Outcomes of Patients with COVID-19 from a Specialized Cancer Care Emergency Room

Abstract

Purpose: Our goal was to identify discrete clinical characteristics associated with safe discharge from an emergency department/urgent care for patients with a history of cancer and concurrent COVID-19 infection during the SARS-CoV-2 pandemic and prior to widespread vaccination.

Patients and methods: We retrospectively analyzed 255 adult patients with a history of cancer who presented to Memorial Sloan Kettering Cancer Center (MSKCC) urgent care center (UCC) from March 1, 2020 to May 31, 2020 with concurrent COVID-19 infection. We evaluated associations between patient characteristics and 30-day mortality from initial emergency department (ED) or urgent care center (UCC) visit and the absence of a severe event within 30 days. External validation was performed on a retrospective data from 29 patients followed at Fred Hutchinson Cancer Research Center that presented to the local emergency department. A late cohort of 108 additional patients at MSKCC from June 1, 2020 to January 31, 2021 was utilized for further validation.

Results: In the MSKCC cohort, 30-day mortality and severe event rate was 15% and 32% respectively. Using stepwise regression analysis, elevated BUN and glucose, anemia, and tachypnea were selected as the main predictors of 30-day mortality. Conversely, normal albumin, BUN, calcium, and glucose, neutrophil-lymphocyte ratio <3, lack of (severe) hypoxia, lack of bradycardia or tachypnea, and negative imaging were selected as the main predictors of an uneventful course as defined as a Lack Of a Severe Event within Thirty Days (LOSETD). Utilizing this information, we devised a tool to predict 30-day mortality and LOSETD which achieved an area under the operating curve (AUC) of 79% and 74% respectively. Similar estimates of AUC were obtained in an external validation cohort. A late cohort at MSKCC was consistent with the prior, albeit with a lower AUC.

Conclusion: We identified easily obtainable variables that predict 30-day mortality and the absence of a severe event for patients with a history of cancer and concurrent COVID-19. This has been translated into a bedside tool that the clinician may utilize to assist disposition of this group of patients from the emergency department or urgent care setting.

Keywords: COVID-19; biostatistics; decision analysis outcomes; medical utilization.

Figure 1.

Distribution of risk scores in MSKCC cohort (n = 255). (a) Distribution of risk scores for mortality within 30 days in patients admitted at first UCC visit (left) and discharged from initial visit (middle), and probability of an outcome based on risk score (right). (b) Distribution of risk scores for LOSETD in patients admitted at first UCC visit (left) and discharged from initial visit (middle), and probability of an outcome based on risk score (right). Red curves: estimated baseline risk in March; blue curves: estimated baseline risk in April/May.

Figure 2.

Receiving operating curve (ROC) for predicting (a) mortality within 30 days (b) LOSETD based on demographics, clinical characteristics, laboratory and imaging studies in the MSKCC cohort and a validation cohort. Estimated ROC curves in the validation cohort were based on the multivariate model in Tables 2 and 3. For left panels, blue curves: ROC at each replication for 5- fold cross validation; red curves: are average ROC curves.