Gupta, Sandeep

ImportanceThere is limited evidence for therapeutic options for pediatric COVID-19 outside of multisystem inflammatory syndrome in children (MIS-C).ObjectiveTo determine whether the use of steroids within 2 days of admission for non–MIS-C COVID-19 in children is associated with hospital length of stay (LOS). The secondary objective was to determine their association with intensive care unit (ICU) LOS, inflammation, and fever defervescence.Design, Setting, and ParticipantsThis cohort study analyzed data retrospectively for children (<18 years) who required hospitalization for non–MIS-C COVID-19. Data from March 2020 through September 2021 were provided by 58 hospitals in 7 countries who participate in the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS) COVID-19 registry.ExposureAdministration of steroids within 2 days of admission.Main Outcomes and MeasuresLength of stay in the hospital and ICU. Adjustment for confounders was done by mixed linear regression and propensity score matching.ResultsA total of 1163 patients met inclusion criteria and had a median (IQR) age of 7 years (0.9-14.3). Almost half of all patients (601/1163, 51.7%) were male, 33.8% (392/1163) were non-Hispanic White, and 27.9% (324/1163) were Hispanic. Of the study population, 184 patients (15.8%) received steroids within 2 days of admission, and 979 (84.2%) did not receive steroids within the first 2 days. Among 1163 patients, 658 (56.5%) required respiratory support during hospitalization. Overall, patients in the steroids group were older and had greater severity of illness, and a larger proportion required respiratory and vasoactive support. On multivariable linear regression, after controlling for treatment with remdesivir within 2 days, country, race and ethnicity, obesity and comorbidity, number of abnormal inflammatory mediators, age, bacterial or viral coinfection, and disease severity according to ICU admission within first 2 days or World Health Organization ordinal scale of 4 or higher on admission, with a random intercept for the site, early steroid treatment was not significantly associated with hospital LOS (exponentiated coefficient, 0.94; 95% CI, 0.81-1.09; P = .42). Separate analyses for patients with an LOS of 2 days or longer (n = 729), those receiving respiratory support at admission (n = 286), and propensity score–matched patients also showed no significant association between steroids and LOS. Early steroid treatment was not associated with ICU LOS, fever defervescence by day 3, or normalization of inflammatory mediators.Conclusions and RelevanceSteroid treatment within 2 days of hospital admission in a heterogeneous cohort of pediatric patients hospitalized for COVID-19 without MIS-C did not have a statistically significant association with hospital LOS.

Abstract Archival tumor samples present a rich resource of annotated specimens for genomics research. However, standard variant calling approaches require a matched normal sample from the same individual, which is often not available with archival tissue. Without a matched normal sample, it is very difficult to distinguish between true somatic variants and germline variants that are private to the individual. Archival FFPE sections often contain adjacent normal tissue, but this normal tissue is often contaminated with infiltrating tumor cells. Comparative somatic variant callers are designed to exclude variants present in the normal sample, so a novel approach is required to leverage sequencing of adjacent normal tissue. Here we present LumosVar 2.0, a software package designed to jointly analyze multiple samples from the same patient. The approach is based on the concept that the allelic fraction of somatic variants, but not germline variants, would be diluted by the presence of normal tissue. Given the allele specific copy number state and expected tumor fraction of each sample, one can model the expected allelic fractions of somatic and germline variants. LumosVar estimates allele specific copy number and tumor sample fractions from the data, and uses the model to call somatic and germline variants. LumosVar is also able to detect sub clonal events and spatial heterogeneity between samples. To evaluate this approach, we used a glioblastoma dataset, where enhancing (high tumor content) and non-enhancing (low tumor content) samples were available for each patient, as well as the matched normal sample to define the true somatic variants. We show that both sensitivity and positive predictive value are improved by analyzing the high tumor and low tumor jointly compared to analyzing the samples individually or in silico pooling of the two samples. Finally, we apply this approach to a set of breast and prostate archival FFPE tumor samples where normal samples were not available for germline sequencing. Citation Format: Rebecca F. Halperin, Winnie S. Liang, Erica Tassone, Jonathan Adkins, Megan Russell, Nhan Tran, Nicole Hank, James Newell, Sandeep Gupta, Michael Berens, Ronald Korn, David W. Craig, Sara A. Byron. Leveraging spatial heterogeneity in tumor purity for improved somatic variant calling of archival tumor-only samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-007. doi:10.1158/1538-7445.AM2017-LB-007