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Objective: Examine the influence of household income on health‐related quality of life (HRQOL) among children with newly diagnosed acute myeloid leukemia (AML). Design: Secondary analysis of data prospectively collected from pediatric patients receiving treatment for AML at 14 hospitals across the United States. Exposure: Household income was self‐reported on a demographic survey. The examined mediators included the acuity of presentation and treatment toxicity. Outcome: Caregiver proxy reported assessment of patient HRQOL from the Peds QL 4.0 survey. Result: Children with AML (n = 131) and caregivers were prospectively enrolled to complete PedsQL assessments. HRQOL scores were better for patients in the lowest versus highest income category (mean ± SD: 76.0 ± 14 household income <$25,000 vs. 59.9 ± 17 income ≥$75,000; adjusted mean difference: 11.2, 95% CI: 2.2–20.2). Seven percent of enrolled patients presented with high acuity (ICU‐level care in the first 72 h), and 16% had high toxicity (any ICU‐level care); there were no identifiable differences by income, refuting mediating roles in the association between income and HRQOL. Enrolled patients were less likely to be Black/African American (9.9% vs. 22.2%), more likely to be privately insured (50.4% vs. 40.7%), and more likely to have been treated on a clinical trial (26.7% vs. 18.5%) compared to eligible unenrolled patients not enrolled. Evaluations of potential selection bias on the association between income and HRQOL suggested differences in HRQOL may be smaller than observed or even in the opposing direction. Conclusions: While primary analyses suggested lower household income was associated with superior HRQOL, differential participation may have biased these results. Future studies should partner with patients/families to identify strategies for equitable participation in clinical research. [ABSTRACT FROM AUTHOR]

The article offers information on a study related to the epidemiology of Recombinant urate oxidase (rasburicase) use in paediatric patients with acute lymphoblastic leukaemia and non-Hodgkin lymphoma. It notes the use of Pediatric Health Information System database (PHIS) for the study which include demographics, diagnosis codes and daily resource utilization data.

Despite the importance of adverse event (AE) reporting, AEs are under-reported on clinical trials. We hypothesized that electronic medical record (EMR) data can ascertain laboratory-based AEs more accurately than those ascertained manually. EMR data on 12 AEs for patients enrolled on two Children's Oncology Group (COG) trials at one institution were extracted, processed and graded. When compared to gold standard chart data, COG AE report sensitivity and positive predictive values (PPV) were 0-21·1% and 20-100%, respectively. EMR sensitivity and PPV were >98·2% for all AEs. These results demonstrate that EMR-based AE ascertainment and grading substantially improves laboratory AE reporting accuracy. [ABSTRACT FROM AUTHOR]

ABSTRACT Aims Smoking cessation trials generally record information on daily smoking behavior, but base analyses on measures of smoking status at the end of treatment (EOT). We present an alternative approach that analyzes the entire sequence of daily smoking status observations. Methods We analyzed daily abstinence data from a smoking cessation trial, using two longitudinal logistic regression methods: a mixed-effects (ME) model and a generalized estimating equations (GEE) model. We compared results to a standard analysis that takes abstinence status at EOT as outcome. We evaluated time-varying covariates (smoking history and time-varying drug effect) in the longitudinal analysis and compared ME and GEE approaches. Results We observed some differences in the estimated treatment effect odds ratios across models, with narrower confidence intervals under the longitudinal models. GEE yields similar results to ME when only baseline factors appear in the model, but gives biased results when one includes time-varying covariates. The longitudinal models indicate that the quit probability declines and the drug effect varies over time. Both the previous day's smoking status and recent smoking history predict quit probability, independently of the drug effect. Conclusion When analysing outcomes of studies from smoking cessation interventions, longitudinal models with multiple outcome data points, rather than just end of treatment, can makes efficient use of the data and incorporate time-varying covariates. The generalized estimating equations approach should be avoided when using time-varying predictors. [ABSTRACT FROM AUTHOR]

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: In the United States, cancer is common, with high morbidity and mortality; cancer incidence varies between states. Online searches reflect public awareness, which could be driven by the underlying regional cancer epidemiology.Objective: The objective of our study was to characterize the relationship between cancer incidence and online Google search volumes in the United States for 6 common cancers. A secondary objective was to evaluate the association of search activity with cancer-related public events and celebrity news coverage.Methods: We performed a population-based, retrospective study of state-level cancer incidence from 2004 through 2013 reported by the Centers for Disease Control and Prevention for breast, prostate, colon, lung, and uterine cancers and leukemia compared to Google Trends (GT) relative search volume (RSV), a metric designed by Google to allow interest in search topics to be compared between regions. Participants included persons in the United States who searched for cancer terms on Google. The primary measures were the correlation between annual state-level cancer incidence and RSV as determined by Spearman correlation and linear regression with RSV and year as independent variables and cancer incidence as the dependent variable. Temporal associations between search activity and events raising public awareness such as cancer awareness months and cancer-related celebrity news were described.Results: At the state level, RSV was significantly correlated to incidence for breast (r=.18, P=.001), prostate (r=-.27, P<.001), lung (r=.33, P<.001), and uterine cancers (r=.39, P<.001) and leukemia (r=.13, P=.003) but not colon cancer (r=-.02, P=.66). After adjusting for time, state-level RSV was positively correlated to cancer incidence for all cancers: breast (P<.001, 95% CI 0.06 to 0.19), prostate (P=.38, 95% CI -0.08 to 0.22), lung (P<.001, 95% CI 0.33 to 0.46), colon (P<.001, 95% CI 0.11 to 0.17), and uterine cancers (P<.001, 95% CI 0.07 to 0.12) and leukemia (P<.001, 95% CI 0.01 to 0.03). Temporal associations in GT were noted with breast cancer awareness month but not with other cancer awareness months and celebrity events.Conclusions: Cancer incidence is correlated with online search volume at the state level. Search patterns were temporally associated with cancer awareness months and celebrity announcements. Online searches reflect public awareness. Advancing understanding of online search patterns could augment traditional epidemiologic surveillance, provide opportunities for targeted patient engagement, and allow public information campaigns to be evaluated in ways previously unable to be measured. [ABSTRACT FROM AUTHOR]