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Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
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Objectives: The study identifies and summarizes information from manuscripts using simulation models for Bladder Cancer (BCA) research.
Methods: We conducted and presented results of a systematic literature search of Medline, Web of Science, and Google scholar, following the PRISMA guidelines for scoping reviews. We summarized extracted key components of the methodology, data sources, and software used for the development of simulation models and classify eligible articles in terms of the study objectives and conclusions.
Results: The 97 identified modeling studies simulating aspects of BCA included models that (1) describe the biological process of carcinogenesis and tumor progression (mostly compartmental models); (2) examine the impact of screening protocols and interventions on disease progression and prognosis (mostly microsimulation models); and (3) assess the cost-effectiveness of BCA treatment and control strategies (cohort-based simulation models or simpler decision tree structures). The scope, objectives, and conclusions of these studies varied substantially. Most focused on evaluating treatments, mostly for non-muscle invasive bladder cancer, with some examining BCA screening and surveillance. Their objectives, methods, and analyses were inconsistently and often incompletely reported.
Conclusions: Simulation models in bladder cancer examine questions that span the range from tumor kinetics to cost effectiveness of tumor management, but shortcomings in their reporting hinder assessments of their applicability and methodological rigor, severely limiting their practical usefulness.
Highlight Statements: We assessed the available landscape of simulation modeling for health decision making in BCA research.Shortcomings in the reporting of this research severely limit their practical usefulness.Future population modeling should assess BCA screening and surveillance.
Strengths: This is the first, to our knowledge, systematic appraisal of simulation models in bladder cancer. Simulation modeling will be a key technology to assess the utility of highly promising novel diagnostics and treatments, while evidence accumulates.The described variation in the objectives, methodological rigor, and reporting of models' development, validation, and analysis likely generalize to other disease areas.
Limitations: This descriptive compendium does not explicitly compare the results of different models between them or with observed data.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12073888 | PMC |
http://dx.doi.org/10.1101/2025.03.17.25324125 | DOI Listing |