About: Mortality and Advanced Support Requirement for Patients With Cancer With COVID-19: A Mathematical Dynamic Model for Latin America

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About: Mortality and Advanced Support Requirement for Patients With Cancer With COVID-19: A Mathematical Dynamic Model for Latin America Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Mortality and Advanced Support Requirement for Patients With Cancer With COVID-19: A Mathematical Dynamic Model for Latin America
Creator	Arrieta, Oscar Cardona, Andrés Luis, ; Otero, Jorge Ricaurte, Luisa Rolfo, Christian Ruiz-Patiño, Alejandro Russo, Alessandro Vargas, Carlos Viola, Lucia Zatarain-Barron, Lucia Carranza, Hernán Martín, Claudio Recondo, Gonzalo Rodriguez, July Sotelo, Carolina Corrales, ; Feliciano Barrón, ; Pino, E Rosell, ; Zyanya, ;
Source	Medline; PMC
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.
has issue date	2020-05-29(xsd:dateTime)
bibo:doi	10.1200/go.20.00156
bibo:pmid	32469610
has license	cc-by
sha1sum (hex)	8f0609594c97b878a1f5bf1d55c8c711094e4c5e
schema:url	https://doi.org/10.1200/go.20.00156
resource representing a document's title	Mortality and Advanced Support Requirement for Patients With Cancer With COVID-19: A Mathematical Dynamic Model for Latin America
has PubMed Central identifier	PMC7268899
has PubMed identifier	32469610
schema:publication	JCO Glob Oncol
resource representing a document's body	covid:8f0609594c97b878a1f5bf1d55c8c711094e4c5e#body_text
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