biostudies-literatureZaorsky NGAmerican Cancer SocietyNCI NIH HHSNIH104-111https://www.ebi.ac.uk/biostudies/studies/S-EPMC9074852biostudies-literatureUnknown158<h4>Background</h4>We propose a predictive model that identifies patients at greatest risk of death after palliative radiotherapy, and subsequently, can help medical professionals choose treatments that better align with patient choice and prognosis.<h4>Methods</h4>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.<h4>Results</h4>A total of 68,505 patients were includeRadiotherapy and oncology : journal of the European Society for Therapeutic Radiology and OncologySurvival after palliative radiation therapy for cancer: The METSSS model.PMC9074852L30 CA231572Fox EJWang MZaorsky NGLin CPatel RTchelebi LTLiang MNewport KBfalseSurvival after palliative radiation therapy for cancer: The METSSS model.<h4>Background</h4>We propose a predictive model that identifies patients at greatest risk of death after palliative radiotherapy, and subsequently, can help medical professionals choose treatments that better align with patient choice and prognosis.<h4>Methods</h4>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.<h4>Results</h4>A total of 68,505 patients were include2021-01-01T00:00:00Z2021 May2025-04-04T23:17:29.047Z2025-04-04T23:17:29.047ZS-EPMC90748523361062310.1016/j.radonc.2021.02.011