A comparison of the 12s rule and Bayesian approach for quality control: application to one-stage clotting factor VIII...

An ideal medical biology internal quality control (IQC) plan should both monitor the laboratory methods efficiently and implement the relevant clinical-biological specifications. However, many laboratories continue to use the 12s quality control rule without considering the high risk of false rejection and without considering the relationship of analytical performance to quality requirements. Alternatively, one can move to the Bayesian arena, enabling probabilistic quantification of the information coming in, on a daily basis from the laboratory's IQC tests, and taking into account the laboratory's medical and economic contexts. Using the example of one-stage clotting factor VIII assay, the present study compares frequentist (12s quality control rule) and Bayesian IQC management with respect to prescriber requirements, process start-up phase issues, and abnormal scenarios in IQC results. To achieve comparable confidence, the traditional 12s quality control rule requires more data than the Bayesian approach in order to detect an increase in the random or systematic error of the method. Moreover, the Bayesian IQC management approach explicitly implements respect of prescriber requirements in terms of calculating the probability that the variable in question lies in a given predefined interval: for example, the factor VIII concentration required after knee surgery in a hemophilia patient.