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1.
Cancer Med ; 9(23): 8747-8753, 2020 12.
Article in English | MEDLINE | ID: covidwho-893206

ABSTRACT

BACKGROUND: There is limited data on outcomes in cancer patients with coronavirus disease 2019 (COVID-19) from lower middle-income countries (LMICs). PATIENTS AND METHODS: This was an observational study, conducted between 12 April and 10 June 2020 at Tata Memorial centre, Mumbai, in cancer patients undergoing systemic therapy with laboratory confirmed COVID-19. The objectives were to evaluate cumulative 30-day all-cause mortality, COVID-19 attributable mortality, factors predicting mortality, and time to viral negativity after initial diagnosis. RESULTS: Of the 24 660 footfalls and 7043 patients evaluated, 230 patients on active systemic therapy with a median age of 42 (1-75) years were included. COVID-19 infection severity, as per WHO criteria, was mild, moderate, and severe in 195 (85%), 11 (5%), and 24 (11%) patients, respectively. Twenty-three patients (10%) expired during follow-up, with COVID-19 attributable mortality seen in 15 patients (6.5%). There were no mortalities in the pediatric cohort of 31 (14%) patients. Advanced stage cancer being treated with palliative intent vs others [30-day mortality 24%% vs 5%, odds ratio (OR) 5.6, 95% CI 2.28-13.78, P < .001], uncontrolled cancer status vs controlled cancer (30-day mortality37.5%% vs 4%%, OR 14, 95% CI 4.46-44.16, P < .001) and severe COVID-19 vs mild COVID-19 (30-day mortality 71% vs 3%, OR 92.29, 95% CI 26.43-322.21, P < .001) were significantly associated with mortality. The median time to SARS-CoV-2 RT-PCR negativity was 17 days [interquartile range (IQR)17-28) in the cohort. CONCLUSIONS: The mortality rates in cancer patients with COVID-19 who are receiving systemic anti-cancer therapy in LMICSs are marginally higher than that reported in unselected COVID-19 cohorts with prolonged time to viral negativity in a substantial number of patients. The pediatric cancer patients tended to have favorable outcomes.


Subject(s)
Antiviral Agents/therapeutic use , COVID-19/prevention & control , Neoplasms/therapy , SARS-CoV-2/drug effects , Adolescent , Adult , Aged , COVID-19/epidemiology , COVID-19/virology , Child , Child, Preschool , Comorbidity , Female , Humans , India/epidemiology , Infant , Male , Middle Aged , Neoplasms/epidemiology , Outcome Assessment, Health Care/methods , Outcome Assessment, Health Care/statistics & numerical data , Pandemics , Prospective Studies , SARS-CoV-2/physiology , Survival Rate , Young Adult
2.
Head Neck ; 42(6): 1173-1178, 2020 06.
Article in English | MEDLINE | ID: covidwho-116849

ABSTRACT

BACKGROUND: The coronavirus infection is rapidly spreading, putting a strain on health care services across the globe. Patients with oral cancer are susceptible often immunosuppressed due to the disease and/or the treatment received. METHODS: We performed a simulation of the currently available data using a multistate and hazards model to provide an objective model for counseling and decision making for health care workers. RESULTS: Stage IV patients with oral cancer who did not receive treatment had progression of disease and an increased mortality rate compared to patients who receive treatment but did not contract COVID-19. The patients who received treatment and got affected with COVID-19 had a far worse impact and higher mortality rate than all other groups. CONCLUSION: Isolation and deferring treatment for stage IV patients with oral cancer, so as to avoid hospital visits and contraction of COVID-19, is an advisable strategy based on this model.


Subject(s)
Cause of Death , Clinical Decision-Making/methods , Coronavirus Infections/epidemiology , Mouth Neoplasms/pathology , Mouth Neoplasms/surgery , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , COVID-19 , Computer Simulation , Coronavirus Infections/prevention & control , Disease Management , Disease-Free Survival , Female , Humans , Male , Mouth Neoplasms/mortality , Neoplasm Invasiveness/pathology , Neoplasm Staging , Patient Selection , Pneumonia, Viral/prevention & control , Proportional Hazards Models , Risk Assessment , Survival Analysis , United States
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