Abstract
Background: Drug-induced thrombocytopenia (DITP) is a severe adverse reaction and a significantly under-recognized clinical problem in children. However, for post-marketing pharmacovigilance purposes, detection of DITP signals is crucial. This study aimed to develop a signal detection model for DITP using the pediatric electronic medical records (EMR) data. Methods: This study used the electronic medical records collected at Beijing Children’s Hospital between 2009 and 2020. A two-stage modeling method was developed to detect the signal of DITP. In the first stage, we calculated the crude incidence by mining cases of thrombocytopenia to select the potential suspected drugs. In the second stage, we constructed propensity score–matched retrospective cohorts of specific screened drugs from the first stage and estimated the odds ratio (OR) and 95% confidence interval (CI) using conditional logistic regression models. The novelty of the signal was assessed by current evidence. Results: In the study, from a total of 839 drugs, 21 drugs were initially screened as potentially inducing thrombocytopenia. In total, we identified 18 positive DITP associations. Of these, potential DITP risk of nystatin (OR: 1.75, 95% CI: 1.37–2.22) and latamoxef sodium (OR: 1.61, 95% CI: 1.38–1.88) were two new DITP signals in both children and adults. Six associations between thrombocytopenia and drugs including imipenem (OR: 1.69, 95% CI: 1.16–2.45), teicoplanin (OR: 4.75, 95% CI: 3.33–6.78), fusidic acid (OR: 2.81, 95% CI: 2.06–3.86), ceftizoxime sodium (OR: 1.83, 95% CI: 1.36–2.45), ceftazidime (OR: 2.16, 95% CI: 1.58–2.95), and cefepime (OR: 5.06, 95% CI: 3.77–6.78) were considered as new signals in children. Conclusion: This study developed a two-stage algorithm to detect safety signals of DITP and found eighteen positive signals of DITP, including six new signals in a pediatric population. This method is a promising tool for pharmacovigilance based on EMR data.
Highlights
Drug-induced thrombocytopenia (DITP) is an adverse reaction and a significantly under-recognized clinical problem
Our study found eighteen positive signals of DITP, including six new signals in a pediatric population
This crucial additional step increased the efficiency and speed of subsequent steps. More complicated confounders, such as relevant diagnoses with clear competing causes and medications that may affect the level of relevant laboratory indicators, were excluded to enhance the reliability and accuracy of the results. These results suggested that our method is a valuable tool to facilitate earlier signal detection using routinely collected electronic medical records (EMR) data
Summary
Drug-induced thrombocytopenia (DITP) is an adverse reaction and a significantly under-recognized clinical problem. It has been reported that more than 300 medications, including antibiotics (Butt et al, 2019; Savage-Elliott et al, 2020), neurological drugs (Kim et al, 2020), and antineoplastic agents (Tam et al, 2019), could lead to DITP in the adult population. Drugs may induce more severe adverse reactions in children, and the relative evidence from adults could not directly apply to the pediatric population. Accurate methods for post-marketing drug safety surveillance and signal detection of DITP in children are urgently needed (Reese et al, 2013). Drug-induced thrombocytopenia (DITP) is a severe adverse reaction and a significantly under-recognized clinical problem in children. This study aimed to develop a signal detection model for DITP using the pediatric electronic medical records (EMR) data
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