Clinical drug investigation · 2020
Data Mining for Adverse Events of Tumor Necrosis Factor-Alpha Inhibitors in Pediatric Patients: Tree-Based Scan Statistic Analyses of Danish Nationwide Health Data.
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Wintzell Viktor, Svanström Henrik, Melbye Mads, Ludvigsson Jonas F, Pasternak Björn, Kulldorff Martin
Аннотация
BACKGROUND AND OBJECTIVES: Tumor necrosis factor-alpha (TNF-α) inhibitors are efficacious and considered generally safe in adults. However, pediatric-specific safety evidence is scarce. The aim of this study was to screen for signals of previously unknown adverse events of TNF-α inhibitors in pediatric patients.
METHODS: We conducted a data-mining study based on routinely collected, nationwide Danish healthcare data for 2004-2016. Using tree-based scan statistics to identify events with unexpectedly high incidence during TNF-α inhibitor use among patients with inflammatory bowel disease or juvenile idiopathic arthritis, two analyses were performed: comparison with episodes of no use and with other time periods from the same patient. Based on incident physician-assigned diagnosis codes from outpatient and inpatient visits in specialist care, we screened thousands of potential adverse events while adjusting for multiple testing.
RESULTS: We identified 1310 episodes of new TNF-α inhibitor use that met the eligibility criteria. Two signals of adverse events of TNF-α inhibitors, as compared with no use, were detected. First, there were excess events of dermatologic complications (ICD-10: L00-L99, 87 vs. 44 events, risk difference [RD] 3.3%), which have been described previously in adults and children. Second, there were excess events of psychiatric diagnosis adjustment disorders (ICD-10: F432, 33 vs. 7 events, RD 2.0%), which was likely associated with the underlying disease and its severity, rather than with the treatment. The self-controlled analysis generated no signal.
CONCLUSIONS: No signals of previously unknown adverse events of TNF-α inhibitors in pediatric patients were detected. The study showed that real-world data and newly developed methods for adverse events data mining can play a particularly important role in pediatrics where pre-approval drug safety data are scarce.
METHODS: We conducted a data-mining study based on routinely collected, nationwide Danish healthcare data for 2004-2016. Using tree-based scan statistics to identify events with unexpectedly high incidence during TNF-α inhibitor use among patients with inflammatory bowel disease or juvenile idiopathic arthritis, two analyses were performed: comparison with episodes of no use and with other time periods from the same patient. Based on incident physician-assigned diagnosis codes from outpatient and inpatient visits in specialist care, we screened thousands of potential adverse events while adjusting for multiple testing.
RESULTS: We identified 1310 episodes of new TNF-α inhibitor use that met the eligibility criteria. Two signals of adverse events of TNF-α inhibitors, as compared with no use, were detected. First, there were excess events of dermatologic complications (ICD-10: L00-L99, 87 vs. 44 events, risk difference [RD] 3.3%), which have been described previously in adults and children. Second, there were excess events of psychiatric diagnosis adjustment disorders (ICD-10: F432, 33 vs. 7 events, RD 2.0%), which was likely associated with the underlying disease and its severity, rather than with the treatment. The self-controlled analysis generated no signal.
CONCLUSIONS: No signals of previously unknown adverse events of TNF-α inhibitors in pediatric patients were detected. The study showed that real-world data and newly developed methods for adverse events data mining can play a particularly important role in pediatrics where pre-approval drug safety data are scarce.