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Performance Characteristics of a Calculated Index Control Method for the phi Multianalyte Assay with Algorithmic
Radwa Ewaisha1,2, Tifani L Flieth1, Karl M Ness1
1Division of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States.
The Journal of Applied Laboratory Medicine
|November 8, 2024
Summary
Quality control for the Prostate Health Index (phi) needs improvement. A new calculated phi QC metric (PHIc) better monitors assay precision and bias, enhancing disease risk score reliability.
Area of Science:
- Clinical Chemistry
- Biomedical Diagnostics
- Prostate Cancer Biomarkers
Background:
- Multianalyte assays with algorithmic analysis (MAAAs) like the Prostate Health Index (phi) are vital for disease risk scoring.
- Current quality control (QC) for phi assesses individual components, potentially missing overall index imprecision and bias.
- This indirect QC may not adequately ensure the reliability of the calculated multicomponent phi value.
Purpose of the Study:
- To evaluate the precision and bias of the Prostate Health Index (phi) compared to its individual components.
- To introduce and assess a novel calculated phi QC metric (PHIc) for improved monitoring of MAAA performance.
- To determine the frequency of QC failures for PHIc versus individual components using Westgard rules.
Main Methods:
- Compared inter- and intra-assay phi precision against individual component assay precision.
- Developed a calculated phi QC metric (PHIc) using QC data from total PSA, free PSA, and p2PSA.
- Analyzed PHIc QC failure rates against individual component QC failures (Westgard 13S, 22S) and examined bias effects on PHIc.
Main Results:
- Average measured phi imprecision (6.7% CV) was significantly higher than individual component imprecision (3.9-4.5% CV).
- Retrospective analysis of 84 QC determinations showed varying failure patterns for PHIc and components based on standard deviations used for Westgard rules.
- Simulated bias in component assays demonstrated nonlinear changes in the PHIc metric.
Conclusions:
- An additional calculated phi QC measure (PHIc) is proposed to effectively monitor MAAA precision and bias.
- Calculated index controls offer a complementary QC approach applicable to other MAAA indices.
- Implementing PHIc can enhance the accuracy and reliability of disease risk scores derived from MAAAs.
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