Risk signal mining and analysis of apremilast based on database of FAERS
Objective The risk signals of apremilast were extracted from the Adverse Event Reporting System(FAERS)of the US Food and Drug Administration(FDA)to provide reference for the safety of clinical use.Methods Reporting Odds ratio method(ROR)and Bayesian confidence interval Progressive neural network(BCPNN)were used to conduct data mining and analysis of apremilast related adverse events(ADE)in the FAERS database from the first quarter of 2014 to the third quarter of 2023.Results A total of 70 075 ADE reports related to the apremilast were retrieved,the majority of patients were female(61.4% )and were concentrated between the ages of 18—65(34.6% ),with the main reporting countries being the United States(96.5% ).70 Positive signals were screened out,involving 12 systems and organs(SOC),mainly including gastrointestinal system diseases,nervous system disorders,psychiatric disorders,infections and infestations.The main PT that occur more frequently were diarrhea,nausea,headache,and abdominal discomfort,etc.The PT with high signal strength ranking included tension headaches,diarrhea,frequent bowel movements,faeces soft,abdominal discomfort and so on.38 New risk signals were found,including latent tuberculosis,gastroenteritis viral,ear infection,upper respiratory tract congestion and gout,etc.Conclusion During the use of apremilast,it is necessary to focus on the patient's gastrointestinal response and assess the patient's psychiatric status,as well as paying close attention to the patients with infection and renal insufficiency function,so as to guarantee the safety of treatment.
apremilastadverse drug eventsdata miningproportional imbalance methodlatent tuberculosisviral gastroenteritisear infection
NETL
NSTL
万方数据
维普
