RT Journal Article
SR Electronic
T1 Development and Validation of a Model Predicting Short Survival (Death Within 30 Days) After Palliative Radiotherapy
JF Anticancer Research
JO Anticancer Res
FD International Institute of Anticancer Research
SP 877
OP 885
VO 34
IS 2
A1 KENT ANGELO
A1 JAN NORUM
A1 ASTRID DALHAUG
A1 ADAM PAWINSKI
A1 GRO AANDAHL
A1 ELLINOR HAUKLAND
A1 KIRSTEN ENGLJÄHRINGER
A1 CARSTEN NIEDER
YR 2014
UL http://ar.iiarjournals.org/content/34/2/877.abstract
AB The present study aimed to develop a predictive model that would allow for reduced utilization of palliative radiotherapy (PRT) during the final 30 days of life in patients with incurable cancer. We performed uni- and multivariate analyses of factors predicting PRT during the final 30 days of life for all PRT courses administered at a dedicated PRT facility between 20.06.2007 and 31.12.2009. We also developed a predictive model by recursive partitioning analysis (RPA), followed by independent validation of its performance in patients treated during 2010 and 2011. We analyzed 579 PRT courses. Median survival was 6.3 months. In 53 cases (9%) PRT was administered during the final 30 days of life. RPA resulted in a model consisting of six parameters (lung or bladder cancer, Eastern Cooperative Oncology Group performance status of 3-4, low hemoglobin, opioid analgesic use, steroid use, known progressive disease outside PRT volume), which correctly identified 75% of PRT courses administered during the final 30 days of life. Maximum survival of patients fulfilling all criteria was 69 days. Death within 40 days occurred in 83% of patients. In the independent validation data set, similar results were obtained: 74% (30 days), 84% (40 days), while maximum survival was 92 days. As demonstrated here and in other recent studies, assigning the right patient to the right palliative approach is challenging. We suggest that patients with lung or bladder cancer and the adverse features mentioned above are at high risk of dying shortly after initiation of PRT. Our model might support decision-making (best supportive care versus PRT) and is the first decision aid specifically addressing PRT near end of life.