Layering strategy-based adverse drug reaction data shadowing effect eliminating method

Abstract

The invention discloses a layering strategy-based adverse drug reaction data shadowing effect eliminating method. According to the method, a data shadowing effect eliminating method is researched in adverse drug reaction signal detection on the basis of the adverse drug reaction report data of China, so that a layering strategy-based adverse drug reaction data shadowing effect eliminating model isdesigned; the data are layered on the whole according to the frequencies of the presence of drugs, adverse reactions and drug-adverse reaction pairs in the report data; and data detection is performed on the layered data through adopting an IC method. According to the invention, reports in which the frequencies of the presence of the drugs, adverse reactions and drug-adverse reaction pairs belongto the same order of magnitude are grouped into the same layer, so that the problem of data shadowing effects caused by excessively large difference of the frequencies of the presence of the drugs, adverse reactions and drug-adverse reaction pairs can be solved, and therefore, the data shadowing effects can be eliminated. With the method of the invention adopted, suspicious signals in the adversedrug reaction reports can be the accurately and reliably detected. The method has important reference significance in clinical care and drug supervision links.

Description

technical field [0001] The invention belongs to the field of signal detection, and in particular relates to a method for eliminating data masking effects in signal detection of adverse drug reactions in my country based on a layering strategy. Background technique [0002] At present, with the improvement of people's living standards, people pay more and more attention to drug safety issues while paying attention to medical drugs. The research on the detection of adverse drug reaction signals at home and abroad began in the 1950s with the "reaction stop" incident. my country's signal detection work mainly collects ADR data through the China Spontaneous Reporting Database and conducts data mining on the collected massive monitoring data. A widely used method in the field of signal detection is the disproportion measurement method, which is based on a four-table table and calculates the disequilibrium of the data distribution in the database. However, due to the existence of...

AI Technical Summary

Problems solved by technology

However, due to the existence of the shadowing effect, the signal detection of the data based on the disproportionate measurement theory cannot dig out the potential connection between the drug and the adverse reaction, so it is necessary to adopt a certain strategy to eliminate the shadowing effect

[0003] Regarding the elimination of the data masking effect in the detection of adverse drug reaction signals, domestic and foreign scholars have done some related research, mainly using methods based on data removal, regression methods based on mathematical models, and covariate stratification methods. Due to the characteristics of a large number of missed reports, false positives, and numerous report combinations in my country's ADR data, a unified method has not yet been formed in the field of data masking effect elimination for adverse drug reactions in my country. How to remove the masking effect to improve the accuracy of signal detection is currently an issue. Research Hot Issues

Images