ABSTRACT
Identification of pathogens with pulmonary presentation in patients with hematologic malignancies may be challenging due to diagnostic difficulty related to the underlying malignancy and limitations of conventional microbiologic methods. Herein, we present a case series of three patients with pulmonary consolidations due to Legionella bozemanae necrotizing pneumonia, Pneumocystis jirovecii pneumonia, and disseminated Scedosporium infection, who were diagnosed by microbial cell-free DNA next-generation sequencing. We observed that this new sequencing modality was in agreement with gold-standard diagnostics, posing a potential solution to the problem of limited capability in diagnosing infections in hematological malignancy patients.
ABSTRACT
As of 10 April 2020, New York State had 180,458 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 9,385 reported deaths. Patients with cancer comprised 8.4% of deceased individuals1. Population-based studies from China and Italy suggested a higher coronavirus disease 2019 (COVID-19) death rate in patients with cancer2,3, although there is a knowledge gap as to which aspects of cancer and its treatment confer risk of severe COVID-194. This information is critical to balance the competing safety considerations of reducing SARS-CoV-2 exposure and cancer treatment continuation. From 10 March to 7 April 2020, 423 cases of symptomatic COVID-19 were diagnosed at Memorial Sloan Kettering Cancer Center (from a total of 2,035 patients with cancer tested). Of these, 40% were hospitalized for COVID-19, 20% developed severe respiratory illness (including 9% who required mechanical ventilation) and 12% died within 30 d. Age older than 65 years and treatment with immune checkpoint inhibitors (ICIs) were predictors for hospitalization and severe disease, whereas receipt of chemotherapy and major surgery were not. Overall, COVID-19 in patients with cancer is marked by substantial rates of hospitalization and severe outcomes. The association observed between ICI and COVID-19 outcomes in our study will need further interrogation in tumor-specific cohorts.
Subject(s)
Coronavirus Infections/mortality , Neoplasms/mortality , Pandemics , Pneumonia, Viral/mortality , Adolescent , Adult , Aged , Betacoronavirus/pathogenicity , COVID-19 , China/epidemiology , Coronavirus Infections/complications , Coronavirus Infections/pathology , Coronavirus Infections/virology , Female , Hospitalization , Humans , Italy/epidemiology , Male , Middle Aged , Neoplasms/complications , Neoplasms/pathology , Neoplasms/virology , Pneumonia, Viral/complications , Pneumonia, Viral/pathology , Pneumonia, Viral/virology , Risk Factors , SARS-CoV-2 , Severity of Illness Index , United States/epidemiology , Young AdultABSTRACT
New York State had 180,458 cases of SARS-CoV-2 and 9385 reported deaths as of April 10th, 2020. Patients with cancer comprised 8.4% of deceased individuals1. Population-based studies from China and Italy suggested a higher COVID-19 death rate in patients with cancer2,3, although there is a knowledge gap as to which aspects of cancer and its treatment confer risk of severe COVID-19 disease4. This information is critical to balance the competing safety considerations of reducing SARS-CoV-2 exposure and cancer treatment continuation. Since March 10th, 2020 Memorial Sloan Kettering Cancer Center performed diagnostic testing for SARS-CoV-2 in symptomatic patients. Overall, 40% out of 423 patients with cancer were hospitalized for COVID-19 illness, 20% developed severe respiratory illness, including 9% that required mechanical ventilation, and 9% that died. On multivariate analysis, age ≥ 65 years and treatment with immune checkpoint inhibitors (ICI) within 90 days were predictors for hospitalization and severe disease, while receipt of chemotherapy within 30 days and major surgery were not. Overall, COVID-19 illness is associated with higher rates of hospitalization and severe outcomes in patients with cancer. Association between ICI and COVID-19 outcomes will need interrogation in tumor-specific cohorts.