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Canadian Expert Consensus Recommendations for the Diagnosis and Management of Glioblastoma : Results of a Delphi Study Mason, Warren P.; Harrison, Rebecca A.; Lapointe, Sarah; Lim-Fat, Mary Jane; MacNeil, Mary V.; Mathieu, David; Perry, James R.; Pitz, Marshall W.; Roberge, David; Tsang, Derek S.; Tsien, Christina; van Landeghem, Frank K. H.; Zadeh, Gelareh; Easaw, Jacob
Abstract
Glioblastoma is the most common and aggressive malignant brain tumor in adults, with an increasing incidence and a poor prognosis. Current challenges in glioblastoma management include rapid tumor growth, limited treatment effectiveness, high recurrence rates, and a significant impact on patients’ quality of life. Given the complexity of glioblastoma care and recent advancements in diagnostic and treatment modalities, updated guidelines are needed in Canada. This Delphi study aimed to develop Canadian consensus recommendations for the diagnosis, classification, and management of newly diagnosed and recurrent glioblastoma. A multidisciplinary panel of 14 Canadian experts in glioblastoma care was convened, and a comprehensive literature review was conducted to synthesize evidence and formulate initial recommendations. Consensus was achieved through three Delphi rounds, in which panelists rated their agreement with recommendation statements on a five-point Likert scale. Statements with ≥75% agreement were accepted, and others were revised for re-voting. Final recommendations were formulated based on the consensus level, strength of evidence, clinical expertise, and consideration of the Canadian healthcare context. These recommendations aim to standardize glioblastoma diagnosis and classification across Canada, provide evidence-based guidance for optimal treatment selection, integrate novel therapies, and enhance the overall quality of care for glioblastoma patients.
Item Metadata
| Title |
Canadian Expert Consensus Recommendations for the Diagnosis and Management of Glioblastoma : Results of a Delphi Study
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| Creator | |
| Publisher |
Multidisciplinary Digital Publishing Institute
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| Date Issued |
2025-04-01
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| Description |
Glioblastoma is the most common and aggressive malignant brain tumor in adults, with an increasing incidence and a poor prognosis. Current challenges in glioblastoma management include rapid tumor growth, limited treatment effectiveness, high recurrence rates, and a significant impact on patients’ quality of life. Given the complexity of glioblastoma care and recent advancements in diagnostic and treatment modalities, updated guidelines are needed in Canada. This Delphi study aimed to develop Canadian consensus recommendations for the diagnosis, classification, and management of newly diagnosed and recurrent glioblastoma. A multidisciplinary panel of 14 Canadian experts in glioblastoma care was convened, and a comprehensive literature review was conducted to synthesize evidence and formulate initial recommendations. Consensus was achieved through three Delphi rounds, in which panelists rated their agreement with recommendation statements on a five-point Likert scale. Statements with ≥75% agreement were accepted, and others were revised for re-voting. Final recommendations were formulated based on the consensus level, strength of evidence, clinical expertise, and consideration of the Canadian healthcare context. These recommendations aim to standardize glioblastoma diagnosis and classification across Canada, provide evidence-based guidance for optimal treatment selection, integrate novel therapies, and enhance the overall quality of care for glioblastoma patients.
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| Subject | |
| Genre | |
| Type | |
| Language |
eng
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| Date Available |
2025-05-12
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
CC BY 4.0
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| DOI |
10.14288/1.0448851
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| URI | |
| Affiliation | |
| Citation |
Current Oncology 32 (4): 207 (2025)
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| Publisher DOI |
10.3390/curroncol32040207
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| Peer Review Status |
Reviewed
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| Scholarly Level |
Faculty; Researcher
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
CC BY 4.0