Detecting Drugs That Cause Thrombocytopenia: A Comparison of Three Methods: Tests for Drug-Dependent Anti-Platelet Antibodies (DDab), Published Case Reports, and Data Mining of the US FDA Adverse Event Reporting System (AERS) Database.
Authors: Li Xiaoning , Aster Richard H. , Curtis Brian R. , Bougie Daniel W. , Vesely Sara K. , George James N. 
Published: April 2020

Acute thrombocytopenia is one of the most common serious adverse reactions to drugs and can be caused by many drugs. For evaluation of unexpected thrombocytopenia, it is important to know the relative risks of thrombocytopenia among the patient’s current medications. However identification of drugs that can cause thrombocytopenia is not standardized; multiple distinct methods are used:

detection of drug-dependent antibodies, analysis of published case reports to establish the level of evidence for the drug as a cause of thrombocytopenia (http://moon.ouhsc.edu/jgeorge), and reporting to MedWatch, the FDA AERS. We have previously compared drugs that had “definite” or “probable” evidence for causing thrombocytopenia in published reports to drugs that had a significant association with thrombocytopenia determined by data mining of the FDA AERS database, defined as a signal of disproportionate reporting (SDR) that exceeded a standard predetermined value (Li, et al. Blood2006;108:140a).

We have now expanded our analysis to include flow cytometry detection of DDab in the serum of patients with suspected drug-induced thrombocytopenia. 401 drugs have been suspected as a cause of thrombocytopenia by serum samples submitted for identification of DDab and in case reports. All 401 drugs, including drugs that were and were not shown to be associated with DDab and also drugs that did or did not have “definite” or “probable” evidence for causing thrombocytopenia in case reports, were searched for in the AERS database using a data mining algorithm to identify a significant association with thrombocytopenia. In this analysis, drugs that were not reported in a publication, were not tested for DDab, or were not found in the AERS database were coded as not significant for that method. 204 (51%) of the 401 drugs were significantly associated with thrombocytopenia by 1 or more methods; DDab identified 12% (47), case reports 19% (75), and data mining 36% (143). However, there was limited agreement among these 3 methods for identifying a significant association with thrombocytopenia.

Significant by all 3 methods 13 drugs (3%) Significant by any 2 methods 35 drugs (9%) Significant only by detection of DDab 21 drugs (5%) Significant only by case reports 39 drugs (10%) Significant only by data mining 96 drugs (24%) Not significant by any of the 3 methods 197 drugs (49%)

None of the 3 methods are sufficient to identify all drugs capable of causing thrombocytopenia. Data mining is a screening tool of existing data and therefore may be more sensitive but less specific than demonstration of DDab and reported clinical evidence. Reports to MedWatch are simple to submit but the reliability is uncertain. Critical assessment of clinical evidence from published case reports may be more specific for identifying drugs that can cause thrombocytopenia, but substantial effort is required to publish a case report. Detection of DDab specifically identifies drugs that can cause thrombocytopenia and also provides understanding of the biologic mechanisms, but tests for DDab are not standardized in routine clinical laboratories.

Conclusions. Use of multiple approaches is important to enhance post-marketing surveillance and to provide a comprehensive understanding of drug-induced thrombocytopenia.