The aim of the present study was to identify factors predicting in-hospital mortality in patients with cancer admitted to a medical Intensive Care Unit (ICU), and to evaluate their functional status and survival during follow-up at the oncology service in the initial 12 months after hospital discharge. A retrospective observational study was performed on 129 consecutive oncological patients with solid tumours admitted to the medical ICU of the Hospital del Mar (Barcelona, Spain) between January 2016 and June 2018. Demographics, and clinical data in-ICU and in-hospital mortality were recorded. Post-hospital discharge follow-up was also carried out. ICU and hospital mortality rates were 24% (n=31) and 40.3% (n=52), respectively. Sequential Organ Failure Assessment (SOFA) score (HR, 1.20; 95% CI, 1.01-1.42; P=0.037), neutropenia on admission (HR, 8.53; 95% CI, 2.15-33.82; P=0.002), metastatic disease (HR, 3.92; 95% CI, 1.82-8.45; P<0.001), need for invasive mechanical ventilation (HR, 5.78; 95% CI, 1.61-20.73; P=0.007), surgery during hospital admission (HR, 0.23; 95% CI, 0.09-0.61; P=0.003) and ICU stay (>48 h) (HR, 0.11; 95% CI, 0.04-0.29; P<0.001) were the independent risk factors for ICU mortality. Overall, 59.5% of the survivors had good functional status at hospital discharge and 28.7% of patients with cancer admitted to the ICU were alive 1 year after hospital discharge, most of them (85.7%) with good functional status (Eastern Cooperative Oncology Group 0-1). In conclusion, hospital mortality may be associated with SOFA score at ICU admission, the need for invasive mechanical ventilation, neutropenia and metastatic disease. Only 40% of patients with oncological disease admitted to the ICU died during their hospital stay, and >50% of the survivors presented good functional status at hospital discharge. Notably, 1 year after hospital discharge, 28.7% of patients were alive, most of them with a good functional status.

The aim of the study was to evaluate the performance of "Acute Physiology and Chronic Health Evaluation II" (APACHE-II), "Simplified Acute Physiology Score 3" (SAPS-3), and "APACHE-II Score for Critically Ill Patients with a Solid Tumor" (APACHE-II_CCP) models in cancer patients admitted to ICU.

Prospective cohort study of 414 patients with an active solid tumor. Discrimination was assessed by area under receiver operating characteristic (AROC) curves and calibration by Hosmer-Lemeshow goodness-of-fit C test (H-L).

The hospital mortality rate was 32.6%. In the total cohort, discrimination for prognostic models were: APACHE-II_CCP (AROC 0.98), APACHE-II (AROC 0.96), SAPS-3 for Central and South American countries (SAPS-3_CSA) (AROC 0.95), and SAPS-3 (AROC 0.91). Calibration was good (p value of H-L test > 0.05) using APACHE-II_CCP, APACHE-II and SAPS-3_CSA models. Estimation of the probability of death was more precise with APACHE-II_CCP (standardized mortality ratio, SMR = 1.03) and SAPS-3 (SMR = 1.08) models. Further analysis showed that discrimination was high with all prognostic model whether for patients with planned ICU admission (AROC APACHE-II_CCP 0.97, APACHE-II 0.96, SAPS-3 0.95, SAPS-3_CSA 0.95) or for patients with unplanned ICU admission (AROC APACHE-II_CCP 0.97, APACHE-II 0.94, SAPS-3 0.86, SAPS-3_CSA 0.95). Calibration was good for all predictive models in both subgroups (p value of H-L test > 0.05, except for APACHE-II model inpatients with planned ICU admission).

In this prospective study, general predictive models (e.g., APACHE-II, SAPS-3) and cancer-specific models (e.g., APACHE-II_CCP) are accurate in predicting hospital mortality. Other studies confirming these results are required.

The study was aimed to describe the characteristics of cancer patients admitted to the oncological ICU and to identify clinical features associated with outcomes.

This is a prospective study (January 2014 to December 2015) of 522 cancer patients consecutively admitted to the oncological ICU. Patients with a length of oncological ICU stay ≤ 1 day were excluded. Demographic and clinical variables were obtained at oncological ICU admission. The primary outcome of interest was hospital mortality. Logistic regression analysis was performed to identify independent risk factors for hospital mortality.

The study cohort consisted of 492 (94.3%) patients with solid tumours and 30 patients (5.7%) with haematological malignancies. Advanced cancer was observed in 53.3%. Unplanned admission accounted for 25.3%. Hospital mortality rate was 13.0% (n = 68), and it was higher for patients with unplanned admission than those for electively admitted patients (35.6% vs. 5.4; p < 0.0001). Stage IV of cancer (OR 5.28; 95% CI 2.71-10.28; p < 0.0001), patients from the emergency department (OR 3.33; 95% CI 1.68-6.61; p = 0.001), unplanned admission (OR 7.99; 95% CI 4.45-14.33; p < 0.0001), non-malignancy-related admission (OR 5.80; 95% CI 3.26-10.32; p < 0.0001), sepsis (OR 4.81; 95% CI 2.28-10.16; p < 0.0001), chemotherapy-induced adverse event (OR 5.64; 95% CI 2.33-13.66; p < 0.0001), and invasive mechanical ventilation (OR 18.70; 95% CI 9.93-35.21; p < 0.0001) were independently associated with increased hospital mortality in multivariate logistic regression analysis.

ICU admission of cancer patients should be based on potential chance of recovering from the acute problem. Clinical predictor for mortality could support this purpose (UIN: researchregistry3484).