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Mortality and Advanced Support Requirement for Patients With Cancer With COVID-19 : A Mathematical Dynamic Model for Latin America
Ruiz-Patiño, Alejandro (Molecular Oncology and Biology Systems Research Group. Universidad el Bosque)
Arrieta, Oscar (Instituto Nacional de Cancerología (Ciutat de Mèxic). Thoracic Oncology Unit)
Pino, Luis E. (Fundación Santa Fe de Bogotá)
Rolfo, Christian (Marlene and Stewart Comprehensive Cancer Center. Experimental Therapeutics Program. School of Medicine. University of Maryland)
Ricaurte, Luisa (Molecular Oncology and Biology Systems Research Group. Universidad el Bosque)
Recondo, Gonzalo (Center for Medical Education and Clinical Research)
Zatarain-Barron, Zyanya Lucia (Instituto Nacional de Cancerología (Ciutat de Mèxic). Thoracic Oncology Unit)
Corrales, Luis. (Department of Oncology. Centro de Investigación y Manejo del Cáncer, San José, Costa Rica)
Martín, Claudio (Thoracic Oncology Unit. Alexander Fleming Institute)
Barrón, Feliciano (Instituto Nacional de Cancerología (Ciutat de Mèxic). Thoracic Oncology Unit)
Vargas, Carlos (Clinical and Translational Oncology Group. Clínica del Country, Bogotá)
Carranza, Hernán (Clinical and Translational Oncology Group. Clínica del Country, Bogotá)
Otero, Jorge (Clinical and Translational Oncology Group. Clínica del Country, Bogotá)
Rodriguez, July (Molecular Oncology and Biology Systems Research Group. Universidad el Bosque)
Sotelo, Carolina (Molecular Oncology and Biology Systems Research Group. Universidad el Bosque)
Viola, Lucia (Fundación Neumológica Colombiana)
Russo, Alessandro (Medical Oncology Unit. Azienda Ospedaliera Papardo)
Rosell, Rafael (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol)
Cardona Zorrilla, Andrés Felipe (Clínica del Country (Bogotà, Colòmbia))

Data: 2020
Resum: 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.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Llengua: Anglès
Document: Article ; recerca ; Versió publicada
Matèria: Betacoronavirus ; Coronavirus Infections ; Delivery of Health Care ; Health Plan Implementation ; Humans ; Incidence ; Intensive Care Units ; Latin America ; Markov Chains ; Models, Statistical ; Neoplasms ; Pandemics ; Pneumonia, Viral ; Prognosis ; Resuscitation ; Time Factors ; COVID-19 ; SARS-CoV-2 ; Coronavirus
Publicat a: JCO global oncology, Vol. 6 (january 2020) , p. 752-760, ISSN 2687-8941

DOI: 10.1200/GO.20.00156
PMID: 32469610


9 p, 774.2 KB

El registre apareix a les col·leccions:
Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències de la salut i biociències > Institut d'Investigació en Ciencies de la Salut Germans Trias i Pujol (IGTP)
Articles > Articles de recerca
Articles > Articles publicats

 Registre creat el 2020-06-22, darrera modificació el 2023-05-23



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