@article {cite-key,
	title = {Prediction model for short-term mortality after palliative radiotherapy for patients having advanced cancer: a cohort study from routine electronic medical data},
	journal = {Scientific Reports},
	volume = {10},
	number = {1},
	year = {2020},
	pages = {5779},
	abstract = {{We developed a predictive score system for 30-day mortality after palliative radiotherapy by using predictors from routine electronic medical record. Patients with metastatic cancer receiving first course palliative radiotherapy from 1 July, 2007 to 31 December, 2017 were identified. 30-day mortality odds ratios and probabilities of the death predictive score were obtained using multivariable logistic regression model. Overall, 5,795 patients participated. Median follow-up was 39.6 months (range, 24.5{\textendash}69.3) for all surviving patients. 5,290 patients died over a median 110 days, of whom 995 (17.2\%) died within 30 days of radiotherapy commencement. The most important mortality predictors were primary lung cancer (odds ratio: 1.73, 95\% confidence interval: 1.47{\textendash}2.04) and log peripheral blood neutrophil lymphocyte ratio (odds ratio: 1.71, 95\% confidence interval: 1.52{\textendash}1.92). The developed predictive scoring system had 10 predictor variables and 20 points. The cross-validated area under curve was 0.81 (95\% confidence interval: 0.79{\textendash}0.82). The calibration suggested a reasonably good fit for the model (likelihood-ratio statistic: 2.81},
	isbn = {2045-2322},
	doi = {10.1038/s41598-020-62826-x},
	url = {https://doi.org/10.1038/s41598-020-62826-x},
	author = {Lee, Shing Fung and Luk, Hollis and Wong, Aray and Ng, Chuk Kwan and Wong, Frank Chi Sing and Luque-Fernandez, Miguel Angel}
}
