Development of a Novel Automated Screening Method for Detection of FVIII Inhibitors

Transcription

1 Development of a Novel Automated Screening Method for Detection of FVIII Inhibitors Matthew S. Evans, MD Assistant Professor of Hematology and Pathology Department of Hematology Hemophilia Treatment Center of Central Pennsylvania Penn State Hershey Medical Center

2 No disclosures Disclosures

3 Objectives Review principles of Factor level assays. Review methods, results and conclusions from a project designed to develop an objective and automated tool for screening of FVIII inhibitors. Review implications of newly developed screening method and potential future applications.

4 Objectives Review principles of Factor level assays. Review methods, results and conclusions from a project designed to develop an objective and automated tool for detection of FVIII inhibitors. Review implications of newly developed screening method and potential future applications.

5 Principles of aptt Practical Haemostasis.com A Practical Guide to Laboratory Haemostasis

6 Principles of aptt Platelet poor plasma [PPP] is incubated at 37 C with phospholipid (cephalin) and a contact activator (e.g. Kaolin,micronized silica or ellagic acid) is added followed by the calcium (all pre warmed to 37 C). Addition of calcium initiates clotting and timing begins. Most laboratories use an automated method for the aptt in which clot formation is deemed to have occurred when the optical density of the mixture has exceeded a certain threshold (clot formation makes the mixture more opaque and less light passes through). The APTT is the time taken for a fibrin clot to form. Practical Haemostasis.com A Practical Guide to Laboratory Haemostasis

7 Principle of Assays to Measure FVIII aptts are performed on serial dilutions of plasma mixed with equal amounts of plasma from a patient deficient in the factor to be measured A standard/calibrator curve is constructed plotting the aptt results (time to clot formation in seconds) versus known concentration on a semi log scale The percent of factor in the patient (test) plasma is then calculated from the normal curve using clotting time from measured aptt of the patient (test) plasma.

8 Principle of Assays to Measure FVIII

9 STA R Evolution FVIII Assay: Specifics aptts are performed on 1:1 mixtures of FVIII deficient plasma and both standard and test plasma at 3 dilutions With STA R, the FVIII deficient plasma is from freeze dried citrated human plasma from which Factor VIII has been removed by immuno adsorption A normal (calibrator) curve and a patient (test) curve are then generated from the clotting times of different dilutions (1:6, 1:15, 1:30 and 1:60 for the calibrator and 1:6, 1:15 and 1:30 for the patient) The curves should be linear when the log of the clotting times of each dilution is plotted against the concentration of Factor VIII The line given by the clotting times of the dilutions of the test plasma should parallel that given by the dilutions of the system control plasma The corrective effect of the test plasma is compared to that of the normal standard (system control) plasma The STA R Evolution automatically converts the results to % activity.

10 FVIII Assay Principles Reason for parallelism curves: In order to minimize the potential for underreporting an activity level or missing presence of an inhibitor substance

11 STA R Evolution FVIII Assay: Principles In absence of inhibitor (disease free state), the standard and patient curves are parallel to each other with the patient s slope (Ps) similar to the slope of a standard curve (Cs).

12 STA R Evolution FVIII Assay: Principles In patients with inhibitor (disease state), the clotting time is prolonged. With each subsequent dilution, the amount of inhibitor is diluted out, leading to shorter clotting times for subsequent dilutions. In practice this leads to a less steep slope (Ps) compared to the standard curve slope (Cs).

13 Proposal Determination of parallelism of these curves is currently a subjective assessment that leads to increased error in reporting, potential missed evaluation for inhibitors and potential unnecessary inhibitor testing. We proposed the development of an objective and automated assessment for determining parallelism as an added screening tool for potential presence of an inhibitor.

14 Objectives Review principles of Factor level assays. Review methods, results and conclusions from a project designed to develop an objective and automated tool for detection of FVIII inhibitors. Review implications of newly developed screening method and potential future applications.

15 Methods/Study Design Population: Factor VIII deficient hemophilia patients with or without inhibitors Intervention: Factor VIII assays on all patient samples Comparison: Compare the ratio of the slope of the curve generated from patient dilutions without detectable inhibitor (disease free state) and Factor VIII deficient hemophilia patients with known inhibitor (disease state) versus the slope of the curve of the standard/calibrator. Determine a cut off for detection of an inhibitor by evaluating the difference in the ratio of the slopes (Ps/Cs) for patients with inhibitor vs those without inhibitor that is predictive for the presence of inhibitor. Outcome: Validate predictive value of determined cut off

16 Methods Performed Factor VIII assays* at appropriate dilutions and examined curves for parallelism with the control curve on a population of Factor VIII deficient hemophiliac patients with inhibitors and without inhibitors. Blinded to result of factor assays, performed Bethesda titers** on all samples using Nijmegen modification to determine presence of an inhibitor in each sample Compared ratio of the slope of patient curve to slope of the standard curves generated from dilutions in patients without detectable inhibitor (disease free state) vs Factor VIII deficient hemophilia patients with known inhibitor (disease state). *Low Factor VIII assay modification on STA Compact using low curve calibration at 1:6, 1:15 and 1:30 dilutions (STA Deficient VIII, Immuno Depleted Plasma for Factor VIII:C assay by STA. Package insert revised September 1994)) **Bethesda assay is standard for quantification of factor inhibitors

17 Results Generated a Bell Curve Bell curve generated using Microsoft Excel program for histograms by development of a bin data set utilizing the average of Ps/Cs ratios +/ 3 standard deviations for both samples with and without inhibitors

18 Results Example of Factor Curve in patient with Inhibitor (Disease state) Ps/Cs=0.144

19 Results Example of Factor Curve in patient without inhibitor (Disease Free state) Ps/Cs= 1.04

20 Results Factor VIII deficient patients with inhibitor (6 samples) Ps/Cs (Slope Ratio) in patients with Inhibitor confirmed by Bethesda titer (6 samples) Average Standard Deviation Histogram from original data *Bin: Data generated using average +/ 3 standard deviations with Microsoft Excel program for histograms Bin Frequency

21 Results Factor VIII deficient patients without inhibitor (11 samples) Ps/Cs (Slope Ratio) in patients without Inhibitor confirmed by Bethesda titer (11 samples) Average Standard Deviation *Bin: Data generated using average +/ 3 standard deviations with Microsoft Excel program for histograms Histogram from original data Bin Frequency

22 Results To improve bell curve, we performed a parameter simulation to generate additional random data points using pre set parameters from our data set based on mean and standard deviation

23 Results Factor VIII deficient patients with inhibitor with Parameter Simulation Histogram from Random inhibitor Data Bin Frequency *Bin: Data generated using average of random data points +/ 3 standard deviations with Microsoft Excel program for histograms Example of random generated numbers Random numbers with data parameters

24 Results Factor VIII deficient patients without inhibitor with Parameter Simulation Histogram from Random Noninhibitor Data Bin Frequency *Bin: Data generated using average of random data points +/ 3 standard deviations with Microsoft Excel program for histograms Example of random generated numbers Random numbers within data parameters

25 Results Bell curve for slope ratios in patients with inhibitor using parameter simulation Frequency Inhibitor P/C ratio Ps/Cs slope ratios Inhibtor P/C ratio *Bell Curve generated as scatter plot using x=bin data (average of Ps/Cs ratio of samples assays +/ 3 standard deviations) and y=frequency

26 Results Bell curve for slope ratios in patients without inhibitor using parameter simulation 800 Noninhibitor P/C ratio Frequency Ps/Cs slope ratios Noninhibitor P/C ratio *Bell Curve generated as scatter plot using x=bin data (average of Ps/Cs ratio of samples assays +/ 3 standard deviations) and y=frequency

27 Results Distribution Curves from comparing Patient to Control Slope Ratio in patients with Inhibitors vs Patient to Control Slope ratio in patients without inhibitor Frequency Ps/Cs slope ratios

28 Determining a Test cut off Using Bell curve, we determined a cut off point to predict for presence of a Factor VIII inhibitor Cut off for predicting presence of a Factor VIII inhibitor was determined to be a ratio of Patient to Standard curve of less than 0.45 Based on samples we evaluated, the cut off of a Ps/Cs of 0.45 was 100% sensitive and 80% specific

29 Validation of Cut off We then re confirmed the validity of this cutoff by applying it to evaluate presence of a FVIII inhibitor in an additional 48 de identified samples from the NHLBI with and without low FVIII inhibitor (Bethesda titers <5) NHLBI: National Heart, Lung, and Blood Institute

30 Results Results of inhibitor screen using ratio of Patient to Control slopes from Parallelism Curves in 48 de identified samples Inhibitor Present on Bethesda Assay Inhibitor Absent on Bethesda Assay Screening test Positive for Inhibitor (Ps/Cs Ratio<0.45) Screening test Negative for Inhibitor (Ps/Cs Ratio>0.45)

31 Results Validation Studies: Statistical Analysis of Inhibitor Screen utilizing ratio of Patient to Control from Parallelism Curves Statistic Percent Sensitivity 100% Specificity 91.6% Predictive Value of Positive Screening Test for an Inhibitor (ratio <0.45) Predictive Value of Negative Screening Test for an Inhibitor (ratio >0.45) 92.3% 100%

32 Objectives Review principles of Factor level assays. Review methods, results and conclusions from a project designed to develop an objective and automated tool for detection of FVIII inhibitors. Review implications of newly developed screening method and potential future applications.

33 Future Implications We propose utilizing this tool and cut off as an automated screening tool for determining presence of an inhibitor during routine FVIII assays. We are evaluating implementation of this objective cut off as an automated tool within STAGO, which is used for factor assays here at HMC We have submitted a technology disclosure form for a possible patent on this screening method. We plan to further explore this cut off in other populations, including patients with FIX inhibitors and lupus anticoagulants and use of medications that inhibit normal clotting pathways (i.e. direct thrombin inhibitors such as dabigatran and Factor Xa inhibitors such as rivaroxaban and apixiban)

34 Thank you My sincerest appreciation and thanks to the following who helped make this project possible: M. Elaine Eyster, MD Keri Donaldson, MD Michael Creer, MD Jeff Sanders, MS Tracey Romanoski The entire Special Hematology Lab Gail Long Harold Harvey, MD and Leah Cream, MD Entire fellowship program

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