Time to address quality control processes applied to antibody testing for infectious diseases

Sigma metrics analysis of serology screening assays to enhance quality and efficiency in New Zealand blood services

Sigma metric analysis was conducted across two New Zealand Blood Services (NZBS) laboratories (Auckland and Christchurch) to optimize quality control (QC) procedures. We evaluated five assays (anti-HCV, HIV Ag/Ab combo, HTLV-I/II, HBsAg, and Syphilis) using internal quality control (IQC) and third-party daily QC data extracted from four Architect i2000SR instruments during Jan 2 -31st, 2023. Mean, standard deviation (SD), and coefficient of variation (CV%) were calculated, assuming zero bias. Sigma metrics were determined using the Total Allowable Error (TEa %) based on difference between positive control mean and signal-to-cutoff (s/co) cut-off. Most assays exhibited CV% values ≤10 % except for HBsAg IQC (18.5 %) and anti-HCV third-party QC (13.4 %) at Christchurch. TEa % ranged from 38 % to 90 %. Overall, the assays demonstrated Six Sigma performance (σ > 6), except for HBsAg IQC (3.97) and anti-HCV third-party QC (5.46) at Christchurch. These high-quality serology assays can benefit from simplified QC design without compromising blood safety.

Quality control for serological testing

OBJECTIVES

The quality control of serological assays remains controversial. The aim of this project was to describe the problems associated with a working model for controlling these assays and solutions, including using a source of well-defined targets and acceptable limits, a process to identify lot-to-lot reagent variation and an interpretation of the result that accounted for the clinical situation. False-negative results are problematic but can be reduced by identifying and comparing reagent lot variation with previous results.

METHODS

The components of the Quality Assurance strategy are the following: Lot-to-lot reagent and calibrator variation assessment; dynamic, big-data approach to determine accurate targets and acceptable limits for manufacturer-provided QC material; negative QC monitoring process; use of commutable EQA with a sufficient method subgroup size to assess bias; clinical assessment of any statistically flagged error; and provision of support to the clinician for the interpretation of results.

RESULTS

The model described has been used for twelve months, and acceptable variation has been maintained.

CONCLUSIONS

The paper presents a solution that emphasizes the early detection of reagent lot variation and patient risk rather than instrument control. Reducing the risk of a false result to patients requires optimal assay quality control and an effective mechanism to support the clinician's use of these results in diagnosis and monitoring. The problems of serological assays are well-known, but there remain few integrated solutions in the literature.

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

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.

Clinical Chemistry and Laboratory Medicine celebrates 60 years – narrative review devoted to the contribution of the journal to the diagnosis of SARS-CoV-2

This review is an integral part of the special issue for the 60 years of the journal Clinical Chemistry and Laboratory Medicine (CCLM). The aim of the review is to highlight the role of the clinical laboratory since the emergence of the “severe acute respiratory syndrome coronavirus 2” (SARS-CoV-2), which causes Coronavirus disease 2019 (COVID-19), with special focus on the contribution of the journal in generating knowledge in SARS-CoV-2 diagnosis. As of October 30, 2022, a total of 186 CCLM publications were dedicated to COVID-19. Of importance, major International Federation of Clinical Chemistry (IFCC) guidelines related to the diagnosis of COVID-19 were published in CCLM. Between early-2020 and late October 2022, COVID-19 publications represented around 27% of all articles in CCLM, highlighting the willingness of the editorial board to help the field in order to better describe and diagnose this new emerging disease. First launched in 1963 under the name “Zeitschrift für Klinische Chemie”, the Journal was entirely devoted to clinical chemistry in the strict sense. The various topics published in relation to COVID-19 including its diagnosis, its impact on biochemical or hematological measures, as well as biosafety measures, is the perfect example that shows that the journal has greatly diversified over time.