Abstract 1690P
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. Table: 1690P
Patient characteristics and association with outcomes
| Association with admission | Association with oxygen | Association with death | |
| p value | p value | p value | |
| Age | 0.054 | 0.0346 | 0.057 |
| Male sex | 1 | 0.52 | 0.051 |
| World Health Organisation COVID-19 severity score | 0.012 | 1.30E-06 | 1.30E-06 |
| Underlying haematological cancer | 0.142 | 0.8655 | 0.036 |
| Dyspnoea | 0.1 | 0.0003 | 0.1 |
| Number of symptoms | 0.492 | 0.0131 | 0.191 |
| C-Reactive Protein (CRP) | 0.022 | 0.00024 | 0.069 |
| Albumin | 0.009 | 0.04 | 0.773 |
| Lactate dehydrogenase (LDH) | 0.205 | 0.0097 | 0.041 |
| National early warning score (NEWS2) | 0.0067 | 0.00000121 | 0.051 |
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.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The Christie NHS Foundation Trust.
Funding
Has not received any funding.
Disclosure
R. Lee: Honoraria (self): Bristol Myers Squibb; Honoraria (self): Astra Zeneca; Research grant/Funding (institution): Bristol Myers Squibb. M.P. Rowe: Travel/Accommodation/Expenses: Astellas Pharma. L. Horsley: Travel/Accommodation/Expenses: Lilly. C. Wilson: Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony: Pfizer; Amgen; Novartis. T. Cooksley: Speaker Bureau/Expert testimony: Bristol Myers Squibb. A. Armstrong: Shareholder/Stockholder/Stock options, husband had shares now sold: Astra Zeneca. All other authors have declared no conflicts of interest.