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

Abstract

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, P < 0.001. 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.

The influence of preoperative dependency on mortality, functional recovery and complications after microsurgical resection of intracranial tumors

“…The functional level of cancer patients as determined by the KPS is strongly linked to the disease burden, and can be used as prognostic predictor in general oncology. [12,13] In patients with intracranial tumors, however, poor functional level may be linked to the location of the lesion than to the general dissemination of the disease. [2] This concept has been substantiated by demonstrating that the prognostic impact of functional status was shown to be independent from tumor volume.…”

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

“…Except for SPT-Tokuhashi, SPTs developed to estimate survival after primary treatment of spinal metastases showed worse performance as compared to SPT-Nieder. The same was true for the well established SPT-Chow which is generally accepted as a valid survival tool in palliative cancer care [ 20 – 22 ]. On the other hand, SPT-Nieder which was developed in a small ( n = 87), inhomogeneous patient sample including reirradiations for brain, bone, and lung metastases, as well as primary tumors, among others [ 23 ], showed acceptable predictive separation.…”

“…In addition to spine-specific scores, we included the SPT as developed by Chow et al [ 20 , 21 ] (SPT-Chow). SPT-Chow was chosen because it is a simple and validated tool, widely applicable in palliative settings [ 22 ]. Furthermore, we included the SPT developed for reirradiation in general by Nieder et al [ 23 ].…”

Risk and reliability modelling for multi-vehicle marine domains

“…This survival plot could also be obtained as a function of time or time/distance ratio, which would likely be the most suitable approach in the present multi-vehicle scenario. Other nonparametric methods that have been used in other fields for survival plots are the Actuarial-Simple and Actuarial-Standard methods for multiple censored data that are arranged in intervals, or the use of Confidence-Bounds [17], [18]. Typical parametric methods used in statistics use a continuous function as the survival plot of a series of data.…”