A New Mortality Prediction Model in Advanced Stage Cancer Patients Requiring Hospitalisation while Receiving Active Systemic Therapy

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dc.authoridCavdar, Eyyup/0000-0001-5885-3047
dc.authoridKaraboyun, Kubilay/0000-0002-1783-8075
dc.contributor.authorKaraboyun, Kubilay
dc.contributor.authorIriagac, Yakup
dc.contributor.authorCavdar, Eyyup
dc.contributor.authorAvci, Okan
dc.contributor.authorSeber, Erdogan Selcuk
dc.date.accessioned2024-10-29T17:59:06Z
dc.date.available2024-10-29T17:59:06Z
dc.date.issued2023
dc.departmentTekirdağ Namık Kemal Üniversitesi
dc.description.abstractObjective: 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 multi-variate analysis established for short-term mortality, higher ALT (OR = 6.75, 95% CI: 2.09 -21.85, p=0.001), rapid deterioration in perfor-mance 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 pallia-tive treatments.
dc.identifier.doi10.29271/jcpsp.2023.05.548
dc.identifier.endpage553
dc.identifier.issn1022-386X
dc.identifier.issn1681-7168
dc.identifier.issue5en_US
dc.identifier.pmid37190691
dc.identifier.scopus2-s2.0-85159450760
dc.identifier.scopusqualityQ3
dc.identifier.startpage548
dc.identifier.urihttps://doi.org/10.29271/jcpsp.2023.05.548
dc.identifier.urihttps://hdl.handle.net/20.500.11776/14625
dc.identifier.volume33
dc.identifier.wosWOS:000991064000013
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherColl Physicians & Surgeons Pakistan
dc.relation.ispartofJcpsp-Journal of The College of Physicians and Surgeons Pakistan
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectMortality prediction
dc.subjectHospitalisation
dc.subjectEstimation of survival
dc.subjectChemotherapy
dc.titleA New Mortality Prediction Model in Advanced Stage Cancer Patients Requiring Hospitalisation while Receiving Active Systemic Therapy
dc.typeArticle

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