A new mortality prediction model in advanced stage cancer patients requiring hospitalisation while receiving active systemic therapy | [Journal of College of Physicians and Surgeons--Pakistan : JCPSP • 2023]

Author(s):

1. Kubilay Karaboyun: Department of Medical Oncology, Faculty of Medicine, Tekirdag Namik Kemal University,Tekirdag,TurkiyeKey Word: Mortality prediction, Hospitalisation, Estimation of survival,Chemotherapy,Turkiye

2. Yakup Iriagac: Department of Medical Oncology, Faculty of Medicine, Tekirdag Namik Kemal University,Tekirdag,TurkiyeKey Word: Mortality prediction, Hospitalisation, Estimation of survival,Chemotherapy,Turkiye

3. Eyyup Cavdar: Department of Medical Oncology, Faculty of Medicine, Tekirdag Namik Kemal University,Tekirdag,TurkiyeKey Word: Mortality prediction, Hospitalisation, Estimation of survival,Chemotherapy,Turkiye

4. Okan Avci: Department of Medical Oncology, Faculty of Medicine, Tekirdag Namik Kemal University,Tekirdag,TurkiyeKey Word: Mortality prediction, Hospitalisation, Estimation of survival,Chemotherapy,Turkiye

5. Erdogan Selcuk Seber: Department of Medical Oncology, Faculty of Medicine, Tekirdag Namik Kemal University,Tekirdag,TurkiyeKey Word: Mortality prediction, Hospitalisation, Estimation of survival,Chemotherapy,Turkiye

Abstract:

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 signi cant 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.

Page(s): 548-553

DOI: 10.29271/jcpsp.2023.05.548

Published: Journal: Journal of College of Physicians and Surgeons--Pakistan : JCPSP, Volume: 33, Issue: 5, Year: 2023

Keywords:

Chemotherapy , Estimation of survival , Mortality prediction , Hospitalisation

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