Survival Prediction Score: A Simple but Age-Dependent Method Predicting Prognosis in Patients Undergoing Palliative RadiotherapyReportar como inadecuado

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ISRN OncologyVolume 2014 2014, Article ID 912865, 5 pages

Clinical Study

Department of Oncology and Palliative Medicine, Nordland Hospital, 8092 Bodø, Norway

Institute of Clinical Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway

Received 17 December 2013; Accepted 13 February 2014; Published 19 March 2014

Academic Editors: P. Herst and G. Metro

Copyright © 2014 Kent Angelo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Purpose. Validation of a Canadian three-tiered prognostic model survival prediction score, SPS in Norwegian cancer patients referred for palliative radiotherapy PRT, and evaluation of age-dependent performance of the model. Patients and Methods. We analyzed all 579 PRT courses administered at a dedicated PRT facility between 20.06.07 and 31.12.2009. SPS was assigned as originally described, That is, by taking into consideration three variables: primary cancer type, site of metastases, and performance status. Results. Patients with poor prognosis non-breast cancer, metastases other than bone, and Karnofsky performance status KPS ≤ 60 had median survival of 13 weeks. Those with intermediate prognosis two of these parameters survived for a median of 29 weeks, and patients with good prognosis for a median of 114 weeks, . While this model performed well in patients who were 60 years or older, it was less satisfactory in younger patients no significant difference between the good and intermediate prognosis groups. Conclusion. SPS should mainly be used to predict survival of elderly cancer patients. However, even in this group accuracy is limited because the good prognosis group contained patients with short survival, while the poor prognosis group contained long-term survivors. Thus, improved models should be developed.

Autor: Kent Angelo, Astrid Dalhaug, Adam Pawinski, Ellinor Haukland, and Carsten Nieder



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