This study aimed to understand and appraise the approaches taken to handle the complexities of a multisystem disease in published decision-analytic model-based economic evaluations of treatments for SLE. A systematic review was conducted to identify all published model-based economic evaluations of treatments for SLE. Treatments that were considered for inclusion comprised antimalarial agents, immunosuppressive therapies, and biologics including rituximab and belimumab. Medline and Embase were searched electronically from inception until September 2018. Titles and abstracts were screened against the inclusion criteria by two reviewers; agreement between reviewers was calculated according to Cohen's κ. Predefined data extraction tables were used to extract the key features, structural assumptions and data sources of input parameters from each economic evaluation. The completeness of reporting for the methods of each economic evaluation was appraised according to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. Six decision-analytic model-based economic evaluations were identified. The studies included azathioprine (n=4), mycophenolate mofetil (n=3), cyclophosphamide (n=2) and belimumab (n=1) as relevant comparator treatments; no economic evaluation estimated the relative cost-effectiveness of rituximab. Six items of the CHEERS statement were reported incompletely across the sample: target population, choice of comparators, measurement and valuation of preference-based outcomes, estimation of resource use and costs, choice of model, and the characterisation of heterogeneity. Complexity in the diagnosis, management and progression of disease can make decision-analytic model-based economic evaluations of treatments for SLE a challenge to undertake. The findings from this study can be used to improve the relevance of model-based economic evaluations in SLE and as an agenda for research to inform future health technology assessment and decision-making.
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http://dx.doi.org/10.1136/lupus-2019-000350 | DOI Listing |
Front Plant Sci
January 2025
College of Big Data, Yunnan Agricultural University, Kunming, China.
Introduction: Weeds are a major factor affecting crop yield and quality. Accurate identification and localization of crops and weeds are essential for achieving automated weed management in precision agriculture, especially given the challenges in recognition accuracy and real-time processing in complex field environments. To address this issue, this paper proposes an efficient crop-weed segmentation model based on an improved UNet architecture and attention mechanisms to enhance both recognition accuracy and processing speed.
View Article and Find Full Text PDFWater Res X
May 2025
National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Engineering Research Center of Beijing, Beijing University of Technology, Beijing 100124, PR China.
Although the treatment of sludge with free nitrous acid can effectively recover short chain fatty acids, the feasibility of sequential nitrite reduction and methane recovery without acidic pH adjustment is still scarcely studied. Therefore, this study aimed to provide insights into the effect of nitrite at different levels on nitrite reduction and methane production. The results showed that the nitrite concentrations of 100, 200, 400 and 800 mg/L were completely reduced in 1, 2, 2 and 4 days, respectively.
View Article and Find Full Text PDFHeliyon
January 2025
Institute of Statistical Research and Training, University of Dhaka, Bangladesh.
This paper examines the current state of food insecurity in Bangladesh and its socio-economic drivers using data from the latest Household Income and Expenditure Survey (HIES 2022). Unlike previous studies that relied on less precise measures of food insecurity, such as food expenditure, diversity, and calorie intake, this study employs the internationally recognized Food Insecurity Experience Scale (FIES) and Rasch model-based thresholds to classify households as food secure or insecure. Multilevel logistic regression is used to identify significant predictors of moderate and severe food insecurity, considering the hierarchical structure of the data, with households nested within geographical clusters.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan 430048, China.
Tea bud localization detection not only ensures tea quality, improves picking efficiency, and advances intelligent harvesting, but also fosters tea industry upgrades and enhances economic benefits. To solve the problem of the high computational complexity of deep learning detection models, we developed the Tea Bud DSCF-YOLOv8n (TBF-YOLOv8n)lightweight detection model. Improvement of the Cross Stage Partial Bottleneck Module with Two Convolutions(C2f) module via efficient Distributed Shift Convolution (DSConv) yields the C2f module with DSConv(DSCf)module, which reduces the model's size.
View Article and Find Full Text PDFFoods
January 2025
Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, 12 South Avenue, Zhongguancun, Beijing 100081, China.
Objective evaluation and in-depth systematic analysis of the effectiveness of implementing a grain support policy series represent an important entry point for improving incentives to grow food, improving grain production support and protection systems, and guaranteeing national food security. Thus, we collected and organized grain support policies during the study period according to the government work reports of 31 provinces in China from 2001 to 2022 and applied a two-way fixed-effects model based on the variables constructed using textual analysis to further explore the effects of a range of grain support policies on grain production gains. The conclusions are as follows: (1) grain support policies significantly contributed to an increase in grain production; (2) grain production gains from grain support policies are more pronounced in less industrialized and disaster-affected areas; (3) a mechanism analysis showed that grain support policies enhanced grain production by expanding the scale of food cultivation, upgrading agricultural mechanization, and strengthening soil erosion control; and (4) further analysis showed that grain support policies increased pesticide use.
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