ArticleScientific reports2020
Prediction model for short-term mortality after palliative radiotherapy for patients having advanced cancer: a cohort study from routine electronic medical data.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of the assessment model for palliative care needs in cancer patients.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Pooled it
- Outcomes of patients receiving urgent palliative radiotherapy for advanced lung cancer: an observational study.BMC palliative care · 2024Observational
- Early mortality in patients with cancer treated with immune checkpoint inhibitors in routine practice.Journal of the National Cancer Institute · 2023Article
- Article
- Palliative appropriateness criteria: external validation of a new method to evaluate the suitability of palliative radiotherapy fractionation.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2023Article
- Identifying patients with malignant spinal cord compression (MSCC) near end of life who can benefit from palliative radiotherapy.Radiation oncology (London, England) · 2022Article
- Dual Use of the METSSS Model Predicting Survival After Palliative Radiotherapy: An Exploratory Analysis.Cureus · 2022Article
- Pre-diagnosis neutrophil-to-lymphocyte ratio and mortality in individuals who develop lung cancer.Cancer causes & control : CCC · 2021Article
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6 authors.
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No grant is acknowledged in the PubMed record.
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.
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