Predictive Model for Survival in Patients With Advanced Cancer Edward Chow, Mohamed Abdolell, Tony Panzarella, Kristin Harris, Andrea Bezjak, Padraig Warde, and Ian Tannock From the Odette Cancer Centre, Sunny- brook Health Sciences Centre; and Prin- cess Margaret Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada. Submitted March 11, 2008; accepted August 15, 2008; published online ahead of print at www.jco.org on November 17, 2008. Supported by the Michael and Karyn Goldstein Cancer Research Fund, Department of Radiation Oncology, University of Toronto, and Odette Cancer Center Radiation Program Fund. Authors’ disclosures of potential con- flicts of interest and author contribu- tions are found at the end of this article. Corresponding author: Edward Chow, MBBS, PhD, FRCPC, Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, Toronto, Ontario, Canada M4N 3M5; e-mail: edward.chow@sunnybrook.ca. © 2008 by American Society of Clinical Oncology 0732-183X/08/2636-5863/$20.00 DOI: 10.1200/JCO.2008.17.1363 A B S T R A C T Purpose To derive and validate a simple predictive model for survival of patients with metastatic cancer attending a palliative radiotherapy clinic. Patients and Methods We described previously a model predicting survival of patients referred for palliative radiotherapy using six prognostic factors: primary cancer site, site of metastases, Karnofsky performance score (KPS), and the fatigue, appetite, and shortness of breath subscales from the Edmonton Symptom Assessment Scale. Here we simplified the model to include only three factors: primary cancer site, site of metastases, and KPS. Each factor was assigned a value proportional to its prognostic weight, and the weighted scores for each patient were summed to obtain a survival prediction score (SPS). Patients were also grouped according to their number of risk factors (NRF): nonbreast cancer, metastases other than bone, and KPS  60. The three- and six- variable models were evaluated for their ability to predict survival in patients referred during a different time period and of those referred to a different cancer center. Results A training set of 395 patients, a temporal validation set of 445 patients, and an external validation set of 467 patients were used. The ability of the three- and six-variable models to separate patients into three prognostic groups and to predict their survival was similar using both SPS and NRF methods in the training, temporal, and external validation data sets. There was no statistically significant difference in the performance of the models. Conclusion The three-variable NRF model is preferred because of its relative simplicity. J Clin Oncol 26:5863-5869. © 2008 by American Society of Clinical Oncology INTRODUCTION The classification of patients with advanced can- cer into groups with similar and predictable sur- vival has the potential to lead to improvement in delivery of care and to minimize undertreatment or overtreatment. 1,2 We developed previously a predictive model for survival of patients with ad- vanced cancer by analyzing prospectively 16 fac- tors in 395 patients referred to our palliative radiotherapy program. 3 We used a Cox propor- tional hazards regression model and found that the following six factors had a statistically signifi- cant impact on survival: primary cancer site, site(s) of metastases, Karnofsky performance score (KPS), and the fatigue, appetite, and short- ness of breath subscalesshortness of breath sub- scales from the Edmonton System Assessment Scale (ESAS). 4 This model has been successfully validated using an independent data set based on referral of patients to the same center during a different time period (temporal validation). The predictive model that we developed in- cludes the patient’s own assessment of fatigue, appe- tite, and shortness of breath from the ESAS. However, this may not be easy or possible to collect if there are language barriers, if patients are too sick to do the survey, and/or if no research assistants are available. The objective of the present study was to evaluate a simpler model using the three readily available parameters: primary cancer site (breast, prostate, lung, and others), site of metastases (bone metastases only v others), and KPS, using both tem- poral and external validation. PATIENTS AND METHODS Rapid Response Radiotherapy Program Database The Rapid Response Radiotherapy Program (RRRP) at Odette Cancer Centre (Toronto, Ontario, Canada) was JOURNAL OF CLINICAL ONCOLOGY O R I G I N A L R E P O R T VOLUME 26  NUMBER 36  DECEMBER 20 2008 © 2008 by American Society of Clinical Oncology 5863 Downloaded from jco.ascopubs.org on July 20, 2016. For personal use only. No other uses without permission. Copyright © 2008 American Society of Clinical Oncology. All rights reserved.