Rates of laboratory adverse events by course in paediatric leukaemia ascertained with automated electronic health record extraction: a retrospective cohort study from the Children's Oncology Group.

Background: Adverse events are often misreported in clinical trials, leading to an incomplete understanding of toxicities. We aimed to test automated laboratory adverse event ascertainment and grading (via the ExtractEHR automated package) to assess its scalability and define adverse event rates for children with acute myeloid leukaemia and acute lymphoblastic leukaemia.

Methods: For this retrospective cohort study from the Children's Oncology Group (COG), we included patients aged 0-22 years treated for acute myeloid leukaemia or acute lymphoblastic leukaemia at Children's Healthcare of Atlanta (Atlanta, GA, USA) from Jan 1, 2010, to Nov 1, 2018, at the Children's Hospital of Philadelphia (Philadelphia, PA, USA) from Jan 1, 2011, to Dec 31, 2014, and at the Texas Children's Hospital (Houston, TX, USA) from Jan 1, 2011, to Dec 31, 2014.

Accuracy of Adverse Event Ascertainment in Clinical Trials for Pediatric Acute Myeloid Leukemia.

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.

Meta-analysis of multiple microarray datasets reveals a common gene signature of metastasis in solid tumors.

Background: Metastasis is the number one cause of cancer deaths. Expression microarrays have been widely used to study metastasis in various types of cancer. We hypothesize that a meta-analysis of publicly available gene expression datasets in various tumor types can identify a signature of metastasis that is common to multiple tumor types.