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Background: Image-defined risk factors (IDRFs) were promulgated for predicting the feasibility and safety of complete primary tumor resection in children with neuroblastoma (NB). There is limited understanding of the impact of individual IDRFs on resectability of the primary tumor or patient outcomes. A multicenter database of patients with high-risk NB was interrogated to answer this question., Design/methods: Patients with high-risk NB (age <20 years) were eligible if cross-sectional imaging was performed at least twice prior to resection. IDRFs and primary tumor measurements were recorded for each imaging study. Extent of resection was determined from operative reports., Results: There were 211 of 229 patients with IDRFs at diagnosis, and 171 patients with IDRFs present pre-surgery. A ≥90% resection was significantly more likely in the absence of tumor invading or encasing the porta hepatis, hepatoduodenal ligament, superior mesenteric artery (SMA), renal pedicles, abdominal aorta/inferior vena cava (IVC), iliac vessels, and/or diaphragm at diagnosis or an overlapping subset of IDRFs (except diaphragm) at pre-surgery. There were no significant differences in event-free survival (EFS) and overall survival (OS) when patients were stratified by the presence versus absence of any IDRF either at diagnosis or pre-surgery., Conclusion: Two distinct but overlapping subsets of IDRFs present either at diagnosis or after induction chemotherapy significantly influence the probability of a complete resection in children with high-risk NB. The presence of IDRFs was not associated with significant differences in OS or EFS in this cohort., (© 2024 Wiley Periodicals LLC.)

Background/objective: Non-clinical aspects of life, such as social, environmental, behavioral, psychological, and economic factors, what we call the sociome, play significant roles in shaping patient health and health outcomes. This paper introduces the Sociome Data Commons (SDC), a new research platform that enables large-scale data analysis for investigating such factors., Methods: This platform focuses on "hyper-local" data, i.e., at the neighborhood or point level, a geospatial scale of data not adequately considered in existing tools and projects. We enumerate key insights gained regarding data quality standards, data governance, and organizational structure for long-term project sustainability. A pilot use case investigating sociome factors associated with asthma exacerbations in children residing on the South Side of Chicago used machine learning and six SDC datasets., Results: The pilot use case reveals one dominant spatial cluster for asthma exacerbations and important roles of housing conditions and cost, proximity to Superfund pollution sites, urban flooding, violent crime, lack of insurance, and a poverty index., Conclusion: The SDC has been purposefully designed to support and encourage extension of the platform into new data sets as well as the continued development, refinement, and adoption of standards for dataset quality, dataset inclusion, metadata annotation, and data access/governance. The asthma pilot has served as the first driver use case and demonstrates promise for future investigation into the sociome and clinical outcomes. Additional projects will be selected, in part for their ability to exercise and grow the capacity of the SDC to meet its ambitious goals., Competing Interests: S.N. served on an advisory board for Avillion/Astra Zeneca, receives royalties from Wolters-Kluwer and Springer, and research funding from NIH and Asthma Allergy Foundation of America. C.S. served on advisory boards for Gilead and Merck, receives royalties from Wolters-Kluwer, and research funding from CDC. A.S. Holds voluntary positions in the American Medical Informatics Association and is an equity investor in healthcare companies and other industries. J.S. reports a potential financial interest in PulmOne Advanced Medical Devices, Ltd, Israel, and research grant funding from NIH, NSF, and Respiratory Health Association of Metropolitan Chicago. S.V. is co-founder and Chief Medical Officer for Litmus Health, Inc., and receives consulting royalties from CVS Accordant., (© The Author(s) 2023.)

Background: Primary immunodeficiency diseases (PIDD) are a group of immune-related disorders that have a current median delay of diagnosis between 6 and 9 years. Early diagnosis and treatment of PIDD has been associated with improved patient outcomes., Objective: To develop a machine learning model using elements within the electronic health record data that are related to prior symptomatic treatment to predict PIDD., Methods: We conducted a retrospective study of patients with PIDD identified using inclusion criteria of PIDD-related diagnoses, immunodeficiency-specific medications, and low immunoglobulin levels. We constructed a control group of age-, sex-, and race-matched patients with asthma. The primary outcome was the diagnosis of PIDD. We considered comorbidities, laboratory tests, medications, and radiological orders as features, all before diagnosis and indicative of symptom-related treatment. Features were presented sequentially to logistic regression, elastic net, and random forest classifiers, which were trained using a nested cross-validation approach., Results: Our cohort consisted of 6422 patients, of whom 247 (4%) were diagnosed with PIDD. Our logistic regression model with comorbidities demonstrated good discrimination between patients with PIDD and those with asthma (c-statistic: 0.62 [0.58-0.65]). Adding laboratory results, medications, and radiological orders improved discrimination (c-statistic: 0.70 vs 0.62, P < .001), sensitivity, and specificity. Extending to the advanced machine learning models did not improve performance., Conclusions: We developed a prediction model for early diagnosis of PIDD using historical data that are related to symptomatic care, which has potential to fill an important need in reducing the time to diagnose PIDD, leading to better outcomes for immunodeficient patients., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

PICU patients who experience critical illness events, such as intubation, are at high risk for morbidity and mortality. Little is known about the impact of these events, which require significant resources, on outcomes in other patients. Therefore, we aimed to assess the association between critical events in PICU patients and the risk of similar events in neighboring patients over the next 6 hours., Design: Retrospective observational cohort study., Setting: Quaternary care PICU at the University of Chicago., Patients: All children admitted to the PICU between 2012 and 2019., Interventions: None., Measurements and Main Results: The primary outcome was a critical event defined as the initiation of invasive ventilation, initiating vasoactive medications, cardiac arrest, or death. The exposure was the occurrence of a critical event among other patients in the PICU within the preceding 6 hours. Discrete-time survival analysis using fixed 6-hour blocks beginning at the time of PICU admission was used to model the risk of experiencing a critical event in the PICU when an event occurred in the prior 6 hours. There were 13,628 admissions, of which 1,886 (14%) had a critical event. The initiation of mechanical ventilation was the most frequent event ( n = 1585; 59%). In the fully adjusted analysis, there was a decreased risk of critical events (odds ratio, 0.82; 95% CI, 0.70-0.96) in the 6 hours following exposure to a critical event. This association was not present when considering longer intervals and was more pronounced in patients younger than 6 years old when compared with patients 7 years and older., Conclusion: Critical events in PICU patients are associated with decreased risk of similar events in neighboring patients. Further studies targeted toward exploring the mechanism behind this effect as well as identification of other nonpatient factors that adversely affect outcomes in children are warranted., Competing Interests: Dr. Volchenboum reported personal fees from Sanford Health, Consumer Value Stores Accordant, and Abbvie and stock in Litmus Health, all outside the submitted work. Dr. Churpek is supported by R01s from National Institute of General Medical Sciences (R01 GM123193), National Heart, Lung, and Blood Institute (R01 HL157262), National Institute of Diabetes and Digestive and Kidney Diseases (R01-DK126933), and a Peer Reviewed Medical Research Program grant from Department of Defense (W81XWH-21-1-0009), all outside of submitted work. Dr Churpek has a patent pending (ARCD. P0535US.P2) for risk stratification algorithms for hospitalized patients and have received research support from EarlySense (Tel Aviv, Israel), all outside of submitted work. Dr. Mayampurath is supported by a career development award from the National Heart, Lung, and Blood Institute (K01HL148390). Dr. Mayampurath has performed consulting services for Litmus Health, Austin, TX, outside of submitted work. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.)

Rhabdomyosarcomas (RMSs) are the most common soft tissue sarcomas in children/adolescents less than 18 years of age with an annual incidence of 1-2/million. Inter/intra-tumour heterogeneity raise challenges in clinical, pathological and biological research studies. Risk stratification in European and North American clinical trials previously relied on clinico-pathological features, but now, incorporates PAX3/7-FOXO1-fusion gene status in the place of alveolar histology. International working groups propose a coordinated approach through the INternational Soft Tissue SaRcoma ConsorTium to evaluate the specific genetic abnormalities and generate and integrate molecular and clinical data related to patients with RMS across different trial settings. We review relevant data and present a consensus view on what molecular features should be assessed. In particular, we recommend the assessment of the MYOD1-LR122R mutation for risk escalation, as it has been associated with poor outcomes in spindle/sclerosing RMS and rare RMS with classic embryonal histopathology. The prospective analyses of rare fusion genes beyond PAX3/7-FOXO1 will generate new data linked to outcomes and assessment of TP53 mutations and CDK4 amplification may confirm their prognostic value. Pathogenic/likely pathogenic germline variants in TP53 and other cancer predisposition genes should also be assessed. DNA/RNA profiling of tumours at diagnosis/relapse and serial analyses of plasma samples is recommended where possible to validate potential molecular biomarkers, identify new biomarkers and assess how liquid biopsy analyses can have the greatest benefit. Together with the development of new molecularly-derived therapeutic strategies that we review, a synchronised international approach is expected to enhance progress towards improved treatment assignment, management and outcomes for patients with RMS., Competing Interests: Conflict of interest statement The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Purpose: The Children's Oncology Group (COG) stratifies the treatment of patients with neuroblastoma on the basis of a combination of biomarkers that include age and tumor histology classified by age-linked International Neuroblastoma Pathology Classification (INPC) criteria. By definition, this leads to a duplication of the prognostic contribution of age. The individual histologic features underlying the INPC have prognostic strength and are incorporated in the International Neuroblastoma Risk Group classification schema. Here, we analyzed data in the International Neuroblastoma Risk Group Data Commons to validate the prognostic strength of the underlying INPC criteria and to determine whether a risk classification devoid of the confounding of age and INPC criteria will identify new prognostic subgroups., Patients and Methods: Event-free survival of patients diagnosed between 1990 and 2002 (cohort 1; n = 10,104) and between 2003 and 2016 (cohort 2; n = 8,761) was analyzed. Recursive partitioning with univariate Cox models of event-free survival ("survival tree regression") was performed using (1) individual INPC criteria (age at diagnosis, histologic category, mitosis-karyorrhexis index (MKI), grade of differentiation) and (2) factors in (1) plus other COG-risk biomarkers (International Neuroblastoma Staging System [INSS] stage, MYCN status, ploidy)., Results: The independent prognostic ability of age, histologic category, MKI, and grade were validated. Four histologic prognostic groups were identified (< 18 months with low v high MKI, and ≥ 18 months with differentiating v undifferentiated/poorly differentiating tumors). Compared with survival trees generated with established COG risk criteria, an additional prognostic subgroup was identified and validated when individual histologic features were analyzed in lieu of INPC., Conclusion: Replacing INPC with individual histologic features in the COG risk classification will eliminate confounding, facilitate international harmonization of risk classification, and provide a schema for more precise prognostication and refined therapeutic approaches.

Background: Radiolabeled metaiodobenzylguanidine (MIBG) is sensitive and specific for detecting neuroblastoma. The extent of MIBG-avid disease is assessed using Curie scores. Although Curie scoring is prognostic in patients with high-risk neuroblastoma, there is no standardized method to assess the response of specific sites of disease over time. The goal of this study was to develop approaches for Curie scoring to facilitate the calculation of scores and comparison of specific sites on serial scans., Procedure: We designed three semiautomated methods for determining Curie scores, each with increasing degrees of computer assistance. Method A was based on visual assessment and tallying of MIBG-avid lesions. For method B, scores were tabulated from a schematic that associated anatomic regions to MIBG-positive lesions. For method C, an anatomic mesh was used to mark MIBG-positive lesions with automatic assignment and tallying of scores. Five imaging physicians experienced in MIBG interpretation scored 38 scans using each method, and the feasibility and utility of the methods were assessed using surveys., Results: There was good reliability between methods and observers. The user-interface methods required 57 to 110 seconds longer than the visual method. Imaging physicians indicated that it was useful that methods B and C enabled tracking of lesions. Imaging physicians preferred method B to method C because of its efficiency., Conclusions: We demonstrate the feasibility of semiautomated approaches for Curie score calculation. Although more time was needed for strategies B and C, the ability to track and document individual MIBG-positive lesions over time is a strength of these methods., (© 2018 Wiley Periodicals, Inc.)

Changes in behavior are necessary to apply genomic discoveries to practice. We prospectively studied medication changes made by providers representing eight different medicine specialty clinics whose patients had submitted to preemptive pharmacogenomic genotyping. An institutional clinical decision support (CDS) system provided pharmacogenomic results using traffic light alerts: green = genomically favorable, yellow = genomic caution, red = high risk. The influence of pharmacogenomic alerts on prescribing behaviors was the primary endpoint. In all, 2,279 outpatient encounters were analyzed. Independent of other potential prescribing mediators, medications with high pharmacogenomic risk were changed significantly more often than prescription drugs lacking pharmacogenomic information (odds ratio (OR) = 26.2 (9.0-75.3), P < 0.0001). Medications with cautionary pharmacogenomic information were also changed more frequently (OR = 2.4 (1.7-3.5), P < 0.0001). No pharmacogenomically high-risk medications were prescribed during the entire study when physicians consulted the CDS tool. Pharmacogenomic information improved prescribing in patterns aimed at reducing patient risk, demonstrating that enhanced prescription decision-making is achievable through clinical integration of genomic medicine., (© 2017 American Society for Clinical Pharmacology and Therapeutics.)

Whole exome sequencing has facilitated the discovery of causal genetic variants associated with human diseases at deep coverage and low cost. In particular, the detection of somatic mutations from tumor/normal pairs has provided insights into the cancer genome. Although there is an abundance of publicly-available software for the detection of germline and somatic variants, concordance is generally limited among variant callers and alignment algorithms. Successful integration of variants detected by multiple methods requires in-depth knowledge of the software, access to high-performance computing resources, and advanced programming techniques. We present ExScalibur, a set of fully automated, highly scalable and modulated pipelines for whole exome data analysis. The suite integrates multiple alignment and variant calling algorithms for the accurate detection of germline and somatic mutations with close to 99% sensitivity and specificity. ExScalibur implements streamlined execution of analytical modules, real-time monitoring of pipeline progress, robust handling of errors and intuitive documentation that allows for increased reproducibility and sharing of results and workflows. It runs on local computers, high-performance computing clusters and cloud environments. In addition, we provide a data analysis report utility to facilitate visualization of the results that offers interactive exploration of quality control files, read alignment and variant calls, assisting downstream customization of potential disease-causing mutations. ExScalibur is open-source and is also available as a public image on Amazon cloud.

Toward our goal of personalized medicine, we comprehensively profiled pre-treatment malignant plasma cells from multiple myeloma patients and prospectively identified pathways predictive of favourable response to bortezomib-based treatment regimens. We utilized two complementary quantitative proteomics platforms to identify differentially-regulated proteins indicative of at least a very good partial response (VGPR) or complete response/near complete response (CR/nCR) to two treatment regimens containing either bortezomib, liposomal doxorubicin and dexamethasone (VDD), or lenalidomide, bortezomib and dexamethasone (RVD). Our results suggest enrichment of 'universal response' pathways that are common to both treatment regimens and are probable predictors of favourable response to bortezomib, including a subset of endoplasmic reticulum stress pathways. The data also implicate pathways unique to each regimen that may predict sensitivity to DNA-damaging agents, such as mitochondrial dysfunction, and immunomodulatory drugs, which was associated with acute phase response signalling. Overall, we identified patterns of tumour characteristics that may predict response to bortezomib-based regimens and their components. These results provide a rationale for further evaluation of the protein profiles identified herein for targeted selection of anti-myeloma therapy to increase the likelihood of improved treatment outcome of patients with newly-diagnosed myeloma., (© 2015 John Wiley & Sons Ltd.)

MYCN-amplification is strongly associated with other high-risk prognostic factors and poor outcome in neuroblastoma. Infrequently, amplification of MYCN has been identified in localized tumors with favorable biologic features. Outcome for these children is difficult to predict and optimal treatment strategies remain unclear. We report a 5-month-old who presented with an MYCN-amplified INSS stage 3, pelvic neuroblastoma. The tumor had favorable histology, hyperdiploidy, and lacked 1p36 and 11q23 aberrations. Although the patient met the criteria for high-risk neuroblastoma, because of the discordant prognostic markers we elected to treat her according to an intermediate-risk protocol. She remains event-free more than 18 months., (Copyright © 2011 Wiley Periodicals, Inc.)

Isovaleryl-CoA dehydrogenase (IVD) is a homotetrameric flavoenzyme, which catalyzes the conversion of isovaleryl-CoA to 3-methylcrotonyl-CoA and transfers electrons to the electron-transferring flavoprotein, and is a member of the acyl-CoA dehydrogenase (ACD) enzyme family. Human IVD crystal structure with a bound substrate analogue shows the guanidino group of Arg387, a conserved residue among other members of the ACD enzyme family, juxtaposed to a phosphate oxygen of the 4'-phosphopantothiene moiety of the substrate analogue. Site-directed mutagenesis was used to investigate the role of Arg387 in substrate binding and enzyme function. Replacing this residue with Lys, Ala, Gln, or Glu resulted in stable proteins. Spectrophotometric substrate binding assays indicated that the Arg387Lys mutant was able to form the charge-transfer complex intermediate with similar efficiency to wild type, while the rest of the mutants were significantly less able to properly form this intermediate. However, the Km of the isovaleryl-CoA for the Arg387Lys mutant was 20.3 compared to 1.5 microM for the wild type. The Km for the rest of the mutants were 75.6, 195, and 550 microM, respectively. The catalytic efficiency per mole of FAD was 20.3, 3.3, 2.0, and 0.34 for the mutants, respectively, compared to 260 microM(-1) x min(-1) for the wild type. These results substantiate the important role of Arg387 in anchoring the substrate, and are consistent with the hypothesis that residues distant from the active site are important for stabilizing the enzyme:substrate/product complex, and could play an important role in the mechanism of the enzyme-catalyzed reaction., (Copyright 2001 Academic Press.)

Isovaleryl-CoA dehydrogenase (IVD) is a homotetrameric mitochondrial flavoenzyme which catalyzes the conversion of isovaleryl-CoA to 3-methylcrotonyl-CoA. PCR of IVD genomic and complementary DNA was used to identify mutations occurring in patients with deficiencies in IVD activity. Western blotting, in vitro mitochondrial import, prokaryotic expression, and kinetic studies of IVD mutants were conducted to characterize the molecular defects caused by the amino acid replacements. Mutations leading to Arg21Pro, Asp40Asn, Ala282Val, Cys328Arg, Val342Ala, Arg363Cys, and Arg382Leu replacements were identified. Western blotting of fibroblast extracts and/or in vitro mitochondrial import experiments indicate that the seven precursor IVD mutant peptides, and a previously identified IVD Leu13Pro mutant, are synthesized and imported into mitochondria. While the IVD Leu13Pro, Arg21Pro, and Cys328Arg mutant peptides are rapidly degraded following mitochondrial import, the other mutant peptides exhibit greater mitochondrial stability, though less than the wild-type enzyme. Active IVD Ala282Val, Val342Ala, Arg363Cys, and Arg382Leu mutants were less stable than wild type when produced in Escherichia coli. The Km values of purified IVD Ala282Val, Val342Ala, and Arg382Leu mutants are 27.0, 2. 8, and 6.9 microM isovaleryl-CoA, respectively, compared to 3.1 microM for the wild type, using the electron-transfer flavoprotein (ETF) fluorescence quenching assay. The catalytic efficiency per mole of FAD content of these three mutants is 4.8, 17.0, and 17.0 microM-1*min-1, respectively, compared to 170 microM-1*min-1 for wild type.