%0 Journal Article
%T Towards better mortality prediction in cancer patients in the ICU: a comparative analysis of prognostic scales: systematic literature review.
%A Cabrera Losada A
%A Correa Oviedo MA
%A Herrera Villazón VC
%A Gil-Tamayo S
%A Molina CF
%A Gimenez-Esparza Vich C
%A Nieto Estrada VH
%J Med Intensiva (Engl Ed)
%V 0
%N 0
%D 2024 Aug 1
%M 39095268
暂无%R 10.1016/j.medine.2024.07.009
%X <B>OBJECTIVE: </B>To evaluate the predictive ability of mortality prediction scales in cancer patients admitted to intensive care units (ICUs).<BR><B>METHODS: </B>A systematic review of the literature was conducted using a search algorithm in October 2022. The following databases were searched: PubMed, Scopus, Virtual Health Library (BVS), and Medrxiv. The risk of bias was assessed using the QUADAS-2 scale.<BR><B>METHODS: </B>ICUs admitting cancer patients.<BR><B>METHODS: </B>Studies that included adult patients with an active cancer diagnosis who were admitted to the ICU.<BR><B>METHODS: </B>Integrative study without interventions.<BR><B>METHODS: </B>Mortality prediction, standardized mortality, discrimination, and calibration.<BR><B>RESULTS: </B>Seven mortality risk prediction models were analyzed in cancer patients in the ICU. Most models (APACHE II, APACHE IV, SOFA, SAPS-II, SAPS-III, and MPM II) underestimated mortality, while the ICMM overestimated it. The APACHE II had the SMR (Standardized Mortality Ratio) value closest to 1, suggesting a better prognostic ability compared to the other models.<BR><B>CONCLUSIONS: </B>Predicting mortality in ICU cancer patients remains an intricate challenge due to the lack of a definitive superior model and the inherent limitations of available prediction tools. For evidence-based informed clinical decision-making, it is crucial to consider the healthcare team's familiarity with each tool and its inherent limitations. Developing novel instruments or conducting large-scale validation studies is essential to enhance prediction accuracy and optimize patient care in this population.