UCSF

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 Childrens Oncology Group (COG), we included patients aged 0-22 years treated for acute myeloid leukaemia or acute lymphoblastic leukaemia at Childrens Healthcare of Atlanta (Atlanta, GA, USA) from Jan 1, 2010, to Nov 1, 2018, at the Childrens Hospital of Philadelphia (Philadelphia, PA, USA) from Jan 1, 2011, to Dec 31, 2014, and at the Texas Childrens 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 Childrens Healthcare of Atlanta, 200 from the Childrens Hospital of Philadelphia, and 294 from the Texas Childrens 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 Baldricks Foundation, and Alexs Lemonade Stand Foundation.