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Positron emission tomography (PET) for prediction of glioma histology: protocol for an individual-level data meta-analysis of test performance

INTRODUCTION: Gliomas, the most commonly diagnosed primary brain tumours, are associated with varied survivals based, in part, on their histological subtype. Therefore, accurate pretreatment tumour grading is essential for patient care and clinical trial design. METHODS AND ANALYSIS: We will perform...

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Detalles Bibliográficos
Autores principales: Trikalinos, Nikolaos A, Nihashi, Takashi, Evangelou, Evangelos, Terasawa, Teruhiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5855451/
https://www.ncbi.nlm.nih.gov/pubmed/29455169
http://dx.doi.org/10.1136/bmjopen-2017-020187
Descripción
Sumario:INTRODUCTION: Gliomas, the most commonly diagnosed primary brain tumours, are associated with varied survivals based, in part, on their histological subtype. Therefore, accurate pretreatment tumour grading is essential for patient care and clinical trial design. METHODS AND ANALYSIS: We will perform an individual-level data meta-analysis of published studies to evaluate the ability of different types of positron emission tomography (PET) to differentiate high from low-grade gliomas. We will search PubMed and Scopus from inception through 30 July 2017 with no language restriction and full-text evaluation of potentially relevant articles. We will choose studies that assess PET using 18-Fludeoxyglucose (18F-FDG), l-[Methyl-()11C]Methionine (11C-MET), 18F-Fluoro-Ethyl-Tyrosine (18F-FET) or (18)F-Fluorothymidine (18F-FLT)for grading, verified with histological confirmation. We will include both prospective and retrospective studies. Bias will be assessed by two reviewers with the Quality Assessment of Diagnostic Accuracy Studies-2 tool and as per method described by Deeks et al. ETHICS AND DISSEMINATION: Ethics approval was not applicable, as this is a meta-analytic study. Results of the analysis will be submitted for publication in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42017078649.