Radio-chemotherapy (RCT) is the primary treatment of anal cancer (AC). However, the role and the optimal total dose of a radiation boost is still unclear. No randomized controlled trials nor systematic reviews have been performed to analyze the efficacy of brachytherapy (BRT) as boost in AC. Therefore, we performed this systematic review based on PRISMA methodology to establish the role of BRT boost in AC. A systematic search of the bibliographic databases: PubMed, Scopus, and Cochrane library from the earliest possible date through January 31, 2018 was performed. At least one of the following outcomes: local control (LC), loco-regional control (LRC), overall survival (OS), disease-free survival (DFS), or colostomy-free survival (CFS) had to be present for inclusion in this systematic review in patients receiving a BRT boost. Data about toxicity and sphincter function were also included. Ten articles fulfilled the inclusion criteria. All the studies had retrospective study design. All studies were classified to provide a level of evidence graded as 3 according to SIGN classification. Median 5-year LC/LRC, CFS, DFS, and OS were: 78.6% (range, 70.7-92.0%), 76.1% (range, 61.4-86.4%), 75.8% (range, 65.9-85.7%), and 69.4% (63.4-82.0%), respectively. The reported toxicities were acceptable. RCT is the treatment cornerstone in AC. High-level evidences from studies on BRT boost in AC are lacking. Further studies should investigate: efficacy of BRT boost in comparison to no boost and to external beam boost, patients who can benefit from this treatment intensification, and optimal radiation dose.
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http://dx.doi.org/10.5114/jcb.2018.76884 | DOI Listing |
J Environ Manage
December 2024
School of Geoscience and Technology, Southwest Petroleum University, Chengdu, 610500, China. Electronic address:
Karstification can reduce the CO concentration in the atmosphere/soil. Accurate estimation of karst carbon sinks is crucial for the study of global climate change. In this study, the Lijiang River Basin was taken as the research area.
View Article and Find Full Text PDFSci Total Environ
December 2024
College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, China.
Polycyclic aromatic hydrocarbons (PAHs) are widespread organic pollutants that pose significant health risks due to their bioaccumulation in the biota. This study examines the global distribution of PAHs in biota, identifies key factors influencing using boosted regression tree (BRT) models, analyzes their transfer through trophic magnification factors (TMF), and evaluates health risks using the EPA risk assessment model. Research on PAHs has grown from 1978 to 2023, peaking in 2021, with 171 out of 241 studies (71.
View Article and Find Full Text PDFPeerJ
December 2024
Departamento de Zoología, Instituto de Biología, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Ecological niche modeling (ENM) is a valuable tool for inferring suitable environmental conditions and estimating species' geographic distributions. ENM is widely used to assess the potential effects of climate change on species distributions; however, the choice of modeling algorithm introduces substantial uncertainty, especially since future projections cannot be properly validated. In this study, we evaluated the performance of seven popular modeling algorithms-Bioclim, generalized additive models (GAM), generalized linear models (GLM), boosted regression trees (BRT), Maxent, random forest (RF), and support vector machine (SVM)-in transferring ENM across time, using Mexican endemic rodents as a model system.
View Article and Find Full Text PDFInt Immunopharmacol
January 2025
Department of General Practice, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing 400037, China. Electronic address:
Objective: This study aimed to screen an immune-related gene (IRG) panel and develop a novel approach for diagnosing pulmonary arterial hypertension (PAH) utilizing bioinformatics and machine learning (ML).
Methods: Gene expression profiles were retrieved from the Gene Expression Omnibus (GEO) database to identify differentially expressed immune-related genes (IRG-DEGs). We employed five machine learning algorithms-LASSO, random forest (RF), boosted regression trees (BRT), XGBoost, and support vector machine recursive feature elimination (SVM-RFE) to identify biomarkers derived from IRG-DEGs associated with the diagnosis of PAH, incorporating them into the IRG-DEGs panel.
Environ Sci Pollut Res Int
December 2024
Forest Research Centre, Associate Laboratory TERRA, School of Agriculture, University of Lisbon, Lisbon, Portugal.
Difficulties have hampered bioassessment in southern European rivers due to limited reference data and the unclear impact of multiple interacting stressors on plant communities. Predictive modelling may help overcome this limitation by aggregating different pressures affecting aquatic organisms and showing the most influential factors. We assembled a dataset of 292 Mediterranean sampling locations on perennial rivers and streams (mainland Portugal) with macrophyte and environmental data.
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