Predicting Survival for Patients with Metastatic Disease. International journal of radiation oncology, biology, physics Benson, K. R., Aggarwal, S., Carter, J. N., von Eyben, R., Pradhan, P., Prionas, N. D., Bui, J. L., Soltys, S. G., Hancock, S., Gensheimer, M. F., Koong, A. C., Chang, D. T. 2019


PURPOSE: This prospective study aimed to determine the accuracy of radiation oncologists in predicting the survival of patients with metastatic disease receiving radiotherapy and to understand factors associated with their accuracy.METHODS AND MATERIALS: This single-institution study surveyed 22 attending radiation oncologists to estimate patient survival. Survival predictions were defined as accurate if the observed survival (OS) was within the correct survival prediction category (0-6 months, >6-12 months, >12-24 months, and >24 months). The physicians made survival estimates for each course of radiation, yielding 877 analyzable predictions for 689 unique patients. Data analysis included Stuart's Tau C, logistic regression models, ordinal logistic regression models, and stepwise selection to examine variable interactions.RESULTS: Of the 877 radiation oncologists' predictions, 39.7% were accurate, 26.5% underestimations, and 33.9% overestimations. Stuart's Tau C showed low correlation between OS and survival estimates (0.3499), consistent with the inaccuracy reported in literature. However, results showed less systematic over-prediction than reported in the literature. Karnofsky performance status (KPS) was the most significant predictor of accuracy with greater accuracy for patients with shorter OS. Estimates were also more accurate for patients with lower KPS. Accuracy by patient age varied by primary site and race. Physician years of experience did not correlate with accuracy.CONCLUSIONS: The sampled radiation oncologists have relatively low accuracy in predicting patient survival. Future investigation should explore how survival estimates influence treatment decisions and how to improve survival prediction accuracy.

View details for DOI 10.1016/j.ijrobp.2019.10.032

View details for PubMedID 31682969