Please use this identifier to cite or link to this item: https://hdl.handle.net/11000/34569
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dc.contributor.authorSarrio Sanz, Pau-
dc.contributor.authorMARTINESZ CAYUELAS, LAURA-
dc.contributor.authorLumbreras, Blanca-
dc.contributor.authorSánchez Caballero, Laura-
dc.contributor.authorPalazón-Bru, Antonio-
dc.contributor.authorGil-Guillén, Vicente F-
dc.contributor.authorGómez-Pérez, Luis-
dc.contributor.otherDepartamentos de la UMH::Salud Pública, Historia de la Ciencia y Ginecologíaes_ES
dc.contributor.otherDepartamentos de la UMH::Medicina Clínicaes_ES
dc.date.accessioned2025-01-15T20:15:22Z-
dc.date.available2025-01-15T20:15:22Z-
dc.date.created2022-05-25-
dc.identifier.citationEur J Clin Invest . 2022 Oct;52(10):e13822es_ES
dc.identifier.issn1365-2362-
dc.identifier.urihttps://hdl.handle.net/11000/34569-
dc.description.abstractIntroduction: To identify risk-predictive models for bladder-specific cancer mortality in patients undergoing radical cystectomy and assess their clinical utility and risk of bias. Methods: Systematic review (CRD42021224626:PROSPERO) in Medline and EMBASE (from their creation until 31/10/2021) was screened to include articles focused on the development and internal validation of a predictive model of specific cancer mortality in patients undergoing radical cystectomy. CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) and Prediction model Risk Of Bias ASsessment Tool (PROBAST) were applied. Results: Nineteen observational studies were included. The main predictors were sociodemographic variables, such as age (18 studies, 94.7%) and sex (17, 89.5% studies), tumour characteristics (TNM stage (18 studies, 94.7%), histological subtype/ grade (15 studies, 78.9%), lymphovascular invasion (10 studies, 52.6%) and treatment with chemotherapy (13 studies, 68.4%). C-index values were presented in 14 studies. The overall risk of bias assessed using PROBAST led to 100% of studies being classified as high risk (the analysis domain was rated to be at high risk of bias in all the studies), and 52.6% showed low applicability. Only 5 studies (26.3%) included an external validation and 2 (10.5%) included a prospective study design. Conclusions: Using clinical predictors to assess the risk of bladder-specific cancer mortality is a feasibility alternative. However, the studies showed a high risk of bias and their applicability is uncertain. Studies should improve the conducting and reporting, and subsequent external validation studies should be developed.es_ES
dc.formatapplication/pdfes_ES
dc.format.extent11es_ES
dc.language.isoenges_ES
dc.publisherWileyes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectmodelses_ES
dc.subjectmortalityes_ES
dc.subjectnomogramses_ES
dc.subjectradical cystectomy,es_ES
dc.subjecturinary bladder neoplasmses_ES
dc.titleMortality prediction models after radical cystectomy for bladder tumour: A systematic review and critical appraisales_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversion10.1111/eci.13822es_ES
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