This clinical trial studies whether T2 star (T2\*) magnetic resonance imaging (MRI) and biomarker blood testing can help predict how World Health Organization (WHO) grade IV gliomas (malignant gliomas) might change or progress over time.
This clinical trial studies whether T2 star (T2\*) magnetic resonance imaging (MRI) and biomarker blood testing can help predict how World Health Organization (WHO) grade IV gliomas (malignant gliomas) might change or progress over time. WHO grade IV gliomas are the most common primary brain tumors. Despite aggressive standard of care treatment, overall survival remains low. Early identification of whether the glioma comes back after a period of improvement (recurrence) remains an important part of treatment management. Early identification of recurrence can be complicated as treatment effects can cause inflammation, making it difficult to identify recurrence on standard MRI. It has been shown that WHO grade IV gliomas have increased iron content and that as the glioma is treated, markers in the blood that represent iron related cell death (biomarkers) increase. T2\* mapping is an MRI technique routinely used to assess iron content within tissues and may help identify recurrence of the glioma on the MRI. The biomarker blood test in this study checks the levels of iron-related cell death biomarkers in the blood, which may help predict how well patients are responding to treatment. T2\* MRI and biomarker blood testing may be an effective way to predict how malignant gliomas might change or progress over time.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
15
Undergo T2\* MRI
Undergo blood sample collection
Undergo standard MRI
University of Iowa Health Care
Iowa City, Iowa, United States
RECRUITINGRelationship between T2 (observed)-weighted imaging (T2*) magnetic resonance imaging relation time and dimeric transferrin receptor expression
Will be characterized with mixed effects regression modeling. Correlation between the two biomarkers will be estimated with the multivariate linear mixed effects regression approach of Hamlett, Ryan, and Wolfinger. Cluster bootstrapping will be employed to calculate a 95% confidence interval for their correlation and a p-value for testing its significance at the 5% level.
Time frame: Up to 3 months post-radiation therapy
Effects of T2* relaxation and/or circulating dimeric transferrin receptor on progression-free survival (PFS)
Cox regression will be used to model the univariable and multivariable effects of T2\* relaxation time and dimeric transferrin receptor on PFS. Time-dependent receiver operating characteristic (ROC) analysis will be performed to estimate ROC curves at 6-months and areas under the curves (AUCs) as measures of prognostic performances. AUCs will be compared to help determine whether the combination of biomarkers is more prognostic than either biomarker alone. Sensitivities and specificities from the ROC curves will also be reported across the observed range of biomarkers (cutoff) values to further characterize their performance in predicting PFS.
Time frame: Up to 3 months post-radiation therapy
PFS
Cumulative PFS will be descriptively summarized over time with the method of Kaplan-Meier.
Time frame: From treatment initiation to the date of first documentation of disease progression or death due to any cause in the absence of documented progression, assessed up to 3 months post-radiation therapy
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