randomized controlled trial(RCT) of Compound Cantharis Capsules, Huisheng Oral Solution, and Jinlong Capsules in treating PLC were retrieved from CNKI, Wanfang, VIP, Web of Science, PubMed, and Cochrane Library. R 4.2 was employed to conduct a network Meta-analysis, on the basis of which the effect values of the three medicines were obtained by indirect comparison. MCDA was performed to establish the value tree based on the benefit-risk indexes. Hiview 3.2 was used to calculate the benefit values, risk values, and benefit-risk values of the three medicines in treating PLC, and a sensitivity analysis was carried out to evaluate the robustness of the results. Oracle Crystal Ball 11.1 was employed to optimize the evaluation results by Monte Carlo simulation. A total of 39 RCTs were included. The results showed that Compound Cantharis Capsules, Huisheng Oral Solution, and Jinlong Capsules combined with transcatheter arterial chemoembolization(TACE) had the benefit values of 45, 51 and 45, the risk values of 59, 47, and 41, and the benefit-risk values of 52, 49, and 43, respectively. The benefit-risk differences and [95%CI] of Compound Cantharis Capsules vs Huisheng Oral Solution, Compound Cantharis Capsules vs Jinlong Capsules, and Huisheng Oral Solution vs Jinlong Capsules were 3.00[-13.09, 21.82], 9.00[-4.39, 24.62], and 6.00[-8.84, 20.28], respectively. Based on the results of MCDA, Huisheng Oral Solution, Jinlong Capsules, and Compound Cantharis Capsules combined with TACE had the greatest benefit, the greatest risk, and the best overall benefit, respectively. Considering the efficacy and safety, the priority of the three oral Chinese patent medicines combined with TACE for treating PLC followed the trend of Compound Cantharis Capsules, Huisheng Oral Solution, and Jinlong Capsules.

Alignment of port policy to the context of the Physical Internet.

The Physical Internet (PI) is a paradigm-changing and technology-driven vision, which is expected to significantly impact the development of the freight transport and logistics (FTL) system of today. However, the development of the FTL system towards the PI creates much uncertainty for its current stakeholders. Ports are one of those stakeholders that are expected to be profoundly affected by these developments. However, research that focuses on port policy, under the uncertain developments towards the PI, is still lacking. By providing port authorities with insights and recommendations on robust policy areas, we address this void in literature. We conduct a scenario analysis in combination with multi-criteria decision analysis (MCDA) to determine the importance of port performance indicators and policy areas in different scenarios. The most significant, uncertain, and orthogonal factors for the development of the PI are technological development and institutional development. We find that for a proper alignment with the PI vision, in three out of four scenarios, ports should prioritize the implementation of digital solutions and standards, as opposed to an infrastructure focused policy.

Development of a decision support tool to compare diagnostic strategies for establishing the herd status for infectious diseases: An example with Salmonella Dublin infection in dairies.

The diagnosis of infectious diseases at herd level can be challenging as different stakeholders can have conflicting priorities. The current study proposes a "proof of concept" of an approach that considers a reasonable number of criteria to rank plausible diagnostic strategies using multi-criteria decision analysis (MCDA) methods. The example of Salmonella Dublin diagnostic in Québec dairy herds is presented according to two epidemiological contexts: (i) in herds with no history of S. Dublin infection and absence of clinical signs, (ii) in herds with a previous history of infection, but absence of clinical signs at the moment of testing. Multiple multiparty exchanges were conducted to determine: 1) stakeholders' groups; 2) the decision problem; 3) solutions to the problem (options) or diagnostic strategies to be ordered; 4) criteria and indicators; 5) criteria weights; 6) the construction of a performance matrix for each option; 7) the multi-criteria analyses using the visual preference ranking organization method for enrichment of evaluations approach; 8) the sensitivity analyses, and 9) the final decision. A total of nine people from four Québec's organizations (the dairy producers provincial association along with the DHI company, the ministry of agriculture, the association of veterinary practitioners, and experts in epidemiology) composed the MCDA team. The decision problem was "What is the optimal diagnostic strategy for establishing the status of a dairy herd for S. Dublin infection when there are no clinical signs of infection?". Fourteen diagnostic strategies composed of the three following parameters were considered: 1) biological samples (bulk tank milk or blood from 10 heifers aged over three months); 2) sampling frequencies (one to three samples collection visits); 3) case definitions to conclude to a positive status using imperfect milk- or blood-ELISA tests. The top-ranking diagnostic strategy was the same in the two contexts: testing the bulk tank milk and the blood samples, all samples collected during one visit and the herd being assigned a S. Dublin positive status if one sample is ELISA-positive. The final decision favored the top-ranking option for both contexts. This MCDA approach and its application to S. Dublin infection in dairy herds allowed a consensual, rational, and transparent ranking of feasible diagnostic strategies while taking into account the diagnostic tests accuracy, socio-economic, logistic, and perception considerations of the key actors in the dairy industry. This promising tool can be applied to other infectious diseases that lack a well-established diagnostic procedure to define a herd status.

Novel approach evaluating powdered raw and hydrothermally treated syenite as stonemeal for tropical environments: Potential effects on groundwater quality and agricultural suitability.

Soluble fertilizers, particularly potash, are often prohibitively expensive or unavailable in Africa. Consequently, alternatives such as powdered silicate rocks, both raw and hydrothermally treated, are being explored as potential solutions, especially for acidic tropical soils. This study investigates the possible impacts of these rocks (syenite) on groundwater quality, which is a critical factor for agricultural activities. The powdered raw material underwent chemical and mineralogical characterization, including X-ray fluorescence and X-ray diffraction, followed by quantitative evaluation of materials by scanning electron microscopy. Both raw and 46 hydrothermally treated materials were subjected to sequential leaching cycles (1, 24, and 192 h) using deionized water, and the resulting leachates were analyzed by inductively coupled plasma atomic emission spectroscopy. Parameters such as electrical conductivity, total dissolved solids, soluble sodium percentage, sodium adsorption ratio, magnesium hazard, Kelly's ratio, and permeability index were also evaluated. Results from the 47 leachates indicated that 64 % of the samples exhibited excellent to acceptable water quality for irrigation purposes across all parameters. Conversely, 6 % to 13 % fell into the doubtful category, and 2 % to 24 % were classified as unsuitable. Consistency index and ratios of approximately 0.07 and 0.042, respectively, were determined using multi-criteria decision analysis (analytic hierarchy process: AHP), confirming the coherence of the decision and pairwise comparison matrix. The weighted coefficients for each criterion ranged from 0.06 to 0.2. Consequently, the optimal sample (Treatment 23) was identified, showing a hydrothermal temperature of 176 °C, a time of 3.9 h, a normality of 4.62, and a liquid-solid ratio of 0.24. This treatment met all high-water quality standards, including low salinity and sodium hazard, as corroborated by the US salinity laboratory and Wilcox diagrams. Furthermore, due to their nutrient release, low concentration of toxic elements, and effective buffering capacity (pH âˆ¼ 10.6), these powdered syenites are suitable for application in acidic soils.

Bottom-up formulations for the multi-criteria decision analysis of oil and gas pipeline decommissioning in the North Sea: Brent field case study.

Many Oil and Gas (O&G) fields in the North Sea have produced their economically recoverable reserves and have entered the decommissioning phase or are close to cessation of production. The subsequent O&G decommissioning process involves a range of stakeholders with specific interests and priorities. This range of inputs to the process highlights the necessity for the development of multi-criteria decision frameworks to help guide the decision-making process. This study presents bottom-up formulations for the economic, environmental, and safety risk criteria to support the multi-criteria decision analysis within the Comparative Assessment (CA) of O&G pipeline decommissioning projects in the North Sea. The approach adapts current guidelines in the O&G industry and considers a range of parameters to provide estimations for the costs, energy usage, greenhouse gas emissions, and safety risks. To verify the effectiveness of the proposed bottom-up formulations, the longest oil export pipeline in the Brent field, PL001/N0501 is selected as a case study. The numerical results revealed the consistency of the results obtained from the proposed approach with those reported in the technical documents by industry. In most cases, the formulations provide estimates with less than 10% differences for the costs, energy usage, emissions, and safety risks. Based on the proposed multi-criteria formulations, the study also presents the use of an immersive decision-making environment within a marine simulator system to help inform the decision-making process by stakeholders.

Multi-Criteria Decision Analysis (MCDA) for sustainability assessment in food sector. A systematic literature review on methods, indicators and tools.

In the last decades, several studies have highlighted the significant impacts of the food sector. Therefore, enhancing sustainability within this sector has become of paramount importance. A crucial step towards achieving this goal involves the definition and implementation of effective sustainability metric and measurements. In this regard, the adoption of multi-criteria decision analysis (MCDA) methods can be seen as one of the most suitable and promising approach to comprehensively capture the complex and broad-ranging effects of agricultural practices and food supply chains. In such context, a systematic review of the scientific literature on multi-criteria approaches and tools for measuring the sustainability of food supply chains (harvest and post-harvest stages) has been carried out, resulting in the selection and analysis of 42 articles. To delve into the selected articles, three main areas of focus have been identified. The first about MCDA methods and their features, revealing the most adopted methods for sustainability assessments of food supply chains. The second, focusing on the participatory approach, led to the definition of a stakeholder's engagement map, highlighting the typology of stakeholders involved, the reasons of their involvement and engagement methods. Lastly, the third focus is related to the analysis and classification of indicators adopted in each study and the sustainability dimensions to which they refer to. The results of the present review study provide a comprehensive overview of the essential aspects to be considered when developing a MCDA for sustainability assessment in the food sector, serving as a valuable resource for both scholars and practitioners.

An ecotourism suitability index for a world heritage city using GIS-multi criteria decision analysis techniques.

The concept of ecotourism has experienced a significant surge in popularity over the past two decades, primarily driven by the multitude of adverse impacts associated with mass tourism. The objective of the study was to develop a comprehensive ecotourism suitability index to guide policymakers in implementing tourism development policies. Given the considerable appeal of the study area to both local and international tourists, it is essential to conduct a systematic evaluation to pinpoint suitable areas for ecotourism development. This necessity arises from the study area's placement within a fragile ecosystem and its proximity to a UNESCO World Heritage site. We employed a Geographic Information Systems (GIS) integrated environment coupled with a fuzzy Multi-Criteria Decision Analysis (MCDA) methodology. The GIS-MCDA integrated framework leverages the Analytic Hierarchy Process (AHP) and a weighted linear combination that seeks to amalgamate many features and criteria to assess ecotourism potential by integrating 20 criteria into six separate categories: landscape, topography, accessibility, climate, forest and wildlife, and negative factors. Weights were allocated to each criterion and factor based on the expert's opinions of their impact on the development of ecotourism. The final ecotourism suitability index comprised five unique classes: very high, high, moderate, less, and not suitable. Results reveal that out of the total areas, 45.4 % (259 km2) are within the high and very high suitable classes. The sensitivity analysis suggested that ecotourism potentials are more favorable to forest and accessibility variables. The generated index can be utilized as a road map since validation verified a 64 % accuracy. Given the dearth of earlier research, this study provides vital support for the development of sustainable ecotourism projects in the study area.

The application of multi-criteria decision analysis in evaluating the value of drug-oriented intervention: a literature review.

Objectives: Multi-Criteria Decision Analysis (MCDA) has gained increasing attention in supporting drug risk-benefit assessment, pricing and reimbursement, as well as optimization of clinical interventions. The objective of this study was to systematically collect and categorize evaluation criteria and techniques of weighting and scoring of MCDA for drug value assessment. Methods: A systematic review of the literature was conducted across seven databases to identify articles utilizing the MCDA frameworks for the evaluation of drug value. Evaluation criteria mentioned in the included studies were extracted and assigned to 5 dimensions including clinical, economic, innovative, societal and humanistic value. A descriptive statistical analysis was performed on the identified drug value evaluation criteria, as well as the weighting and scoring techniques employed. The more a criterion or technique were mentioned in articles, the more important we consider it. Results: Out of the 82 articles included, 111 unique criteria were identified to evaluate the value of drug. Among the 56 unique criteria (448 times) used to measure clinical value, the most frequently mentioned were "comparative safety/tolerability" (58 times), "comparative effectiveness/efficacy" (56 times), "comparative patient-perceived health/patient reported outcomes" (37 times), "disease severity" (34 times), and "unmet needs" (25 times). Regarding economic value measurement, out of the 20 unique criteria (124 times), the most frequently utilized criteria were "cost of intervention" (17 times), "comparative other medical costs" (16 times), and "comparative non-medical costs" (18 times). Out of the 10 criteria (18 times) for assessing innovative value, "a novel pharmacological mechanism" was the most frequently mentioned criterion (5 times). Among the 22 criteria (73 times) used to measure societal value, "system capacity and appropriate use of intervention" was the most frequently cited criterion (14 times). Out of the 3 criteria (15 times) utilized to measure humanistic value, "political/historical/cultural context" was the most frequently mentioned criterion (9 times). Furthermore, 11 scoring and 11 weighting techniques were found from various MCDA frameworks. "Swing weighting" and "a direct rating scale" were the most frequently used techniques in included articles. Conclusion: This study comprehensively presented the current evaluation dimensions, criteria, and techniques for scoring and weighting in drug-oriented MCDA articles. By highlighting the frequently cited evaluation criteria and techniques for scoring and weighting, this analysis will provide a foundation to reasonably select appropriate evaluation criteria and technique in constructing the MCDA framework that aligns with research objectives.

Value contribution of blood-based neurofilament light chain as a biomarker in multiple sclerosis using multi-criteria decision analysis.

Introduction: Multiple sclerosis (MS) is a chronic autoimmune demyelinating disease that represents a leading cause of non-traumatic disability among young and middle-aged adults. MS is characterized by neurodegeneration caused by axonal injury. Current clinical and radiological markers often lack the sensitivity and specificity required to detect inflammatory activity and neurodegeneration, highlighting the need for better approaches. After neuronal injury, neurofilament light chains (NfL) are released into the cerebrospinal fluid, and eventually into blood. Thus, blood-based NfL could be used as a potential biomarker for inflammatory activity, neurodegeneration, and treatment response in MS. The objective of this study was to determine the value contribution of blood-based NfL as a biomarker in MS in Spain using the Multi-Criteria Decision Analysis (MCDA) methodology. Materials and methods: A literature review was performed, and the results were synthesized in the evidence matrix following the criteria included in the MCDA framework. The study was conducted by a multidisciplinary group of six experts. Participants were trained in MCDA and scored the evidence matrix. Results were analyzed and discussed in a group meeting through reflective MCDA discussion methodology. Results: MS was considered a severe condition as it is associated with significant disability. There are unmet needs in MS as a disease, but also in terms of biomarkers since no blood biomarker is available in clinical practice to determine disease activity, prognostic assessment, and response to treatment. The results of the present study suggest that quantification of blood-based NfL may represent a safe option to determine inflammation, neurodegeneration, and response to treatments in clinical practice, as well as to complement data to improve the sensitivity of the diagnosis. Participants considered that blood-based NfL could result in a lower use of expensive tests such as magnetic resonance imaging scans and could provide cost-savings by avoiding ineffective treatments. Lower indirect costs could also be expected due to a lower impact of disability consequences. Overall, blood-based NfL measurement is supported by high-quality evidence. Conclusion: Based on MCDA methodology and the experience of a multidisciplinary group of six stakeholders, blood-based NfL measurement might represent a high-value-option for the management of MS in Spain.

Application of hybrid multi-criteria decision-making approach to analyze wastewater microalgae culture systems for bioenergy production.

Bioenergy generation from microalgae can significantly contribute to climate mitigation and renewable energy production. In this regard, several multi-criteria decision-making method were employed to prioritize appropriate microalgae culture system for bioenergy production. Entropy weight, Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were the employed MCDA method. Fourteen microalgae culture systems were selected as a case study, which contain teen monoculture and four dual-culture. Initially, through ans in-depth review of the literature and expert views, four categories total eight indicators were selected as the evaluation indices of the study, namely 1) Proliferation: Half growth cycle and Max growth rate,2) Biomass output: Bio-crude yield and Lipid yield, 3) Nutrient utilization: residual concentration of total Nitrogen and total Phosphorus, and, 4) Stability: coefficient of variation of Bio-crude yield and Lipid yield. The result indicated that "Pediastrum sp. & Micractinium sp." was identified as the most bioenergy potential microalgae culture system, and the evaluation results of entropy weight method and CRITIC method are similar. It is pertinent to note that 1)the entropy weight method exhibits lower sample size requirements, 2) the critic method excels when dealing with larger sample sizes, and 3) the TOPSIS method necessitates the incorporation of appropriate weighting methods to ensure credible results. In the application stage, the key indicators related to cost can be further included in the evaluation indices.

Setting a shared development agenda: prioritizing the sustainable development goals in the Dominican Republic with fuzzy-LMAW.

The sustainable development goals (SDGs) were established by the United Nations as an international call to eradicate poverty, safeguard the environment, and guarantee that everyone lives in peace and prosperity by 2030. The SDGs aim to balance growth and sustainability in three dimensions: social, economic and environmental. However, in the post-pandemic era, when resources for public development policies are scarce, nations face the problem of prioritizing which SDGs to pursue. A lack of agreement is one of the determinants of low performance levels of the SDGs, and multicriteria decision analysis tools can help in this task, which is especially relevant in developing countries that are falling behind in achieving the SDGs. To test the feasibility and appropriateness of one of these tools, the Fuzzy Logarithm Methodology of Additive Weights, we apply it to prioritize the SDGs in the Dominican Republic, to see if the priorities established are consistent. Seventeen experts were surveyed, and the main result was that Decent work and economic growth was the most important goal for the country. Our findings, consistent with the literature, show the path to similar applications in other developing countries to enhance performance levels in the achievement of the SDGs.

Development of the Emirates Multi-Criteria Decision Analysis Tool for Orphan Drugs.

Background The number of orphan drug approvals is currently increasing globally. This creates a significant burden on payers and healthcare systems. This study aimed to create a multi-criteria decision analysis (MCDA) tool for evaluating orphan drugs within the United Arab Emirates (UAE). The intended result of the tool is to provide evidence-based guidance to decision-makers in reimbursement and procurement decisions. Methods We conducted a literature search and local expert interviews to identify relevant preliminary criteria for the MCDA tool. Then we conducted a structured consensus-building session for healthcare experts and decision-makers in the UAE to develop the Emirati MCDA tool for orphan drugs. The experts voted for the criteria to be included in the tool and their ranking according to importance, as well as the weight of each criterion and its scoring function. To improve understanding and facilitate the voting process, experts were provided with a brief illustration of similar tools conducted in other countries before the voting sessions. Finally, the tool was developed in a Microsoft Excel sheet (Microsoft Corporation, Redmond, Washington, United States), and it was validated and tested based on real case studies, then it was fine-tuned accordingly based on the experts' discussions. The final tool was provided to the attendees to guide their decisions in the reimbursement and procurement of orphan drugs. Results The created tool provides a score for each analyzed orphan drug based on its value. Ten criteria were included in the final MCDA tool. These were cost-effectiveness (25.1% of the weight), magnitude of health gain (20.1%), availability of therapeutic alternative (14.3%), disease severity (11%), budget impact (7.9%), disease rarity (5.6%), strength of clinical evidence (5.6%), burden on households (4.5%), indication uniqueness (3.2%), and patients' age (2.6%). Conclusions Implementation of evidence-based healthcare necessitates assessing the fair value of each health technology. Addressing the high unmet medical needs and improving healthcare for patients with rare diseases are priorities within the UAE. The created Emirates MCDA tool for orphan drugs has the potential to help decision-makers implement value-based and evidence-based reimbursement decisions for orphan drugs.

Synthesis of relevant information around non-core domains to support Multi-Criteria Decision Analysis (MCDA) for decision making.

Countries fundamentally base macro and micro decision making in the field of health on economic considerations, the budgetary impact of technologies being a major criterion. Nevertheless, the value of the technology of interest and its dimensions are more complex if we seek to take decisions based on the value itself. The use of structured and explicit approaches that require the assessment of multiple criteria that reflect the dimensions of this value may significantly improve the quality of the decision making. Multi-criteria decision analysis (MCDA) is a complementary decision-making tool that is able to systematically incorporate dimensions or domains such as ethical, organisational, legal, environmental and social considerations, as well as costs and benefits of medical interventions, together with the distinct perspectives of the interested parties. The objective of this article is to propose the implementation of analysis of non-core domains, in reports of Health Technology Assessment (HTA) agencies/units. To assess the scientific evidence on MCDA techniques a systematic review was conducted using structured searches in biomedical databases and websites of various HTA organisations. A consensus group was held using the nominal group technique and involving users of healthcare services, providers, managers and academics. Complementary, a survey was sent to HTA agencies to ascertain the degree of implementation of MCDA in their methods. 42 articles reporting the use of non-core criteria for the assessment of health technologies were included in the analysis. From these articles, a total of 216 non-core criteria were retrieved and categorised into domains by the researchers, and of these, 56 were classified as socioeconomic, 59 as organisational, 10 as legal, 8 as environmental and 47 as ethical, while 36 were considered to relate to other domains. The consensus group, based on the 216 non-core criteria obtained from the systematic review, proposed, and defined 26 criteria that participants considered necessary for decision making in healthcare. The consensus group did not consider that any of the domains should be given more weight than others or that any individual criteria should dominate. These approaches can serve as a framework of reference for a well-structured systematic discussion concerning the basis of individual criteria and the evidence supporting them.

Application of Multi-Criteria Decision Analysis (MCDA) to Prioritize Real-World Evidence Studies for Health Technology Management: Outcomes and Lessons Learned by the Canadian Real-World Evidence for Value of Cancer Drugs (CanREValue) Collaboration.

Multi-criteria decision analysis (MCDA) is a value assessment tool designed to help support complex decision-making by incorporating multiple factors and perspectives in a transparent, structured approach. We developed an MCDA rating tool, consisting of seven criteria evaluating the importance and feasibility of conducting potential real-world evidence (RWE) studies aimed at addressing uncertainties stemming from initial cancer drug funding recommendations. In collaboration with the Canadian Agency for Drugs and Technologies in Health's Provincial Advisory Group, a validation exercise was conducted to further evaluate the application of the rating tool using RWE proposals varying in complexity. Through this exercise, we aimed to gain insight into consensus building and deliberation processes and to identify efficiencies in the application of the rating tool. An experienced facilitator led a multidisciplinary committee, consisting of 11 Canadian experts, through consensus building, deliberation, and prioritization. A total of nine RWE proposals were evaluated and prioritized as low (n = 4), medium (n = 3), or high (n = 2) priority. Through an iterative process, efficiencies and recommendations to improve the rating tool and associated procedures were identified. The refined MCDA rating tool can help decision-makers prioritize important and feasible RWE studies for research and can enable the use of RWE for the life-cycle evaluation of cancer drugs.

Quantitative Benefit-Risk Evaluation of Rivaroxaban in Patients After Peripheral Arterial Revascularization: The VOYAGER PAD Trial.

BACKGROUND: The VOYAGER PAD (Efficacy and Safety of Rivaroxaban in Reducing the Risk of Major Thrombotic Vascular Events in Subjects With Symptomatic Peripheral Artery Disease Undergoing Peripheral Revascularization Procedures of the Lower Extremities) trial compared rivaroxaban (2.5 mg twice a day) plus aspirin with aspirin alone in patients with symptomatic peripheral artery disease requiring endovascular or surgical limb revascularization, with 50% receiving clopidogrel background therapy. The New Drug Indication application includes benefit-risk assessments using clinical judgment to balance benefits against risks. During its review, the US Food and Drug Administration requested additional quantitative benefit-risk analyses with formal weighting approaches. METHODS AND RESULTS: Benefits and risks were assessed using rate differences between treatment groups (unweighted analysis). To account for clinical importance of the end points, a multi-criteria decision analysis was conducted using health state utility values as weights. Monte Carlo simulations incorporated statistical uncertainties of the event rates and utility weights. Intent-to-treat and on-treatment analyses were conducted. For unweighted intent-to-treat analyses, rivaroxaban plus aspirin would result in 120 (95% CI, -208 to -32) fewer events of the primary composite end point (per 10 000 patient-years) compared with aspirin alone. Rivaroxaban caused an excess of 40 (95% CI, 8-72) Thrombolysis in Myocardial Infarction major bleeding events, which was largely driven by nonfatal, nonintracranial hemorrhage Thrombolysis in Myocardial Infarction major bleeding events. For weighted analyses, rivaroxaban resulted in the utility equivalent of 13.7 (95% CI, -85.3 to 52.6) and 68.1 (95% CI, 7.9-135.7) fewer deaths per 10 000 patient-years (intent-to-treat and on-treatment, respectively), corresponding to probabilities of 64.4% and 98.7%, respectively, that benefits outweigh risks favoring rivaroxaban per Monte Carlo simulation. CONCLUSIONS: These analyses show a favorable benefit-risk profile of rivaroxaban therapy in the VOYAGER PAD trial, with findings generally consistent between the unweighted and weighted approaches.

Forest fire risk zoning based on fuzzy logic and analytical network process.

Forest fires have a significant impact on human life, property safety, and ecological environment. Deve-loping high-quality forest fire risk maps is beneficial for preventing forest fires, guiding resource allocation for firefighting, assisting in fire suppression efforts, and supporting decision-making. With a multi-criteria decision analysis (MCDA) method based on geographic information systems (GIS) and literature review, we assessed the main factors influencing the occurrences of forest fires in Youxi County, Fujian Province. We analyzed the importance of each fire risk factor using the analytic network process (ANP) and assigned weights, and evaluated the sub-standard weights using fuzzy logic assessment. Using ArcGIS aggregation functions, we generated a forest fire risk map and validated it with satellite fire points. The results showed that the areas classified as level 4 or higher fire risk accounted for a considerable proportion in Youxi County, and that the central and northern regions were at higher risk. The overall fire risk situation in the county was severe. The fuzzy ANP model demonstrated a high accuracy of 85.8%. The introduction of this novel MCDA method could effectively improve the accuracy of forest fire risk mapping at a small scale, providing a basis for early fire warning and the planning and allocation of firefighting resources.

An integrated new approach for optimizing rainwater harvesting system with dams site selection in the Dewana Watershed, Kurdistan Region, Iraq.

Water scarcity in Kurdistan-Iraq has become a crucial problem, particularly in semi-arid regions, as a result of severe droughts over the last decades. One potential solution to this water shortage is using rainwater harvesting (RWH) techniques. In this study, optimal sites of RWH in the Dewana watershed were identified using a combination of remote sensing (RS) and geographic information system (GIS), with multi-criteria decision analysis (MCDA) models, including analytical hierarchy process (AHP) and weighted sum method (WSM). Sixteen thematic layers are used. As a result of the AHP and WSM models, 236.89 km2 and 267.15 km2 were identified as highly suitable areas for RWH techniques in the suitability index map. They identified 13.06 km2 (5.55%) and 58 km2 (21.81%) as highly suitable for constructing dams in the dam site selection maps. The present study found that 11 proposed dam sites are suitable for dam construction. The weighted product model (WPM) was used to rank the proposed dam sites, with Dams #10 and #2 being the top-ranked sites. Accuracy assessment results indicated that the WSM model outperformed the AHP model with an overall accuracy rate of 50.5% and 52.78%, respectively. However, the AHP model demonstrated a higher receiver operating characteristic (ROC) and an area under the curve (AUC) score of 1.00, while the WSM model had an AUC of 0.78.

Towards circular economy indicators: Evidence from the European Union.

The European Union (EU) is moving towards sustainable development, and a key role is played by circular economy (CE) models geared towards reducing pressure on natural resources, generating jobs and fostering economic opportunities. Indicators are able to aggregate a variety of information and their use, through the use of multi-criteria decision analysis (MCDA), allows the performance of alternatives to be monitored. This work aims to calculate the performance of the EU27 in the years 2019 and 2020 according to 15 CE indicators available on Eurostat. The results of the Analytic Hierarchy process show that the greatest impact on circularity is determined by the category 'competitiveness and innovation', which together with the category 'global sustainability and resilience' accounts for two thirds of the overall weight. The MCDA results show that Belgium prevails in both the baseline and alternative scenarios, ahead of Italy and the Netherlands respectively. In general, circular policies see western European countries excel, while the performance of eastern European countries is weaker. The implications of this work highlight the three main barriers to the development of CE models: (i) illegal waste management; (ii) lack of knowledge and low level of investment in circular technologies and (iii) low distribution of value among stakeholders. In this way, resource management based on circularity will enable Europe to meet the challenges of sustainability with less dependence on imported raw materials.