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Cancer Research and Treatment > Epub ahead of print
doi: https://doi.org/10.4143/crt.2023.1243    [Epub ahead of print]
Development of a Prediction Model for Delirium in Hospitalized Patients with Advanced Cancer
Eun Hee Jung1 , Shin Hye Yoo2 , Si Won Lee3,4,5 , Beodeul Kang6 , Yu Jung Kim1
1Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
2Center for Palliative Care and Clinical Ethics, Seoul National University Hospital, Seoul, Korea
3Palliative Care Center, Yonsei Cancer Center, Yonsei University Health System, Seoul, Korea
4Division of Medical Oncology, Yonsei Cancer Center, Yonsei University Health System, Seoul, Korea
5Yonsei Graduate School, Yonsei University College of Medicine, Seoul, Korea
6Division of Medical Oncology, Department of Internal Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea
Correspondence  Si Won Lee ,Tel: 82-2-2228-4595, Fax: 82-2-2227-8084 , Email: LEESIWON925@yuhs.ac
Beodeul Kang ,Tel: 82-31-780-3438, Fax: 82-31-780-3929, Email: wb0707@cha.ac.kr
Received: November 21, 2023;  Accepted: February 23, 2024.  Published online: February 26, 2024.
*Eun Hee Jung and Shin Hye Yoo contributed equally to this work.
ABSTRACT
Purpose
Delirium is a common neurocognitive disorder in patients with advanced cancer and is associated with poor clinical outcomes. As a potentially reversible phenomenon, early recognition of delirium by identifying the risk factors demands attention. We aimed to develop a model to predict the occurrence of delirium in hospitalized patients with advanced cancer.
Materials and Methods
This retrospective study included patients with advanced cancer admitted to the oncology ward of four tertiary cancer centers in Korea for supportive cares and excluded those discharged due to death. The primary endpoint was occurrence of delirium. Sociodemographic characteristics, clinical characteristics, laboratory findings, and concomitant medication were investigated for associating variables. The predictive model developed using multivariate logistic regression was internally validated by bootstrapping.
Results
From January 2019 to December 2020, 2,152 patients were enrolled. The median age of patients was 64 years, and 58.4% were male. A total of 127 patients (5.9%) developed delirium during hospitalization. In multivariate logistic regression, age, body mass index, hearing impairment, previous delirium history, length of hospitalization, chemotherapy during hospitalization, blood urea nitrogen and calcium levels, and concomitant antidepressant use were significantly associated with the occurrence of delirium. The predictive model combining all four categorized variables showed the best performance among the developed models (area under the curve 0.831, sensitivity 80.3%, and specificity 72.0%). The calibration plot showed optimal agreement between predicted and actual probabilities through internal validation of the final model.
Conclusion
We proposed a successful predictive model for the risk of delirium in hospitalized patients with advanced cancer.
Key words: Delirium, Neoplasms, Palliative care, Predictive model
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