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. 2016 May 1;34(13):1537-43.
doi: 10.1200/JCO.2015.65.5860. Epub 2016 Feb 16.

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

Affiliations

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

Tamara P Miller et al. J Clin Oncol. .

Abstract

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.

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Conflict of interest statement

Authors' disclosures of potential conflicts of interest are found in the article online at www.jco.org. Author contributions are found at the end of this article.

Figures

Fig 1.
Fig 1.
Pyramid plot of average number of grade 3 to 5 adverse events per patient compared between AAML03P1 and AAML0531 arm B. Red bars indicate targeted toxicities in AAML03P1 and/or AAML0531 arm B. An infection case reporting form was created for AAML0531 and was required to be completed as part of the Common Terminology Criteria for Adverse Events submission for reporting of bloodstream infections on the clinical trial.
Fig 2.
Fig 2.
Adverse event (AE) definition complexity and work required to ascertain AEs. Pink shading indicates AEs that could be electronically captured; yellow shading indicates AEs that could be electronically captured, but may need manual review to verify grading; blue shading indicates AEs that can be triggered for review electronically, but would need manual review for ascertainment and grading; italics indicate AEs that were not included in chart abstraction, but were commonly reported in cooperative group acute myeloid leukemia clinical trials as shown in Figure 1. AE definition complexity is based on a combination of the ease of interpretation of the Common Terminology Criteria for Adverse Events (CTCAE) definition and the clinical complexity of the AE. AKI, acute kidney injury; ARDS, adult respiratory distress syndrome; DIC, disseminated intravascular coagulation; IFI, invasive fungal infection; VGS, viridans group streptococci. (*)CTCAE version 4, which is currently used, does not include acute renal failure, which is a clinically defined toxicity on the basis of use of dialysis, but instead includes acute kidney injury, which is a laboratory-based toxicity defined by creatinine level, except for grade 4, which requires the patient to receive dialysis.

Comment in

References

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