Methods

Data sources

Obtain ASCII data packages from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) for case reports from the first quarter of 2004 to the fourth quarter of 2022, which are divided into seven tables, including patient demographic information (DEMO), drug information (DRUG), reported indications for drug use (INDI), treatment start and end dates (HER), and adverse events (REAC), Adverse event outcome (OUTC) and reporting source (RPSR). Import data cleaning and signal mining into SAS9.4 software. Using the common names of acyclovir, valacyclovir, ganciclovir and famciclovir to retrieve the obtained data, and obtain the ADR report records of the first suspected drugs.

Disproportionality analysis

Exclude duplicate reports, information uncertainty reports, and other reports containing abnormal information from the standardized data, and filter out data with a number of reports ≥ 3. According to the four grid table (Table 1), calculate the corresponding ROR, PRR, IC, and the corresponding 95% confidence interval (CI) lower limit, and count the number of signals to exclude reports that do not meet the threshold requirements. The larger the lower 95% CI limit of the ROR value, the stronger the signal, indicating a stronger connection between the target drug and the target ADR. In this study, in order to overcome the high false positive rate caused by estimation errors in traditional frequency methods to some extent, we chose signals that meet the standards of the three algorithms mentioned above for research. The criteria for determining the signal strength of the BCPNN method are: ① no signal (-): IC ≤ 0; ② Signal weak (+): 0 < IC ≤ 1.5; ③ In the signal (++): 1.5 < IC ≤ 3; ④ Signal strength (+++): IC>3.