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dc.contributor.advisorNieder, Carsten
dc.contributor.authorKämpe, Thomas André Ankill
dc.description.abstractPurpose: The purpose of this study is to find out if there is any correlation between symptoms and prognosis in patients who are undergoing palliative radiation therapy (PRT). And with these findings develop a better prognostic model to predict survival. Method: A retrospective review of 102 PRT records was performed. The patients were treated between 2012 and 2015 and scored their symptoms before PRT on the Edmonton Symptom Assessment System (ESAS). Uni- and multivariate analyses were performed to identify potential predictive factors, and from these a predictive model was developed. Results: Median survival was 246 days. Multivariate analyses confirmed the significance of 6 factors, from which a predictive model was developed. These were ESAS pain (while not moving), ESAS appetite, ECOG performance status, pleural effusion/ pleural metastases, iv. antibiotics during or within 2 weeks before PRT and no systemic cancer treatment. Median survival in patients with 5-6 of these predictive factors was 56 days, while patients with one or less had a median survival of 696 days. Conclusion: Developing exact predictive models in cancer patients were PRT is considered is a difficult task to achieve, and many factors must be taken into consideration. Our model does however show great potential. Given validation in another population, it can serve as an objective tool for clinicians when recommending optimal treatment for patients.en_US
dc.publisherUiT Norges arktiske universiteten_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.rights.holderCopyright 2016 The Author(s)
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)en_US
dc.subjectVDP::Medical disciplines: 700::Clinical medical disciplines: 750::Oncology: 762en_US
dc.subjectVDP::Medisinske Fag: 700::Klinisk medisinske fag: 750::Onkologi: 762en_US
dc.titleImpact of pre-treatment symptoms on survival after palliative radiotherapy. An improved model to predict prognosis?en_US
dc.typeMaster thesisen_US

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Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
Med mindre det står noe annet, er denne innførselens lisens beskrevet som Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)