# A modified quality control protocol for infectious disease serology based on the Westgard rules

## TL;DR

This paper introduces an asymmetric quality control protocol for infectious disease serology to reduce false rejections compared to traditional methods.

## Contribution

The novel asymmetric protocol uses different control limits for negative and positive QC data to lower false rejection rates.

## Key findings

- Protocol 1 had a higher rejection rate, especially after reagent lot changes.
- False rejections were more common in negative QC data, with a total Pfr of 27–65%.
- The asymmetric protocol reduced the proportion of analytes with Pfr by over 20%.

## Abstract

When traditional statistical quality control protocols, represented by the Westgard protocol were applied to infectious disease serology, the rejection limits were questioned because of the high rejection probability. We first define the probability of false rejection (Pfr) and error detection (Ped) for infectious disease serology. QC data in 6 months were collected and the Pfr of each rule in the Westgard protocol and Rilibak protocol was evaluated. Then, as improvements, we chose different rules for negative and positive QC data to constitute an asymmetric protocol, furthermore, while reagent lot changes, the mean value of QC protocol is reset with the first 15 QC results of new lot reagent. QC materials and Standard Reference Materials were tested synchronously in the next 6 months, to verify whether the Pfr and Ped of the asymmetric protocol could meet the requirement. Protocol 1 exhibited the higher level of rejection rate among the two protocols, especially after reagent lot changes; Pfr below the lower control limit (LCL) was 1.39–21.78 times higher than the upper control limit (UCL); false rejections were more likely to occur in negative QC data, with Pfr-total of 27–65%. The asymmetric protocol can significantly reduce the proportion of analytes with Pfr by over 20%. Systematic error due to reagent lot changes and random error due to routine QC data variation were considered potential factors for excessive Pfr. Asymmetric QC protocol that can reduce Pfr by different control limits for negative and positive QC data.