Clinical biochemistry · 2026
Evidence-based extension of reagent shelf-life beyond expiry using patient-based moving averages, westgard sigma rules, and CLSI EP25.
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Khelil Mohamed Mokhtar, Badrick Tony
Аннотация
BACKGROUND: Reagent stability is a significant determinant of analytical reliability in clinical laboratories. Post-expiry reagent use is often discouraged due to the potential risk of systematic bias; however, empirical data supporting or refuting such restrictions are limited.
METHODS: This study evaluated the post-expiry performance of free T3 (FT3) and free T4 (FT4) immunoassays on the Abbott Architect i1000SR analyzer using an integrated framework combining three complementary approaches: (i) a simulation-optimized moving average (MA) model based on real patient data (ii) Westgard Sigma rules quality control, and (iii) Clinical and Laboratory Standards Institute EP25-A drift analysis. The MA was optimised via Monte Carlo simulations using a step-shift bias model, which defined the optimal window size (N) for 90% detection power and 0% false rejection rate. Stability was then assessed across three reagent lots per analyte, spanning both pre- and post-expiration phases.
RESULTS: Westgard rules provided the earliest analytical alerts, while EP25 confirmed sustained drift relative to allowable total error. The MA detected progressive instability, showing strong concordance with EP25 after lag correction (N × cadence). FT4 indicated extended stability of up to 19 months post-expiry, while FT3 showed limited stability (<4 months). These differences reflected distinct assay robustness and kinetics.
CONCLUSIONS: The combination of Westgard sigma rules, EP25, and simulation-optimized MA provides a reproducible, data-driven framework for post-expiry reagent stability assessment. Optimizing MA with real patient data enhances detection performance, bridging theoretical quality-control design and routine laboratory application. This integrated approach enables laboratories to make scientifically justified, cost-effective decisions regarding reagent reuse beyond manufacturer expiry dates.
METHODS: This study evaluated the post-expiry performance of free T3 (FT3) and free T4 (FT4) immunoassays on the Abbott Architect i1000SR analyzer using an integrated framework combining three complementary approaches: (i) a simulation-optimized moving average (MA) model based on real patient data (ii) Westgard Sigma rules quality control, and (iii) Clinical and Laboratory Standards Institute EP25-A drift analysis. The MA was optimised via Monte Carlo simulations using a step-shift bias model, which defined the optimal window size (N) for 90% detection power and 0% false rejection rate. Stability was then assessed across three reagent lots per analyte, spanning both pre- and post-expiration phases.
RESULTS: Westgard rules provided the earliest analytical alerts, while EP25 confirmed sustained drift relative to allowable total error. The MA detected progressive instability, showing strong concordance with EP25 after lag correction (N × cadence). FT4 indicated extended stability of up to 19 months post-expiry, while FT3 showed limited stability (<4 months). These differences reflected distinct assay robustness and kinetics.
CONCLUSIONS: The combination of Westgard sigma rules, EP25, and simulation-optimized MA provides a reproducible, data-driven framework for post-expiry reagent stability assessment. Optimizing MA with real patient data enhances detection performance, bridging theoretical quality-control design and routine laboratory application. This integrated approach enables laboratories to make scientifically justified, cost-effective decisions regarding reagent reuse beyond manufacturer expiry dates.