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A validated integrated clinical and molecular glioblastoma long-term survival-predictive nomogram

Ferguson, Sherise D., Hodges, Tiffany R., Majd, Nazanin K., Alfaro-Munoz, Kristin, Al-Holou, Wajd N., Suki, Dima, de Groot, John F., Fuller, Gregory N. and Khasraw, Mustafa 2021, A validated integrated clinical and molecular glioblastoma long-term survival-predictive nomogram, Neuro-Oncology Advances, vol. 3, no. 1, January-December, pp. vdaa146-vdaa146, doi: 10.1093/noajnl/vdaa146.

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Title A validated integrated clinical and molecular glioblastoma long-term survival-predictive nomogram
Author(s) Ferguson, Sherise D.
Hodges, Tiffany R.
Majd, Nazanin K.
Alfaro-Munoz, Kristin
Al-Holou, Wajd N.
Suki, Dima
de Groot, John F.
Fuller, Gregory N.
Khasraw, MustafaORCID iD for Khasraw, Mustafa orcid.org/0000-0003-3249-9849
Journal name Neuro-Oncology Advances
Volume number 3
Issue number 1
Season January-December
Start page vdaa146
End page vdaa146
Publisher Oxford University Press
Place of publication Oxford, Eng.
Publication date 2021-01
ISSN 2632-2498
2632-2498
Keyword(s) glioblastoma
long-term survival
nomogram
outcome
prediction
Summary BackgroundGlioblastoma (GBM) is the most common primary malignant brain tumor in adulthood. Despite multimodality treatments, including maximal safe resection followed by irradiation and chemotherapy, the median overall survival times range from 14 to 16 months. However, a small subset of GBM patients live beyond 5 years and are thus considered long-term survivors.MethodsA retrospective analysis of the clinical, radiographic, and molecular features of patients with newly diagnosed primary GBM who underwent treatment at The University of Texas MD Anderson Cancer Center was conducted. Eighty patients had sufficient quantity and quality of tissue available for next-generation sequencing and immunohistochemical analysis. Factors associated with survival time were identified using proportional odds ordinal regression. We constructed a survival-predictive nomogram using a forward stepwise model that we subsequently validated using The Cancer Genome Atlas.ResultsUnivariate analysis revealed 3 pivotal genetic alterations associated with GBM survival: both high tumor mutational burden (P = .0055) and PTEN mutations (P = .0235) negatively impacted survival, whereas IDH1 mutations positively impacted survival (P < .0001). Clinical factors significantly associated with GBM survival included age (P < .0001), preoperative Karnofsky Performance Scale score (P = .0001), sex (P = .0164), and clinical trial participation (P < .0001). Higher preoperative T1-enhancing volume (P = .0497) was associated with shorter survival. The ratio of TI-enhancing to nonenhancing disease (T1/T2 ratio) also significantly impacted survival (P = .0022).ConclusionsOur newly devised long-term survival-predictive nomogram based on clinical and genomic data can be used to advise patients regarding their potential outcomes and account for confounding factors in nonrandomized clinical trials.
Language eng
DOI 10.1093/noajnl/vdaa146
Indigenous content off
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30147246

Document type: Journal Article
Collections: Faculty of Health
School of Medicine
Open Access Collection
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.