Article ; Online: Mortality and Advanced Support Requirement for Patients With Cancer With COVID-19: A Mathematical Dynamic Model for Latin America.
JCO global oncology
2020 Volume 6, Page(s) 752–760
Abstract: ... requirement for the care of patients with cancer infected with COVID-19 in Latin America. A dynamic multistate ... respiratory viral infections, patients with cancer are at higher risk of becoming infected by COVID-19 and ... incidence tendency, Latin America would be expected to lose approximately 111,725 patients with cancer ...
| Abstract | Purpose: In the midst of a global pandemic, evidence suggests that similar to other severe respiratory viral infections, patients with cancer are at higher risk of becoming infected by COVID-19 and have a poorer prognosis. Methods: We have modeled the mortality and the intensive care unit (ICU) requirement for the care of patients with cancer infected with COVID-19 in Latin America. A dynamic multistate Markov model was constructed. Transition probabilities were estimated on the basis of published reports for cumulative probability of complications. Basic reproductive number (R0) values were modeled with R using the EpiEstim package. Estimations of days of ICU requirement and absolute mortality were calculated by imputing number of cumulative cases in the Markov model. Results: Estimated median time of ICU requirement was 12.7 days, median time to mortality was 16.3 days after infection, and median time to severe event was 8.1 days. Peak ICU occupancy for patients with cancer was calculated at 16 days after infection. Deterministic sensitivity analysis revealed an interval for mortality between 18.5% and 30.4%. With the actual incidence tendency, Latin America would be expected to lose approximately 111,725 patients with cancer to SARS-CoV-2 (range, 87,116-143,154 patients) by the 60th day since the start of the outbreak. Losses calculated vary between < 1% to 17.6% of all patients with cancer in the region. Conclusion: Cancer-related cases and deaths attributable to SARS-CoV-2 will put a great strain on health care systems in Latin America. Early implementation of interventions on the basis of data given by disease modeling could mitigate both infections and deaths among patients with cancer. |
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| MeSH term(s) | Betacoronavirus/pathogenicity ; COVID-19 ; Coronavirus Infections/complications ; Coronavirus Infections/mortality ; Coronavirus Infections/therapy ; Coronavirus Infections/virology ; Delivery of Health Care/organization & administration ; Delivery of Health Care/statistics & numerical data ; Health Plan Implementation/statistics & numerical data ; Humans ; Incidence ; Intensive Care Units/organization & administration ; Intensive Care Units/statistics & numerical data ; Latin America/epidemiology ; Markov Chains ; Models, Statistical ; Neoplasms/complications ; Neoplasms/mortality ; Neoplasms/therapy ; Neoplasms/virology ; Pandemics/statistics & numerical data ; Pneumonia, Viral/complications ; Pneumonia, Viral/mortality ; Pneumonia, Viral/therapy ; Pneumonia, Viral/virology ; Prognosis ; Resuscitation/statistics & numerical data ; SARS-CoV-2 ; Time Factors |
| Keywords | covid19 |
| Language | English |
| Publishing date | 2020-05-29 |
| Publishing country | United States |
| Document type | Journal Article |
| ISSN | 2687-8941 |
| ISSN (online) | 2687-8941 |
| DOI | 10.1200/GO.20.00156 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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