ArticleAnnals of translational medicine2021
Characteristics and clinical subtypes of cancer patients in the intensive care unit: a retrospective observational study for two large databases.
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Multiple Clustering Algorithms for Ovarian Cancer Subtyping (MCAOCS): identifying clinical phenotypes and treatment response in critical care.Journal of ovarian research · 2026Article
- Outcome prediction for critical care patients with respiratory neoplasms using a multilayer perceptron neural network.Einstein (Sao Paulo, Brazil) · 2023Article
- A Systematic Review and Meta-Analysis Evaluating Geographical Variation in Outcomes of Cancer Patients Treated in ICUs.Critical care explorations · 2022Review
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5 authors.
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Abstract
backgroundPrevious studies have reported very different mortality rates among cancer patients in the intensive care unit (ICU), implying different clinical subtypes. We aimed to reveal the clinical subtypes and demonstrate the importance of segregating the patients in clinical research, and to report the ICD-level mortality of cancer patients in the ICU.
methodsTwo ICU databases (MIMIC-III and eICU) were utilized to identify cancer patients. Mortality based on ICD-level diagnoses were calculated, and K-means clustering was used to identify different clinical subtypes in the MIMIC database. Clinical characteristics and outcomes were compared among subtypes, and the calibration of SAPS II and APACHE IV among different subtypes was evaluated.
resultsIn total, 6,505 (13.8%) cancer patients of the MIMIC database and 7,351 (4.9%) ones in eICU database, were enrolled in the study. Metastasis involving pleura, metastasis involving the liver, and acute myeloid leukemia were in the top 5 diagnoses with the highest mortality in both databases. Clinical subtypes identified by K-means clustering were closely associated with admission type (elective or emergency) and clinical service provider (surgical or medical). In a four-cluster pattern, nearly all patients in the first cluster were elective admissions (99.1%), whereas in the rest of the clusters, most were emergency admissions (93.7%). Most surgical patients were in the 1+2 clusters (92.0%) and most medical patients were in the 3+4 clusters (93.5%). Most characteristics and outcomes as well as the calibration of SAPS II and APACHE IV scoring systems were significantly different among clinical subtypes.
conclusionsDifferent clinical subtypes can be well identified by admission type and clinical service provider among ICU patients with cancer. Caution should be exercised when considering these patients as a whole population both in clinical practice and research. Moreover, APACHE IV has better calibration than SAPS II for cancer patients at low risk of mortality in the ICU.
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