• Edward Chow, KinWah Fung, Tony Panzarella, Andrea Bezjak, Cyril Danjoux, and Ian Tannock.
• Toronto-Sunnybrook Regional Cancer Centre, University of Toronto, Toronto, Canada. Edward.Chow@tsrcc.on.ca
• Int. J. Radiat. Oncol. Biol. Phys. 2002 Aug 1; 53 (5): 1291-302.

PurposeTo develop a predictive model for survival from the time of presentation in an outpatient palliative radiotherapy clinic.Methods And MaterialsSixteen factors were analyzed prospectively in 395 patients seen in a dedicated palliative radiotherapy clinic in a large tertiary cancer center using Cox's proportional hazards regression model.ResultsSix prognostic factors had a statistically significant impact on survival, as follows: primary cancer site, site of metastases, Karnofsky performance score (KPS), and fatigue, appetite, and shortness of breath scores from the modified Edmonton Symptom Assessment Scale. Risk group stratification was performed (1) by assigning weights to the prognostic factors based on their levels of significance, and (2) by the number of risk factors present. The weighting method provided a Survival Prediction Score (SPS), ranging from 0 to 32. The survival probability at 3, 6, and 12 months was 83%, 70%, and 51%, respectively, for patients with SPS or=20 (n = 133) (p < 0.0001). Corresponding survival probabilities based on number of risk factors were as follows: 85%, 72%, and 52% (or=5 factors)(n = 180)(p < 0.0001).ConclusionClinical prognostic factors can be used to predict prognosis among patients attending a palliative radiotherapy clinic. If validated in an independent series of patients, the model can be used to guide clinical decisions, plan supportive services, and allocate resource use.

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