Purpose Reporting of adverse events (AEs) in clinical trials is critical to understanding treatment safety, but data on AE accuracy are limited. This study sought to determine the accuracy of AE reporting for pediatric acute myeloid leukemia clinical trials and to test whether an external electronic data source can improve reporting. Methods Reported AEs were evaluated on two trials, Children’s Oncology Group AAML03P1 and AAML0531 arm B, with identical chemotherapy regimens but with different toxicity reporting requirements. Chart review for 12 AEs for patients enrolled in AAML0531 at 14 hospitals was the gold standard. The sensitivity and positive predictive values (PPV) of the AAML0531 AE report and AEs detected by review of Pediatric Health Information System (PHIS) billing and microbiology data were compared with chart data. Results Select AE rates from AAML03P1 and AAML0531 arm B differed significantly and correlated with the targeted toxicities of each trial. Chart abstraction was performed on 204 patients (758 courses) on AAML0531. AE report sensitivity was < 50% for eight AEs, but PPV was > 75% for six AEs. AE reports for viridans group streptococcal bacteremia, a targeted toxicity on AAML0531, had a sensitivity of 78.3% and PPV of 98.1%. PHIS billing data had higher sensitivity (> 50% for nine AEs), but lower PPV (< 75% for 10 AEs). Viridans group streptococcal detection using PHIS microbiology data had high sensitivity (92.3%) and PPV (97.3%). Conclusion The current system of AE reporting for cooperative oncology group clinical trials in pediatric acute myeloid leukemia underestimates AE rates. The high sensitivity and PPV of PHIS microbiology data suggest that using external data sources may improve the accuracy of AE reporting.

Background Although corticosteroids remain a mainstay of treatment for acute lymphoblastic leukemia (ALL), they can cause troublesome neurobehavioral changes during active treatment, especially in young children. We evaluated acute neurobehavioral side effects of corticosteroid therapy in preschool versus school-age children by obtaining structured reports weekly for one month. Procedure Parents of 62 children (2 to 17 years at diagnosis) treated on Dana-Farber Cancer Institute (DFCI) ALL Consortium Protocol 00-01 participated during the continuation phase of treatment. Patients received cyclical twice-daily 5-day courses of prednisone (40 mg/m2/day) or dexamethasone (6 mg/m2/day). Parents completed behavior rating scales about their child weekly during one steroid cycle [baseline (Day 0), active steroid (Day 7), post-steroid (Days 14 and 21)]. Results Behavioral side effects increased significantly (p < .001) during the steroid week for preschool children (< 6 years) on measures of emotional control, mood, behavior regulation, and executive functions, returning to baseline during the two ‘off-steroid’ weeks. In contrast, school-age children (≥ 6 years) did not demonstrate an increase in side effects during the steroid week. Steroid type (prednisone vs. dexamethasone) was not a significant predictor of neurobehavioral side effects. Conclusions Preschool children are at greater risk for neurobehavioral side effects during active steroid treatment for ALL than school age children and adolescents. Dexamethasone was not associated with more neurobehavioral side effects than prednisone. Counseling of families about side-effects should be adapted according to age. The observed effects, moreover, were transient, reducing concerns about longer-term neurobehavioral toxicities.

Background Pediatric oncology patients are at increased risk for invasive bacterial infection due to immunosuppression. The risk of such infection in the absence of severe neutropenia (absolute neutrophil count (ANC) ≥500/μl) is not well established and a validated prediction model for blood stream infection (BSI) risk offers clinical utility. Methods A six-site retrospective external validation was conducted using a previously published risk prediction model for BSI in febrile pediatric oncology patients without severe neutropenia, the Esbenshade/Vanderbilt (EsVan) model. A reduced model (EsVan2) excluding two less clinically reliable variables was also created using the initial EsVan model derivative cohort, and validated using all five external validation cohorts. One dataset was only used in sensitivity analyses due to missing some variables. Results From the five primary data sets, there were a total of 1197 febrile episodes and 76 episodes of bacteremia. The overall C-statistic for predicting bacteremia was 0.695 with a 0.50 calibration slope for the original model and 1.0 calibration slope when recalibration was applied to the model. The model performed better in predicting high-risk bacteremia (Gram negative or Staphylococcus aureus infection) versus BSI alone with a C-statistic of 0.801 and a calibration slope of 0.65. The EsVan2 model outperformed the EsVan model across datasets with a C-statistic 0.733 for predicting BSI and 0.841 for high-risk BSI. Conclusions This external validation shows that the EsVan and EsVan2 models are able to predict BSI across multiple performance sites and could assist in decision making in clinical practice once validated and implemented prospectively.

Black patients with acute myeloid leukemia (AML) experience higher mortality than White patients. We compared induction mortality, acuity of illness prior to chemotherapy, and insurance type between Black and White patients to assess whether acuity of presentation mediates the disparity. Within a retrospective cohort of 1,122 children with AML treated with two courses of standard induction chemotherapy between 2004 and 2014 in the Pediatric Health Information System (PHIS) database, the association between race (Black versus White) and inpatient mortality during induction was examined. Intensive Care Unit (ICU)-level resource utilization during the first 72 hours following admission for initial AML chemotherapy was evaluated as a potential mediator. The total effect of race on mortality during Induction I revealed a strong association (unadjusted HR 2.75, CI: 1.18, 6.41). Black patients had a significantly higher unadjusted risk of requiring ICU-level resources within the first 72 hours after initial presentation (17% versus 11%; RR 1.52, CI: 1.04, 2.24). Mediation analyses revealed the indirect effect of race through acuity accounted for 61% of the relative excess mortality during Induction I. Publicly insured patients experienced greater induction mortality than privately insured patients regardless of race. Black patients with AML have significantly greater risk of induction mortality and are at increased risk for requiring ICU-level resources soon after presentation. Higher acuity amongst Black patients accounts for a substantial portion of the relative excess mortality during Induction I. Targeting factors affecting acuity of illness at presentation may lessen racial disparities in AML induction mortality.

Background Adverse events (AEs) on Children's Oncology Group (COG) trials are reported manually by clinical research assistants (CRAs). The Common Terminology Criteria for Adverse Events (CTCAE) was developed to provide standardized definitions for identifying and grading AEs. The CTCAE has expanded significantly over its five versions, but the impact of CTCAE definitional changes has not been examined. Procedure This study compared AE number and ascertainment among the first four CTCAE versions using a case vignette. Each CTCAE version was used to create a list of AEs and grades by two separate CRAs. Results The CTCAE expanded from 9 categories and 49 AEs in v1.0 to 26 categories and 790 AEs in v4.0. CRAs independently selected different approaches to AE ascertainment—comprehensive and parsimonious. The number of AEs identified in the parsimonious approach was stable with 10–14 in each CTC version. The comprehensive approach identified 9, 20, 29, and 37 AEs in CTC versions 1.0, 2.0, 3.0, and 4.0, respectively. Only approximately 65% of AEs were conclusively graded in versions 2.0 to 4.0 using the comprehensive approach. Conclusions CTCAE has increased in complexity. Although this increased complexity allows for more granular AE reporting, these data demonstrate potential unintended negative consequences of increasing CTC AE complexity, including the risk of varying approaches to AE capture. A comprehensive evaluation of CTC AE definitions and CRA reporting practices across COG institutions and AEs are needed to improve the accuracy and efficiency of AE reporting.

SUMMARYCellularization of the Drosophila embryo is the process by which a syncytium of ~6000 nuclei is subdivided into discrete cells. In order to individualize the cells, massive membrane addition needs to occur by a process that is not fully understood. The exocyst complex is required for some, but not all, forms of exocytosis and plays a role in directing vesicles to appropriate domains of the plasma membrane. Sec5 is a central component of this complex and we here report the isolation of a new allele of sec5 that has a temperature-sensitive phenotype. Using this allele, we investigated whether the exocyst complex is required for cellularization. Embryos from germline clones of the sec5 ts1 allele progress normally through cycle 13. At cellularization, however, cleavage furrows do not invaginate between nuclei and consequently cells do not form. A zygotically translated membrane protein, Neurotactin, is not inserted into the plasma membrane and instead accumulates in cytoplasmic puncta. During cellularization, Sec5 becomes concentrated at the apical end of the lateral membranes, which is likely to be the major site of membrane addition. Subsequently, Sec5 concentrates at the sub-apical complex, indicating a role for Sec5 in the polarized epithelium. Thus, the exocyst is necessary for, and is likely to direct, the polarized addition of new membrane during this form of cytokinesis.

Summary 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.

Background A better understanding of drivers of treatment costs may help identify effective cost containment strategies and prioritize resources. We aimed to develop a method for estimating inpatient costs for pediatric patients with acute myeloid leukemia (AML) enrolled on NCI-funded Phase III trials, compare costs between AAML0531 treatment arms (standard chemotherapy ± gemtuzumab ozogamicin (GMTZ)), and evaluate primary drivers of costs for newly diagnosed pediatric AML. Procedure Patients from the AAML0531 trial were matched on hospital, sex, and dates of birth and diagnosis to the Pediatric Health Information Systems (PHIS) database to obtain daily billing data. Inpatient treatment costs were calculated as adjusted charges multiplied by hospital-specific cost-to-charge ratios. Generalized linear models were used to compare costs between treatment arms and courses, and by patient characteristics. Results Inpatient costs did not differ by randomized treatment arm. Costs varied by course with stem cell transplant being most expensive, followed by Intensification II (cytarabine/mitoxantrone) and Induction I (cytarabine/daunorubicin/etoposide). Room/board and pharmacy were the largest contributors to inpatient treatment cost, representing 74% of the total cost. Higher AML risk group (P = 0.0003) and older age (P < 0.0001) were associated with significantly higher daily inpatient cost. Conclusions Costs from external data sources can be successfully integrated into NCI-funded Phase III clinical trials. Inpatient treatment costs did not differ by GMTZ exposure but varied by chemotherapy course. Variation in cost by course was driven by differences in duration of hospitalization through room/board charges as well as increased clinical and pharmacy charges in specific courses. Pediatr Blood Cancer