Jenkinson, Michael D.

Abstract Background DNA methylation profiling can be used to robustly predict postsurgical outcomes and response to radiotherapy (RT) for meningioma patients. To allow for seamless integration of these complementary models into clinical practice, a practical framework is needed. Methods We leveraged a cohort of nearly 2000 surgically-treated meningiomas with DNA methylation profiling and clinical outcomes data. Existing methylation-based prediction models were dichotomized to yield four risk groups: low and high recurrent risk, each with RT sensitive and resistant subgroups. Risk groups were correlated with progression-free survival in the context of existing biomarkers including extent of resection and WHO grade. Results We first demonstrated that all risk groups benefit from gross total resection. All “high-risk, RT sensitive” tumors (n = 306, 15.7%) also benefited from adjuvant RT: after GTR, median PFS increased from 4.68 (4.13-9.48) years to not reached (P = .003); after subtotal resection (STR), from 2.12 (1.59-3.02) to 4.09 (3.41-not reached) years (P = .004). “Low-risk, RT sensitive cases” (n = 1207, 61.8%) also benefited from RT after STR (median PFS 7.39 (6.66-12.8) vs. 16.53 (10.35-not reached) years, P = .03), suggesting that RT be considered in these patients. Neither “low-risk RT resistant” (n = 84, 4.3%) nor “high-risk RT resistant” (n = 356, 18.2%) cases benefited from RT, and the latter group was associated with universally poor outcomes. Conclusions We identify methylation-defined risk groups of meningioma for which additional benefit is gained from adjuvant RT, leading to a clinical decision-making framework for straightforward integration of molecular models into clinical practice.

AbstractBackgroundWith increasing molecular analyses of meningiomas, there is a need to harmonize language used to capture clinical data across centers to ensure that molecular alterations are appropriately linked to clinical variables of interest. Here the International Consortium on Meningiomas presents a set of core and supplemental meningioma-specific common data elements (CDEs) to facilitate comparative and pooled analyses.MethodsThe generation of CDEs followed the 4-phase process similar to other National Institute of Neurological Disorders and Stroke (NINDS) CDE projects: discovery, internal validation, external validation, and distribution.ResultsThe CDEs were organized into patient- and tumor-level modules. In total, 17 core CDEs (10 patient level and 7 tumor level) as well as 14 supplemental CDEs (7 patient level and 7 tumor level) were defined and described. These CDEs are now made publicly available for dissemination and adoption.ConclusionsCDEs provide a framework for discussion in the neuro-oncology community that will facilitate data-sharing for collaborative research projects and aid in developing a common language for comparative and pooled analyses. The meningioma-specific CDEs presented here are intended to be dynamic parameters that evolve with time and The Consortium welcomes international feedback for further refinement and implementation of these CDEs.

Abstract BACKGROUND With increasing studies reporting on the molecular profiling of meningiomas, there is a need to harmonize language used to capture clinical data across centers to ensure that molecular alterations are appropriately linked to clinical variables of interest. Here the International Consortium on Meningiomas presents a final set of core and supplemental meningioma-specific Common Data Elements (CDEs) to facilitate comparative and pooled analyses. METHODS The generation of CDEs followed the four-phase process similar to other National Institute of Neurological Disorders and Stroke (NINDS) CDE projects: development/discovery based on data from published and ongoing meningioma trials, internal validation, external validation including presentation of our data form at the Society for Neuro-Oncology previously, and distribution. RESULTS We developed a set of CDEs organized into patient- and tumor-level modules. In total, the Consortium identified 16 core CDEs (9 patient-level and 7-tumour-level) e.g. age at index surgery, diagnosis of neurofibromatosis, prior chemotherapy or radiation, tumor location, extent of resection, recurrence, etc. An additional 15 supplemental CDEs were defined and described (8 patient-level and 7 tumour-level) e.g. race, cause of death, multiple tumors, tumor size, Simpson grade, second intervention, etc. These CDES are now made publicly available for dissemination and adoption. We also present a narrative review and analysis of recent and ongoing meningioma trials. CONCLUSIONS These CDEs provide a framework for discussion in the neuro-oncology community that will facilitating data sharing for collaborative research projects and aid in developing a common language for comparative and pooled analyses. The CDEs are intended to be dynamic parameters that evolve with time and The Consortium welcomes international feedback for further refinement and implementation of these CDEs.

Abstract With increasing epidemiological and biological studies on meningiomas, standardized clinical data capture will be necessary to interpret results across studies and to translate them to clinical practice. To meet this need for consistent clinical data capture, the International Consortium on Meningioma, has developed a set of common data elements (CDEs), to be used across clinical and biological research. Building from terminology used in clinical practice and ongoing studies, we used a consensus-of-experts approach to arrive at a set of standardized and vetted data elements. Areas of focus include patient characteristics, patient history, radiological and intra-operative description, histological diagnosis and molecular testing, non-surgical interventions, and surveillance. These data elements are implemented in Research Electronic Data Capture (REDCap) forms. With REDCap implementation, components of the CDE set can be selected and instituted in a local REDCap instance for efficient study start-up. The scope of the current CDE set focuses on surgically treated meningioma. However, modular forms provide flexibility and to allow the scope to be expanded to include non-surgically treated meningioma. Dissemination plans are underway to introduce the CDEs to neuro-oncology researchers and clinicians through publication and presentations, where feedback will be solicited. Adoption of CDEs for research will improve consistency and interpretability across studies, expediting research in this frequently occurring tumor.