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Abstract: Aims: To determine the efficacy of radiotherapy for the palliation of pain from bone metastases among patients in their last 3 months of life. Materials and methods: Mutually exclusive, prospectively gathered Edmonton Symptom Assessment System and Brief Pain Inventory databases compiled from patients with bone metastases receiving palliative radiotherapy were reviewed. Demographic information and response rates from patients dying within 3 months of beginning radiotherapy were analysed. Results: From a total of 918 patients, 232 dying within 3 months of beginning treatment were identified. There were 148 men and 84 women. Their median age was 69 years and their median Karnofsky Performance Status was 60. The three most common primary cancers were lung (34%), prostate (18%) and gastrointestinal (14%). Fifty-eight percent of patients received single fraction treatment. A pain response was evaluable for the 109 (47%) patients with available follow-up information. The overall response rates were 70% at 1 month and 63% at 2 months, which included complete and partial responses in accordance with the International Bone Metastases Consensus definitions. Conclusions: Despite their limited lifespan, patients reported pain relief after palliative radiotherapy. Patients suffering from painful bone metastases with an estimated survival of 3 months should still be considered for palliative radiotherapy. [Copyright &y& Elsevier]

Background: Few studies incorporate patient self-assessment scales in prognostic models of survival prediction. The Edmonton Symptom Assessment Scale (ESAS) is commonly used as a symptom screening tool in cancer patients. Objective: The goal of this study was to evaluate the prognostic value of the ESAS for survival prediction in the advanced cancer population. Materials and Methods: Patients completed the ESAS and demographic information prior to palliative radiotherapy consultation and at follow-up at the Odette Cancer Centre between 1999 and 2009. Generalized estimating equation (GEE) methodology was applied to analyze ESAS trends within the last months of life. One-way analysis of variance (ANOVA) with repeated measurements was used to characterize trends between time periods. Results: ESAS records (2377) from 808 patients (433 male and 375 female) were included in this cohort. Median age was 68 years (range 32-95) with median Karnofsky performance status (KPS) of 60 (range 10-100). Primary cancer sites were of the lung (36%), breast (20%), and prostate (19%). All nine ESAS symptoms significantly deteriorated in the last 4 weeks immediately before death when compared with those scores in the preceding months. At one week prior to death, the worst ESAS symptoms experienced by patients were fatigue, appetite, and well-being with mean scores of 7.4, 6.9, and 6.1, respectively. Conclusions: All ESAS scores significantly worsened in the last 4 weeks prior to death compared with those in the previous months. Sudden deterioration of the global ESAS symptoms may predict impending death. Future studies on a prognostic model should incorporate both ESAS symptom severity and trends. [ABSTRACT FROM AUTHOR]

In observational studies on cancer patients, progression of performance status over time can be described by using a multistate model in which state-to-state transitions represent changes in a patient's health condition. Although a patient experiences transitions in continuous time, assessments on the patient are often made at irregularly spaced time points. In this paper, the authors formulate a Markov 4-state model for examining longitudinal data on performance status collected under intermittent observation. The cohort consisted of 11,342 patients diagnosed with cancer in Ontario, Canada, from 2007 to 2009. The authors extend the model to estimate the predicted probability of reaching the absorbing state, death, over various time intervals. The authors also illustrate what happens to the estimated transition intensities if the true observational scheme is overlooked. Methods for multistate analysis should be used by epidemiologists, since they prove particularly useful for examining the complexities of disease processes. [ABSTRACT FROM PUBLISHER]