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Overall survival after reirradiation of spinal metastases – independent validation of predictive models
BACKGROUND: It is unknown if survival prediction tools (SPTs) sufficiently predict survival in patients who undergo palliative reirradiation of spinal metastases. We therefore set out to clarify if SPTs can predict survival in this patient population. METHODS: We retrospectively analyzed spinal reir...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4782309/ https://www.ncbi.nlm.nih.gov/pubmed/26951042 http://dx.doi.org/10.1186/s13014-016-0613-y |
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author | Buergy, Daniel Siedlitzki, Lena Boda-Heggemann, Judit Wenz, Frederik Lohr, Frank |
author_facet | Buergy, Daniel Siedlitzki, Lena Boda-Heggemann, Judit Wenz, Frederik Lohr, Frank |
author_sort | Buergy, Daniel |
collection | PubMed |
description | BACKGROUND: It is unknown if survival prediction tools (SPTs) sufficiently predict survival in patients who undergo palliative reirradiation of spinal metastases. We therefore set out to clarify if SPTs can predict survival in this patient population. METHODS: We retrospectively analyzed spinal reirradiations performed (n = 58, 52 patients, 44 included in analysis). SPTs for patients with spinal metastases were identified and compared to a general palliative score and to a dedicated SPT to estimate prognosis in palliative reirradiation independent of site (SPT-Nieder). RESULTS: Consistently in all tests, SPT-Nieder showed best predictive performance as compared to other tools. Items associated with survival were general condition (KPS), liver metastases, and steroid use. Other factors like primary tumor site, pleural effusion, and bone metastases were not correlated with survival. We adapted an own score to the data which performed comparable to SPT-Nieder but avoids the pleural effusion item. Both scores showed good performance in identifying long-term survivors with late recurrences. CONCLUSIONS: Survival prediction in case of spinal reirradiation is possible with sufficient predictive separation. Applying SPTs in case of reirradiation helps to identify patients with good life expectancy who might benefit from dose escalation or longer treatment courses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13014-016-0613-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4782309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-47823092016-03-09 Overall survival after reirradiation of spinal metastases – independent validation of predictive models Buergy, Daniel Siedlitzki, Lena Boda-Heggemann, Judit Wenz, Frederik Lohr, Frank Radiat Oncol Research BACKGROUND: It is unknown if survival prediction tools (SPTs) sufficiently predict survival in patients who undergo palliative reirradiation of spinal metastases. We therefore set out to clarify if SPTs can predict survival in this patient population. METHODS: We retrospectively analyzed spinal reirradiations performed (n = 58, 52 patients, 44 included in analysis). SPTs for patients with spinal metastases were identified and compared to a general palliative score and to a dedicated SPT to estimate prognosis in palliative reirradiation independent of site (SPT-Nieder). RESULTS: Consistently in all tests, SPT-Nieder showed best predictive performance as compared to other tools. Items associated with survival were general condition (KPS), liver metastases, and steroid use. Other factors like primary tumor site, pleural effusion, and bone metastases were not correlated with survival. We adapted an own score to the data which performed comparable to SPT-Nieder but avoids the pleural effusion item. Both scores showed good performance in identifying long-term survivors with late recurrences. CONCLUSIONS: Survival prediction in case of spinal reirradiation is possible with sufficient predictive separation. Applying SPTs in case of reirradiation helps to identify patients with good life expectancy who might benefit from dose escalation or longer treatment courses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13014-016-0613-y) contains supplementary material, which is available to authorized users. BioMed Central 2016-03-08 /pmc/articles/PMC4782309/ /pubmed/26951042 http://dx.doi.org/10.1186/s13014-016-0613-y Text en © Buergy et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Buergy, Daniel Siedlitzki, Lena Boda-Heggemann, Judit Wenz, Frederik Lohr, Frank Overall survival after reirradiation of spinal metastases – independent validation of predictive models |
title | Overall survival after reirradiation of spinal metastases – independent validation of predictive models |
title_full | Overall survival after reirradiation of spinal metastases – independent validation of predictive models |
title_fullStr | Overall survival after reirradiation of spinal metastases – independent validation of predictive models |
title_full_unstemmed | Overall survival after reirradiation of spinal metastases – independent validation of predictive models |
title_short | Overall survival after reirradiation of spinal metastases – independent validation of predictive models |
title_sort | overall survival after reirradiation of spinal metastases – independent validation of predictive models |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4782309/ https://www.ncbi.nlm.nih.gov/pubmed/26951042 http://dx.doi.org/10.1186/s13014-016-0613-y |
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