Lakshmi Nayak1, Lisa M DeAngelis2, Alba A Brandes3, David M Peereboom4, Evanthia Galanis5, Nancy U Lin6, Riccardo Soffietti7, David R Macdonald8, Marc Chamberlain9, James Perry10, Kurt Jaeckle11, Minesh Mehta12, Roger Stupp13, Alona Muzikansky14, Elena Pentsova2, Timothy Cloughesy15, Fabio M Iwamoto16, Joerg-Christian Tonn17, Michael A Vogelbaum4, Patrick Y Wen1, Martin J van den Bent18, David A Reardon1. 1. Center for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA. 2. Department of Neurology, Memorial Sloan-Kettering Cancer Center, New York, USA. 3. Department of Medical Oncology, Azienda USL-IRCCS Institute of Neurological Science, Bologna, Italy. 4. Rose Ella Burkhardt Brain Tumor and Neuro-Oncology Center, Cleveland Clinic, Cleveland, Ohio, USA. 5. Department of Oncology, Mayo Clinic, Rochester, Minnesota, USA. 6. Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA. 7. Department of Neurology and Neuro-Oncology, University of Turin, Turin, Italy. 8. Department of Oncology, London Health Sciences Centre, University of Western Ontario, London, Ontario, Canada. 9. Department of Neurology, Fred Hutchinson Cancer Research Center and Seattle Cancer Care Alliance, University of Washington School of Medicine, Seattle, Washington, USA. 10. Division of Neurology, Sunnybrook Health Science Center, University of Toronto, Toronto, Ontario, Canada. 11. Department of Neurology and Hematology/Oncology, Mayo Clinic, Jacksonville, Florida, USA. 12. Department of Radiation Oncology, Miami Cancer Institute, Miami, Florida, USA. 13. Department of Oncology, University of Zurich, Zurich, Switzerland. 14. Biostatistics Center, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. 15. Neuro-Oncology Program, Ronald Reagan UCLA Medical Center, University of CaliforniaLos Angeles, Los Angeles, California, USA. 16. Division of Neuro-Oncology, Neurological Institute of New York College of Physicians and Surgeons, Columbia University, New York, USA. 17. Department of Neurosurgery, LMU University of Munich, Munich, Germany. 18. Neuro-Oncology Unit, Erasmus MC Cancer Center, Erasmus MC, Rotterdam, The Netherlands.
Abstract
Background: The Macdonald criteria and the Response Assessment in Neuro-Oncology (RANO) criteria define radiologic parameters to classify therapeutic outcome among patients with malignant glioma and specify that clinical status must be incorporated and prioritized for overall assessment. But neither provides specific parameters to do so. We hypothesized that a standardized metric to measure neurologic function will permit more effective overall response assessment in neuro-oncology. Methods: An international group of physicians including neurologists, medical oncologists, radiation oncologists, and neurosurgeons with expertise in neuro-oncology drafted the Neurologic Assessment in Neuro-Oncology (NANO) scale as an objective and quantifiable metric of neurologic function evaluable during a routine office examination. The scale was subsequently tested in a multicenter study to determine its overall reliability, inter-observer variability, and feasibility. Results: The NANO scale is a quantifiable evaluation of 9 relevant neurologic domains based on direct observation and testing conducted during routine office visits. The score defines overall response criteria. A prospective, multinational study noted a >90% inter-observer agreement rate with kappa statistic ranging from 0.35 to 0.83 (fair to almost perfect agreement), and a median assessment time of 4 minutes (interquartile range, 3-5). Conclusion: The NANO scale provides an objective clinician-reported outcome of neurologic function with high inter-observer agreement. It is designed to combine with radiographic assessment to provide an overall assessment of outcome for neuro-oncology patients in clinical trials and in daily practice. Furthermore, it complements existing patient-reported outcomes and cognition testing to combine for a global clinical outcome assessment of well-being among brain tumor patients.
Background: The Macdonald criteria and the Response Assessment in Neuro-Oncology (RANO) criteria define radiologic parameters to classify therapeutic outcome among patients with malignant glioma and specify that clinical status must be incorporated and prioritized for overall assessment. But neither provides specific parameters to do so. We hypothesized that a standardized metric to measure neurologic function will permit more effective overall response assessment in neuro-oncology. Methods: An international group of physicians including neurologists, medical oncologists, radiation oncologists, and neurosurgeons with expertise in neuro-oncology drafted the Neurologic Assessment in Neuro-Oncology (NANO) scale as an objective and quantifiable metric of neurologic function evaluable during a routine office examination. The scale was subsequently tested in a multicenter study to determine its overall reliability, inter-observer variability, and feasibility. Results: The NANO scale is a quantifiable evaluation of 9 relevant neurologic domains based on direct observation and testing conducted during routine office visits. The score defines overall response criteria. A prospective, multinational study noted a >90% inter-observer agreement rate with kappa statistic ranging from 0.35 to 0.83 (fair to almost perfect agreement), and a median assessment time of 4 minutes (interquartile range, 3-5). Conclusion: The NANO scale provides an objective clinician-reported outcome of neurologic function with high inter-observer agreement. It is designed to combine with radiographic assessment to provide an overall assessment of outcome for neuro-oncology patients in clinical trials and in daily practice. Furthermore, it complements existing patient-reported outcomes and cognition testing to combine for a global clinical outcome assessment of well-being among brain tumorpatients.
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