학술논문
A New Mortality Prediction Model in Advanced Stage Cancer Patients Requiring Hospitalisation while Receiving Active Systemic Therapy
ORIGINAL ARTICLE
ORIGINAL ARTICLE
Document Type
Report
Source
Journal of the College of Physicians and Surgeons Pakistan. May 2023, Vol. 33 Issue 5, p548, 6 p.
Subject
Language
English
ISSN
1022-386X
Abstract
INTRODUCTION Accurate estimation of remaining life expectancy in patients with advanced cancer is important for the patient's future life plans and their caregivers and the effects on decision-making regarding medical [...]
Objective: To predict short and long-term mortality in patients who were admitted to the emergency department and then hospitalised unplanned in medical oncology-ward. Study Design: An observational study. Place and Duration of the Study: Department of Medical Oncology, Tekirdag Namik Kemal University Hospital, Tekirdag, Turkiye, from May 2021 to May 2022. Methodology: Consecutive patients admitted to the emergency department with unplanned hospitalisation in the oncology ward, were included. Patients receiving treatment with the curative intent, patients hospitalised for febrile neutropenia, and terminally ill patients requiring intensive care unit follow-up at admission were excluded from the study. Univariate and multivariate logistic regression analyses were used to identify predictive factors for short and long-term mortality-dependent variables. Results: This study included 253 advanced cancer patients. The number of patients who died in the ward within 10 days (short-term mortality) was 28 (11.1%). Ninety patients (35.6%) died afterwards anytime in the ward during the study (long-term mortality). In the multivariate analysis established for short-term mortality, higher ALT (OR = 6.75, 95% CI: 2.09 - 21.85, p=0.001), rapid deterioration in performance status (OR = 5.49, 95% CI: 1.81-16.67, p=0.003), higher CRP (OR = 5.86, 95% CI: 1.20-28.53, p=0.029), higher procalcitonin (OR = 7.94, 95% CI: 0.99 - 63.82, p=0.051), and higher lactate (OR = 2.47, 95% CI: 0.94-6.51, p=0.067) showed significant predictive features. Conclusion: The decision of whether to continue treatment or not is challenging in cancer patients who require unplanned hospitalisation while receiving palliative systemic therapy. New mortality estimation models can be used in making the transition from life-long to palliative treatments. Key Word: Mortality prediction, Hospitalisation, Estimation of survival, Chemotherapy.
Objective: To predict short and long-term mortality in patients who were admitted to the emergency department and then hospitalised unplanned in medical oncology-ward. Study Design: An observational study. Place and Duration of the Study: Department of Medical Oncology, Tekirdag Namik Kemal University Hospital, Tekirdag, Turkiye, from May 2021 to May 2022. Methodology: Consecutive patients admitted to the emergency department with unplanned hospitalisation in the oncology ward, were included. Patients receiving treatment with the curative intent, patients hospitalised for febrile neutropenia, and terminally ill patients requiring intensive care unit follow-up at admission were excluded from the study. Univariate and multivariate logistic regression analyses were used to identify predictive factors for short and long-term mortality-dependent variables. Results: This study included 253 advanced cancer patients. The number of patients who died in the ward within 10 days (short-term mortality) was 28 (11.1%). Ninety patients (35.6%) died afterwards anytime in the ward during the study (long-term mortality). In the multivariate analysis established for short-term mortality, higher ALT (OR = 6.75, 95% CI: 2.09 - 21.85, p=0.001), rapid deterioration in performance status (OR = 5.49, 95% CI: 1.81-16.67, p=0.003), higher CRP (OR = 5.86, 95% CI: 1.20-28.53, p=0.029), higher procalcitonin (OR = 7.94, 95% CI: 0.99 - 63.82, p=0.051), and higher lactate (OR = 2.47, 95% CI: 0.94-6.51, p=0.067) showed significant predictive features. Conclusion: The decision of whether to continue treatment or not is challenging in cancer patients who require unplanned hospitalisation while receiving palliative systemic therapy. New mortality estimation models can be used in making the transition from life-long to palliative treatments. Key Word: Mortality prediction, Hospitalisation, Estimation of survival, Chemotherapy.