Coronavirus Disease 2019 in Pediatric Oncology Patients: A Matched–Cohort Analysis of the SCCM Discovery Viral Infection and Respiratory Illness Universal Study COVID-19 Registry

Abstract

Background: There is a paucity of multicenter data describing the impact of coronavirus disease 2019 on hospitalized pediatric oncology patients. Using a large, multicenter, Society of Critical Care Medicine (SCCM) Discovery Viral Infection and Respiratory Illness University Study (VIRUS) database, we aimed at assessing outcomes of COVID-19 infection in this population. Method: This is a matched-cohort study involving children below 18 years of age hospitalized with COVID-19 between March 2020 and January 2021. Using the VIRUS; COVID-19 Registry database, children with oncologic diseases were compared with propensity score matched (age groups, sex, race, and ethnicity) cohort of children without oncologic diseases for the prevalence of Multisystem Inflammatory Syndrome in Children (MIS-C), intensive care unit (ICU) admission, interventions, hospital, and ICU length of stay. Results:The number of children in the case and control groups was 45 and 180, respectively. ICU admission rate was similar in both groups ([47.7 vs 51.7%], P = 0.63). The proportion of children requiring noninvasive and invasive mechanical ventilation, and its duration were similar between groups, same as hospital mortality. Interestingly, MIS-C was significantly lower in the oncology group compared with the control (2.4 vs 24.6%; P = 0.0002).Conclusions: In this study using a multicenter VIRUS database, ICU admission rate, interventions, and outcomes of COVID-19 were similar in children with the oncologic disease compared with control patients. The incidence of MIS-C is lower in oncologic patients.

Prognostic factors for multisystem inflammatory syndrome in children: A systematic review and meta‐analysis

“…The database searches yielded 5183 records, of which 3081 were screened following deduplication. We retrieved 56 full‐texts for further screening, of which 12 observational studies were included for analysis (N = 18 024) 22–33 . A list of studies excluded during the full‐text screening phase can be found in Data S1.…”

“…Of the 12 included studies, reviewers judged 9 to have a high risk of bias 22,24,26,28–33 . The most frequent source of potential bias in these studies was related to the insufficient adjustment of important confounders in their multivariable regression models.…”

“…Of the 12 included studies, reviewers judged 9 to have a high risk of bias. 22,24,26,[28][29][30][31][32][33] The most frequent source of potential bias in these studies was related to the insufficient adjustment of important confounders in their multivariable regression models. Other sources of bias included an insufficient number of events based on their number of tested predictors, improper dichotomisation of continuous variables, and the use of inappropriate model-building methods.…”

“…We retrieved 56 full-texts for further screening, of which 12 observational studies were included for analysis (N = 18 024). [22][23][24][25][26][27][28][29][30][31][32][33] A list of studies excluded during the full-text screening phase can be found in Data S1. The PRISMA flowchart for the study selection process is illustrated in Figure 1, and study characteristics are tabulated in Table S7.…”