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Prediction of recurrence-associated death from localized prostate cancer with a charlson comorbidity index–reinforced machine learning model
- Source :
- Open Medicine, Open Medicine, Vol 14, Iss 1, Pp 593-606 (2019)
- Publication Year :
- 2019
- Publisher :
- Walter de Gruyter GmbH, 2019.
-
Abstract
- Research has failed to resolve the dilemma experienced by localized prostate cancer patients who must choose between radical prostatectomy (RP) and external beam radiotherapy (RT). Because the Charlson Comorbidity Index (CCI) is a measurable factor that affects survival events, this research seeks to validate the potential of the CCI to improve the accuracy of various prediction models. Thus, we employed the Cox proportional hazard model and machine learning methods, including random forest (RF) and support vector machine (SVM), to model the data of medical records in the National Health Insurance Research Database (NHIRD). In total, 8581 individuals were enrolled, of whom 4879 had received RP and 3702 had received RT. Patients in the RT group were older and exhibited higher CCI scores and higher incidences of some CCI items. Moderate-to-severe liver disease, dementia, congestive heart failure, chronic pulmonary disease, and cerebrovascular disease all increase the risk of overall death in the Cox hazard model. The CCI-reinforced SVM and RF models are 85.18% and 81.76% accurate, respectively, whereas the SVM and RF models without the use of the CCI are relatively less accurate, at 75.81% and 74.83%, respectively. Therefore, CCI and some of its items are useful predictors of overall and prostate-cancer-specific survival and could constitute valuable features for machine-learning modeling.
- Subjects :
- Prostatectomy
business.industry
Proportional hazards model
Medical record
medicine.medical_treatment
030232 urology & nephrology
General Medicine
medicine.disease
Machine learning
computer.software_genre
03 medical and health sciences
Prostate cancer
Liver disease
0302 clinical medicine
030220 oncology & carcinogenesis
Heart failure
medicine
Medicine
Dementia
Artificial intelligence
External beam radiotherapy
business
computer
Research Article
Subjects
Details
- ISSN :
- 23915463
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- Open Medicine
- Accession number :
- edsair.doi.dedup.....d1e31b23aa0f3fc56d0d36a80d11f6e2
- Full Text :
- https://doi.org/10.1515/med-2019-0067