Utilization of Assay Performance Characteristics to Estimate Hemoglobin A 1c Result Reliability A. Woodworth, N. Korpi-Steiner, J.J. Miller, L.V. Rao, J. Yundt-Pacheco, L. Kuchipudi, C.A. Parvin, J.M. Rhea, and R. Molinaro August © Copyright 2014 by the American Association for Clinical Chemistry

© Copyright 2009 by the American Association for Clinical Chemistry Introduction – Quality Control and Risk  Analytical Quality Control (QC) Programs are developed in all CLIA Certified Laboratories to rapidly identify and correct errors.  CMS Recently Introduced a new type of QC Plan – Individualized QC Plan (IQCP)  Laboratories can decide to use traditional QC approaches, or  Risk management strategies  The risk of reporting an unreliable patient result can be determined using analytical performance requirements and characteristics of an individual assay.

© Copyright 2009 by the American Association for Clinical Chemistry Introduction  A risk based IQCP for Hemoglobin (Hb) A 1c  Ideal to pilot a risk analysis because: −Harmonized and Standardized −Defined performance characteristics −Both lab and POC platforms −Large body of clinical information guides testing  This Hb A 1c risk assessment utilizes: −Assay performance characteristics in clinical settings −Three different acceptance limits ( ±5%, 6%, and 7%) −Standard QC practice ( 1-2S with 2 levels of QC) −Same number of patients between QC events (100)

© Copyright 2009 by the American Association for Clinical Chemistry Quantitative Tools Utilized for Risk Assessment  Assay imprecision (%CV) and accuracy (%Bias)  Allowable Total Error (TE a ) - Quality specifications for acceptable differences between the true and measured results for a given assay  Patient Weighted Sigma Metrics – Sigma value calculated and averaged over the observed Hb A 1c patient distribution, where σ = [(TE a -%Bias)/CV]  E(N uf ) – The number of final patient results with errors > TE a each time there is a QC out of range  In-Control % Unreliable - Probability (%) of producing results with errors > TE a when the assay is in-control

© Copyright 2009 by the American Association for Clinical Chemistry Introduction  Aim of this Study  To evaluate the risk of reporting an unreliable Hb A 1c result when using currently available NGSP-Certified Hb A 1c methods.  The risk assessment employed: −6 different methods across 4 academic medical centers  See Editorial:  Little, RR. Performance of Hb A 1c Assay Methods: Good Enough? Clin Chem 2014;60:8:1031.

© Copyright 2009 by the American Association for Clinical Chemistry Question  Besides analytical error, what other sources of error should be considered when evaluating the risk of reporting an unreliable result? How are these errors detected?

© Copyright 2009 by the American Association for Clinical Chemistry Materials and Methods- Hb A 1c Assays InstrumentManufacturerMethodology Variant II Turbo (version 1.0) BioRadIon-Exchange HPLC Variant IIBioRadIon-Exchange HPLC Tosoh G8TosohIon-Exchange HPLC Capillarys 2Sebia Capillary Electrophoresis Cobas Integra 800RocheImmunoassay DCA Vantage-1 (old cal) SiemensPoint of Care DCA Vantage-2 (new cal) SiemensPoint of Care

© Copyright 2009 by the American Association for Clinical Chemistry Materials and Methods (n=40/lab)

© Copyright 2009 by the American Association for Clinical Chemistry Questions  What fixed conditions were used for the assessment of risk of reporting an unreliable result for each assay?  What different TE a settings were used and why?

© Copyright 2009 by the American Association for Clinical Chemistry Results – Figure 2 The percentage bias of all methods was calculated using the linear regression relationships over a range of NGSP target value-assigned Hb A 1c concentrations. These biases varied widely across the different platforms with the greatest variability in the Variant II and Integra 800 assays at low Hb A 1c concentrations. Precision was determined using vendor specific QC material and ranged from 1.28% % and 0.8% % at the low and high levels, respectively (For more detail see table 1).

© Copyright 2009 by the American Association for Clinical Chemistry The predicted change in the expected number of unreliable patient results prior to an accepted QC event E(N u f), represented in the y axis and computed over a range of possible out-of control conditions [systematic error (SE)] shown on the x axis for each Hb A 1c assay platform evaluated. Each assumes a 1-2s QC rule with 2 QCs and a mean of 100 Hb A 1c examinations between QC events and an Allowable Total Error (TE a ) of 6%. The lines for the Capillary 2 (3D) and DCA Vantage Lot 2 (3G) are almost flat because the E(N uf ) is minimal. Results – Figure 3

© Copyright 2009 by the American Association for Clinical Chemistry Results – Table 2 Three different measures of risk of reporting an unreliable result were calculated for each assay at 3 different Allowable Total Errors (TE a = 5%, 6% and 7%) including the patient weighted sigma, the % of unreliable results while the assay is in control (In-control % unreliable), and the maximum number of unreliable results due to an out of control condition (Max E(N uf )). Each was calculated assuming a 1-2s QC rule with 2 QC events per day and 100 patient samples between QC events. The Capillarys 2 had the lowest and the Integra 800 had the highest number of expected unreliable results while the assay was in control and out of control at 5% TE a.

© Copyright 2009 by the American Association for Clinical Chemistry Questions  Which was more influential on method performance (precision or bias) and how can this be checked regularly?  Based on the findings of this study, Is your laboratory running an appropriate amount of QC for your Hb A 1c method?

© Copyright 2009 by the American Association for Clinical Chemistry Summary and Conclusions  Three types of analytical characteristics can be used to assess risk of reporting an unreliable Hb A 1c result:  Assay performance characteristics (precision and bias)  QC Strategies (# of QC samples + rules)  Clinical performance requirements (TE a goals)  Risk estimates for reporting unreliable results based upon analytical performance alone varied almost 500 fold across the 6 Hb A 1c assay platforms.  At a ±6% TE a budget, all but one Hb A 1c assay in this study requires the “max affordable” QC be run.  Risk estimates for individual laboratories’ Hb A 1c methods can be utilized to assess QC practices and residual risk for reporting an unreliable Hb A 1c result.

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