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Detection of Drug-Induced Thrombocytopenia Signals in Children Using Routine Electronic Medical Records
Xiaolu Nie1,2, Lulu Jia3, Xiaoxia Peng2
1Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Insights
This study developed a two-stage model using electronic medical records to detect drug-induced thrombocytopenia (DITP) in children. The model identified 18 DITP associations, including six novel signals, improving pediatric pharmacovigilance.
Area of Science:
- Pharmacovigilance
- Pediatric Pharmacology
- Data Mining
Background:
- Drug-induced thrombocytopenia (DITP) is a severe, under-recognized adverse drug reaction in children.
- Effective post-marketing pharmacovigilance is crucial for detecting DITP signals.
- Electronic medical records (EMR) offer a valuable resource for signal detection.
Purpose of the Study:
- To develop and validate a signal detection model for DITP using pediatric EMR data.
- To identify potential drug-causative agents of thrombocytopenia in children.
- To enhance the safety monitoring of medications in pediatric populations.
Main Methods:
- Utilized a two-stage modeling approach on EMR data from Beijing Children's Hospital (2009-2020).
- Stage 1: Calculated crude incidence to screen potential drugs causing thrombocytopenia.
- Stage 2: Employed propensity score-matched cohorts and conditional logistic regression to assess drug-specific DITP risk (OR, 95% CI).
Main Results:
- Screened 839 drugs, identifying 21 potential candidates for DITP.
- Confirmed 18 positive DITP associations.
- Identified two novel DITP signals (nystatin, latamoxef sodium) in both children and adults, and six new signals in children (imipenem, teicoplanin, fusidic acid, ceftizoxime sodium, ceftazidime, cefepime).
Conclusions:
- A two-stage algorithm effectively detects DITP safety signals in pediatric EMR data.
- Eighteen DITP associations were identified, including six novel signals specific to the pediatric population.
- This EMR-based method shows promise as a tool for pediatric pharmacovigilance.
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.
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