Please use this identifier to cite or link to this item:
|Title:||A clinical decision support tool to predict survival in cancer patients beyond 120 days after palliative chemotherapy||Authors:||Ng, T.
|Issue Date:||1-Aug-2012||Citation:||Ng, T., Chew, L., Yap, C.W. (2012-08-01). A clinical decision support tool to predict survival in cancer patients beyond 120 days after palliative chemotherapy. Journal of Palliative Medicine 15 (8) : 863-869. ScholarBank@NUS Repository. https://doi.org/10.1089/jpm.2011.0417||Abstract:||Background: Palliative chemotherapy is often administered to terminally ill cancer patients to relieve symptoms. Yet, unnecessary use of chemotherapy can worsen patients' quality of life due to treatment-related toxicities. Thus, accurate prediction of survival in terminally ill patients can help clinicians decide on the most appropriate palliative care for these patients. However, studies have shown that clinicians often make imprecise predictions of survival in cancer patients. Hence, the purpose of this study was to create a clinical decision support tool to predict survival in cancer patients beyond 120 days after palliative chemotherapy. Materials and Methods: Data were obtained from a retrospective study of 400 randomly selected terminally ill cancer patients in the National Cancer Centre Singapore (NCCS) from 2008 to 2009. After removing patients with missing data, there were 325 patients remaining for model development. Three classification algorithms, naive Bayes (NB), neural network (NN), and support vector machine (SVM) were used to create the models. A final model with the best prediction performance was then selected to develop the tool. Results: The NN model had the best prediction performance. The accuracy, specificity, sensitivity, and area under the curve (AUC) of this model were 78%, 82%, 74%, and 0.857, respectively. Five patient attributes (albumin level, alanine transaminase level (ATL), absolute neutrophil count, Eastern Cooperative Oncology Group (ECOG) status, and number of metastatic sites) were included in the model. Conclusions: A decision support tool to predict survival in cancer patients beyond 120 days after palliative chemotherapy was created. With further validation, this tool coupled with the professional judgment of clinicians can help improve patient care. © Copyright 2012, Mary Ann Liebert, Inc.||Source Title:||Journal of Palliative Medicine||URI:||http://scholarbank.nus.edu.sg/handle/10635/105553||ISSN:||10966218||DOI:||10.1089/jpm.2011.0417|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Apr 3, 2020
WEB OF SCIENCETM
checked on Mar 18, 2020
checked on Mar 28, 2020
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.