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Objective: Sepsis remains a high cause of death, particularly in immunocompromised patients with cancer. The study was to develop a model to predict hospital mortality of septic patients with cancer in intensive care unit (ICU)., Design: Retrospective observational study., Setting: Medical Information Mart for Intensive Care IV (MIMIC IV) and eICU Collaborative Research Database (eICU-CRD)., Participants: A total of 3796 patients in MIMIC IV and 549 patients in eICU-CRD were included., Primary Outcome Measures: The model was developed based on MIMIC IV. The internal validation and external validation were based on MIMIC IV and eICU-CRD, respectively. Candidate factors were processed with the least absolute shrinkage and selection operator regression and cross-validation. Hospital mortality was predicted by the multivariable logistical regression and visualised by the nomogram. The model was assessed by the area under the curve (AUC), calibration curve and decision curve analysis curve., Results: The model exhibited favourable discrimination (AUC: 0.726 (95% CI: 0.709 to 0.744) and 0.756 (95% CI: 0.712 to 0.801)) in the internal and external validation sets, respectively, and better calibration capacity than Acute Physiology and Chronic Health Evaluation IV in external validation., Conclusions: Despite that the predicted model was based on a retrospective study, it may also be helpful to predict the hospital morality of patients with solid cancer and sepsis., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: A great increase in the number of patients needs critical care to the intensive care unit (ICU) due to improvements in oncology. The aim of the study was to explore risk factors affecting survival of critically ill patients with solid cancers in ICU., Methods: The study retrospectively reviewed patients between 2001 and 2012, which were collected by Medical Information Mart for Intensive Care III (MIMIC-III) from the Beth Israel Deaconess Medical Center in Boston, MA, USA., Results: A total of 38,508 adult patients, who were admitted to ICUs and 8,308 (21.6%) were diagnosed as an underlying malignancy; 1,671 and 3,165 adult patients with sold cancer were admitted to surgical ICU (SICU) and medical ICU (MICU), respectively. Patients in SICU had a higher survival rate at the point of 28-, 90-day, and 1-, 3-year than patients in MICU (P<0.001 for all). Multivariate analysis demonstrated that age ≥70, emergency admission, the presence of metastases, Oxford Acute Severity of Illness Score (OASIS) ≥30 and sepsis were independent risk factors affecting 28-day survival in SICU. In MICU, emergency admission, metastatic disease, Sequential Organ Failure Assessment (SOFA) ≥3, Simplified Acute Physiology Score II (SAPS II) ≥39, Acute Physiology Score III (APS III) ≥40, Oxford Acute Severity of Illness Score (OASIS) ≥30, Elixhauser comorbidity index ≥9 and sepsis were independent risk factors for 28-day survival rate. The area under curve (AUC) of the OASIS for predicting ICU mortality was 0.824 [95% confidence interval (CI): 0.805-0.842], which was obviously higher than other scores in SICU. The AUC of the SAPS II for predicting ICU mortality was 0.820 (95% CI: 0.806-0.833), which was slightly higher than other scores in MICU., Conclusions: Patients with cancer in SICU have longer survival time than patients with cancer in MICU. The prediction of prognosis of critically ill cancer patients can guide treatment and optimize medical resources.