PURPOSE: The rapid spread of the SARS-CoV-2 pandemic around the world caused most healthcare services to turn substantial attention to treatment of these patients and also to alter the structure of healthcare systems to address an infectious disease. As a result, many cancer patients had their treatment deferred during the pandemic, increasing the time-to-treatment initiation, the number of untreated patients (which will alter the dynamics of healthcare delivery in the post-pandemic era) and increasing their risk of death. Hence, we analyzed the impact on global cancer mortality considering the decline in oncology care during the COVID-19 outbreak using head and neck cancer, a known time-dependent disease, as a model.METHODS: An online practical tool capable of predicting the risk of cancer patients dying due to the COVID-19 outbreak and also useful for mitigation strategies after the peak of the pandemic has been developed, based on a mathematical model. The scenarios were estimated by information of 15 oncological services worldwide, given a perspective from the five continents and also some simulations were conducted at world demographic data.RESULTS: The model demonstrates that the more that cancer care was maintained during the outbreak and also the more it is increased during the mitigation period, the shorter will be the recovery, lessening the additional risk of dying due to time-to-treatment initiation.CONCLUSIONS: This impact of COVID-19 pandemic on cancer patients is inevitable, but it is possible to minimize it with an effort measured by the proposed model.
The hidden curve behind COVID-19 outbreak: the impact of delay in treatment initiation in cancer patients and how to mitigate the additional risk of dying-the head and neck cancer model / L.L. Matos, C.H.Q. Forster, G.N. Marta, G. Castro Junior, J.A. Ridge, D. Hirata, A. Miranda-Filho, A. Hosny, A. Sanabria, V. Gregoire, S.G. Patel, J.J. Fagan, A.K. D'Cruz, L. Licitra, H. Mehanna, S. Hao, A. Psyrri, S. Porceddu, T.J. Galloway, W. Golusinski, N.Y. Lee, E.H. Shiguemori, J.E. Matieli, A.P.A.C. Shiguemori, L.R. Diamantino, L.F. Schiaveto, L. Leão, A.F. Castro, A.L. Carvalho, L.P. Kowalski. - In: CANCER CAUSES & CONTROL. - ISSN 0957-5243. - 32:5(2021 May), pp. 459-471. [10.1007/s10552-021-01411-7]
The hidden curve behind COVID-19 outbreak: the impact of delay in treatment initiation in cancer patients and how to mitigate the additional risk of dying-the head and neck cancer model
L. Licitra;
2021
Abstract
PURPOSE: The rapid spread of the SARS-CoV-2 pandemic around the world caused most healthcare services to turn substantial attention to treatment of these patients and also to alter the structure of healthcare systems to address an infectious disease. As a result, many cancer patients had their treatment deferred during the pandemic, increasing the time-to-treatment initiation, the number of untreated patients (which will alter the dynamics of healthcare delivery in the post-pandemic era) and increasing their risk of death. Hence, we analyzed the impact on global cancer mortality considering the decline in oncology care during the COVID-19 outbreak using head and neck cancer, a known time-dependent disease, as a model.METHODS: An online practical tool capable of predicting the risk of cancer patients dying due to the COVID-19 outbreak and also useful for mitigation strategies after the peak of the pandemic has been developed, based on a mathematical model. The scenarios were estimated by information of 15 oncological services worldwide, given a perspective from the five continents and also some simulations were conducted at world demographic data.RESULTS: The model demonstrates that the more that cancer care was maintained during the outbreak and also the more it is increased during the mitigation period, the shorter will be the recovery, lessening the additional risk of dying due to time-to-treatment initiation.CONCLUSIONS: This impact of COVID-19 pandemic on cancer patients is inevitable, but it is possible to minimize it with an effort measured by the proposed model.File | Dimensione | Formato | |
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