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. The ExtractEHR automated package acquired, cleaned, and graded laboratory data as per Common Terminology Criteria for Adverse Events (CTCAE) version 5 for 22 commonly evaluated grade 3-4 adverse events (fatal events were not evaluated) with numerically based CTCAE definitions. Descriptive statistics tabulated adverse event frequencies. Adverse events ascertained by ExtractEHR were compared to manually reported adverse events for patients enrolled in two COG trials (AAML1031, NCT01371981; AALL0932, NCT02883049). Analyses were restricted to protocol-defined chemotherapy courses (induction I, induction II, intensification I, intensification II, and intensification III for acute myeloid leukaemia; induction, consolidation, interim maintenance, delayed intensification, and maintenance for acute lymphoblastic leukaemia). FINDINGS: Laboratory adverse event data from 1077 patients (583 from Children's Healthcare of Atlanta, 200 from the Children's Hospital of Philadelphia, and 294 from the Texas Children's Hospital) who underwent 4611 courses (549 for acute myeloid leukaemia and 4062 for acute lymphoblastic leukaemia) were extracted, processed, and graded. Of the 166 patients with acute myeloid leukaemia, 86 (52%) were female, 80 (48%) were male, 96 (58%) were White, and 132 (80%) were non-Hispanic. Of the 911 patients with acute lymphoblastic leukaemia, 406 (45%) were female, 505 (55%) were male, 596 (65%) were White, and 641 (70%) were non-Hispanic. Patients with acute myeloid leukaemia had the most adverse events during induction I and intensification II. Hypokalaemia (one [17%] of six to 75 [48%] of 156 courses) and alanine aminotransferase (ALT) increased (13 [10%] of 134 to 27 [17%] of 156 courses) were the most prevalent non-haematological adverse events in patients with acute myeloid leukaemia, as identified by ExtractEHR. Patients with acute lymphoblastic leukaemia had the greatest number of adverse events during induction and maintenance (eight adverse events with prevalence ≥10%; induction and maintenance: anaemia, platelet count decreased, white blood cell count decreased, neutrophil count decreased, lymphocyte count decreased, ALT increased, and hypocalcaemia; induction: hypokalaemia; maintenance: aspartate aminotransferase [AST] increased and blood bilirubin increased), as identified by ExtractEHR. 187 (85%) of 220 total comparisons in 22 adverse events in four AAML1031 and six AALL0923 courses were substantially higher with ExtractEHR than COG-reported adverse event rates for adverse events with a prevalence of at least 2%. INTERPRETATION: ExtractEHR is scalable and accurately defines laboratory adverse event rates for paediatric acute leukaemia; moreover, ExtractEHR seems to detect higher rates of laboratory adverse events than those reported in COG trials. These rates can be used for comparisons between therapies and to counsel patients treated on or off trials about the risks of chemotherapy. ExtractEHR-based adverse event ascertainment can improve reporting of laboratory adverse events in clinical trials. FUNDING: US National Institutes of Health, St Baldrick's Foundation, and Alex's Lemonade Stand Foundation.

Genomic decision support needs in pediatric primary care.

Clinical genome and exome sequencing can diagnose pediatric patients with complex conditions that often require follow-up care with multiple specialties. The American Academy of Pediatrics emphasizes the role of the medical home and the primary care pediatrician in coordinating care for patients who need multidisciplinary support. In addition, the electronic health record (EHR) with embedded clinical decision support is recognized as an important component in providing care in this setting. We interviewed 6 clinicians to assess their experience caring for patients with complex and rare genetic findings and hear their opinions about how the EHR currently supports this role. Using these results, we designed a candidate EHR clinical decision support application mock-up and conducted formative exploratory user testing with 26 pediatric primary care providers to capture opinions on its utility in practice with respect to a specific clinical scenario. Our results indicate agreement that the functionality represented by the mock-up would effectively assist with care and warrants further development.