ArticleRadiation oncology (London, England)2016
Overall survival after reirradiation of spinal metastases - independent validation of predictive models.
Article in Radiation oncology (London, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Development of a Predictive Model for Large-Volume Pleural Effusion After Separation Surgery in Patients With Spinal Metastatic Tumors.Cancer reports (Hoboken, N.J.) · 2025Article
- Predicting the survival of patients with painful tumours treated with palliative radiotherapy: a secondary analysis using the 3-variable number-of-risk-factors model.Radiation oncology (London, England) · 2024Article
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Authors and funding
5 authors.
Funding
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Abstract
backgroundIt 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.
methodsWe 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).
resultsConsistently 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.
conclusionsSurvival 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.
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