|Year : 2018 | Volume
| Issue : 3 | Page : 97-103
Ongoing evolution of response assessment in glioma: Where do we stand?
Li Yi1, Haolang Ming2, Shengping Yu2, Bingcheng Ren2, Xuejun Yang1
1 Department of Neurosurgery, Tianjin Medical University General Hospital; Laboratory of Neuro-Oncology, Tianjin Neurological Institute, Tianjin, China
2 Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China
|Date of Web Publication||29-Jun-2018|
Dr. Xuejun Yang
154 An-shan Road, Tianjin 300052
Source of Support: None, Conflict of Interest: None
The investigation and development of recently introduced agents or radiological measurements caused emergent misunderstandings to the response assessment of glioma. To date, the classical Macdonald criteria and the response assessment of neuro-oncology (RANO) criteria have been used successively for the evaluation of glioma outcome. However, ongoing efforts on complementary assessments are necessary to combat this malignancy. In this review, we highlight the shortcomings of the current criteria and introduce the initiative effort of RANO guideline and its offspring. We also discuss some future barriers for accurate assessment of treatment response in glioma.
Keywords: Assessment, glioma, neuro-oncology, response assessment
|How to cite this article:|
Yi L, Ming H, Yu S, Ren B, Yang X. Ongoing evolution of response assessment in glioma: Where do we stand?. Glioma 2018;1:97-103
|How to cite this URL:|
Yi L, Ming H, Yu S, Ren B, Yang X. Ongoing evolution of response assessment in glioma: Where do we stand?. Glioma [serial online] 2018 [cited 2022 Jun 29];1:97-103. Available from: http://www.jglioma.com/text.asp?2018/1/3/97/235648
| Introduction|| |
Despite promising preliminary progress made in central nervous system (CNS) tumor, clinical trial expansion, and drug development, especially concerning glioblastoma multiforme (GBM), improvements toward clinical outcomes have been rather modest.,,, The complex heterogeneity, plasticity, and therapeutic resistance of these malignancies may largely account for this disappointing phenomenon.,, The incomplete response assessment system of clinical outcomes is another underlying cause for the confounding of true prognostic benefits expected in patients with brain tumors. For example, the use of newly introduced drugs or radiologic techniques can lead to unexpected imaging changes that mimic a false progression or remission regarding tumor status. Alternatively, a misleading imaging finding may cause discrepancies in neuro-oncology response assessment and criteria standards in clinical trials, which may eventually impede the process of drug development. Considering these circumstances, the response assessment of neuro-oncology (RANO) has been formed based on the previous Macdonald criteria to offer updated guidelines. It also intends to help relieve the discrepancies between radiographic changes and clinical practices and therefore to translate drug investigation into clinical benefit.
| Limitations of Current Assessments|| |
In 1990, Macdonald et al. reported criteria to assess tumor response in patients with high-grade gliomas (HGGs). These criteria, which rely primarily on bi-dimensional tumor measurements made on computed tomography or magnetic resonance imaging (MRI) scans, clinical status, and change in corticosteroid requirement following treatment, marked a transition from a subjective interpretation of clinical and radiologic changes toward more objective radiologically based criteria. The Macdonald criteria consider the enhancing tumor area as the primary measure and also consider the use of steroids and changes in the neurologic status. According to the Macdonald criteria, tumor progression is defined as a 25% increase in the size of the contrast-enhancing lesion. Due to the objectivity of the Macdonald criteria in determining the response to therapy, these criteria were widely accepted in different clinical trials where they were used to make comparisons across different therapeutic interventions.
Nevertheless, with the advent and usage of novel therapeutics, various latent limitations of these criteria began emerging. For example, the Macdonald criteria only addressed the contrast-enhancing component of the tumor, which is only a surrogate to true tumor growth/activity. Specifically, the enhancement may also reflect a disrupted blood–brain barrier (BBB) after corticosteroid administration, as well as inflammation, postsurgical changes, and radiation necrosis.,,,, Both pseudoprogression and pseudoresponse (i.e., an increase in the nontumoral enhancing area and a decrease in the enhancing area, respectively) highlighted that enhancement by itself is not a true measurement of tumor activity., As a result, such limitations may lead to premature discontinuation of an actually effective therapeutic agent, thereby producing a “vicious circle” between drug development and clinical practice.
| Pseudoprogression After Radiotherapy and Temozolomide Chemotherapy|| |
Since the introduction of radiotherapy (RT) plus concomitant and adjuvant temozolomide (TMZ) as the standard-of-care for patients with glioblastoma, there has been an increasing awareness of progressive and enhancing lesions on MRI, noted immediately after the treatment., As these lesions mimic tumor progression, the resulting subacute radiation effects have been termed pseudoprogression.,,, Pseudoprogression is defined as a transient increase in contrast enhancement with or without associated T2-weighted and fluid-attenuated inversion recovery (FLAIR) changes in the absence of true tumor progression. It is seen in up to 50% of patients with glioblastoma who receive RT, both with and without TMZ., Early studies described this occurrence in patients treated with hyperfractionated RT to the brainstem and in cerebral gliomas after intra-arterial carmustine chemotherapy, administered alone or with RT., These findings implied that this event might occur more frequently in patients who are treated intensively. Interestingly, some studies have found an association between the incidence of pseudoprogression and increased survival, perhaps because pseudoprogression represents an active “inflammatory” response against the tumor. Methylation of the O 6-methylguanine-DNA methyltransferase promoter additionally enhances the risk of developing pseudoprogression. Although this phenomenon may be associated with neurological decline and increased steroid requirements, it typically resolves spontaneously within 3 months even if treatment is continued. The physiological mechanisms behind these events have not been fully understood. However, it is likely that chemo-RT prompts a higher degree of tumor cell killing, as well as endothelial cell killing. This increased cell killing might lead to the destruction of the BBB and secondary reactions, including edema and abnormal vessel permeability in the tumor region, mimicking tumor progression, rather than subsequent early treatment-related necrosis in some patients and milder subacute RT reactions in others.
| Pseudoresponse After Antiangiogenic Agent Treatment|| |
Targeting angiogenesis in glioblastoma through inhibition of vascular endothelial growth factor (VEGF)-mediated signaling (bevacizumab, aflibercept) or integrin function (cilengitide) has been a major focus in drug development. These agents have shown a rapid decrease in contrast enhancement with a tremendous response rate and increased progression-free survival (PFS). However, there has been only a rather modest effect on overall survival (OS).
Contrast-enhanced MRI was conducted as the basic measurement for determining response in those trials. Improvements were seen as early as 18 days after initiating therapy with bevacizumab and were associated with clinical benefits in some patients. Moreover, in 20%–60% of patients who received VEGF-targeted therapy (i.e., bevacizumab and cediranib), a decrease in the nonenhancing portion of the tumor was identified in T2/FLAIR sequences of the follow-up MRI examinations. This suggested a tumor reduction despite the modest effect on patient outcome. Such phenomenon of a decrease in contrast enhancement without a true reduction of tumor burden is termed as pseudoresponse. The underlying mechanism of pseudoresponse is believed to be attributed to normalization of an abnormally permeable BBB and circumventing effects of angiogenesis inhibition., It has been demonstrated that a very rapid change will occur within hours after antiangiogenic treatment, which produces a normalization of the BBB as shown on MRI. This decreased pattern regarding contrast enhancement will last for just a few days or weeks, after which other routes of tumor compensation may take precedence and even stimulate the so-called vessel co-option. Interestingly, the vascular normalization has been shown to be correlated with increased OS and PFS in glioblastoma patients, while an early postbevacizumab progression would be highly correlated with reduced OS and serve as a useful MRI biomarker for failed anti-VEGF therapy.
| Delayed Responses and Therapy-Induced Inflammation After Immunotherapy|| |
In the past few years, immunotherapy has provided promising clinical advances in the treatment of several tumors. The Food and Drug Administration (FDA) approved the first two checkpoint inhibitors that target cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) in March 2011 (ipilimumab) and programmed cell death protein 1 (PD-1, pembrolizumab and nivolumab) in the late 2014 and March 2015 for metastatic melanoma and nonsmall cell lung cancer.,, T-lymphocytes are the most critical immune cell type to infiltrate tumors, and while advances in T-cell checkpoint therapy are beginning to reach clinical relevance in GBM, corresponding improvement in effective monitoring of the immune response is needed.,,, As the immunotherapy of GBM was not associated with pseudoresponse phenomena, the decreased size of an enhancing lesion is a straightforward indication of a true antitumor effect., In contrast, an accurate differentiation of contrast enhancement regarding progressive imaging lesion was frequently found in patients treated with immune-targeted therapies. In addition, the increase in tumor burden was not always true tumor progression as response can occur even after radiological progression., There are two main interpretations that exist for a possible disconnect between early imaging findings and subsequent therapeutic benefit. First, effective immune responses need time to evolve, and early imaging might reflect true progressive disease on the basis of continued tumor growth before the stimulation of the immune response, as well as the development of new lesions. Abnormal imaging findings can also represent successful stimulation of the immune response because movement of tumor-infiltrating lymphocytes into the tumor can induce an apparent increase in the tumor size.,, Second, the immune-mediated inflammatory response in the areas of macroscopic and microscopic infiltrative tumor may also mimic the radiological features of tumor progression with increased enhancement and edema.,,
| The Response Assessment of Neuro-Oncology Criteria and Its Offspring in Glioma|| |
Recognizing the challenge in determining response to antiangiogenic agents in the treatment of malignant glioma, the response assessment in neuro-oncology (RANO) working group was formed and in 2010 published the updated response assessment criteria for use in clinical trials of HGG. The original effort of RANO was focused on critically appraising the strengths and shortcomings of the Macdonald criteria with the additional goal of updating new criteria specific for the treatment response assessment., Since then, RANO has expanded to create working groups that are focused on other tumors, including brain metastases, leptomeningeal metastases, spinal tumors, meningiomas, and pediatric brain tumors, as well as other clinical trial end points, such as clinical outcome assessments, seizures, corticosteroid use, and positron emission tomography imaging to improve outcome criteria for neuro-oncology over the last 8 years. Although additional refinements might be needed, efforts by RANO have been extensively adopted and are increasingly being used in neuro-oncology trials. To date, the RANO working group is an international volunteer collaboration of neuro-oncologists, medical oncologists, radiation oncologists, neurosurgeons, neuro-radiologists, and regulatory groups (among others), who are dedicated to developing objective and tumor-specific response criteria for various tumor subtypes., Here, we briefly list the major aspects of the updated additional criteria that were included in the response assessment in neuro-glioma [Table 1].
|Table 1: Summarize of the response assessment of neuro.oncology response criteria for glioma|
Click here to view
Response assessment of neuro-oncology – High-grade gliomas
The RANO criteria built on the Macdonald criteria using two-dimensional tumor measurements, which included a definition of progression for patients being considered for enrolment in clinical trials (≥25% increase in the product of perpendicular diameters compared with baseline or best response); definitions for measurable disease (two perpendicular diameters of at least 10 mm, visible on two or more axial slices that are preferably, at most, 5 mm apart with 0 mm skip); and allowance of up to five target lesions.,
To address pseudoprogression, the RANO criteria recommended that within the first 12 weeks (3 months) after irradiation, patients should be excluded from clinical trials for recurrent disease unless progression is clearly outside the radiation field, or there is clear histologic documentation of progression.,
To account for pseudoresponses after antiangiogenic therapies, patients who achieved partial or complete responses required a confirmatory scan at least 4 weeks before they were considered as true responses. In addition, the RANO criteria not only defined progression as a 25% increase in contrast-enhancing area over baseline or best response but also included any significant enlargement of nonenhancing T2/FLAIR signal on MRI that was attributed to tumor growth.
Of importance, there were also recommendations for dealing with equivocal imaging changes, which allowed patients to stay in the study with a repeat scan in ≥4 weeks. If progression is subsequently confirmed, the time of progression is backdated to the time point at which the issue was first suspected. This prevents patients from being discontinued prematurely from studies when imaging findings are equivocal.
Response assessment of neuro-oncology – Low-grade gliomas
Low-grade glioma (LGG) refers to WHO Grade I and Grade II tumors, which is a uniformly fatal disease of young adults (mean age, 41 years), with survival averaging approximately 7 years. The prognosis of LGG mainly depends on histology (astrocytic vs. oligodendroglial features), presence/absence of molecular markers (i.e., 1p/19q co-deletion, isocitrate dehydrogenase mutations), and other clinical risk factors (age, performance status, and seizure activity).
Since LGGs represent a benign mass compared to HGGs, the response criteria that are defined for LGG will differ substantially. Unlike HGGs, the LGG response criteria assess T2/FLAIR rather than contrast enhancement as these tumors rarely enhance. In addition, because these tumors grow very slowly, it will take a long time to reach a 25% increased level in lesion size. Furthermore, improved seizure control, symptom burden, and quality of life (QoL) are requisite clinical orders of treatment feedback despite stable imaging findings.,,
Considering these factors, the RANO-LGG criteria were published. The radiological assessment is mainly based on T2/FLAIR changes although new or increased contrast enhancement is recognized as an indicator of transformation to a higher grade tumor. In addition, the RANO-LGG criteria introduce the category of minor response, which is characterized as a 25%–49% decrease in size of the T2/FLAIR hyperintensive lesion. It also recommended more detailed clinical response criteria using a composite score of neurological function, seizure activity, neurocognitive functioning, symptom burden, and QoL.,,
Immunotherapy-response assessment in neuro-oncolgy
As a promising area in the treatment of neuro-oncological malignancies, immunotherapy-treated tumors exhibit delayed responses or therapy-induced inflammation-related radiological changes similar to pseudoprogression.,, In this circumstance, a refinement of the response assessment criteria for patients undergoing immunotherapy is warranted., The immunotherapy response assessment in neuro-oncolgy (iRANO) guidelines incorporate previous criteria defined by the RANO working group to specify complete response, partial response, minor response, stable disease, progressive disease, and nonevaluable disease for patients with malignant gliomas, LGGs, and brain metastases. The critical part of the iRANO criteria is specific additional standards for the confirmation of disease progression in patients with neuro-oncological malignancies undergoing immunotherapy. Moreover, the iRANO criteria advocate for the definition of radiographic progression in appropriate patients determined by clinical status and time from initiation of immunotherapy.
Based on RANO criteria and the Macdonald criteria, the iRANO interpreted the confirmation of radiographic progression to define progressive disease and the appropriate time to confirm radiographic progression. Immune-related response criteria guidelines state that an early increase in lesion size or new lesions cannot define progressive disease unless further progressive changes are confirmed upon follow-up imaging, provided that patients do not have a significant clinical decline.,, Specifically, the iRANO working group recommends a 6-month immunotherapy window for patients without clinical decline, where early progressive imaging findings do not preclude subsequent clinical benefit. In addition, repeat imaging needs to be performed after 3 months for comparison with the scan of the initial tumor to assess potential disease progression. Only if the repeat assessment confirms disease progression, should the patient then retrospectively be classified as having progressive disease and the treatment should be discontinued. If the repeat imaging shows stabilization or reduction in tumor burden, treatment should be continued. In addition, tissue acquisition is thought to be feasible if there is any difficulty in clarifying the cause of the progressive imaging findings.
| Neurologic Assessment In Neuro-Oncology|| |
Clinical status is also a major assessment that measures the benefits of the treatment based on the patients' QoL, neurologic status, or function. The current clinical status assessment includes the Karnofsky performance status, MD Anderson Symptom Inventory brain tumor module, and Mini-Mental State Examination.,, However, while these assessment tools were used globally and might correlate with OS, they lack specificity and reproducibility and may not accurately capture the neurologic changes of patients. In this context, the Neurologic Assessment in Neuro-Oncology (NANO) working group formed and developed specific parameters to measure the clinical status of patients with brain tumors. The NANO scale evaluates nine major domains of neurologic function that are most relevant to patients with supratentorial, infratentorial, and brainstem tumors. Tests include gait, strength, upper extremity ataxia, sensation, visual fields, facial strength, language, level of consciousness, and behavior.,
The neurological scale integrated into the RANO and the classical Macdonald criteria specifies the priority of clinical status in overall assessment and provides a much more comprehensive assessment system of treatment outcome. To confirm its repeatability, a prospective multinational study was conducted to assess routine office visits to determine the interobserver variability and feasibility. An interobserver agreement rate ranging from 90.7% to 96.4% and a median assessment time of 4 min were observed. Further efforts aim to assess its validity and utility relative to radiographic and overall outcome.,
| End Point Selection|| |
To identify more effective therapies for these tumors, there is an increasing number of clinical trials being developed and conducted. Nonetheless, the most appropriate study end points to be used in these studies remain subject to further debate, whereas early-phase trials might focus on the identification of a therapeutic signal to guide decisions on further development, and late-phase trials might focus on the confirmation of therapeutic impact by considering clinically meaningful end points.,,, OS is considered the gold standard and most objective study end point. However, its use is limited in studies that investigate tumors characterized by a longer clinical lifespan (e.g., LGG, meningioma), and subsequent salvage treatments that may have an influence on OS could confound the true effect of the investigated agent.,,, Whether PFS can be an appropriate primary end point in phase III trials – or whether OS should be the primary end point in these trials as a matter of principle – is an ongoing discussion in oncology. A recent novel statistical model study found that compared to using either end point alone, considering both OS and earlier events such as PFS would be more robust and efficient for glioblastoma trials.,,
| Future Expectations|| |
Given the emergence of newly advanced imaging modalities such as volumetric tumor measurements, digital subtraction maps, and magnetic resonance spectroscopy, detecting changes in tumor size is becoming more accurate. However, confirmation of these expectations will require time. Moreover, the RANO proposals regarding the immunotherapy, neurological assessment, brain metastases, and leptomeningeal metastases criteria need to be validated in clinical practice and the outcomes must be compared between studies. In addition, it is inevitable that novel therapies and combined medical treatment strategies might cause substantial confusion in the definition of the radiological imaging assessments of clinical status. As to biopsy samples, the gold standard for diagnosis can be difficult to interpret due to the potential heterogeneity of these lesions and the findings of mixed tissues. Nonetheless, it is believed that the different published RANO guidelines, to date, based on the best currently available evidence and updates, would increase the accuracy and efficiency of the early valuation of novel therapies and therefore improve the outcome of CNS malignancies.
Financial support and sponsorship
The research is funded by the National Natural Science Foundation of China (No. 81472352) and Natural Science Foundation of Tianjin City (No. 15JCZDJC36200).
Conflicts of interest
There are no conflicts of interest.
| References|| |
Alexander BM, Galanis E, Yung WK, Ballman KV, Boyett JM, Cloughesy TF, et al.
Brain malignancy steering committee clinical trials planning workshop: Report from the targeted therapies working group. Neuro Oncol 2015;17:180-8.
Guishard AF, Yakisich JS, Azad N, Iyer AKV. Translational gap in ongoing clinical trials for glioma. J Clin Neurosci 2018;47:28-42.
Piccioni DE, Kesari S. Clinical trials of viral therapy for malignant gliomas. Expert Rev Anticancer Ther 2013;13:1297-305.
Prabhu S, Harris F, Lea R, Snape TJ. Small-molecule clinical trial candidates for the treatment of glioma. Drug Discov Today 2014;19:1298-308.
Batchelor TT, Mulholland P, Neyns B, Nabors LB, Campone M, Wick A, et al.
Phase III randomized trial comparing the efficacy of cediranib as monotherapy, and in combination with lomustine, versus lomustine alone in patients with recurrent glioblastoma. J Clin Oncol 2013;31:3212-8.
Jin X, Kim LJ, Wu Q, Wallace LC, Prager BC, Sanvoranart T, et al.
Targeting glioma stem cells through combined BMI1 and EZH2 inhibition. Nat Med 2017;23:1352-61.
Quail DF, Joyce JA. The microenvironmental landscape of brain tumors. Cancer Cell 2017;31:326-41.
Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H, et al.
Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 2014;344:1396-401.
Macdonald DR, Cascino TL, Schold SC Jr., Cairncross JG. Response criteria for phase II studies of supratentorial malignant glioma. J Clin Oncol 1990;8:1277-80.
Sharma M, Juthani RG, Vogelbaum MA. Updated response assessment criteria for high-grade glioma: Beyond the Macdonald criteria. Chin Clin Oncol 2017;6:37.
van den Bent MJ, Vogelbaum MA, Wen PY, Macdonald DR, Chang SM. End point assessment in gliomas: Novel treatments limit usefulness of classical Macdonald's criteria. J Clin Oncol 2009;27:2905-8.
Cairncross JG, Macdonald DR, Pexman JH, Ives FJ. Steroid-induced CT changes in patients with recurrent malignant glioma. Neurology 1988;38:724-6.
Watling CJ, Lee DH, Macdonald DR, Cairncross JG. Corticosteroid-induced magnetic resonance imaging changes in patients with recurrent malignant glioma. J Clin Oncol 1994;12:1886-9.
Kumar AJ, Leeds NE, Fuller GN, Van Tassel P, Maor MH, Sawaya RE, et al.
Malignant gliomas: MR imaging spectrum of radiation therapy- and chemotherapy-induced necrosis of the brain after treatment. Radiology 2000;217:377-84.
Finn MA, Blumenthal DT, Salzman KL, Jensen RL. Transient postictal MRI changes in patients with brain tumors may mimic disease progression. Surg Neurol 2007;67:246-50.
Ulmer S, Braga TA, Barker FG 2nd
, Lev MH, Gonzalez RG, Henson JW, et al.
Clinical and radiographic features of peritumoral infarction following resection of glioblastoma. Neurology 2006;67:1668-70.
Brandsma D, van den Bent MJ. Pseudoprogression and pseudoresponse in the treatment of gliomas. Curr Opin Neurol 2009;22:633-8.
Hygino da Cruz LC Jr., Rodriguez I, Domingues RC, Gasparetto EL, Sorensen AG. Pseudoprogression and pseudoresponse: Imaging challenges in the assessment of posttreatment glioma. AJNR Am J Neuroradiol 2011;32:1978-85.
Stupp R, Mason WP, Van den B, Martin J, Weller M, Fisher B, et al
. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. Clin Med Oncol 2017;2:421-2.
Reuter M, Gerstner ER, Rapalino O, Batchelor TT, Rosen B, Fischl B. Impact of MRI head placement on glioma response assessment. J Neurooncol 2014;118:123-9.
Perry JR, Laperriere N, O'Callaghan CJ, Brandes AA, Menten J, Phillips C, et al.
Short-course radiation plus temozolomide in elderly patients with glioblastoma. N
Engl J Med 2017;376:1027-37.
Neuwelt EA, Ambady P. The impact of pseudoprogression on the current treatment strategy of glioblastoma patients. J Clin Oncol 2015;33: e13055.
Wang S, Martinez-Lage M, Sakai Y, Chawla S, Kim SG, Alonso-Basanta M, et al.
Differentiating tumor progression from pseudoprogression in patients with glioblastomas using diffusion tensor imaging and dynamic susceptibility contrast MRI. AJNR Am J Neuroradiol 2016;37:28-36.
Kebir S, Fimmers R, Galldiks N, Schäfer N, Mack F, Schaub C, et al.
Late pseudoprogression in glioblastoma: Diagnostic value of dynamic O-(2-[18F]fluoroethyl)-L-tyrosine PET. Clin Cancer Res 2016;22:2190-6.
van West SE, de Bruin HG, van de Langerijt B, Swaak-Kragten AT, van den Bent MJ, Taal W.
Incidence of pseudoprogression in low-grade gliomas treated with radiotherapy. Neuro Oncol 2017;19:719-25.
Taal W, Brandsma D, de Bruin HG, Bromberg JE, Swaak-Kragten AT, Smitt PA, et al.
Incidence of early pseudo-progression in a cohort of malignant glioma patients treated with chemoirradiation with temozolomide. Cancer 2008;113:405-10.
Brandsma D, Stalpers L, Taal W, Sminia P, van den Bent MJ. Clinical features, mechanisms, and management of pseudoprogression in malignant gliomas. Lancet Oncol 2008;9:453-61.
Hoffman WF, Levin VA, Wilson CB. Evaluation of malignant glioma patients during the postirradiation period. J Neurosurg 1979;50:624-8.
Brandes AA, Tosoni A, Spagnolli F, Frezza G, Leonardi M, Calbucci F, et al.
Disease progression or pseudoprogression after concomitant radiochemotherapy treatment: Pitfalls in neurooncology. Neuro Oncol 2008;10:361-7.
Gahramanov S, Varallyay C, Tyson RM, Lacy C, Fu R, Netto JP, et al.
Diagnosis of pseudoprogression using MRI perfusion in patients with glioblastoma multiforme may predict improved survival. CNS Oncol 2014;3:389-400.
Brandes AA, Franceschi E, Tosoni A, Blatt V, Pession A, Tallini G, et al.
MGMT promoter methylation status can predict the incidence and outcome of pseudoprogression after concomitant radiochemotherapy in newly diagnosed glioblastoma patients. J Clin Oncol 2008;26:2192-7.
Lin AL, White M, Miller-Thomas MM, Fulton RS, Tsien CI, Rich KM, et al.
Molecular and histologic characteristics of pseudoprogression in diffuse gliomas. J Neurooncol 2016;130:529-33.
Gahrmann R, van den Bent M, van der Holt B, Vernhout RM, Taal W, Vos M, et al.
Comparison of 2D (RANO) and volumetric methods for assessment of recurrent glioblastoma treated with bevacizumab-a report from the BELOB trial. Neuro Oncol 2017;19:853-61.
Norden AD, Young GS, Setayesh K, Muzikansky A, Klufas R, Ross GL, et al.
Bevacizumab for recurrent malignant gliomas: Efficacy, toxicity, and patterns of recurrence. Neurology 2008;70:779-87.
Clarke JL, Chang S. Pseudoprogression and pseudoresponse: Challenges in brain tumor imaging. Curr Neurol Neurosci Rep 2009;9:241-6.
Sorensen AG, Batchelor TT, Zhang WT, Chen PJ, Yeo P, Wang M, et al.
A”vascular normalization index” as potential mechanistic biomarker to predict survival after a single dose of cediranib in recurrent glioblastoma patients. Cancer Res 2009;69:5296-300.
Boxerman JL, Zhang Z, Safriel Y, Larvie M, Snyder BS, Jain R, et al.
Early post-bevacizumab progression on contrast-enhanced MRI as a prognostic marker for overall survival in recurrent glioblastoma: Results from the ACRIN 6677/RTOG 0625 central reader study. Neuro Oncol 2013;15:945-54.
Hodi FS, O'Day SJ, McDermott DF, Weber RW, Sosman JA, Haanen JB, et al.
Improved survival with ipilimumab in patients with metastatic melanoma. N
Engl J Med 2010;363:711-23.
Wolchok JD, Kluger H, Callahan MK, Postow MA, Rizvi NA, Lesokhin AM, et al.
Nivolumab plus ipilimumab in advanced melanoma. N
Engl J Med 2013;369:122-33.
Robert C, Long GV, Brady B, Dutriaux C, Maio M, Mortier L, et al.
Nivolumab in previously untreated melanoma without BRAF mutation. N
Engl J Med 2015;372:320-30.
Chiou VL, Burotto M. Pseudoprogression and immune-related response in solid tumors. J Clin Oncol 2015;33:3541-3.
Antonios JP, Soto H, Everson RG, Moughon D, Orpilla JR, Shin NP, et al.
Immunosuppressive tumor-infiltrating myeloid cells mediate adaptive immune resistance via a PD-1/PD-L1 mechanism in glioblastoma. Neuro Oncol 2017;19:796-807.
McCracken MN, Vatakis DN, Dixit D, McLaughlin J, Zack JA, Witte ON, et al.
Noninvasive detection of tumor-infiltrating T cells by PET reporter imaging. J Clin Invest 2015;125:1815-26.
Müller I, Altherr D, Eyrich M, Flesch B, Friedmann KS, Ketter R, et al.
Tumor antigen-specific T cells for immune monitoring of dendritic cell-treated glioblastoma patients. Cytotherapy 2016;18:1146-61.
Okada H, Weller M, Huang R, Finocchiaro G, Gilbert MR, Wick W, et al.
Immunotherapy response assessment in neuro-oncology: A report of the RANO working group. Lancet Oncol 2015;16:e534-42.
Aquino D, Gioppo A, Finocchiaro G, Bruzzone MG, Cuccarini V. MRI in glioma immunotherapy: Evidence, pitfalls, and perspectives. J Immunol Res 2017;2017:5813951.
Wolchok JD, Hoos A, O'Day S, Weber JS, Hamid O, Lebbé C, et al.
Guidelines for the evaluation of immune therapy activity in solid tumors: Immune-related response criteria. Clin Cancer Res 2009;15:7412-20.
Qin L, Li X, Stroiney A, Qu J, Helgager J, Reardon DA, et al.
Advanced MRI assessment to predict benefit of anti-programmed cell death 1 protein immunotherapy response in patients with recurrent glioblastoma. Neuroradiology 2017;59:135-45.
Ranjan S, Quezado M, Garren N, Boris L, Siegel C, Lopes Abath Neto O, et al.
Clinical decision making in the era of immunotherapy for high grade-glioma: Report of four cases. BMC Cancer 2018;18:239.
Ribas A, Chmielowski B, Glaspy JA. Do we need a different set of response assessment criteria for tumor immunotherapy? Clin Cancer Res 2009;15:7116-8.
Preusser M, Lim M, Hafler DA, Reardon DA, Sampson JH. Prospects of immune checkpoint modulators in the treatment of glioblastoma. Nat Rev Neurol 2015;11:504-14.
Ribas A. Safety and tumor responses with lambrolizumab (anti–PD-1) in Melanoma. N
Engl J Med 2013;369:134-44.
Okada H, Kohanbash G, Zhu X, Kastenhuber ER, Hoji A, Ueda R, et al.
Immunotherapeutic approaches for glioma. Crit Rev Immunol 2009;29:1-42.
Nishino M, Giobbie-Hurder A, Gargano M, Suda M, Ramaiya NH, Hodi FS.
Developing a common language for tumor response to immunotherapy: Immune-related response criteria using unidimensional measurements. Clin Cancer Res 2013;19:3936-43.
Wolchok J. How recent advances in immunotherapy are changing the standard of care for patients with metastatic melanoma. Ann Oncol 2012;23:viii15-21.
Chang SM, Wen PY, Vogelbaum MA, Macdonald DR, Van den B, Martin J. Response assessment in neuro-oncology (RANO): More than imaging criteria for malignant glioma. Neuro Oncol Pract 2015;2:npv037.
Wen PY, Macdonald DR, Reardon DA, Cloughesy TF, Sorensen AG, Galanis E, et al.
Updated response assessment criteria for high-grade gliomas: Response assessment in neuro-oncology working group. J Clin Oncol 2010;28:1963-72.
van den Bent MJ, Wefel JS, Schiff D, Taphoorn MJ, Jaeckle K, Junck L, et al.
Response assessment in neuro-oncology (a report of the RANO group): Assessment of outcome in trials of diffuse low-grade gliomas. Lancet Oncol 2011;12:583-93.
Nayak L, DeAngelis LM, Brandes AA, Peereboom DM, Galanis E, Lin NU, et al.
The neurologic assessment in neuro-oncology (NANO) scale: A tool to assess neurologic function for integration into the response assessment in neuro-oncology (RANO) criteria. Neuro Oncol 2017;19:625-35.
Carceller F, Mandeville H, Mackinnon AD, Saran F. Facing pseudoprogression after radiotherapy in low grade gliomas. Transl Cancer Res 2017;6:S254-8.
Chinot OL, Macdonald DR, Abrey LE, Zahlmann G, Kerloëguen Y, Cloughesy TF.
Response assessment criteria for glioblastoma: Practical adaptation and implementation in clinical trials of antiangiogenic therapy. Curr Neurol Neurosci Rep 2013;13:347.
Huang RY, Rahman R, Ballman KV, Felten SJ, Anderson SK, Ellingson BM, et al.
The impact of T2/FLAIR evaluation per RANO criteria on response assessment of recurrent glioblastoma patients treated with Bevacizumab. Clin Cancer Res 2016;22:575-81.
Hattingen E, Jurcoane A, Daneshvar K, Pilatus U, Mittelbronn M, Steinbach JP, et al.
Quantitative T2 mapping of recurrent glioblastoma under bevacizumab improves monitoring for non-enhancing tumor progression and predicts overall survival. Neuro Oncol 2013;15:1395-404.
Claus EB, Walsh KM, Wiencke JK, Molinaro AM, Wiemels JL, Schildkraut JM, et al.
Survival and low-grade glioma: The emergence of genetic information. Neurosurg Focus 2015;38:E6.
Qian Z, Li Y, Fan X, Zhang C, Wang Y, Jiang T.
Molecular and clinical characterization of IDH associated immune signature in lower-grade gliomas. Oncoimmunology 2018;7:e1434466.
Wen PY, Chang SM, Van den Bent MJ, Vogelbaum MA, Macdonald DR, Lee EQ.
Response assessment in neuro-oncology clinical trials. J Clin Oncol 2017;35:2439-49.
Eisele SC, Wen PY, Lee EQ. Assessment of brain tumor response: RANO and its offspring. Curr Treat Options Oncol 2016;17:35.
Avila EK, Chamberlain M, Schiff D, Reijneveld JC, Armstrong TS, Ruda R, et al.
Seizure control as a new metric in assessing efficacy of tumor treatment in low-grade glioma trials. Neuro Oncol 2017;19:12-21.
Koekkoek JA, Dirven L, Heimans JJ, Postma TJ, Vos MJ, Reijneveld JC, et al.
Seizure reduction is a prognostic marker in low-grade glioma patients treated with temozolomide. J Neurooncol 2016;126:347-54.
Reardon DA, Gokhale PC, Klein SR, Ligon KL, Rodig SJ, Ramkissoon SH, et al.
Glioblastoma eradication following immune checkpoint blockade in an orthotopic, immunocompetent model. Cancer Immunol Res 2016;4:124-35.
Sundar R, Cho BC, Brahmer JR, Soo RA. Nivolumab in NSCLC: Latest evidence and clinical potential. Ther Adv Med Oncol 2015;7:85-96.
Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF, et al.
Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N
Engl J Med 2012;366:2443-54.
Hamid O, Robert C, Daud A, Hodi FS, Hwu WJ, Kefford R, et al.
Safety and tumor responses with lambrolizumab (anti-PD-1) in melanoma. N
Engl J Med 2013;369:134-44.
Brahmer JR, Tykodi SS, Chow LQ, Hwu WJ, Topalian SL, Hwu P, et al.
Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. N
Engl J Med 2012;366:2455-65.
Armstrong TS, Vera-Bolanos E, Gning I, Acquaye A, Gilbert MR, Cleeland C, et al.
The impact of symptom interference using the MD Anderson symptom inventory-brain tumor module (MDASI-BT) on prediction of recurrence in primary brain tumor patients. Cancer 2011;117:3222-8.
Orr ST, Aisner J. Performance status assessment among oncology patients: A review. Cancer Treat Rep 1986;70:1423-9.
Brown PD, Buckner JC, O'Fallon JR, Iturria NL, O'Neill BP, Brown CA, et al.
Importance of baseline mini-mental state examination as a prognostic factor for patients with low-grade glioma. Int J Radiat Oncol Biol Phys 2004;59:117-25.
Armstrong TS, Bishof AM, Brown PD, Klein M, Taphoorn MJ, Theodore-Oklota C.
Determining priority signs and symptoms for use as clinical outcomes assessments in trials including patients with malignant gliomas: Panel 1 report. Neuro Oncol 2016;18:ii1-12.
Butowski N, Chang SM. Endpoints for clinical trials and revised assessment in neuro-oncology. Curr Opin Neurol 2012;25:780-5.
Alexander BM, Brown PD, Ahluwalia MS, Aoyama H, Baumert BG, Chang SM, et al.
Clinical trial design for local therapies for brain metastases: A guideline by the response assessment in neuro-oncology brain metastases working group. Lancet Oncol 2018;19:e33-42.
Wilson MK, Karakasis K, Oza AM. Outcomes and endpoints in trials of cancer treatment: The past, present, and future. Lancet Oncol 2015;16:e32-42.
Vredenburgh JJ, Desjardins A, Herndon JE 2nd
, Marcello J, Reardon DA, Quinn JA, et al.
Bevacizumab plus irinotecan in recurrent glioblastoma multiforme. J Clin Oncol 2007;25:4722-9.
Ballman KV, Buckner JC, Brown PD, Giannini C, Flynn PJ, LaPlant BR, et al.
The relationship between six-month progression-free survival and 12-month overall survival end points for phase II trials in patients with glioblastoma multiforme. Neuro Oncol 2007;9:29-38.
Lamborn KR, Yung WK, Chang SM, Wen PY, Cloughesy TF, DeAngelis LM, et al.
Progression-free survival: An important end point in evaluating therapy for recurrent high-grade gliomas. Neuro Oncol 2008;10:162-70.
van den Bent MJ, Brandes AA, Rampling R, Kouwenhoven MC, Kros JM, Carpentier AF, et al.
Randomized phase II trial of erlotinib versus temozolomide or carmustine in recurrent glioblastoma: EORTC brain tumor group study 26034. J Clin Oncol 2009;27:1268-74.
Han K, Ren M, Wick W, Abrey L, Das A, Jin J, et al.
Progression-free survival as a surrogate endpoint for overall survival in glioblastoma: A literature-based meta-analysis from 91 trials. Neuro Oncol 2014;16:696-706.
Trippa L, Wen PY, Parmigiani G, Berry DA, Alexander BM. Combining progression-free survival and overall survival as a novel composite endpoint for glioblastoma trials. Neuro Oncol 2015;17:1106-13.
Huang RY, Rahman R, Ballman KV, Felten SJ, Anderson SK, Ellingson BM, et al.
The impact of T2/FLAIR evaluation per RANO criteria on response assessment of recurrent glioblastoma patients treated with bevacizumab. Clin Cancer Res 2015;22:575.
Rudà R, Soffietti R. What is new in the management of epilepsy in gliomas? Curr Treat Options Neurol 2015;17:351.
Khan MN, Sharma AM, Pitz M, Loewen SK, Quon H, Poulin A, et al.
High-grade glioma management and response assessment-recent advances and current challenges. Curr Oncol 2016;23:e383-91.
|This article has been cited by|
||Assessment of neurological function using the National Institute of Health Stroke Scale in patients with gliomas
| ||Anna Maria Zeitlberger,Marie-Claire Flynn,Monika Hollenstein,Thomas Hundsberger |
| ||Neuro-Oncology Practice. 2021; |
|[Pubmed] | [DOI]|
||Case Report: Single-Cell Transcriptomic Analysis of an Anaplastic Oligodendroglioma Post Immunotherapy
| ||Guangyang Yu,Madison K. Butler,Abdalla Abdelmaksoud,Ying Pang,Yu-Ting Su,Zachary Rae,Kimia Dadkhah,Michael C. Kelly,Young K. Song,Jun S. Wei,Masaki Terabe,Ramya Atony,Kelly Mentges,Brett J. Theeler,Marta Penas-Prado,John Butman,Kevin Camphausen,Kareem A. Zaghloul,Edjah Nduom,Martha Quezado,Kenneth Aldape,Terri S. Armstrong,Mark R. Gilbert,James L. Gulley,Javed Khan,Jing Wu |
| ||Frontiers in Oncology. 2021; 10 |
|[Pubmed] | [DOI]|