This retrospective observational study evaluated outpatient treatment patterns among patients with molecular-based viral diagnostic testing for suspected upper respiratory tract infections in the United States. Patients with a respiratory viral test were identified from 1 August 2016 to 1 July 2019 in a large national reference laboratory database linked to IQVIA’s prescription and medical claims databases. Antibiotic and influenza antiviral treatment patterns were reported up to 7 days post-test result. Predictors of antibiotic utilization were assessed using multivariable logistic regression. Among 9561 patients included in the study, 24.6% had evidence of ≥1 filled antibiotic prescription. Antibiotic utilization was higher in patients who tested negative for all viral targets (odds ratio [OR], 1.33; 95% confidence interval [CI], 1.17–1.50) and patients positive for non-influenza viruses (OR, 1.28; 95% CI, 1.09–1.51) compared with those influenza-positive only. Age ≥ 50 years and location outside of the northeast United States also predicted antibiotic utilization. Influenza antivirals were more common in influenza-positive patients compared with patients with other test results (32.5% vs. 3.6–9.0%). Thus, in this real-world study, antibiotic utilization was elevated in patients positive for non-influenza viruses, although antibiotics would generally not be indicated. Further research on pairing diagnostic tools with outpatient antibiotic stewardship programs is needed.

BackgroundSpecialty medications have transformed management of chronic inflammatory conditions. There is a critical need to elucidate underlying barriers and medication‐related problems (MRPs) that might contribute to specialty medication non‐adherence in order to minimize disease progression, treatment failure, and increased healthcare utilization.ObjectiveTo characterize MRPs for patients taking specialty medications for chronic inflammatory conditions and identify factors associated with experiencing MRPs.MethodsRetrospective cohort study of patients prescribed specialty medications for chronic inflammatory conditions at a single, regional, tertiary medical center, who filled their prescriptions at Walgreens pharmacy between 1/1/2014 and 12/31/2016. Electronic health records were manually reviewed to find documented medication problems. MRPs were then analyzed to identify common themes. Differences in baseline characteristics for patients with or without documented MRPs were compared using Fisher's exact test for categorical variables and Mann Whitney U test for continuous variables. Student's t test was used to determine associations between 12‐month proportion of days covered (PDC) and the presence of any MRP.ResultsOf 272 patients who were prescribed specialty medications for chronic inflammatory conditions, 98 patients (36%) experienced a total of 131 documented MRPs. Four major themes associated with these problems emerged: prescription processing issues (31%), insurance problems (24%), medication use problems (22%), and side effects (18%). Patients were less likely to have a documented MRP if they were African American (P = .032) and patients with MRPs had a greater proportion of missed clinic visits. Mean 12‐month PDC (n = 167) was 0.61 and was not significantly associated with having a documented MRP (P = .7).ConclusionUse of specialty medications for patients with chronic inflammatory conditions continues to increase. Gaining a greater understanding of the MRPs that affect specialty medication use for chronic inflammatory conditions can help identify practice innovations and policies to improve patient care.

Treatment failure in glioblastoma, the most common and lethal primary brain tumor in adults, is often attributed to intratumoral heterogeneity as it fosters tumor evolution and selection of resistant clones. Sources of intratumoral heterogeneity may include genomic alterations, such as single-nucleotide and structural variants, and epigenomic alterations, such as changes in chromatin structure and transcriptional regulation. The relative extent and functional significance of these contributors to intratumoral heterogeneity in glioblastoma have yet to be elucidated. In collaboration with neurosurgeons and neuro-imaging experts, we have established a novel approach towards characterizing intratumoral heterogeneity in three-dimensional (3D) space. For patients undergoing tumor resection, we utilize 3D surgical neuronavigation to safely acquire ~10 samples representing maximal anatomical diversity. Samples are mapped by 3D spatial coordinates and integrated with patient MRI scans for 360º visualization of sample location in context of the brain. We have now conducted whole-exome sequencing (Exome-Seq), assay for transposase-accessible chromatin (ATAC-Seq), and RNA-sequencing (RNA-Seq) for 83 spatially mapped samples obtained from 8 patients with primary IDH-WT glioblastoma. Integrative data analysis provides unprecedented insight into sources of intratumoral heterogeneity in glioblastoma and their 3D spatial patterning. We find that tumor cells show aberrant transcription factor activity, activation of fetal brain programs, and variable chromatin accessibility at CTCF-binding loop anchors indicating plasticity in higher-order chromatin structure. Chromosome conformation capture analysis by Hi-C extends these findings and reveals intratumoral differences in long-range chromatin interactions due to structural variants and enhancer hijacking. Further, we use deconvolution to identify microenvironmental contributors to epigenomic intratumoral heterogeneity including neural, glial, and immune populations. We define chromatin signatures associated with microenvironmental cell types and states, revealing their 3D spatial patterning, and validate these findings by single-cell ATAC-Seq. Our work thus establishes both tumor and microenvironmental sources of intratumoral heterogeneity in glioblastoma, revealing their chromatin programs and 3D spatial patterning. As a resource for further investigation, we have developed an interactive data sharing platform that enables visualization of brain tumor intratumoral heterogeneity in 360 degrees. Citation Format: Radhika Mathur, Qixuan Wang, Patrick Schupp, Ana Nikolic, Takafumi Yamaguchi, Stephanie Hilz, Chibo Hong, Ivan Smirnov, Marisa LaFontaine, Joanna Phillips, Susan Chang, Yan Li, Janine Lupo, Paul Boutros, Marco Gallo, Michael Oldham, Feng Yue, Joseph Costello. 3D spatial sampling and integrated omics reveal sources and patterning of intratumoral heterogeneity in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3621.

INTRODUCTION It is estimated that 25 to 35% of patients experience treatment-induced effects that can mimic recurrent high-grade gliomas. This diagnostic challenge is complicated by the coexistence of treatment-related changes and recurrent tumor within the same lesion which limits the accuracy of classification based on summary metrics of multi-parametric MRI. This study aimed to determine whether different MR features were relevant for distinguishing pathological features of recurrent tumor from the effects of treatment in the contrast enhancing and non-enhancing lesions of recurrent high-grade gliomas. METHODS Leveraging our unique dataset of image-guided tissue samples that directly maps pathology to MR characteristics, we analyzed 291 tissue samples (222 recurrent tumor; 69 treatment effect) with known coordinates on imaging from 139 patients that underwent preoperative 3T MRI and surgery for a suspected high-grade recurrent tumor. 8 MR parameter values from perfusion-weighted, diffusion-weighted, and MR spectroscopic imaging at each tissue sample location were tested for association with histopathological outcome using univariate and multivariate generalized estimating equation models for enhancing and non-enhancing tissue samples. Individual cutoff values were determined and evaluated using ROC-Curve analysis with 5-fold cross-validation. RESULTS In tissue samples obtained from contrast-enhancing lesions, elevated relative cerebral blood volume (rCBV) was significantly associated with the presence of recurrent tumor (p< 0.03), while increases in normalized choline (nCho) and choline-to-NAA index (CNI) were significantly associated with the presence of recurrent tumor in non-enhancing tissue samples (p< 0.008). Cutoff values of 1.6(rCBV), 2.7(CNI), and 2.1(nCho) had the highest performance. CONCLUSION Our results confirm the utility of rCBV in distinguishing the effects of treatment from recurrent tumor within the contrast enhancing lesion. We report a novel finding that metabolic parameters can differentiate recurrent tumor from treatment-related changes in the non-enhancing lesion of high-grade gliomas. These results will help improve future management of patients with suspected recurrence.