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CLRM-13 RELEVANCE OF RECURSIVE PARTITIONING ANALYSIS (RPA) CLASSIFICATION IN THE CURRENT CARE OF PATIENTS WITH BRAIN METASTASES (BMETS)
BACKGROUND: Patients diagnosed with BMETS want to know their prognosis and the benefit of treatment to make informed decisions. Clinician and patient biases frequently provide survival estimates that are too optimistic or pessimistic. We postulated that that RPA remains a useful tool to communicate...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354187/ http://dx.doi.org/10.1093/noajnl/vdac078.033 |
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author | Sarai, Guneet Amidon, Ryan F Bovi, Joesph A Thomas, Alissa A Novicoff, Wendy Schuetz, Samantha Singh, Rohit Chang, Amy Sheehan, Jason P Fadul, Camilo E |
author_facet | Sarai, Guneet Amidon, Ryan F Bovi, Joesph A Thomas, Alissa A Novicoff, Wendy Schuetz, Samantha Singh, Rohit Chang, Amy Sheehan, Jason P Fadul, Camilo E |
author_sort | Sarai, Guneet |
collection | PubMed |
description | BACKGROUND: Patients diagnosed with BMETS want to know their prognosis and the benefit of treatment to make informed decisions. Clinician and patient biases frequently provide survival estimates that are too optimistic or pessimistic. We postulated that that RPA remains a useful tool to communicate prognosis and potential benefit from brain-directed treatment (BDT). We evaluated real-world data on RPA class and survival of patients with newly diagnosed BMETS from three academic institutions. METHODS: We retrospectively reviewed the records of patients with BMETS between 2017 and 2019 who had at least 6 months of follow up. Excluded were patients with leptomeningeal or only dural/calvarial metastases. We calculated the RPA and according to class compared Kaplan-Meier survival curves. RESULTS: We have data on 642 cases with median age of 65 years; 80% had lung, breast, melanoma, and renal as the primary cancer. Sixty (9.3%) patients received palliative care only, while 582 (90.7%) had BDT. The median survival of all patients according to RPA in months was 18.0 (I), 9.4 (II), and 2.4 (III) and for those receiving BDT (n=582), it was 19.2 (I), 11.2 (II), and 2.9 (III). There were statistically significant differences for BDT survival curves adjusted for multiple comparisons (I-II p=0.0124; II-III p<0.0001; I-III p<0.0001). For patients in RPA class III who received WBRT (n=62), the median survival was 2.9 months, and, for SRS (n=37), it was 3.5 months. We will present updated data including additional 238 cases and propose predictive/prognostic models based on our cohort that optimizes the RPA application in clinical practice. CONCLUSION: In contemporary practice, the RPA classification remains significantly relevant in making care decisions for patients diagnosed with BMETS. Treatment recommendations for patients in RPA class III should be the result of multidisciplinary discussions with consideration for early palliative care involvement to de-escalate and avoid inefficacious BDT. |
format | Online Article Text |
id | pubmed-9354187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-93541872022-08-09 CLRM-13 RELEVANCE OF RECURSIVE PARTITIONING ANALYSIS (RPA) CLASSIFICATION IN THE CURRENT CARE OF PATIENTS WITH BRAIN METASTASES (BMETS) Sarai, Guneet Amidon, Ryan F Bovi, Joesph A Thomas, Alissa A Novicoff, Wendy Schuetz, Samantha Singh, Rohit Chang, Amy Sheehan, Jason P Fadul, Camilo E Neurooncol Adv Supplement Abstracts BACKGROUND: Patients diagnosed with BMETS want to know their prognosis and the benefit of treatment to make informed decisions. Clinician and patient biases frequently provide survival estimates that are too optimistic or pessimistic. We postulated that that RPA remains a useful tool to communicate prognosis and potential benefit from brain-directed treatment (BDT). We evaluated real-world data on RPA class and survival of patients with newly diagnosed BMETS from three academic institutions. METHODS: We retrospectively reviewed the records of patients with BMETS between 2017 and 2019 who had at least 6 months of follow up. Excluded were patients with leptomeningeal or only dural/calvarial metastases. We calculated the RPA and according to class compared Kaplan-Meier survival curves. RESULTS: We have data on 642 cases with median age of 65 years; 80% had lung, breast, melanoma, and renal as the primary cancer. Sixty (9.3%) patients received palliative care only, while 582 (90.7%) had BDT. The median survival of all patients according to RPA in months was 18.0 (I), 9.4 (II), and 2.4 (III) and for those receiving BDT (n=582), it was 19.2 (I), 11.2 (II), and 2.9 (III). There were statistically significant differences for BDT survival curves adjusted for multiple comparisons (I-II p=0.0124; II-III p<0.0001; I-III p<0.0001). For patients in RPA class III who received WBRT (n=62), the median survival was 2.9 months, and, for SRS (n=37), it was 3.5 months. We will present updated data including additional 238 cases and propose predictive/prognostic models based on our cohort that optimizes the RPA application in clinical practice. CONCLUSION: In contemporary practice, the RPA classification remains significantly relevant in making care decisions for patients diagnosed with BMETS. Treatment recommendations for patients in RPA class III should be the result of multidisciplinary discussions with consideration for early palliative care involvement to de-escalate and avoid inefficacious BDT. Oxford University Press 2022-08-05 /pmc/articles/PMC9354187/ http://dx.doi.org/10.1093/noajnl/vdac078.033 Text en © The Author(s) 2022. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Supplement Abstracts Sarai, Guneet Amidon, Ryan F Bovi, Joesph A Thomas, Alissa A Novicoff, Wendy Schuetz, Samantha Singh, Rohit Chang, Amy Sheehan, Jason P Fadul, Camilo E CLRM-13 RELEVANCE OF RECURSIVE PARTITIONING ANALYSIS (RPA) CLASSIFICATION IN THE CURRENT CARE OF PATIENTS WITH BRAIN METASTASES (BMETS) |
title | CLRM-13 RELEVANCE OF RECURSIVE PARTITIONING ANALYSIS (RPA) CLASSIFICATION IN THE CURRENT CARE OF PATIENTS WITH BRAIN METASTASES (BMETS) |
title_full | CLRM-13 RELEVANCE OF RECURSIVE PARTITIONING ANALYSIS (RPA) CLASSIFICATION IN THE CURRENT CARE OF PATIENTS WITH BRAIN METASTASES (BMETS) |
title_fullStr | CLRM-13 RELEVANCE OF RECURSIVE PARTITIONING ANALYSIS (RPA) CLASSIFICATION IN THE CURRENT CARE OF PATIENTS WITH BRAIN METASTASES (BMETS) |
title_full_unstemmed | CLRM-13 RELEVANCE OF RECURSIVE PARTITIONING ANALYSIS (RPA) CLASSIFICATION IN THE CURRENT CARE OF PATIENTS WITH BRAIN METASTASES (BMETS) |
title_short | CLRM-13 RELEVANCE OF RECURSIVE PARTITIONING ANALYSIS (RPA) CLASSIFICATION IN THE CURRENT CARE OF PATIENTS WITH BRAIN METASTASES (BMETS) |
title_sort | clrm-13 relevance of recursive partitioning analysis (rpa) classification in the current care of patients with brain metastases (bmets) |
topic | Supplement Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354187/ http://dx.doi.org/10.1093/noajnl/vdac078.033 |
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