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Radiation Oncology
Published in: Radiation Oncology 1/2016

Open Access 01-12-2016 | Research

Overall survival after reirradiation of spinal metastases – independent validation of predictive models

Authors: Daniel Buergy, Lena Siedlitzki, Judit Boda-Heggemann, Frederik Wenz, Frank Lohr

Published in: Radiation Oncology | Issue 1/2016

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Abstract

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.
Appendix
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Metadata
Title
Overall survival after reirradiation of spinal metastases – independent validation of predictive models
Authors
Daniel Buergy
Lena Siedlitzki
Judit Boda-Heggemann
Frederik Wenz
Frank Lohr
Publication date
01-12-2016
Publisher
BioMed Central
Published in
Radiation Oncology / Issue 1/2016
Electronic ISSN: 1748-717X
DOI
https://doi.org/10.1186/s13014-016-0613-y

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