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- Publisher Website: 10.1038/s41598-020-62826-x
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- PMID: 32238885
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Article: Prediction model for short-term mortality after palliative radiotherapy for patients having advanced cancer: a cohort study from routine electronic medical data
Title | Prediction model for short-term mortality after palliative radiotherapy for patients having advanced cancer: a cohort study from routine electronic medical data |
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Authors | |
Issue Date | 2020 |
Citation | Scientific Reports, 2020, v. 10, n. 1, article no. 5779 How to Cite? |
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. |
Persistent Identifier | http://hdl.handle.net/10722/303661 |
PubMed Central ID | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Lee, Shing Fung | - |
dc.contributor.author | Luk, Hollis | - |
dc.contributor.author | Wong, Aray | - |
dc.contributor.author | Ng, Chuk Kwan | - |
dc.contributor.author | Wong, Frank Chi Sing | - |
dc.contributor.author | Luque-Fernandez, Miguel Angel | - |
dc.date.accessioned | 2021-09-15T08:25:46Z | - |
dc.date.available | 2021-09-15T08:25:46Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Scientific Reports, 2020, v. 10, n. 1, article no. 5779 | - |
dc.identifier.uri | http://hdl.handle.net/10722/303661 | - |
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. | - |
dc.language | eng | - |
dc.relation.ispartof | Scientific Reports | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.title | Prediction model for short-term mortality after palliative radiotherapy for patients having advanced cancer: a cohort study from routine electronic medical data | - |
dc.type | Article | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1038/s41598-020-62826-x | - |
dc.identifier.pmid | 32238885 | - |
dc.identifier.pmcid | PMC7113237 | - |
dc.identifier.scopus | eid_2-s2.0-85082979089 | - |
dc.identifier.volume | 10 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | article no. 5779 | - |
dc.identifier.epage | article no. 5779 | - |
dc.identifier.eissn | 2045-2322 | - |
dc.identifier.isi | WOS:000563465100014 | - |