Survival after palliative radiation therapy for cancer: The METSSS model.

Abstract Background We propose a predictive model that identifies patients at greatest risk of death after palliative radiotherapy, which can help medical professionals choose treatments that better align with patient choice and prognosis. Methods The National Cancer Database was queried for recipients of palliative radiotherapy during first course of treatment. Cox regression models and adjusted hazard ratios with 95% confidence intervals were used to evaluate survival predictors. The mortality risk index was calculated using predictors from the estimated Cox regression model, with higher values indicating higher mortality risk. Based on tertile cutpoints, patients were divided into low, medium, and high risk groups. Results A total of 68,505 patients were included from 2010-2014 (median age 65.7 years, standard deviation 11.8 years, IQR 16, median 66). Upon univariable and multivariable analyses, several risk factors were found to predict survival: (1) location of metastases (liver, bone, lung, and brain); (2) age >65 years; (3) tumor primary (prostate, breast, and lung); (4) male; (5) Charlson-Deyo comorbidity score of 3+; and (6) radiotherapy site, including bone, brain and eye, thorax, and stomach, liver, pancreas, kidney, and abdomen. The median survival times were 11.66 months, 5.09 months, and 3.28 months in the low (n=22,621), medium (n=22,638), and high risk groups (n=22,611), respectively. A nomogram was created and validated to predict survival, available online, https://tinyurl.com/METSSSmodel . Conclusion We created a predictive nomogram for survival of patients receiving palliative radiotherapy during their first course of treatment (named METSSS), based on Metastases location, Elderly (>65 years), Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy.