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Pediatric cancer treatment, especially for brain tumors, can have profound and complicated late effects. With the survival rates increasing because of improved detection and treatment, a more comprehensive understanding of the impact of current treatments on neurocognitive function and brain structure is critically needed. A frontline medulloblastoma clinical trial (SJMB03) has collected data, including treatment, clinical, neuroimaging, and cognitive variables. Advanced methods for modeling and integrating these data are critically needed to understand the mediation pathway from the treatment through brain structure to neurocognitive outcomes. We propose an integrative Bayesian mediation analysis approach to model jointly a treatment exposure, a high‐dimensional structural neuroimaging mediator, and a neurocognitive outcome and to uncover the mediation pathway. The high‐dimensional imaging‐related coefficients are modeled via a binary Ising–Gaussian Markov random field prior (BI‐GMRF), addressing the sparsity, spatial dependency, and smoothness and increasing the power to detect brain regions with mediation effects. Numerical simulations demonstrate the estimation accuracy, power, and robustness. For the SJMB03 study, the BI‐GMRF method has identified white matter microstructure that is damaged by cancer‐directed treatment and impacts late neurocognitive outcomes. The results provide guidance on improving treatment planning to minimize long‐term cognitive sequela for pediatric brain tumor patients. [ABSTRACT FROM AUTHOR]

In this paper, we consider weak solutions of the Euler–Lagrange equation to a variational energy functional modeling the geometrically nonlinear Cosserat micropolar elasticity of continua in dimension three, which is a system coupling between the Poisson equation and the equation of |$p$| -harmonic maps (⁠|$2\le p\le 3$|⁠). We show that if a weak solution is stationary, then its singular set is discrete for |$2

Background: Whether social determinants of health are associated with survival in the context of pediatric oncology-targeted immunotherapy trials is not known. We examined the association between poverty and event-free survival (EFS) and overall survival (OS) for children with high-risk neuroblastoma treated in targeted immunotherapy trials.Methods: We conducted a retrospective cohort study of 371 children with high-risk neuroblastoma treated with GD2-targeted immunotherapy in the Children's Oncology Group trial ANBL0032 or ANBL0931 at a Pediatric Health Information System center from 2005 to 2014. Neighborhood poverty exposure was characterized a priori as living in a zip code with a median household income within the lowest quartile for the cohort. Household poverty exposure was characterized a priori as sole coverage by public insurance. Post hoc analyses examined the joint effect of neighborhood and household poverty using a common reference. All statistical tests were 2-sided.Results: In multivariable Cox regressions adjusted for disease and treatment factors, household poverty-exposed children experienced statistically significantly inferior EFS (hazard ratio [HR] = 1.90, 95% confidence interval [CI] = 1.28 to 2.82, P = .001) and OS (HR = 2.79, 95% CI = 1.63 to 4.79, P < .001) compared with unexposed children. Neighborhood poverty was not independently associated with EFS or OS. In post hoc analyses exploring the joint effect of neighborhood and household poverty, children with dual-poverty exposure (neighborhood poverty and household poverty) experienced statistically significantly inferior EFS (HR = 2.21, 95% CI = 1.48 to 3.30, P < .001) and OS (HR = 3.70, 95% CI = 2.08 to 6.59, P < .001) compared with the unexposed group.Conclusions: Poverty is independently associated with increased risk of relapse and death among neuroblastoma patients treated with targeted immunotherapy. Incorporation of social and environmental factors in future trials as health-care delivery intervention targets may increase the benefit of targeted therapies. [ABSTRACT FROM AUTHOR]

Pediatric phase I trials are usually carried out after the adult trial testing the same agent has started, but not completed yet. As the pediatric trial progresses, in light of the accrued interim data from the concurrent adult trial, the pediatric protocol often is amended to modify the original pediatric dose escalation design. In practice, this is done frequently in an ad hoc way, interrupting patient accrual and slowing down the trial. We developed a pediatric‐continuous reassessment method (PA‐CRM) to streamline this process, providing a more efficient and rigorous method to find the maximum tolerated dose for pediatric phase I oncology trials. We use a discounted joint likelihood of the adult and pediatric data, with a discount parameter controlling information borrowing between pediatric and adult trials. According to the interim adult and pediatric data, the discount parameter is adaptively updated using the Bayesian model averaging method. Numerical study shows that the PA‐CRM improves the efficiency and accuracy of the pediatric trial and is robust to various model assumptions. [ABSTRACT FROM AUTHOR]

The rapid acceleration of genetic data collection in biomedical settings has recently resulted in the rise of genetic compendiums filled with rich longitudinal disease data. One common feature of these data sets is their plethora of interval‐censored outcomes. However, very few tools are available for the analysis of genetic data sets with interval‐censored outcomes, and in particular, there is a lack of methodology available for set‐based inference. Set‐based inference is used to associate a gene, biological pathway, or other genetic construct with outcomes and is one of the most popular strategies in genetics research. This work develops three such tests for interval‐censored settings beginning with a variance components test for interval‐censored outcomes, the interval‐censored sequence kernel association test (ICSKAT). We also provide the interval‐censored version of the Burden test, and then we integrate ICSKAT and Burden to construct the interval censored sequence kernel association test—optimal (ICSKATO) combination. These tests unlock set‐based analysis of interval‐censored data sets with analogs of three highly popular set‐based tools commonly applied to continuous and binary outcomes. Simulation studies illustrate the advantages of the developed methods over ad hoc alternatives, including protection of the type I error rate at very low levels and increased power. The proposed approaches are applied to the investigation that motivated this study, an examination of the genes associated with bone mineral density deficiency and fracture risk. [ABSTRACT FROM AUTHOR]

Survival data can contain an unknown fraction of subjects who are “cured” in the sense of not being at risk of failure. We describe such data with cure-mixture models, which separately model cure status and the hazard of failure among non-cured subjects. No diagnostic currently exists for evaluating the fit of such models; the popular Schoenfeld residual (Schoenfeld, 1982. Partial residuals for the proportional hazards regression-model. Biometrika 69, 239–241) is not applicable to data with cures. In this article, we propose a pseudo-residual, modeled on Schoenfeld's, to assess the fit of the survival regression in the non-cured fraction. Unlike Schoenfeld's approach, which tests the validity of the proportional hazards (PH) assumption, our method uses the full hazard and is thus also applicable to non-PH models. We derive the asymptotic distribution of the residuals and evaluate their performance by simulation in a range of parametric models. We apply our approach to data from a smoking cessation drug trial. [ABSTRACT FROM PUBLISHER]

Increased understanding of the underlying mechanisms of cognitive remediation is needed to facilitate development of intervention strategies for childhood cancer survivors experiencing cognitive late effects. Accordingly, a pilot functional magnetic resonance imaging (fMRI) study was conducted with 14 cancer survivors (12.02 ± 0.09 years old), who participated in a cognitive remediation clinical trial, and 28 healthy children (12.7 ± 0.6 years old). The ventral visual areas, cerebellum, supplementary motor area, and left inferior frontal cortex were significantly activated in the healthy participants during a continuous performance task. In survivors, brain activation in these regions was diminished at baseline, and increased upon completion of remediation and at a 6-month follow-up. The fMRI activation index for each region of interest was inversely associated with the Conners' Clinical Competence Index (p<.01). The pilot study suggests that fMRI is useful in evaluating neural responses to cognitive remediation. [ABSTRACT FROM PUBLISHER]

Summary In smoking cessation clinical trials, subjects commonly receive treatment and report daily cigarette consumption over a period of several weeks. Although the outcome at the end of this period is an important indicator of treatment success, substantial uncertainty remains on how an individual's smoking behavior will evolve over time. Therefore it is of interest to predict long-term smoking cessation success based on short-term clinical observations. We develop a Bayesian method for prediction, based on a cure-mixture frailty model we proposed earlier, that describes the process of transition between abstinence and smoking. Specifically we propose a two-stage prediction algorithm that first uses importance sampling to generate subject-specific frailties from their posterior distributions conditional on the observed data, then samples predicted future smoking behavior trajectories from the estimated model parameters and sampled frailties. We apply the method to data from two randomized smoking cessation trials comparing bupropion to placebo. Comparisons of actual smoking status at one year with predictions from our model and from a variety of empirical methods suggest that our method gives excellent predictions. [ABSTRACT FROM AUTHOR]

Background Performance validity tests (PVTs) and symptom validity tests (SVTs) are essential to neuropsychological evaluations, helping ensure findings reflect true abilities or concerns. It is unclear how PVTs and SVTs perform in children who received radiotherapy for brain tumors. Accordingly, we investigated the rate of noncredible performance on validity indicators as well as associations with fatigue and lower intellectual functioning. Methods Embedded PVTs and SVTs were investigated in 98 patients with pediatric craniopharyngioma undergoing proton radiotherapy (PRT). The contribution of fatigue, sleepiness, and lower intellectual functioning to embedded PVT performance was examined. Further, we investigated PVTs and SVTs in relation to cognitive performance at pre-PRT baseline and change over time. Results SVTs on parent measures were not an area of concern. PVTs identified 0–31% of the cohort as demonstrating possible noncredible performance at baseline, with stable findings 1 year following PRT. Reliable digit span (RDS) noted the highest PVT failure rate; RDS has been criticized for false positives in pediatric populations, especially children with neurological impairment. Objective sleepiness was strongly associated with PVT failure, stressing need to consider arousal level when interpreting cognitive performance in children with craniopharyngioma. Lower intellectual functioning also needs to be considered when interpreting task engagement indices as it was strongly associated with PVT failure. Conclusions Embedded PVTs should be used with caution in pediatric craniopharyngioma patients who have received PRT. Future research should investigate different cut-off scores and validity indicator combinations to best differentiate noncredible performance due to task engagement versus variable arousal and/or lower intellectual functioning. [ABSTRACT FROM AUTHOR]

Phytosulfokine (PSK), a plant peptide hormone with a wide range of biological functions, is recognized by its receptor PHYTOSULFOKINE RECEPTOR 1 (PSKR1). Previous studies have reported that PSK plays important roles in plant growth, development, and stress responses. However, the involvement of PSK in fruit development and quality formation remains largely unknown. Here, using tomato (Solanum lycopersicum) as a research model, we show that exogenous application of PSK promotes the initiation of fruit ripening and quality formation, while these processes are delayed in pskr1 mutant fruits. Transcriptomic profiling revealed that molecular events and metabolic pathways associated with fruit ripening and quality formation are affected in pskr1 mutant lines and transcription factors are involved in PSKR1-mediated ripening. Yeast screening further identified that DEHYDRATION-RESPONSIVE ELEMENT BINDING PROTEIN 2F (DREB2F) interacts with PSKR1. Silencing of DREB2F delayed the initiation of fruit ripening and inhibited the promoting effect of PSK on fruit ripening. Moreover, the interaction between PSKR1 and DREB2F led to phosphorylation of DREB2F. PSK improved the efficiency of DREB2F phosphorylation by PSKR1 at the tyrosine-30 site, and the phosphorylation of this site increased the transcription level of potential target genes related to the ripening process and functioned in promoting fruit ripening and quality formation. These findings shed light on the involvement of PSK and its downstream signaling molecule DREB2F in controlling climacteric fruit ripening, offering insights into the regulatory mechanisms governing ripening processes in fleshy fruits. Phytosulfokine promotes fruit ripening and quality formation in tomato by enhancing PHYTOSULFOKINE RECEPTOR1-mediated phosphorylation of DEHYDRATION-RESPONSIVE ELEMENT BINDING PROTEIN 2F. [ABSTRACT FROM AUTHOR]

Summary: Panel‐count data arise when each study subject is observed only at discrete time points in a recurrent event study, and only the numbers of the event of interest between observation time points are recorded (Sun and Zhao, 2013). However, sometimes the exact number of events between some observation times is unknown and what we know is only whether the event of interest has occurred. In this article, we will refer this type of data to as mixed panel‐count data and propose a likelihood‐based semiparametric regression method for their analysis by using the nonhomogeneous Poisson process assumption. However, we establish the asymptotic properties of the resulting estimator by employing the empirical process theory and without using the Poisson assumption. Also, we conduct an extensive simulation study, which suggests that the proposed method works well in practice. Finally, the method is applied to a Childhood Cancer Survivor Study that motivated this study. [ABSTRACT FROM AUTHOR]

Patients with newly diagnosed acute myeloid leukemia initiated on antifungal prophylaxis were found to have lower induction mortality and resource utilization rates compared to those not receiving prophylaxis.Background. Invasive fungal infections cause significant morbidity and mortality for children with acute myeloid leukemia (AML). Data on the comparative effectiveness of antifungal prophylaxis in this population are limited.Methods. A pediatric AML cohort was assembled from the Pediatric Health Information System database using ICD-9 codes and pharmacy data. Antifungal prophylaxis status was determined by pharmaceutical data review within 21 days of starting induction chemotherapy. Patients were followed until end of induction, death, or loss to follow-up. Cox regression analyses compared induction mortality and resources utilized between patients receiving and not receiving antifungal prophylaxis. A propensity score accounted for variation in demographic factors, location of care, and severity of illness at presentation.Results. Eight hundred seventy-one AML patients were identified; the induction case fatality rate was 3.7%. In the adjusted Cox regression model, patients receiving antifungal prophylaxis (57%) had a decreased hazard for induction mortality (hazard ratio [HR], 0.42; 95% confidence interval [CI], .19–.90). Children receiving prophylaxis were less frequently exposed to broad-spectrum gram-positive (incidence rate ratio [IRR], 0.87; 95% CI, .79–.97) and antipseudomonal β-lactam agents (HR, 0.91; 95% CI, .85–.96), had fewer blood cultures (IRR, 0.78; 95% CI, .71–.86), and had fewer chest CT scans (IRR, 0.73; 95% CI, .60–.88).Conclusions. Antifungal prophylaxis in pediatric AML patients was associated with reduced induction mortality rates and supportive care resources. Further investigation is necessary to determine whether antifungal prophylaxis should include antimold activity. [ABSTRACT FROM PUBLISHER]

Background Infections are a leading cause of morbidity and mortality in children with cancer. Although data are limited, the impact of infection in this population appears to be amplified in low- and middle-income countries. Defining the epidemiology of infection in a specific region is paramount to developing effective interventions. This study aims to define the epidemiology of and outcomes from infection in children with leukemia in the Dominican Republic. Methods A retrospective cohort was assembled of children newly diagnosed with leukemia between July 1, 2015 and June 30, 2017 at Hospital Infantil Dr. Robert Reid Cabral in Santo Domingo. Patients were identified from the Pediatric Oncology Network Database and hospital admissions from the Oncology admissions logbook. Medical records and microbiology results were reviewed to identify all inpatient invasive infections. Distance from a child's home to the hospital was determined using ArcGIS 10.5.1. Infection rates were described in discrete time periods after diagnosis and risk factors for invasive infection were explored using Poisson regression. Results The cohort included 68 patients; 54 (79.4%) with acute lymphoblastic leukemia and 14 (20.6%) with acute myeloblastic leukemia. The cohort was 48.5% female, had a median age at diagnosis of 7.3 years (range 1.1–16.6), and a median weight-for-age of 45.5 percentile (range 0–99.9). There were 1.2 invasive infections per 100 days at risk in the first 60 days after diagnosis, 0.8 from > 60–100 days, and 0.4 from > 100–180 days. Gastroenteritis, skin/soft-tissue infection, and pneumonia were most frequent, with bacteremia most common in the first 60 days. In a multivariate Poisson regression model, age ≥10 years (IRR 0.49, 95% CI 0.28–0.85) and distance from the hospital >100 km (IRR 0.34, 95% CI 0.14 – 0.81) were each protective against infection in the first 180 days after diagnosis. During the 2-year period, 8 of 22 (36%) patient deaths were related to infection. Conclusion Invasive infections were common and a prominent source of death in this cohort. Interventions aimed at reducing infection should target the first 60 days after diagnosis. Decreased infection incidence among children of older age and farther distance from the hospital were unexpected and warrant further investigation. Disclosures All authors: No reported disclosures. [ABSTRACT FROM AUTHOR]

Background Antibiotic exposure is common among children with leukemia. However, limited data exist regarding the risk of Clostridium difficile infection (CDI) across anti-pseudomonal β-lactam antibiotics commonly used for fever and neutropenia. Methods A multicenter cohort of children with newly diagnosed acute lymphoblastic leukemia (ALL) was established from 43 freestanding children's hospitals from 1999 to 2009. Patients were followed until their index CDI event, defined by the CDI ICD-9 code plus a C difficile test charge, or until 180 days from ALL diagnosis. Cox proportional hazards models were performed to identify the hazards of CDI after exposure to anti-pseudomonal β-lactams, adjusting for demographics, other antibiotic exposures, severity of illness, antacids, gastrointestinal manipulation, and confounding by hospital. Results A cohort of 8268 ALL patients was assembled; median age was 5.5 years (interquartile range, 3.26–10.58). Two-hundred sixty-eight (3.2%) patients developed CDI within 180 days of ALL diagnosis. Each 1-day increase in exposure to an anti-pseudomonal β-lactam within the prior 30 days was associated with a significantly increased risk for CDI (hazard ratio [HR], 1.05; 95% confidence interval [CI], 1.01, 1.09). Ceftazidime (HR, 1.05; 95% CI, 1.02, 1.08) and cefepime (HR, 1.07; 95% CI, 1.02, 1.12) were each independently associated with CDI. Conclusions Efforts to reduce total exposure to anti-pseudomonal β-lactam agents may help to reduce the risk of CDI in children with newly diagnosed ALL. Cefepime and ceftazidime were independently associated with CDI, whereas anti-pseudomonal penicillins and carbapenems were not. These findings, if confirmed, have potential implications for antibiotic choice during periods of fever and neutropenia. [ABSTRACT FROM PUBLISHER]