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Incidence of Tumour Progression and Pseudoprogression in High-Grade Gliomas: a Systematic Review and Meta-Analysis

期刊

CLINICAL NEURORADIOLOGY
卷 28, 期 3, 页码 401-411

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s00062-017-0584-x

关键词

Treatment response assessment; Meta-analysis; Pseudoprogression; Incidence; High-grade gliomas

资金

  1. Mandema stipendium from the University of Groningen
  2. Junior Scientific Masterclass pilot grant for the University of Groningen

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Background High-grade gliomas are the most common primary brain tumours. Pseudoprogression describes the false appearance of radiation-induced progression on MRI. A distinction should be made from true tumour progression to correctly plan treatment. However, there is wide variation of reported pseudoprogression. We thus aimed to establish the incidence of pseudoprogression and tumour progression in high-grade glioma patients with a systematic review and meta-analysis. Methods We searched PubMed, Embase and Web of Science on the incidence of pseudoprogression and tumour progression in adult high-grade glioma patients from 2005, the latest on 8 October 2014. Histology or imaging follow-up was used as reference standard. Extracted data included number of patients with worsening of imaging findings on T1 postcontrast or T2/FLAIR, pseudoprogression and tumour progression. Study quality was assessed. Heterogeneity was tested with I (2) . Pooling of the results was done with random models using Metaprop in STATA (StataCorp. Stata Statistical Software. College Station, TX: StataCorp LP). Results We identified 73 studies. MRI progression occurred in 2603 patients. Of these, 36% (95% confidence interval [CI] 33-40%) demonstrated pseudoprogression, 60% (95%CI 56-64%) tumour progression and unknown outcome was present in the remaining 4% of the patients (range 1-37%). Conclusion This meta-analysis demonstrated for the first time a notably high pooled incidence of pseudoprogression in patients with a form of progression across the available literature. This highlighted the full extent of the problem of the currently conventional MRI-based Response Assessment in Neuro-Oncology (RANO) criteria for treatment evaluation in high-grade gliomas. This underscores the need for more accurate treatment evaluation using advanced imaging to improve diagnostic accuracy and therapeutic approach.

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