A strong signal screening method for adverse reaction signals of SRS combination drug

Abstract

The invention discloses a strong signal screening method for SRS combined drug adverse reaction signals, comprising: acquiring data through the spontaneous drug adverse event reporting system SRS, and obtaining combined drug adverse reaction signal set X={D 1 ,D 2 ,...,D x},D x is the drug combination judged as an adverse reaction signal; assuming that the signal exclusion set in the t-th cycle is Y t , then select the signal D with the largest current signal metric st As a strong signal, and put the signal into the signal exclusion set Y t Form a new signal exclusion set Y t+1 , and then start the t+1th round of circulation, and so on, to get the set of signals with the largest signal metric in each round of circulation, that is, the strong signal set S={D s1 ,D s2 ,...,D st}, screen out strong signals with significant case data basis from a large number of combined drug adverse reaction signals, which improves the quality of signal recommendation.

Description

technical field [0001] The invention relates to the technical field of signal screening, in particular to a strong signal screening method for SRS combined drug adverse reaction signals, where SRS stands for Spontaneous Reporting System of Drug Adverse Events. Background technique [0002] Limited by factors such as the scope of the experiment, research objects, and time, it is impossible to complete all combined drug interaction studies in the pre-marketing stage. Many potential drug interactions are only discovered after the drug is used on a large scale and for a long time after it is marketed. Spontaneous Reporting System (SRS) provides an important data source for post-marketing drug interaction signal screening. For example, the US FDA Adverse Event Reporting System (FDA Adverse Event Reporting System, FAERS), etc., truly reflects the complexity of drug safety in real life. According to the survey, 60% of the adverse event reports in the patient’s drug use are more tha...

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