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Development of a model to predict hospital admission and severe outcome in cancer patients with COVID-19
Lee, Rebecca J Zhou, Cong Shotton, R Tivey, Ann Dickens, E. Huddar, P. McKenzie, H. Boyce, H. Maynard, A. Rowe, M. P.
Lee, Rebecca J
Zhou, Cong
Shotton, R
Tivey, Ann
Dickens, E.
Huddar, P.
McKenzie, H.
Boyce, H.
Maynard, A.
Rowe, M. P.
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Abstract
Background: Patients (pts) with cancer are at increased risk of severe COVID-19
infection and death. Due to the heterogeneity of manifestations of COVID-19, accurate
assessment of patients presenting to hospital is crucial. Early identification of pts
who are likely to deteriorate allows timely discussions regarding escalation of care. It
is equally important to identify pts who could be safely managed at home. To aid
clinical decision making, we developed a model to determine which pts should be
admitted vs. discharged at presentation to hospital.
Methods: Consecutive pts with solid or haematological malignancies presenting with
symptoms who tested positive for SARS-CoV-2 at 10 UK hospitals from March-May
2020 were identified following institutional board approval. Clinical and laboratory
data were extracted from pt records. Clinical outcome measures were discharge
within 24 hours, requirement for oxygen at any stage during admission and death. The
associations between clinical features and outcomes were examined using ANOVA or
Chi-squared tests. A logistic model was developed using clinical features with p<0.05
to predict patients who need hospital admission.
Results: 52 pts were included (27 male, 25 female; median age 63). 80.5% pts had
solid cancers, 19.5% haematological. Association analysis indicated that smoking
status, prior cancer therapy and comorbidities had no significant association with
outcomes. A number of other factors presented in the table had significant associations.
A multivariate logistic regression model was generated to predict need for
admission to hospital. Of note, age and male sex lost significance in the multivariate
model (p>0.8). Using haematological cancer, NEWS2 score, dyspnoea, CRP and albumin,
the model predicted requirement for admission with an area under the curve
of 0.88.
Conclusions: We have developed a model to predict which pts require hospital
admission. Further refinement and validation in larger cohorts of pts will be presented
Description
Date
2020
Publisher
Collections
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Keywords
Type
Meetings and Proceedings
Citation
Lee R, Zhou C, Shotton R, Tivey A, Dickens E, Huddar P, et al. 1690P Development of a model to predict hospital admission and severe outcome in cancer patients with COVID-19. Annals of Oncology. 2020;31:S999-S.