Endotoxin-Like Reactions With Intravenous Gentamicin Results From Pharmacovigilance Tools Under Investigation

2005 ◽  
Vol 26 (4) ◽  
pp. 391-394 ◽  
Author(s):  
Manfred Hauben ◽  
Lester Reich

AbstractObjective:To apply two data mining algorithms (DMAs) to Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) reports that involved endotoxin-like reactions with intravenous gentamicin to determine whether a signal of disproportionate reporting of these events would have been generated concurrently with surveillance based on clinical observation.Design:Multi-item gamma-Poisson shrinker (MGPS) and proportional reporting ratios (PRRs) were used. Data used for data mining consisted of an extract of the FDA AERS database. Previously published details of clusters of endotoxin-like reactions to intravenous gentamicin were used to select adverse events for data mining.Results:The first signal of disproportionate reporting with any relevant event occurred in 1998, the year in which the outbreak was identified and evaluated by the Centers for Disease Control and Prevention and the FDA. In 1997, there were only 6 reports of rigors in the AERS; this jumped to 68 in 1998. In 1998, a signal was generated for endotoxic shock with PRRs but not with MGPS, based on one case.Conclusions:The two DMAs generated signals concurrently with the influx of reports. It would have been difficult for safety reviewers to ignore an increase in rigors by traditional methods of safety surveillance; therefore, DMAs might not have had a great deal to offer in this instance. If data mining were considered as a second-line defense to diligent clinical observations under similar circumstances, simple disproportionality methods such as PRRs might be more useful than DMAs such as MGPS when commonly cited thresholds are used.

2019 ◽  
Vol 14 (1) ◽  
pp. 21-26 ◽  
Author(s):  
Viswam Subeesh ◽  
Eswaran Maheswari ◽  
Hemendra Singh ◽  
Thomas Elsa Beulah ◽  
Ann Mary Swaroop

Background: The signal is defined as “reported information on a possible causal relationship between an adverse event and a drug, of which the relationship is unknown or incompletely documented previously”. Objective: To detect novel adverse events of iloperidone by disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs). Methodology: The US FAERS database consists of 1028 iloperidone associated Drug Event Combinations (DECs) which were reported from 2010 Q1 to 2016 Q3. We consider DECs for disproportionality analysis only if a minimum of ten reports are present in database for the given adverse event and which were not detected earlier (in clinical trials). Two data mining algorithms, namely, Reporting Odds Ratio (ROR) and Information Component (IC) were applied retrospectively in the aforementioned time period. A value of ROR-1.96SE>1 and IC- 2SD>0 were considered as the threshold for positive signal. Results: The mean age of the patients of iloperidone associated events was found to be 44years [95% CI: 36-51], nevertheless age was not mentioned in twenty-one reports. The data mining algorithms exhibited positive signal for akathisia (ROR-1.96SE=43.15, IC-2SD=2.99), dyskinesia (21.24, 3.06), peripheral oedema (6.67,1.08), priapism (425.7,9.09) and sexual dysfunction (26.6-1.5) upon analysis as those were well above the pre-set threshold. Conclusion: Iloperidone associated five potential signals were generated by data mining in the FDA AERS database. The result requires an integration of further clinical surveillance for the quantification and validation of possible risks for the adverse events reported of iloperidone.


Blood ◽  
2010 ◽  
Vol 116 (12) ◽  
pp. 2127-2133 ◽  
Author(s):  
Jessica A. Reese ◽  
Xiaoning Li ◽  
Manfred Hauben ◽  
Richard H. Aster ◽  
Daniel W. Bougie ◽  
...  

Abstract Drug-induced immune thrombocytopenia (DITP) is often suspected in patients with acute thrombocytopenia unexplained by other causes, but documenting that a drug is the cause of thrombocytopenia can be challenging. To provide a resource for diagnosis of DITP and for drug safety surveillance, we analyzed 3 distinct methods for identifying drugs that may cause thrombocytopenia. (1) Published case reports of DITP have described 253 drugs suspected of causing thrombocytopenia; using defined clinical criteria, 87 (34%) were identified with evidence that the drug caused thrombocytopenia. (2) Serum samples from patients with suspected DITP were tested for 202 drugs; drug-dependent, platelet-reactive antibodies were identified for 67 drugs (33%). (3) The Food and Drug Administration's Adverse Event Reporting System database was searched for drugs associated with thrombocytopenia by use of data mining algorithms; 1444 drugs had at least 1 report associated with thrombocytopenia, and 573 (40%) drugs demonstrated a statistically distinctive reporting association with thrombocytopenia. Among 1468 drugs suspected of causing thrombocytopenia, 102 were evaluated by all 3 methods, and 23 of these 102 drugs had evidence for an association with thrombocytopenia by all 3 methods. Multiple methods, each with a distinct perspective, can contribute to the identification of drugs that can cause thrombocytopenia.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaojiang Tian ◽  
Yao Yao ◽  
Guanglin He ◽  
Yuntao Jia ◽  
Kejing Wang ◽  
...  

AbstractThis current investigation was aimed to generate signals for adverse events (AEs) of darunavir-containing agents by data mining using the US Food and Drug Administration Adverse Event Reporting System (FAERS). All AE reports for darunavir, darunavir/ritonavir, or darunavir/cobicistat between July 2006 and December 2019 were identified. The reporting Odds Ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN) were used to detect the risk signals. A suspicious signal was generated only if the results of the three algorithms were all positive. A total of 10,756 reports were identified commonly observed in hepatobiliary, endocrine, cardiovascular, musculoskeletal, gastrointestinal, metabolic, and nutrition system. 40 suspicious signals were generated, and therein 20 signals were not included in the label. Severe high signals (i.e. progressive extraocular muscle paralysis, acute pancreatitis, exfoliative dermatitis, acquired lipodystrophy and mitochondrial toxicity) were identified. In pregnant women, umbilical cord abnormality, fetal growth restriction, low birth weight, stillbirth, premature rupture of membranes, premature birth and spontaneous abortion showed positive signals. Darunavir and its boosted agents induced AEs in various organs/tissues, and were shown to be possibly associated with multiple adverse pregnant conditions. This study highlighted some novel and severe AEs of darunavir which need to be monitored prospectively.


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