Kristin A Waite1, Gino Cioffi1, Carol Kruchko2, Nirav Patil3, Daniel J Brat4, Janet M Bruner5, Roger E McLendon6, Tarik Tihan7, Quinn T Ostrom8, Jill S Barnholtz-Sloan1. 1. Division of Cancer Epidemiology and Genetics, Trans-Divisional Research Program, National Cancer Institute, Bethesda, Maryland, USA. 2. Central Brain Tumor Registry of the United States (CBTRUS), Hinsdale, Illinois, USA. 3. University Hospitals, Cleveland, Ohio. 4. Department of Pathology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA. 5. Department of Pathology, MD Anderson Cancer Center, Houston, Texas, USA. 6. Department of Pathology, Duke University Medical Center Durham , North Carolina, USA. 7. Department of Pathology, Division of Neuropathology, University of California San Francisco, San Francisco, California, USA. 8. The Preston Robert Tisch Brain Tumor Center, Duke University Medical Center, Durham, North Carolina, USA.
Abstract
Background: The Central Brain Tumor Registry of the United States (CBTRUS) uses a histology grouping model based on the World Health Organization (WHO) classifications to group records for clinically relevant statistical reporting. Newly identified genetic markers more accurately stratify patients than histology alone and were incorporated into the 2016 update to the WHO Classification. Methods: CBTRUS and consulting neuropathologists reviewed and aligned histology groupings with the 2016 WHO update. "Obsolete" (terms not currently in use) histology nomenclature along with their International Classification of Disease, Oncology 3rd edition (ICD-O-3) codes were identified, some histologies were reclassified to 2016 WHO, and new codes found in 2016 WHO were incorporated. An evaluation of the frequency of histology codes affected in the realignment process, and incidence and survival pre- and post-realignment was conducted. Results: After review, 67 codes were noted as obsolete, 51 codes were reclassified, and 12 new codes were incorporated. Histology groups most affected were mesenchymal tumors and neuronal/mixed neuronal-glial tumors. Reorganization resulted in 2588 (0.65%) cases with grouping reassignment or reporting change, indicating that the 2016 WHO Classification revision has impacted the collection and reporting of primary brain and other CNS tumors. Conclusion: This work demonstrates the need to be responsive to changes in classification and coding in order to ensure the most up-to-date and accurate statistics for brain and CNS tumors. This will require collaboration from all stakeholders within the brain tumor community, so to have the ability to reconcile clinical practices and surveillance requirements. Published by Oxford University Press 2022.
Background: The Central Brain Tumor Registry of the United States (CBTRUS) uses a histology grouping model based on the World Health Organization (WHO) classifications to group records for clinically relevant statistical reporting. Newly identified genetic markers more accurately stratify patients than histology alone and were incorporated into the 2016 update to the WHO Classification. Methods: CBTRUS and consulting neuropathologists reviewed and aligned histology groupings with the 2016 WHO update. "Obsolete" (terms not currently in use) histology nomenclature along with their International Classification of Disease, Oncology 3rd edition (ICD-O-3) codes were identified, some histologies were reclassified to 2016 WHO, and new codes found in 2016 WHO were incorporated. An evaluation of the frequency of histology codes affected in the realignment process, and incidence and survival pre- and post-realignment was conducted. Results: After review, 67 codes were noted as obsolete, 51 codes were reclassified, and 12 new codes were incorporated. Histology groups most affected were mesenchymal tumors and neuronal/mixed neuronal-glial tumors. Reorganization resulted in 2588 (0.65%) cases with grouping reassignment or reporting change, indicating that the 2016 WHO Classification revision has impacted the collection and reporting of primary brain and other CNS tumors. Conclusion: This work demonstrates the need to be responsive to changes in classification and coding in order to ensure the most up-to-date and accurate statistics for brain and CNS tumors. This will require collaboration from all stakeholders within the brain tumor community, so to have the ability to reconcile clinical practices and surveillance requirements. Published by Oxford University Press 2022.
Authors: Vishesh Khanna; Rebecca L Achey; Quinn T Ostrom; Hunter Block-Beach; Carol Kruchko; Jill S Barnholtz-Sloan; Peter M de Blank Journal: J Neurooncol Date: 2017-08-21 Impact factor: 4.130
Authors: David N Louis; Arie Perry; Guido Reifenberger; Andreas von Deimling; Dominique Figarella-Branger; Webster K Cavenee; Hiroko Ohgaki; Otmar D Wiestler; Paul Kleihues; David W Ellison Journal: Acta Neuropathol Date: 2016-05-09 Impact factor: 17.088
Authors: David N Louis; Arie Perry; Pieter Wesseling; Daniel J Brat; Ian A Cree; Dominique Figarella-Branger; Cynthia Hawkins; H K Ng; Stefan M Pfister; Guido Reifenberger; Riccardo Soffietti; Andreas von Deimling; David W Ellison Journal: Neuro Oncol Date: 2021-08-02 Impact factor: 13.029
Authors: David N Louis; Hiroko Ohgaki; Otmar D Wiestler; Webster K Cavenee; Peter C Burger; Anne Jouvet; Bernd W Scheithauer; Paul Kleihues Journal: Acta Neuropathol Date: 2007-07-06 Impact factor: 17.088