Abstract
ObjectiveTo evaluate the predictive ability of mortality prediction scales in cancer patients admitted to intensive care units. DesignA 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. SettingIntensive care units admitting cancer patients. ParticipantsStudies that included adult patients with an active cancer diagnosis who were admitted to the intensive care unit. InterventionsIntegrative study without interventions. Main variables of interestMortality prediction, standardized mortality, discrimination, and calibration. ResultsSeven 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. ConclusionsPredicting mortality in intensive care unit 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.
Published Version
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