%0 Journal Article
%T Survival Prediction Score: A Simple but Age-Dependent Method Predicting Prognosis in Patients Undergoing Palliative Radiotherapy
%A Kent Angelo
%A Astrid Dalhaug
%A Adam Pawinski
%A Ellinor Haukland
%A Carsten Nieder
%J ISRN Oncology
%D 2014
%R 10.1155/2014/912865
%X 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) ¡Ü 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. 1. Introduction Gradual refinement of palliative oncological treatment approaches has contributed to better, prognosis-adapted cancer care. In part, disease trajectories extend over many years, even in patients without curative treatment option. In contrast, other patients with poorly responding tumors often face rapid disease progression and, as a direct consequence, limited survival. Clinicians are trying to tailor their treatment approaches by estimating patients¡¯ prognosis. While physicians¡¯ clinical experience and previous course of disease might provide hints [1, 2], a large number of more objective assessments tools have been developed [3¨C8], both for research purposes, patient stratification in clinical trials, and decision making. The choice between different tools might not always be easy. Ideally, prognostic scores are easy to administer, without need for expensive imaging or biomarker assessment, and valid across different institutions and countries [9]. The survival prediction score (SPS) developed by Chow et al. is among the tools that might be widely applicable, because it is based on three readily available parameters: primary cancer type, site of metastases, and performance status [10]. The present study reexamines
%U http://www.hindawi.com/journals/isrn.oncology/2014/912865/