A Prospective Phase II Randomized Trial to Compare Intensity Modulated Proton Radiotherapy (IMPT) vs. Intensity Modulated Radiotherapy (IMRT) for Newly Diagnosed Glioblastoma (WHO Grade IV)
Phase: PHASE2
Conditions: Brain Cancer
Sponsor: M.D. Anderson Cancer Center

2013-0097 
March 1, 2019 
Version 15 
Page 1 
                                                                                                                                                                                                        
 
A prospective Phase II randomized trial to compare intensity modulated proton radiotherapy 
(IMPT) vs. intensity modulated radiotherapy (IMRT) for newly diagnosed Glioblastoma (WHO 
Grade IV) 
 
 
 
1.0      Abstract 
2.0      Schema 
3.0      Objectives 
4.0      Background 
5.0      Background Information on Treatment Modalities and Correlative Studies 
6.0      Patient Eligibility 
7.0      Treatment Plan 
8.0      Pretreatment Evaluation 
9.0      Evaluation During Study 
10.0 
Criteria for Response and Toxicity 
11.0 
Criteria for Discontinuation of Therapy 
12.0 
Statistical Considerations 
13.0 
Data and Protocol Management 
14.0 
Reporting Requirements 
15.0 
References 
 
 
 
 

2013-0097 
March 1, 2019 
Version 15 
Page 2 
 
1.0   Abstract 
 
 Glioblastoma (GBM) accounts for 25% of all primary central nervous system (CNS) 
tumors in adults and historically has been associated with median survival times of less 
than a year [1].   However, the addition of temozolomide to radiotherapy has resulted in 
significant improvements in survival, especially for certain subsets of patients [2].  With the 
improvement in survival times there are growing concerns about the negative effects of 
treatment, especially the potential for cognitive deficits after cranial radiotherapy.  
Decreasing the amount of brain exposed to radiation has a significant impact on cognitive 
function after radiation [3-5].  Proton radiotherapy is a treatment modality which has been 
safely and effectively used in the treatment of GBMs with low rates of toxicity such as 
radiation necrosis [6, 7].  Additionally, there is some pre-clinical evidence that supports 
greater impact on tumor cell death with protons compared to photons [8].   Previous 
studies have shown that intensity modulated proton therapy (IMPT) can allow for more 
conformal target coverage than conventional intensity modulated photon radiation therapy 
(IMRT) while minimizing doses to normal tissues such as the contralateral hippocampus 
[9].  The decreased dose to critical normal brain tissue resulting from conformal proton 
radiotherapy has been suggested to translate into improved cognitive function based on 
radiation dose cognitive effect models [10].  Additionally, improved conformality of dose 
delivery by IMPT may allow for dose escalation in the treatment of GBM which has been 
demonstrated to improve median survival time as a result of improved central control of 
tumors [11].  The purpose of the current study is to prospectively assess the cognitive 
sequelae, quality of life, and local control outcomes of patient with glioblastoma treated 
with IMPT versus IMRT.  
 
 
 

2013-0097 
March 1, 2019 
Version 15 
Page 3 
 
2.0  Schema 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Stratify: 
RPA Class III or IV vs. V 
MMSE:  21-26 vs. 27-30 
Age:  Less than 65 vs. 65 and older 
Neurocognitive testing 
(post-surgery, pre-radiotherapy) 
Arm 1 
IMRT 
Arm 2 
IMPT 
Eligible Patients 
Screened for Inclusion/Exclusion Criteria 
Informed Consent 
14 
22 
12 
10 
Months 
16 
18 
20 
24 
8 
6 
4 
2 

2013-0097 
March 1, 2019 
Version 15 
Page 4 
Eligibility Checklist 
 
1. __________ Histological diagnosis of:  Glioblastoma or Gliosarcoma (WHO Grade IV) 
adapted RPA class III, IV, or V (Y/N) 
2. __________ Age 18 years or older at registration (Y/N) 
3. __________ Informed consent must be signed (Y/N) 
4. __________ Patient has a baseline Mini Mental Status Examination score of 21 or 
greater (Y/N) 
5. __________ KPS 70 (Y/N) 
6. __________ Eligible to have treatment by IMRT or IMPT as determined by radiation 
oncologist (Y/N) 
7. __________ Patient is able to obtain an MRI with and without contrast with a 
glomerular filtration rate (eGFR) ≥ 30 mg/min/1.72m2 (Y/N) 
8. __________ Patient has adequate liver, renal, and hematologic function within 14 
days of registration as defined by Aspartate Amino Transferase (AST)/Alanine 
Amino Transferase (ALT)/Alkaline Phosphatase < 3 times normal, creatinine 
<1.7 mg/dl, BUN < 35mg/dl, absolute neutrophil count >1,800 cells/mm3, 
Hemoglobin > 10 g/dl,  and platelet count > 100,000 (Y/N) 
9. __________ Patient is able to adequately read, write and speak to participate in the 
cognitive and quality of life assessments, allowing for mild to moderate deficits 
in these functions due to tumor  (Y/N) 
10.  _________ Patient is planning to receive concurrent temozolamide (Y/N) 
11. _________ Patient has no prior history of brain radiation (Y/N) 

2013-0097 
March 1, 2019 
Version 15 
Page 5 
12. _________ Patient has not had prior surgical resection of brain for other brain 
tumors  (Y/N) 
13. _________ Female patients of child bearing potential are not pregnant based on 
serum Beta-HCG test (Y/N)  
14. _________ Patient does not have gliomatosis (Y/N) 
15. _________ Patient has not had Glialdel (BCNU) wafers implanted (Y/N) 
16. __________ Patient weight is less than or equal to 136 kilograms (Y/N) 
 

2013-0097 
March 1, 2019 
Version 15 
Page 6 
3.0 Objectives 
3.1 Primary Objectives 
3.1.1 To assess whether treatment with IMPT results in longer time to cognitive 
failure compared with IMRT. Cognitive failure is defined as the first 
cognitive failure on any of the following six cognitive outcome variables: 
Hopkins Verbal Learning Test Revised (HVLT-R) Total Recall, HVLT-R 
Delayed Recall, HVLT-R Delayed Recognition, Controlled Oral Word 
Association (COWA), Trail Making Test (TMT) Part A or Part B. 
3.2 Secondary Objectives 
3.2.1 To determine local control in the brain post radiation treatment. 
3.2.2 To determine overall survival in each treatment arm.   
3.2.3 To assess quality of life measured at two month intervals for a total of two 
years post-radiotherapy for both treatment arms.   
3.2.4 To assess the pattern of cognitive change in memory at two month 
intervals for two years post-treatment as well as executive function and 
processing speed.  
3.2.5 MRI diffusion weighted images (DWI) and reconstructed apparent diffusion 
coefficient (ADC) maps will be analyzed to see if there is a difference 
between pre- and post-treatment scans.  These will also be analyzed for 
differences between the two treatment modalities.  
3.2.6 To evaluate if diffusion tensor imaging (DTI) correlates to the cognitive 
changes and if there are differences between the two treatment 
modalities.   
3.2.7 To assess the pre-treatment factors of recursive partitioning analysis (RPA) 
class and mini mental status examination (MMSE) in the predictive 
determination of local and distant control and cognitive outcome in each 
treatment arm. 
3.2.8 To assess the correlation between location of primary lesion, total volume 
of intracranial disease, and cognitive outcome in each treatment arm. 
3.2.9 To determine the relationship between MGMT promoter methylation 
status and cognitive and local control outcomes.   
3.2.10 To document and descriptively compare post-treatment adverse side 
effects between the two treatment arms. 
3.2.11 To determine the relation between dosimetric parameters and cognitive 
and local control outcomes. 
3.3 Correlative objectives 
3.3.1 To determine if Apo E (i.e., Apo E2, Apo E3, and Apo E4) genotyping may 
prove to be a predictor of radiation induced neurocognitive decline (or 
neuro-protection). 
3.3.2 To determine if inflammatory markers (i.e., IL-1, IL-6, and TNF-α) may 
prove to be predictors of radiation induced neurocognitive decline. 
3.3.3 To determine if hormone and growth factors [i.e., glucocorticoids (e.g., 
cortisol), gonadal steroids (e.g., estradiol, testosterone, progesterone), 

2013-0097 
March 1, 2019 
Version 15 
Page 7 
growth hormone, human chorionic gonadotropin (hCG), insulin-like 
growth factor-1 (IGF-1), and neuronal growth factor (NGF)] may prove to 
be a predictor of radiation induced neurocognitive decline. 
3.3.4 To validate the prognostic significance of a combined multi-molecular 
marker survival classifier called the Molecular Clinical Prognosticator 
(MCP). 
 
4.0 Background 
 
 
Gliomas represent the most common primary brain tumor in the adult population.  
Malignant gliomas include anaplastic astryocytoma (AA) and glioblastoma multiforme (GBM) 
and have an annual incidence of 3 to 4 per 100,000, with over 80% of these being GBMs [12].  
The standard treatment for glioblastoma is maximal safe resection followed by involved-field 
radiation.  A pooled analysis of six randomized trials demonstrated that there is a significant 
survival benefit to the addition of radiation therapy after surgical resection [13].  Historically 
outcomes have been quite poor with median survival of less than one year for GBM [12].   
 
Recently, combined modality treatment including the addition of concurrent and/or 
adjuvant temozolomide has resulted in significant improvement in outcomes for glioblastoma 
patients [2, 14].  Stupp et. al. demonstrated a 2 year overall survival (OS) rate of 27.2% with 
concomitant and adjuvant temozolomide as compared to a 10.9% 2 year OS rate with radiation 
alone [2].  This response was found to be durable at 5 years of follow up.  Indeed, patients with 
favorable prognostic categories such as MGMT promoter methylation had even better survival 
outcomes.  With improved outcomes and longer survival an increasing number of patients are 
at risk for secondary adverse effects from radiation treatment, particularly cognitive decline.   
 
 Cognitive function has been increasingly recognized as a key primary outcome 
measurement following cranial radiotherapy.  Several studies have suggested that in high grade 
glioma patients tumor progression was the dominant cause of cognitive decline [15-17].  
However, these studies were done in the era prior to the introduction of combined modality 
treatment when median survival was less than one year.  While tumor progression is a key 
factor in cognitive function, prolonged survival with combined modality treatment will also lead 
to an increasing number of patients who develop treatment related late toxicity.   
 
Data in low grade glioma patients suggests that the amount of brain exposed to radiation as 
well as the dose of radiation has a significant impact on cognitive function [3, 4, 18].  Similarly, 
metastatic brain cancer patients receiving stereotactic radiation have improved cognitive 
outcomes compared to patients treated with whole brain radiation therapy [19].  This has led 
to an increased interest in using more focused radiation therapy for glioblastoma. 
 
Currently most patients with glioblastoma are treated using either 3D conformal or 
intensity modulated radiation therapy (IMRT) with photon beams.  These modalities allow for 
conformal dosing to tumor while minimizing dose to surrounding normal structures.  However, 

2013-0097 
March 1, 2019 
Version 15 
Page 8 
surrounding normal structures continue to receive low to moderate doses of radiation.  Proton 
beam therapy is an alternative technology which may provide more conformal dosing with less 
dosing to normal structures.   
 
Proton radiotherapy has been previously demonstrated to be safe and effective in the 
treatment of high grade gliomas [6, 7, 20].  Additionally, there is preclinical evidence that 
proton radiotherapy may have a greater impact on tumor cell death.  Moertel et al. have 
demonstrated that human glioblastoma cells in culture experience increased G2 cell cycle arrest 
and decreased DNA double strand break repair when irradiated with protons versus photons 
[8].  This suggests a potential advantage of proton therapy in glioblastoma patients. 
 
Previous studies have also demonstrated that IMPT can allow for more conformal dosing 
than IMRT.  IMPT can take advantage of proton characteristics such as less lateral scatter, lack 
of exit dose, and steep distal dose fall-off to increase conformality.   For example, Rosenschold 
et al. compared treatment plans using IMRT versus IMPT for high grade glioma patients.  They 
found increased planning target volume (PTV) coverage conformality with IMPT.  Additionally, 
IMPT plans had increased sparing of healthy tissue both for whole brain doses as well as to 
critical structures such as the contralateral hippocampus [9].   
 
Decreased dosage to critical normal brain tissues has been suggested to translate into 
improved cognitive function.  Merchant et al. compared dose characteristics for four types of 
common childhood brain tumors treated using conformal protons versus photons and in dose-
volume modeling systems found that proton plans resulted in better cognitive outcomes.  
Specific advantages included decreased IQ loss, less cochlea damage, and decreased endocrine 
effects[10].  The study of long term benefit of proton therapy in pediatric patients will require 
years of follow up but the preliminary results are encouraging.  Similarly Arvold et al. modeled 
doses for protons versus photons in the treatment of benign meningiomas.  They showed that 
protons could decrease the risk of radiation associated secondary malignancies by half and that 
lower doses to critical structures supporting cognitive functions such as memory including the 
temporal lobe and hippocampus could be achieved with proton plans [21].   
 
While the theoretical dosimetric advantages of proton plans are intriguing we do not have 
randomized data comparing cognitive outcomes in glioblastoma patients treated with these 
two modalities.  We hypothesize that IMPT will result in improved cognitive outcomes.  In this 
trial we propose to address this question by prospectively randomizing patients with 
glioblastoma to treatment with IMRT versus IMPT.  Patients will be stratified by RPA class, Mini 
Mental Status Examination score (21-26 vs. 27-30)[17], and age (less than 65 vs. 65 and older).  
These factors are known to have prognostic significance.  The primary endpoint will be time to 
first cognitive failure on any of the following six cognitive test variables:  HVLT-R Total Recall, 
HVLT-R Delayed Recall, HVLT-R Delayed Recognition, COWA, and TMT A or B.  Secondary 
endpoints will include local control and overall survival outcomes as well as quality of life.   
Addressing this question in a prospective randomized fashion can be accomplished at MDACC 
given the high volume of cancer patients with glioblastoma treated at our center.   
 

2013-0097 
March 1, 2019 
Version 15 
Page 9 
 
5.0 Background Information on Treatment Modalities and Correlative Studies 
5.1 Background on Treatment Modalities 
  
 
Intensity modulated radiotherapy uses photon beams to deliver treatment.  The 
advantage of this treatment modality over traditional or 3D-conformal radiation lies in 
increasing dose conformality.  By dividing each radiation field into a number of separate 
beamlets, using inverse planning and intensity modulation, and then adding beamlets 
together to form a cumulative dose distribution the treatment can be highly sculpted to 
the tumor.  In multiple tumor types this technique has been shown to greatly reduce 
side effects while maximizing tumoricidal doses to the target.  However, this technique 
is constrained by the physical properties of photons.  Photons deposit dose as they 
travel through normal tissues both upon entrance and exit after passing through the 
target.  As multiple beam angles are used, one criticism of IMRT is the “low dose bath” 
that surrounding normal tissues receive.  While IMRT is a substantial improvement over 
conventional or even 3D techniques and is now the standard for irradiation of 
glioblastoma at our institution, IMPT may be even more advantageous.   
 
 
Intensity modulated proton therapy is also a method of delivering ablative doses 
to the primary tumor while minimizing radiation to surrounding normal structure. The 
basis of the advantage of protons over photons in general lies in their action in exposed 
tissues.  Specifically, in contrast to photons which are absorbed throughout the course 
of their beam path, protons have a finite range of action that is dependent on the initial 
proton energy.  Protons traverse most of the beam path and then deposit their energy 
near the target in the Bragg peak with little or no exit dose.  When several beams of 
closely spaced energies are combined a spread-out Bragg peak (SOBP) can be created 
which results in a modulated proton beam.  In IMPT there is simultaneous optimization 
of all Bragg peaks from all incident beams.  This ability to modify treatment voxel by 
voxel results in increased dose conformality.  IMPT was pioneered at the Paul Scherrer 
Institute in Switzerland but is now being offered commercially by Varian Medical 
Systems (Palo Alto, CA).  IMPT has been proposed as being most useful in treating 
complex field shapes such as brain tumors.   
 
In short, IMRT and IMPT have many similarities.  Both involve the delivery of 
fractionated, daily radiation to targeted brain tissues although they accomplish this with 
different modalities.  In both treatment types radiation is highly targeted to specific sites 
in the brain to include gross residual disease as well as areas at high clinical risk of 
microscopic disease.  However, as delineated above there are differences between the 
two treatment modalities.  In particular the decreased exit and low doses to normal 
structures with IMPT suggest that there may be a significant difference between the two 
modalities in regards to cognitive outcomes.  However, there is an increased cost 
associated with IMPT and as stewards of our healthcare system it is important to show if 
there is a measurable clinical benefit associated with the use of IMPT.    
 

2013-0097 
March 1, 2019 
Version 15 
Page 10 
5.2 Background for correlative studies 
5.2.1 Genetic Markers 
Apolipoprotein E (ApoE) is an important factor in remodeling and repairing 
neurons in response to injury or stress through its lipid transport function. In 
fact, recent data suggests that patients having the Apo E4 isoform realize 
Alzheimer’s dementia far earlier than those without it [22].  This allele is present 
in 16% of the general population and 50% of patients with late onset Alzheimer’s 
dementia [23]. Given the similar mechanisms of dementia between Alzheimer’s 
dementia and radiation induced dementia (e.g. vascular or metabolic), Apo E4 
genotyping may prove to be a predictor of radiation induced neuronal damage. 
The Apo E4 protein binds rapidly and tightly to beta amyloid. Normally beta 
amyloid exists in a soluble form. However, when bound by Apo E4 protein, beta 
amyloid becomes insoluble and is more likely to be deposited in plaques which 
may lead to changes in microvasculature, ultimately leading to neurocognitive 
decline. Further, patients with just one copy of the Apo E4 allele have 
demonstrated accelerated hippocampal volume loss which can also compromise 
neurocognitive function [24]. Recent preclinical mouse data from Crawford and 
Villasana have shown neurogenesis in the hippocampus and hippocampal 
dysfunction depending on Apo E status [25, 26]. Patients with Apo E2 and Apo E3 
alleles, on the contrary, tend to have one quarter the risk of developing 
Alzheimer’s disease. It is felt that the E2 and E3 alleles are able to facilitate repair 
and protection from neuronal damage. Apo E genotyping will be performed to 
assess whether a subgroup of patients exists that is genetically predisposed to 
developing neurocognitive decline (or neuroprotection). 
 
5.2.2 Inflammatory Markers 
Markers of inflammation are elevated with aging and their increase has been 
associated with cognitive decline [27, 28]. Epidemiological and retrospective 
data reveals an improvement in neurocognitive function with the use of NSAIDs 
in patients with Alzheimer’s dementia, supporting an inflammatory process 
involved in neurocognitive decline [23]. Chronic inflammation as a result of mass 
effect from tumor or treatment related inflammation may be associated with 
neurocognitive deficits and can be measured in plasma. Interleukin 1 (IL-1), 
Interleukin 6 (IL-6), and Tumor Necrosis Factor alpha are pro-inflammatory 
cytokines that are a measure of inflammation and have been shown to be 
elevated in patients with Alzheimer’s dementia [29-32].  In this study, 
inflammatory biomarkers will be measured at baseline (after registration, but 
prior to treatment) and at each follow-up visit when neurocognitive testing is 
performed. 
 
5.2.3 Hormone and Growth Factors 
Aging and memory decline is associated with the disruption of hormone 
regulation, including glucocorticoids, gonadal steroids, and growth hormone 
[33]. Cortisol, human chorionic gonadotropin (hCG), insulin-like growth factor-1 

2013-0097 
March 1, 2019 
Version 15 
Page 11 
(IGF-1), and neuronal growth factor (NGF), have all recently been associated with 
cognitive decline in Alzheimer’s disease [34, 35]. ELISA testing of serum 
specimens for each hormone and growth factor will be performed at baseline 
(after registration, but prior to treatment) and at each follow-up visit when 
neurocognitive testing is performed.  
 
5.2.4 Molecular Clinical Prognosticator (MCP) 
 
Classification according to both molecular biomarkers and the well-validated 
Glioma RTOG recursive partitioning analysis (RPA) classification [36, 37] is 
important for accurate survival prediction.  Robust survival classification are 
important both in planning randomized trials for stratification and for selection 
of patients for appropriate therapy.  In order to increase the survival 
classification resolution while minimizing the impact on patient enrollment 
requirements, we have developed a new prognostic classifier, the MCP.  The 
MCP was developed using methodologies suitable for archival, formalin-fixed, 
paraffin-embedded (FFPE) tissue.  In its development, a generalized “training and 
validation” approach was used in which the statistical model was built on a set of 
cases to optimize survival class discrimination (training set) and a subsequent, 
blinded and independent cohort was used to validate this model (validation set). 
The training set consisted of approximately 250 GBM specimens that were then 
validated using 725 specimens obtained prospectively as a requirement for 
randomization in the RTOG 0525 trial.  It is thus a fully validated prognostic 
classification scheme.   
 
The MCP consists of 4 molecular components each of which is an 
independent prognostic marker after adjusting for RTOG RPA class.  First, we 
include a comprehensive, 10 assay analysis of the MGMT promoter which more 
robustly predicts outcome compared to the standard single assay used in prior 
glioma trials [38]. Second, refinement of a gene expression (mRNA) classifier 
based on 19 genes  that expands on a prior mRNA-based gene predictor [39]. 
Third, we have incorporated IDH1 mutation status, a well-known genetic 
prognostic marker in gliomas [40].  As a fourth and final molecular component, 
an optimal set of gene promoters from the glioma CpG Island Methylator 
Phenotype (G-CIMP) [41] signature was selected to include 6 gene assays.  
Patients are divided in 1 of 3 risk groups based on the number of methylated 
sites.  
 
The combination of these 4 molecular classifications resulted in 72 possible 
risk groups (the product of 3 MGMT, 4 mRNA, 2 IDH1, and 3 CIMP) that were 
then subjected to classification partitioning resulting in 4 molecular-prognostic 
(MP) groups.  These 4 MP groups were then combined with the 3 RTOG RPA 
classes (12 risk groups total, the product of 4 MP and 3 RPA) and partitioned 
again into 4 resulting molecular-clinical prognostic (MCP) classes.  The MCP 

2013-0097 
March 1, 2019 
Version 15 
Page 12 
provides robust survival classification of patients with GBM.  We propose to 
further validate it using patients from the current trial. 
 
 
6.0 Patient Eligibility 
 
Inclusion Criteria: 
6.1 All patients must have histological proof of glioblastoma or gliosarcoma (WHO 
Grade IV) adapted RPA class III, IV, or V.  
6.2 All patients must be 18 years of age. 
6.3 All patients must sign informed consent verifying that they are aware of the 
investigational nature of this study in keeping with the rules and policies of 
M.D. Anderson Cancer Center. The only acceptable consent form is the one 
approved by M.D. Anderson IRB. 
6.4 All patients must have a baseline Mini Mental Status Examination score 21. 
6.5 All patients must have a KPS 70. 
6.6 All patients must be eligible to have either IMRT or IMPT as determined by the 
study radiation oncologist. 
6.7 All patients must be able to undergo MRI with and without contrast with a 
glomerular filtration rate (eGFR) greater than or equal to 30 mg/min/1.72 m2. 
6.8 All patients must have adequate liver, renal, and hematologic function within 14 
days of registration as defined by Aspartate Amino Transferase (AST)/Alanine 
Amino Transferase (ALT)/Alkaline Phosphatase < 3 times normal, creatinine 
<1.7 mg/dl, BUN < 35mg/dl, absolute neutrophil count >1,800 cells/mm3, 
Hemoglobin > 10 g/dl,  and platelet count > 100,000.  
6.9 All patients must be able to adequately read, write and speak to participate in 
the cognitive and quality of life assessments.  However mild to moderate 
deficits in these functions due to tumor are allowed.  
 
Exclusion Criteria: 
6.10 Patients will be excluded if they are not planning to receive concurrent 
temozolomide. 
6.11 Patients will be excluded if they have had prior radiation to the brain. 
6.12 Patients will be excluded if they have had prior surgical resection of brain for 
other brain tumors.  
6.13 Patients will be excluded if they are pregnant as assessed by serum b-HCG.  A 
serum b-HCG test will be performed no greater than 14 days prior to study 
registration for women of childbearing potential. 
6.14 Patients with gliomatosis will be excluded. 
6.15 Patients with Glialdel (BCNU) implanted wafers will be excluded.  
6.16 Patients weighing greater than 136 kilograms will be excluded.  

2013-0097 
March 1, 2019 
Version 15 
Page 13 
 
7.0 Treatment Plan 
 
7.1 Eligible patients will be randomized in equal numbers to each treatment arm 
using CORe. Randomization will be stratified using the following factors: 
7.1.1 RPA class (III or IV vs. V) 
7.1.2 Mini Mental Status Examination score (21-26 vs. 27-30) 
7.1.3 Age (less than 65 vs. 65 or older) 
7.2 Following randomization, insurance pre-authorization will be obtained for the 
specified treatment modality.  If a patient’s insurance will not cover payment 
for the assigned treatment arm, that patient will be removed from the study and 
will be treated off protocol.   
7.3 Radiation target definition for glioblastoma as follows.  GTV defined as tumor 
cavity and any T1 tumor enhancement.  CTV will include GTV + 2 cm margin 
customized to include FLAIR enhancement (if thought by the radiation 
oncologist to be tumor) and exclude bone, fascia, and other anatomical barriers. 
PTV-50 will include CTV + 3-5 mm and will be treated to 50 Gy in 30 fractions.  
PTV-60 boost volume will include GTV + 3-5 mm and will be treated to 60 Gy in 
30 fractions.   
7.4 For patients randomized to IMRT, treatment will be planned using Pinnacle 
software system.  Planning will be based on non contrast CT images obtained at 
time of simulation in addition to MRI scan.  Treatment will be delivered using 
linear accelerator.  Fractionated radiation will be delivered daily M-F with 
weekends off for all patients.  IMRT plans use a configuration of five to seven 
isocentric 6-MV photon beams delivered in a step-and-shoot technique.  For 
inverse planning specified dose constraints are given to organs at risk including 
the brainstem, spinal cord, optic chiasm, optic nerves, and cochlea.   
7.5 For patients randomized to IMPT treatment planning will be conducted using 
the Varian Eclipse system.   The same target delineation and expansions will be 
used as detailed above for IMRT.  Treatment will then be delivered using the 
250 MeV synchrotron (Hitachi Ltd. Power Systems, Ibarakiken, Japan) at the 
Proton Therapy Center at MD Anderson Cancer Center.  Treatments will be 
delivered as once daily fractions, 5 days per week M-F with weekends off for all 
patients.  IMPT may be planned using either multi-field optimization or single 
field optimization depending on the individual patient case.  In single field 
optimization each field is optimized to deliver the prescribed dose to the target 
volume.  Multi-field optimization uses simultaneous spot optimization and has 
been previously described [42].  Additionally if passive scatter is utilized, 
physical aperatures or compensators are utilized to modify the intensity of the 
beam.  Beam angles are similar to those used for 3D proton therapy.  For 
purposes of inverse planning specified dose constraints are used for organs at 
risk as in IMRT planning.  The RBE for proton irradiation is set at 1.1.  Thus the 
dose unit, Gy (RBE) is proton dose in Gy x RBE of 1.1.   
7.6 Dose limitations to critical structures.  Below is a list of dose constraints to 
critical structures.  Every effort should be made to achieve these normal tissue 
constraints.   

2013-0097 
March 1, 2019 
Version 15 
Page 14 
 
Brainstem 
 
V60Gy<0.01cc and V55Gy <0.5cc and V30 <33% 
Brain  
 
V30Gy<50%    
Chiasm 
 
Max dose<54Gy   
Cochlea (Left) 
Max dose<45Gy  and mean < 30 Gy 
Cochlea (Right) 
Max dose<45Gy  and mean < 30 Gy 
Eye (Left) 
 
Max dose<40Gy and mean < 30 Gy 
Eye (Right) 
 
Max dose<40Gy and mean < 30 Gy 
Len (Left) 
 
Max dose<5Gy    
Len (Right) 
 
Max dose<5Gy   
Optic Nerve (Left) 
Max dose<54Gy   
Optic Nerve (Right) Max dose<54Gy   
Hippocampus 
No defined dose constraint.  See below. 
 
In addition, bilateral hippocampal contours will be manually generated on the fused 
planning MRI CT image set by the treating physician.  These contours should be 
generated as performed in RTOG 0933.  
 
 
8.0  Pretreatment Evaluation 
 
8.1 A history and physical, including detailed neurological exam and recording of 
Karnofsky Performance Status (KPS) will be performed on all patients enrolled. 
8.2 Patients will be referred for a detailed neuropsychological evaluation by the 
neuropsychology team. Neuropsychological evaluation will include the battery 
of standardized tests and measures listed below which will comprise the 
primary instruments of interest for the purposes of this study.  This 
standardized battery is routinely used to assess patients with intracranial 
tumors at MDACC.   The following tests were selected because they are widely 
used, standardized psychometric instruments that have been shown to be 
sensitive to the neurotoxic effects of cancer treatment in other clinical trials 
[19, 43, 44].  Normative data have been published for all tests that take into 
account age, education and sex, where appropriate.  These tests were also 
selected to minimize practice effects on repeated administration.  The memory 
test has six alternate forms and the verbal fluency test has two alternate forms. 
Additional tests and measures will be administered to patients at the discretion 
of the attending neuropsychologist based on clinical need for each individual 
patient.  The neuropsychological evaluation will take approximately 2 hours of 
face-to-face contact with the patient to complete all of the testing.  All 
reasonable effort will be made to complete testing prior to the start of radiation 
therapy.  However, in cases where this is not possible evaluation will be 
completed within the first 5 fractions of radiation treatment.  

2013-0097 
March 1, 2019 
Version 15 
Page 15 
  
 
 
Cognitive Function Measured  
 
  Test    
 
 
 
 
 
 
                          
Memory  
 
 
 
 Hopkins Verbal Learning Test-Revised[45]         
  
 
Psychomotor Speed        
 
 Trail Making Test Part A[46]                                 
 
 
Executive Function  
 
 
 Trail Making Test Part B [46] 
                   
 
     
 
Executive Function  
  
 
 Controlled Oral Word Association[47]                   
 
 
 
Symptom/QOL Measures          
Test 
 
 
 
 
 
 
 
                          
Symptom 
 
 
 
MD Anderson Symptom Inventory Brain Tumor (MDASI-BT) [48]     
Quality of Life 
 
 
 
EORTC QLQ C30/BN20 [49] 
 
 
 
 
    
 
8.3 Laboratory studies including CBC, liver function tests including AST, ALT, 
alkaline phosphatase, electrolytes, and Blood Urea Nitrogen (BUN)/Serum 
creatinine. 
8.4 Routine MRI of the brain with and without contrast and including diffusion 
weighted images must be obtained prior to initiation of radiation and no 
greater than 4 weeks prior to study registration and reviewed by radiology to 
identify all measurable disease.  This scan will be considered the baseline scan 
(time 0). 
 
 
9.0  Evaluation During Study 
 
9.1 A history and physical exam will be performed at two month intervals for a total 
of 24 months of follow up after the completion of the assigned treatment (±30 
days).  Note the first evaluation after radiotherapy will frequently be performed 
approximately 4 weeks after completion of radiotherapy and then the study 
will continue with history and physical exam at 2 month intervals.    
9.2 Neuropsychological testing will be performed at each follow up visit, up to two 
years post radiation treatment.  Reasonable effort will be made to complete this 
testing prior to patients meeting with their physicians and receiving 
information about the status of their disease. 
9.3 Routine MR imaging of the brain performed with and without contrast will be 
obtained at each follow up visit at 2 month intervals (±30 days) until 
recurrence or up to two years post radiation treatment.  Note the first 
evaluation after radiotherapy will frequently be performed approximately 4 
weeks after completion of radiotherapy and then the study would continue 
with follow-up imaging at 2 month intervals.   These post-treatment scans will 
be analyzed and compared to baseline scans for identification of regions 
demonstrating changes in contrast enhancement including size, heterogeneity 
and rim thickness. Qualitative estimation of associated T2-FLAIR changes will 
also be evaluated. Early stages of malignant gliomas have demonstrated 
decreased water diffusion. Routinely obtained diffusion weighted images and 
reconstructed ADC maps will be analyzed to see if there is a difference between 
pre- and various post-treatment scans. Based on contrast enhancing imaging 
features, manually selected regions of interest on ADC maps will be 

2013-0097 
March 1, 2019 
Version 15 
Page 16 
quantitatively analyzed, normalized to contralateral unaffected brain 
parenchyma and compared on serial scans.  Similarly DTI maps and cognitive 
functions will be correlated. 
9.4 Medication usage (specifically steroid dose, narcotic pain medications, 
antiepileptic agents, psychostimulants) will be recorded. Steroid doses will be 
adjusted based on clinical and radiographic criteria.  
9.5 Requirements for more frequent evaluation will be documented.  Data on 
unscheduled follow-ups will also be documented. 
9.6 Research blood products will be collected within the first five fractions of 
treatment and at each evaluation period as stated above. At each interval, 2 
tubes (10 mL) of serum (using “red” top tube, no additive) and 1 tube (10 mL) 
of whole blood (EDTA additive, “purple” top tube) will be collected.  
 
10.0 Criteria for Response and Toxicity 
10.1 Definition of primary endpoint: 
10.1.1 Time to cognitive failure on any of the 6 primary variables from the 
pre-specified cognitive tests (HVLT-R total recall, HVLT-R delayed 
recall, HVLT-R delayed recognition, TMT Part A or Part B, COWA)  
with failure defined as a decline that meets or exceeds the reliable 
change index (RCI) for each cognitive test variable.  A cumulative 
incidence approach will be used to estimate median time to cognitive 
failure in order to account for the competing risks of disease 
progression and death.  Patients experiencing disease progression or 
patients that died prior to experiencing cognitive failure will be 
considered as having had a competing event. Progressive disease 
frequently causes cognitive decline, and the goal of this study is to 
assess the impact of the radiation treatment itself on cognitive 
decline.   
10.2 Definitions of secondary endpoints: 
10.2.1 Local control and distant control in the brain will be measured by 
contrast-enhanced brain MRI scan using Response Assessment in 
Neuro-Oncology (RANO)Criteria, as follows [50].   
10.2.1.1 Complete Response (CR): Requires all of the following 1) 
complete disappearance of all enhancing measurable and 
non-measurable disease sustained for a minimum of 4 
weeks; 2) no new lesions; 3) stable or improving non-
enhancing (T2/FLAIR) lesions; 4) patients must be off 
corticosteroids (or on physiologic replacement doses only); 
and 5) stable or improved clinically. 
10.2.1.2 Partial Response (PR): Requires all of the following: 1) ≥50% 
decrease compared with baseline in the sum of products of 
perpendicular diameters of all measurable enhancing 
lesions sustained for at least 4 weeks; 2) no progression of 
non-measurable disease; 3) no new lesions; 4) stable or 
improved non-enhancing (T2/FLAIR) lesions on the same 

2013-0097 
March 1, 2019 
Version 15 
Page 17 
or lower dose of corticosteroids compared with the 
baseline scan; 5) stable or improved clinically.   
10.2.1.3 Progressive Disease (PD): Defined as any of the following 1) 
≥25% increase in the sum of the products of perpendicular 
diameters of enhancing lesions compared with the smallest 
tumor measurement obtained either at baseline (if no 
decrease) or best response, on stable or increasing dose of 
corticosteroids; 2) significant increase in T2/FLAIR non-
enhancing lesion on stable or increasing doses of 
corticosteroids compared with baseline or best response 
not caused by comorbid events (i.e. radiation therapy, 
demyelination, ischemic injury postoperative changes); 
3)any new lesion; 4) clear clinical deterioration not 
attributable to other causes apart from tumor (i.e. seizures, 
medication adverse effects, complications of therapy, 
cerebrovascular events, infection, or decrease in 
corticosteroid dose); 5) failure to return for evaluation due 
to death or deteriorating condition; 6) clear progression of 
non-measurable disease. 
When making the diagnosis of progressive disease it is import 
to recognize the possibility of pseudo-progression, especially if 
the patient is clinically stable. In those situations, treatment 
should continue and status of local control should be evaluated 
with a repeat interval scan.  If the subsequent scan confirms 
progression then the date of progression should be backdated 
to the original scan suggesting progression. 
10.2.1.4 Stable Disease (SD): Requires all of the following 1) does not 
qualify for complete response, partial response, or 
progression; 2) stable FLAIR/T2 lesions on corticosteroid 
dose no greater than at baseline; 3) clinical status stable.  
10.2.1.5 For local control, PD is considered local failure, or stable 
disease with deterioration of the neurological examination 
with a grade III or worse toxicity on the CTCAE v.4.0 scale 
(see Appendix).  All others (CR, PR, asymptomatic SD) are 
deemed success. 
10.2.2 Overall survival will be measured from registration until death.  After 
2 years of follow-up event monitoring will be used.  
10.2.2.1 Patients with unknown vital status will be censored at the 
date of last visit or MRI scan. 
10.2.3 Quality of life will be measured at each two month interval follow up 
visit out to two years using the EORTC QLQ C30/BN20 and the MD 
Anderson Symptom Inventory Brain Tumor (MDASI-BT).  
10.2.4 At each two month interval follow up visit out to 2 years all six pre-
specified cognitive test variables will be assessed.  The pattern of 
cognitive change in memory, executive function, and processing speed 
will be assessed at each time point.  The composite cognitive function 

2013-0097 
March 1, 2019 
Version 15 
Page 18 
score will be determined by averaging standardized Z-scores from all 
pre-specified cognitive test variables (5 out of 6 are required to 
calculate a composite score). 
10.2.5 MRI imaging including diffusion weighted images (DWI) and 
reconstructed apparent diffusion coefficient (ADC) maps will be 
analyzed for differences between pre- and post-treatment scans.  
They will also be analyzed for differences between the two treatment 
modalities.   
10.2.6 Diffusion tensor imaging (DTI) will be analyzed for correlation to the 
cognitive changes and for differences between the two treatment 
modalities.   
10.2.7 Pre-treatment factors of RPA class and MMSE will be assessed for 
predictive determination of local and distant control and cognitive 
outcome in each treatment arm.   
10.2.8 Assessment will be made for correlation between location of primary 
lesion, total volume of intracranial disease, and cognitive outcome for 
each of the treatment arms. 
10.2.9 The relationship between MGMT promoter methylation status and 
cognitive and local control outcomes will be assessed.   
10.2.10 Post treatment side effects will be recorded at each follow up visit 
out to two years.  Toxicity will be recorded according the Common 
Terminology Criteria for Adverse Events v4.0.3 for Nervous System 
Disorders.  Only grade 3 and above toxicity that is directly related to 
therapy will be required to be documented.  Pretreatment symptoms 
should not be considered as toxicity related to the treatment and are 
not required to be documented unless the symptoms worsen as a 
result of therapy.   
10.2.11 Dosimetric parameters such as dose to the hippocampus will be 
analyzed for relationship with cognitive and local control outcomes.   
 
10.3 Evaluation of correlative markers 
10.3.1 Genetic markers: DNA will be extracted within the first five fractions 
of treatment in the laboratory of the Study Chair.  Apo E (i.e., Apo E2, 
Apo E3, and Apo E4) genes will be analyzed for single nucleotide 
polymorphisms (SNPs) either by Taqman or direct sequencing. 
10.3.2 Inflammatory Markers: Serum specimens collected within the first five 
fractions of treatment and at each follow-up visit will be analyzed 
using commercially-available ELISAs from R&D Systems, Inc. for the 
following inflammatory biomarkers: interleukin 1 (IL-1), interleukin 6 
(IL-6), and tumor necrosis factor alpha (TNFα). These markers will be 
assayed in the laboratory of the Study Chair. 
10.3.3 Hormone and Growth Factors: Serum specimens collected within the 
first five fractions of treatment and at each follow-up visit will be 
analyzed using commercially available Enzyme Linked 
Immunosorbant Assays (ELISAs) for the following hormone and 
growth factors: glucocorticoids (e.g., cortisol), gonadal steroids (e.g., 

2013-0097 
March 1, 2019 
Version 15 
Page 19 
estradiol, testosterone, progesterone), growth hormone, human 
chorionic gonadotropin (hCG), insulin-like growth factor-1 (IGF-1), 
and neuronal growth factor (NGF). These assays will be performed in 
the laboratory of the Study Chair. 
10.3.4 A portion of the serum and DNA will initially be analyzed as described 
above. According to patient consent information, the remaining body 
fluid biospecimens will be stored as de-identified frozen specimens in 
locked storage at -70ºC in the laboratory of the Study Chair. As new 
protocols are developed they will be presented for IRB review and 
approval. 
10.3.5 Return of Genetic Testing Research Results: Because the results 
generated by the genetic testing included in this section are not 
currently anticipated to have clinical relevance to the patient or their 
family members, the genetic results will not be disclosed to the 
patients or their physicians. If at any time, genetic results are obtained 
that may have clinical relevance, IRB review and approval will be 
sought regarding the most appropriate manner of disclosure and 
whether or not validation in a Food and Drug Administration (FDA) 
Clinical Laboratory Improvement Amendments (CLIA)-certified 
setting will be required. Sharing of research data with individual 
patients should only occur when data have been validated by multiple 
studies and testing has been done in CLIA-approved laboratories. 
10.3.6 For analysis of MCP class, all assays will be performed on residual 
formalin-fixed, paraffin embedded (FFPE) tissue remaining after 
pathological diagnosis.  Representative hemotoxylin and eosin 
sections will be used to identify tumor content by an M.D. Anderson 
Neuropathologist. FFPE-derived RNA and DNA will be prepared using 
the MasterPure Complete DNA and RNA purification kit (Epicentre 
Biotechnologies, Madison, WI) following deparaffinization using 
Citrisolve (Amity International, Anderson,SC).  MGMT promotor 
methylation and G-CIMP status will be determined by bisulfite 
conversion of DNA and real-time PCR amplification.  IDH1 status will 
be determined from the medical record or by direct sequencing when 
necessary. 19-gene mRNA signature will be determined by real-time 
PCR following reverse transcription of mRNA 
 
 
11.0 Criteria for Removal from the Study 
 
11.1 Analysis will be by intention-to-treat and those patients who withdraw from 
the study after randomization, but prior to receiving treatment will be tracked 
to ensure there is no bias introduced into the study. 
11.2 Patients who do not complete the assigned treatment will be recorded and 
followed.  These patients can be treated by best medical therapy as per the 
judgment of the treating physicians.   
 

2013-0097 
March 1, 2019 
Version 15 
Page 20 
12.0 Statistical Considerations 
 
12.1 Randomization procedure:  A stratified block randomization procedure will be 
used.   Randomization will be performed using CORe. The randomization strata 
are as defined above in section 7.0, and the block size will be 6.  Patients who 
withdraw from the study after randomization, but prior to receiving treatment 
will be considered a cancel and replaced. 
12.2 Sample size: With IMRT the cognitive function failure rate at 4 months is 45%, 
based off of comparative analyses of the cognitive failure rate of RTOG 0614 
and compared to the cognitive impairment seen on RTOG 0525; we hope to 
demonstrate that IMPT can achieve a cognitive function failure rate at 4 months 
of only 30%. We assume the time to cognitive failure in each treatment arm 
follows an exponential distribution. A cognitive failure rate of 45% at 4 months 
then implies a median time to cognitive failure of 4.6 months, while a cognitive 
failure rate of 30% at 4 months implies a median time to cognitive failure of 7.8 
months. 
 
We will use a 1-sided significance level of 0.20 as suggested by Rubinstein et 
al. [51]for phase II screening trials. We expect to enroll 2 patients per month, 
and we will randomize 60 evaluable patients (30 to each treatment arm). We 
will have 80% power to detect an improvement in cognitive failure at 4 
months from 45% in the IMRT arm to 30% in the IMPT arm. We expect to 
observe 43 events, and the analysis will be performed once we have observed 
these events. We define evaluable patients as those who have received the 
assigned treatment and completed baseline and at least one follow-up 
neurocognitive testing.  We expect we will need an over accrual of 33% to 
account for those patients not evaluable.  Therefore the target total enrollment 
sample size is 90 patients to accrue a total of 60 evaluable patients.  We expect 
to observe 43 events, and we expect the trial to take 41 months to observe 
these events.    
12.3 Primary Analysis: The analysis will be performed on the intention-to-treat 
principle. Considering those patients who are not evaluable as treatment 
failures.  We will use the methods of Gooley et al. [52]to estimate the 
cumulative incidence of cognitive failure in each treatment arm, considering 
progressive disease and death before cognitive failure as competing events. We 
will estimate the cumulative incidence of cognitive failure at 4 months with 
95% confidence intervals. We will use the methods of Fine and Gray [53]to test 
for a difference between treatment arms with respect to the cumulative 
incidence of cognitive failure, considering progressive disease and death before 
cognitive failure as competing events. Our model will include treatment arm 
and the stratification factors used at randomization.  
12.4 Secondary Analysis: 
We will repeat the primary analysis on only those patients considered 
evaluable. All the secondary analyses described below will be performed using 
all patients as well as using only evaluable patients.  We will estimate the 
cumulative incidence of local failure using the methods of Gooley et al. 

2013-0097 
March 1, 2019 
Version 15 
Page 21 
considering death as a competing event. We will model the time to local failure 
using the methods of Fine and Gray to test for differences between treatment 
arms, considering death as a competing event. Our model will include 
treatment arm and the stratification factors used at randomization, as well as 
selected dosimetric parameters. We will similarly analyze time to distant 
failure. 
 
We will use the product limit estimator of Kaplan and Meier [54] to estimate 
overall survival stratified by treatment arm. We will also use Cox proportional 
hazards regression [55]to model overall survival as a function of treatment 
arm and the stratification factors used at randomization. 
 
We will use descriptive statistics to summarize by treatment arm the quality of 
life data at each assessment time. We will also use boxplots to summarize the 
quality of life data by treatment arm at each assessment time. We will model 
the quality of life data using mixed effects regression methods with repeated 
measures. The model will include treatment arm, selected dosimetric 
parameters, baseline cognitive function, location of the primary tumor (left vs. 
right hemisphere, if bilateral disease is present, location will be determined by 
the hemisphere with highest burden of disease), and the stratification factors 
used at randomization as fixed effects and patient as a random effect. We will 
similarly analyze the cognitive tests.  For nearly all the prior mentioned 
analyses we will also plan to conduct an as-treated analysis. 
 
We will tabulate by treatment arm the adverse events by grade and 
relationship to treatment. 
 
We will use logistic regression methods to model the logit of the probability of 
neurocognitive decline as function of ApoE (i.e., Apo E2, Apo E3, Apo E4) 
genotyping, inflammatory markers (i.e., IL-1, IL-6, TNF-α), and hormone 
growth factors (i.e., glucocorticoids, gonadal steroids, growth hormone, human 
chorionic gonadotrpin, insulin-like growth factor-1, neuronal growth factor). 
 
Determination of MCP class will be determined by RPA analysis using results 
of MGMT, IDH1, G-CIMP, and mRNA assays as well as RTOG RPA class.  We will 
use descriptive statistics to report class distributions overall and by treatment 
arm.  Survival by classes will be visualized on Kaplan/Meier plots, compared 
by the logrank test.  The Cox proportional hazards regression will be used to 
model MCP classification, adjusting for treatment arm and stratification 
factors.   
 
13.0 Data and Protocol Management 
13.1 To ensure protocol compliance, the principal investigator, treating radiation 
oncologist, study neuroradiologist and research nurse will review the patient 
data and MRI films prior to randomization. All required pretreatment data 

2013-0097 
March 1, 2019 
Version 15 
Page 22 
should be available before a decision to enroll the patient on the protocol is 
made. 
13.2 All data with the exception of the neuropsychological data will be collected by 
the research nurse in charge of the protocol. This includes pretreatment, 
treatment, and post treatment data.  The neuropsychological data will be 
collected by members of the Section of Neuropsychology.  Dr. Wefel will 
maintain a study specific database containing the cognitive outcomes.  The 
medical and neuropsychological databases will be integrated by the study 
statistician at the time of analysis and/or to prepare for MDACC DSMB review.   
The study chairman will act as the final arbitrator of all study parameters 
should a difference of opinion exist. Patients who meet eligibility criteria will be 
registered in CORe.  
13.3 De-identified DICOM images and matched clinical variables will be shared with 
Dr. Thomas Yankeelov, PhD, University of Texas at Austin, Biomedical 
Engineering, TX, US; using secured M.D. Anderson Box cloud. The purpose of 
this collaboration is to spearhead an effort to leverage advanced imaging 
modalities, including multi-parametric and functional MRI to identify clinically 
applicable non-invasive means of characterizing radiation-induced normal 
brain injury and subsequent prediction of patterns of cognitive side effects. 
13.4 De-identified DICOM images and matched clinical variables will be shared with 
Dr. Arvind Rao, PhD, University of Michigan, Department of Computational 
Medicine & Bioinformatics; using secured M.D. Anderson Box cloud. The 
purpose of this collaboration is to spearhead an effort to leverage advanced 
imaging modalities, including longitudinal multi-parametric and functional MRI 
to identify clinically applicable non-invasive means of characterizing patterns of 
tumor response to radiation treatment. 
13.5 Imaging data may be shared with Björn Hårdemark at RaySearch 
Laboratories in order to analyze using advanced imaging tools. All patient 
data will be de-identified according the RSNA’s MIRC protocols and using 
MIRC specified software. This tool de-identifies all DICOM tags that can 
identify a patient as an individual by replacing them with a randomly 
generated number or discarding their value all together.  Following de-
identiftication, the data is compressed and uploaded to a secure BOX 
repository (supported by MD Anderson), and collaborators will be given 
instructions on how to access the data. MD Anderson will have primary 
oversight over data and any future use of data must be in the context of an 
IRB approved protocol. 
  
14.0 Reporting Requirements 
 
14.1 Radiation using either photon or proton technique has known associated risks, 
including tumor swelling, neurological decline, edema, and radiation necrosis.  
Nonetheless, radiation is considered standard of care.  Adverse treatment 
reactions will be reported to the IRB. Standard monitoring procedures as noted 
above to detect and treat postoperative complications will be followed.  

2013-0097 
March 1, 2019 
Version 15 
Page 23 
14.2 All attempts will be made to preserve patients’ confidentiality. Patient records 
will be kept electronically or in secure file cabinets and handled only by 
responsible personnel. 
14.3 Study progress and analyses of safety data will be presented to the MDACC 
DSMB on an annual basis, or as requested. 
15.0 References 
 
1. 
DeAngelis, L.M., Brain tumors. . New England Journal of Medicine, 2001. 344(2): p. 
114-23. 
2. 
Stupp, R., et al., Effects of radiotherapy with concomitant and adjuvant temozolomide 
versus radiotherapy alone on survival in glioblastoma in a randomised phase III study: 
5-year analysis of the EORTC-NCIC trial. Lancet Oncology, 2009. 10(5): p. 459-66. 
3. 
Brown, P.D., et al., The neurocognitive effects of radiation in adult low-grade glioma 
patients. Neuro-Oncology, 2003. 5(3): p. 161-7. 
4. 
Laack, N.N. and P.D. Brown, Cognitive sequelae of brain radiation in adults. Seminars 
in Oncology, 2004. 31(5): p. 702-13. 
5. 
Khuntia, D., et al., Whole-brain radiotherapy in the management of brain metastasis. 
Journal of Clinical Oncology, 2006. 24(8): p. 1295-304. 
6. 
Mizumoto, M., et al., Phase I/II trial of hyperfractionated concomitant boost proton 
radiotherapy for supratentorial glioblastoma multiforme. Int J Radiat Oncol Biol Phys, 
2010. 77(1): p. 98-105. 
7. 
Combs, S.E., et al., Heidelberg Ion Therapy Center (HIT): Initial clinical experience in 
the first 80 patients. Acta Oncol, 2010. 49(7): p. 1132-40. 
8. 
Moertel, H., et al., Effects of low energy protons on clonogenic survival, DSB repair and 
cell cycle in human glioblastoma cells and B14 fibroblasts. Radiotherapy & Oncology, 
2004. 73 Suppl 2: p. S115-8. 
9. 
Rosenschold, P.M., et al., Photon and proton therapy planning comparison for 
malignant glioma based on CT, FDG-PET, DTI-MRI and fiber tracking. Acta Oncologica, 
2011. 50(6): p. 777-83. 
10. 
Merchant, T.E., et al., Proton versus photon radiotherapy for common pediatric brain 
tumors: comparison of models of dose characteristics and their relationship to 
cognitive function. Pediatric Blood & Cancer, 2008. 51(1): p. 110-7. 
11. 
Fitzek, M.M., et al., Accelerated fractionated proton/photon irradiation to 90 cobalt 
gray equivalent for glioblastoma multiforme: results of a phase II prospective trial. 
Journal of Neurosurgery, 1999. 91(2): p. 251-60. 
12. 
DeAngelis, L.M., Brain tumors. N Engl J Med, 2001. 344(2): p. 114-23. 
13. 
Laperriere, N., L. Zuraw, and G. Cairncross, Radiotherapy for newly diagnosed 
malignant glioma in adults: a systematic review. Radiotherapy & Oncology, 2002. 
64(3): p. 259-73. 
14. 
Stupp, R., et al., Radiotherapy plus concomitant and adjuvant temozolomide for 
glioblastoma. N Engl J Med, 2005. 352(10): p. 987-96. 
15. 
Torres, I.J., et al., A longitudinal neuropsychological study of partial brain radiation in 
adults with brain tumors. Neurology, 2003. 60(7): p. 1113-8. 
16. 
Taylor, B.V., et al., Effects of radiation and chemotherapy on cognitive function in 
patients with high-grade glioma. J Clin Oncol, 1998. 16(6): p. 2195-201. 

2013-0097 
March 1, 2019 
Version 15 
Page 24 
17. 
Brown, P.D., et al., Detrimental effects of tumor progression on cognitive function of 
patients with high-grade glioma. J Clin Oncol, 2006. 24(34): p. 5427-33. 
18. 
Kiebert, G.M., et al., Quality of life after radiation therapy of cerebral low-grade 
gliomas of the adult: results of a randomised phase III trial on dose response (EORTC 
trial 22844). EORTC Radiotherapy Co-operative Group. Eur J Cancer, 1998. 34(12): p. 
1902-9. 
19. 
Chang, E.L., et al., Neurocognition in patients with brain metastases treated with 
radiosurgery or radiosurgery plus whole-brain irradiation: a randomised controlled 
trial. Lancet Oncol, 2009. 10(11): p. 1037-44. 
20. 
Combs, S.E., Radiation therapy. Recent Results in Cancer Research, 2009. 171: p. 
125-40. 
21. 
Arvold, N.D., et al., Projected second tumor risk and dose to neurocognitive structures 
after proton versus photon radiotherapy for benign meningioma. Int J Radiat Oncol 
Biol Phys, 2012. 83(4): p. e495-500. 
22. 
Caselli, R.J., et al., Longitudinal modeling of age-related memory decline and the APOE 
epsilon4 effect. The New England journal of medicine, 2009. 361(3): p. 255-63. 
23. 
Teunissen, C.E., et al., Biochemical markers related to Alzheimer's dementia in serum 
and cerebrospinal fluid. Neurobiology of aging, 2002. 23(4): p. 485-508. 
24. 
Helbecque, N. and P. Amouyel, Commonalities between genetics of cardiovascular 
disease and neurodegenerative disorders. Current opinion in lipidology, 2004. 15(2): 
p. 121-7. 
25. 
Villasana, L., et al., Passive avoidance learning and memory of 56Fe sham-irradiated 
and irradiated human apoE transgenic mice. Radiatsionnaia biologiia, radioecologiia 
/ Rossiiskaia akademiia nauk, 2008. 48(2): p. 167-70. 
26. 
Crawford, F., et al., Apolipoprotein E-genotype dependent hippocampal and cortical 
responses to traumatic brain injury. Neuroscience, 2009. 159(4): p. 1349-62. 
27. 
Yaffe, K., et al., Inflammatory markers and cognition in well-functioning African-
American and white elders. Neurology, 2003. 61(1): p. 76-80. 
28. 
Krabbe, K.S., M. Pedersen, and H. Bruunsgaard, Inflammatory mediators in the 
elderly. Experimental gerontology, 2004. 39(5): p. 687-99. 
29. 
Cacabelos, R., et al., Serum tumor necrosis factor (TNF) in Alzheimer's disease and 
multi-infarct dementia. Methods and findings in experimental and clinical 
pharmacology, 1994. 16(1): p. 29-35. 
30. 
Blum-Degen, D., et al., Interleukin-1 beta and interleukin-6 are elevated in the 
cerebrospinal fluid of Alzheimer's and de novo Parkinson's disease patients. 
Neuroscience letters, 1995. 202(1-2): p. 17-20. 
31. 
Tarkowski, E., et al., Intracerebral production of tumor necrosis factor-alpha, a local 
neuroprotective agent, in Alzheimer disease and vascular dementia. Journal of clinical 
immunology, 1999. 19(4): p. 223-30. 
32. 
Martinez, M., et al., Increased cerebrospinal fluid fas (Apo-1) levels in Alzheimer's 
disease. Relationship with IL-6 concentrations. Brain research, 2000. 869(1-2): p. 
216-9. 
33. 
Foster, T.C., Biological markers of age-related memory deficits: treatment of senescent 
physiology. CNS drugs, 2006. 20(2): p. 153-66. 
34. 
Tuszynski, M.H., et al., A phase 1 clinical trial of nerve growth factor gene therapy for 
Alzheimer disease. Nature medicine, 2005. 11(5): p. 551-5. 

2013-0097 
March 1, 2019 
Version 15 
Page 25 
35. 
Ding, Q., et al., Insulin-like growth factor I interfaces with brain-derived neurotrophic 
factor-mediated synaptic plasticity to modulate aspects of exercise-induced cognitive 
function. Neuroscience, 2006. 140(3): p. 823-33. 
36. 
Curran, W.J., Jr., et al., Recursive partitioning analysis of prognostic factors in three 
Radiation Therapy Oncology Group malignant glioma trials. J Natl Cancer Inst, 1993. 
85(9): p. 704-10. 
37. 
Li, J., et al., Validation and Simplification of the Radiation Therapy Oncology Group 
Recursive Partitioning Analysis Classification for Glioblastoma. Int J Radiat Oncol Biol 
Phys, 2010. 
38. 
Hegi, M.E., et al., MGMT gene silencing and benefit from temozolomide in glioblastoma. 
N Engl J Med, 2005. 352(10): p. 997-1003. 
39. 
Colman, H., et al., A multigene predictor of outcome in glioblastoma. Neuro Oncol, 
2010. 12(1): p. 49-57. 
40. 
Parsons, D.W., et al., An integrated genomic analysis of human glioblastoma 
multiforme. Science, 2008. 321(5897): p. 1807-12. 
41. 
Noushmehr, H., et al., Identification of a CpG island methylator phenotype that defines 
a distinct subgroup of glioma. Cancer Cell, 2010. 17(5): p. 510-22. 
42. 
Zhang, X., et al., Intensity-modulated proton therapy reduces the dose to normal tissue 
compared with intensity-modulated radiation therapy or passive scattering proton 
therapy and enables individualized radical radiotherapy for extensive stage IIIB non-
small-cell lung cancer: a virtual clinical study. Int J Radiat Oncol Biol Phys, 2010. 
77(2): p. 357-66. 
43. 
Meyers, C.A. and P.D. Brown, Role and relevance of neurocognitive assessment in 
clinical trials of patients with CNS tumors. J Clin Oncol, 2006. 24(8): p. 1305-9. 
44. 
Herman, M.A., et al., Neurocognitive and functional assessment of patients with brain 
metastases: a pilot study. Am J Clin Oncol, 2003. 26(3): p. 273-9. 
45. 
Benedict, R.H.B., et al., Hopkins verbal learning test - Revised: Normative data and 
analysis of inter-form and test-retest reliability. Clinical Neuropsychologist, 1998. 
12(1): p. 43-55. 
46. 
Lezak MD, H.D., Loring DW, Neuropsychological Assessment. 2004, New York, NY: 
Oxford University Press. 
47. 
Benton, A., Hamsher KdeS, Multilingual Aphasia Examination. 1989, Iowa City, IA: 
AJA Associates. 
48. 
Cleeland, C.S., et al., Assessing symptom distress in cancer patients: the M.D. Anderson 
Symptom Inventory. Cancer, 2000. 89(7): p. 1634-46. 
49. 
Taphoorn, M.J., et al., An international validation study of the EORTC brain cancer 
module (EORTC QLQ-BN20) for assessing health-related quality of life and symptoms 
in brain cancer patients. Eur J Cancer, 2010. 46(6): p. 1033-40. 
50. 
Wen, P.Y., et al., Updated response assessment criteria for high-grade gliomas: 
response assessment in neuro-oncology working group. J Clin Oncol, 2010. 28(11): p. 
1963-72. 
51. 
Rubinstein, L.V., et al., Design issues of randomized phase II trials and a proposal for 
phase II screening trials. J Clin Oncol, 2005. 23(28): p. 7199-206. 
52. 
Gooley, T.A., et al., Estimation of failure probabilities in the presence of competing 
risks: new representations of old estimators. Stat Med, 1999. 18(6): p. 695-706. 

2013-0097 
March 1, 2019 
Version 15 
Page 26 
53. 
Fine, J. and R. Gray, A proportional hazards model for the subdistribution of a 
competing risk. JASA, 1999. 94: p. 496-509. 
54. 
Kaplan, E.L. and P. Meier, Nonparametric estimation from incomplete observations. 
JASA, 1958. 53: p. 457-481. 
55. 
Cox, D.R., Regression models and life tables (with discussion). JRSS B, 1972. 34: p. 187-
220.