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Prediction model for shortterm mortality after palliative radiotherapy for patients having advanced cancer: a cohort study from routine electronic medical data
dc.contributor.author | Lee, Shing Fung | |
dc.contributor.author | Luk, Hollis | |
dc.contributor.author | Wong, Aray | |
dc.contributor.author | Kwan Ng, Chuk | |
dc.contributor.author | Chi Sing Wong, Frank | |
dc.contributor.author | Luque Fernández, Miguel Ángel | |
dc.date.accessioned | 2024-10-03T08:13:30Z | |
dc.date.available | 2024-10-03T08:13:30Z | |
dc.date.issued | 2020-04-01 | |
dc.identifier.citation | Shing Fung, L. et. al. Sci Rep 10, 5779 (2020). [https://doi.org/10.1038/s41598-020-62826-x] | es_ES |
dc.identifier.uri | https://hdl.handle.net/10481/95460 | |
dc.description.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, 24.5–69.3) 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: 1.47–2.04) and log peripheral blood neutrophil lymphocyte ratio (odds ratio: 1.71, 95% confidence interval: 1.52–1.92). The developed predictive scoring system had 10 predictor variables and 20 points. The cross-validated area under curve was 0.81 (95% confidence interval: 0.79–0.82). The calibration suggested a reasonably good fit for the model (likelihood-ratio statistic: 2.81, P = 0.094), providing an accurate prediction for almost all 30-day mortality probabilities. The predictive scoring system accurately predicted 30-day mortality among patients with stage IV cancer. Oncologists may use this to tailor palliative therapy for patients. | es_ES |
dc.description.sponsorship | Miguel Servet I Investigator Award (grant CP17/00206 EU-FEDER) from the National Institute of Health, Carlos III (ISCIII), Madrid, Spain | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Springer Nature | es_ES |
dc.rights | Atribución 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.title | Prediction model for shortterm mortality after palliative radiotherapy for patients having advanced cancer: a cohort study from routine electronic medical data | es_ES |
dc.type | journal article | es_ES |
dc.rights.accessRights | open access | es_ES |
dc.identifier.doi | 10.1038/s41598-020-62826-x | |
dc.type.hasVersion | VoR | es_ES |