Since 1979, the World Health Organization (WHO) has periodically published a consensus classification and grading of tumors of the central nervous system (CNS) to ensure uniform histopathologic ...diagnostic criteria worldwide. In 2016, the WHO published an update of the fourth edition of the classification of CNS tumors. This article summarizes the major changes in the update and discusses their impact on clinical practice.
For the first time, the 2016 revision of the WHO classification uses molecular parameters in addition to traditional histology to diagnose many CNS tumors, resulting in major restructuring of the classification of many tumors, especially gliomas, ependymomas, and medulloblastomas. Accordingly, nomenclature for selected entities now includes both a histopathologic diagnosis and defining molecular features.
The use of integrated phenotypic and genotypic parameters for the classification of CNS tumors introduces greater objectivity to the diagnosis but also requires more widespread availability of molecular testing. It is hoped that these changes will lead to greater diagnostic accuracy with more biologically homogeneous diagnostic entities and improved patient management and determination of prognosis.
Epidemiology of Brain Metastases Nayak, Lakshmi; Lee, Eudocia Quant; Wen, Patrick Y.
Current oncology reports,
02/2012, Letnik:
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Journal Article
Recenzirano
Brain metastases are one of the most common neurologic complications of cancer. The incidence is 9%–17% based on various studies, although the exact incidence is thought to be higher. The incidence ...is increasing with the availability of improved imaging techniques which aid early diagnosis, and effective systemic treatment regimens which prolong life, thus allowing cancer to disseminate to the brain. Lung cancer, breast cancer, and melanoma are the most frequent to develop brain metastases, and account for 67%–80% of all cancers. Most patients with brain metastases have synchronous extracerebral metastases. Some patients present with no known primary cancer diagnosis. In children, brain metastases are rare; germ cell tumors, sarcomas, and neuroblastoma are the common offenders.
A scorecard to evaluate magnetic resonance imaging (MRI) findings during the course of leptomeningeal metastases (LM) has been proposed by the Response Assessment in Neuro-Oncology (RANO) group.
To ...explore the feasibility of the Leptomeningeal Assessment in Neuro-Oncology (LANO) scorecard, cerebrospinal MRIs of 22 patients with LM from solid tumors were scored by 10 neuro-oncologists and 9 neuroradiologists at baseline and at follow-up after treatment. Raters were blinded for clinical data including treatment. Agreement between raters of single items was evaluated using a Krippendorff alpha coefficient. Agreement between numerical parameters such as scores for changes between baseline and follow-up and total scores was evaluated by determining the intraclass coefficient of correlation.
Most raters experienced problems with the instructions of the scorecard. No acceptable alpha concordance coefficient was obtained for the rating of single items at baseline or follow-up. The most concordant ratings were obtained for spinal nodules. The concordances were worst for brain linear leptomeningeal enhancement and cranial nerve enhancement. Discordance was less prominent among neuroradiologists than among neuro-oncologists. High variability was also observed for evaluating changes between baseline and follow-up and for total scores.
Assessing response of LM by MRI remains challenging. Central imaging review is therefore indispensable for clinical trials. Based on the present results, we propose a new, simplified scorecard that will require validation using a similar approach as pursued here. The main challenges are to define measurable versus nonmeasurable (target) lesions and measures of change that allow assessment of response.
Diffuse gliomas are malignant brain tumors that include lower-grade gliomas (LGGs) and glioblastomas. Transformation of low-grade glioma into a higher tumor grade is typically associated with ...contrast enhancement on magnetic resonance imaging. Mutations in the isocitrate dehydrogenase 1 (
) gene occur in most LGGs (> 70%). Ivosidenib is an inhibitor of mutant IDH1 (mIDH1) under evaluation in patients with solid tumors.
We conducted a multicenter, open-label, phase I, dose escalation and expansion study of ivosidenib in patients with m
solid tumors. Ivosidenib was administered orally daily in 28-day cycles.
In 66 patients with advanced gliomas, ivosidenib was well tolerated, with no dose-limiting toxicities reported. The maximum tolerated dose was not reached; 500 mg once per day was selected for the expansion cohort. The grade ≥ 3 adverse event rate was 19.7%; 3% (n = 2) were considered treatment related. In patients with nonenhancing glioma (n = 35), the objective response rate was 2.9%, with 1 partial response. Thirty of 35 patients (85.7%) with nonenhancing glioma achieved stable disease compared with 14 of 31 (45.2%) with enhancing glioma. Median progression-free survival was 13.6 months (95% CI, 9.2 to 33.2 months) and 1.4 months (95% CI, 1.0 to 1.9 months) for the nonenhancing and enhancing glioma cohorts, respectively. In an exploratory analysis, ivosidenib reduced the volume and growth rates of nonenhancing tumors.
In patients with m
advanced glioma, ivosidenib 500 mg once per day was associated with a favorable safety profile, prolonged disease control, and reduced growth of nonenhancing tumors.
Isocitrate dehydrogenase (
) mutations in glioma patients confer longer survival and may guide treatment decision making. We aimed to predict the
status of gliomas from MR imaging by applying a ...residual convolutional neural network to preoperative radiographic data.
Preoperative imaging was acquired for 201 patients from the Hospital of University of Pennsylvania (HUP), 157 patients from Brigham and Women's Hospital (BWH), and 138 patients from The Cancer Imaging Archive (TCIA) and divided into training, validation, and testing sets. We trained a residual convolutional neural network for each MR sequence (FLAIR, T2, T1 precontrast, and T1 postcontrast) and built a predictive model from the outputs. To increase the size of the training set and prevent overfitting, we augmented the training set images by introducing random rotations, translations, flips, shearing, and zooming.
With our neural network model, we achieved IDH prediction accuracies of 82.8% (AUC = 0.90), 83.0% (AUC = 0.93), and 85.7% (AUC = 0.94) within training, validation, and testing sets, respectively. When age at diagnosis was incorporated into the model, the training, validation, and testing accuracies increased to 87.3% (AUC = 0.93), 87.6% (AUC = 0.95), and 89.1% (AUC = 0.95), respectively.
We developed a deep learning technique to noninvasively predict
genotype in grade II-IV glioma using conventional MR imaging using a multi-institutional data set.
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Summary Immunotherapy is a promising area of therapy in patients with neuro-oncological malignancies. However, early-phase studies show unique challenges associated with the assessment of ...radiological changes in response to immunotherapy reflecting delayed responses or therapy-induced inflammation. Clinical benefit, including long-term survival and tumour regression, can still occur after initial disease progression or after the appearance of new lesions. Refinement of the response assessment criteria for patients with neuro-oncological malignancies undergoing immunotherapy is therefore warranted. Herein, a multinational and multidisciplinary panel of neuro-oncology immunotherapy experts describe immunotherapy Response Assessment for Neuro-Oncology (iRANO) criteria based on guidance for the determination of tumour progression outlined by the immune-related response criteria and the RANO working group. Among patients who demonstrate imaging findings meeting RANO criteria for progressive disease within 6 months of initiating immunotherapy, including the development of new lesions, confirmation of radiographic progression on follow-up imaging is recommended provided that the patient is not significantly worse clinically. The proposed criteria also include guidelines for the use of corticosteroids. We review the role of advanced imaging techniques and the role of measurement of clinical benefit endpoints including neurological and immunological functions. The iRANO guidelines put forth in this Review will evolve successively to improve their usefulness as further experience from immunotherapy trials in neuro-oncology accumulate.
Lower grade gliomas (LGGs) are malignant brain tumors. Current therapy is associated with short- and long-term toxicity. Progression to higher tumor grade is associated with contrast enhancement on ...MRI. The majority of LGGs harbor mutations in the genes encoding isocitrate dehydrogenase 1 or 2 (
). Vorasidenib (AG-881) is a first-in-class, brain-penetrant, dual inhibitor of the mutant IDH1 and mutant IDH2 enzymes.
We conducted a multicenter, open-label, phase I, dose-escalation study of vorasidenib in 93 patients with mutant
(m
) solid tumors, including 52 patients with glioma that had recurred or progressed following standard therapy. Vorasidenib was administered orally, once daily, in 28-day cycles until progression or unacceptable toxicity. Enrollment is complete; this trial is registered with ClinicalTrials.gov, NCT02481154.
Vorasidenib showed a favorable safety profile in the glioma cohort. Dose-limiting toxicities of elevated transaminases occurred at doses ≥100 mg and were reversible. The protocol-defined objective response rate per Response Assessment in Neuro-Oncology criteria for LGG in patients with nonenhancing glioma was 18% (one partial response, three minor responses). The median progression-free survival was 36.8 months 95% confidence interval (CI), 11.2-40.8 for patients with nonenhancing glioma and 3.6 months (95% CI, 1.8-6.5) for patients with enhancing glioma. Exploratory evaluation of tumor volumes in patients with nonenhancing glioma showed sustained tumor shrinkage in multiple patients.
Vorasidenib was well tolerated and showed preliminary antitumor activity in patients with recurrent or progressive nonenhancing m
LGG.
We discuss designs and interpretable metrics of bias and statistical efficiency of "externally controlled" trials (ECT) and compare ECT performance to randomized and single-arm designs.
We specify an ...ECT design that leverages information from real-world data (RWD) and prior clinical trials to reduce bias associated with interstudy variations of the enrolled populations. We then used a collection of clinical studies in glioblastoma (GBM) and RWD from patients treated with the current standard of care to evaluate ECTs. Validation is based on a "leave one out" scheme, with iterative selection of a single-arm from one of the studies, for which we estimate treatment effects using the remaining studies as external control. This produces interpretable and robust estimates on ECT bias and type I errors.
We developed a model-free approach to evaluate ECTs based on collections of clinical trials and RWD. For GBM, we verified that inflated false positive error rates of standard single-arm trials can be considerably reduced (up to 30%) by using external control data.
The use of ECT designs in GBM, with adjustments for the clinical profiles of the enrolled patients, should be preferred to single-arm studies with fixed efficacy thresholds extracted from published results on the current standard of care.
Development of novel therapies for CNS tumors requires reliable assessment of response and progression. This requirement has been particularly challenging in neuro-oncology for which contrast ...enhancement serves as an imperfect surrogate for tumor volume and is influenced by agents that affect vascular permeability, such as antiangiogenic therapies. In addition, most tumors have a nonenhancing component that can be difficult to accurately quantify. To improve the response assessment in neuro-oncology and to standardize the criteria that are used for different CNS tumors, the Response Assessment in Neuro-Oncology (RANO) working group was established. This multidisciplinary international working group consists of neuro-oncologists, medical oncologists, neuroradiologists, neurosurgeons, radiation oncologists, neuropsychologists, and experts in clinical outcomes assessments, working in collaboration with government and industry to enhance the interpretation of clinical trials. The RANO working group was originally created to update response criteria for high- and low-grade gliomas and to address such issues as pseudoresponse and nonenhancing tumor progression from antiangiogenic therapies, and pseudoprogression from radiochemotherapy. RANO has expanded to include working groups that are focused on other tumors, including brain metastases, leptomeningeal metastases, spine tumors, pediatric brain tumors, and meningiomas, as well as other clinical trial end points, such as clinical outcomes assessments, seizures, corticosteroid use, and positron emission tomography imaging. In an effort to standardize the measurement of neurologic function for clinical assessment, the Neurologic Assessment in Neuro-Oncology scale was drafted. Born out of a workshop conducted by the Jumpstarting Brain Tumor Drug Development Coalition and the US Food and Drug Administration, a standardized brain tumor imaging protocol now exists to reduce variability and improve reliability. Efforts by RANO have been widely accepted and are increasingly being used in neuro-oncology trials, although additional refinements will be needed.
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