QA IN HEMA AND HEMOSTASIS TESTING

• Quality


  The ability to provide accurate, reproducible assay results that offer clinically useful information
• Quality assurance (QA)


  The broader concept, encompassing preanalytical, analytical, and postanalytical variables
• Quality control (QC)


  Processes employed to document assay validity, accuracy, and precision, including external quality assessment, publication of reference intervals (RIs) and therapeutic ranges, and lot-to-lot validation
• Components of quality assurance

  • Preanalytical variables
  • Analytical variables
  • Postanalytical variables
• Preanalytical quality assurance components and laboratory staff responsibility

  • Test orders
  • Test request forms
  • Stat orders and timeliness
  • Specimen collection
  • Specimen transport
  • Specimen management
• Postanalytical quality assurance and laboratory staff responsibility

  • Publication of reports
  • Timeliness
  • Patient satisfaction
• Statistical significance


  When applying a statistical test, the statistician begins with a null hypothesis stating that there is no difference between or among the means or variances of the populations being compared
• Power


  The ability of a statistical test to reject the null hypothesis when the null hypothesis is false
• Significant


  A specific meaning based on the P-value, and it should not be generalized to imply practical or clinical significance
• Mean (X)


  The arithmetic mean, or average, of a data set is the sum (Σ) of the individual data values divided by the number (n) of data points
• Geometric mean


  The n root of the product of n individual data points, used to compute means of unlike data sets
• Median


  The data point that separates the upper half from the lower half of a data set (sample)
• Mode


  The data point that appears most often in the sample
• Variance (σ²)


  Expresses the deviation of each data point from its expected value, usually the mean of the data set (sample) from which the data point is drawn
• Standard deviation (SD)


  A commonly used measure of dispersion, the square root of the variance and the mean distance of all the data points in a sample from the sample mean
• Precision


  Expression of reproducibility or dispersion about the mean, often expressed as SD or CV%
• Accuracy


  Measure of agreement between an assay value and the theoretical "true value" of its analyte
• Primary standard


  Material of known, fixed composition that is prepared in pure form, often by determining its dry mass on an analytical balance
• Secondary standard


  Preserved plasma preparation at a certified known concentration, previously calibrated to a primary standard
• Calibrator


  Preserved human blood cell suspensions, sometimes supplemented with microlatex particles or nucleated avian red blood cells, used to calibrate hematology assays
• Method validation


  1. Proof of accuracy

  2. Precision

  3. Reportable ranges, including the analytical measurement range (AMR)

  4. Detection of interfering substances
• Modifications to FDA-approved assays and laboratory-developed tests (LDTs) have additional requirements, including analytical sensitivity and specificity, specimen and reagent stability, and carryover
• Comparability


  May take the place of accuracy in hematology testing when a true value is not applicable
• Comparing a new or modified assay to a reference method

  1. Student t-test

  2. Analysis of variance (ANOVA)

  3. Linear regression

  4. Pearson correlation coefficient

  5. Bland-Altman plot
• Student t-test


  Compares the mean of a data set (sample) of a new or modified assay to the sample mean of a reference assay
• ANOVA


  Compares variances of more than two data sets
• Pearson correlation coefficient


  Compares a set of paired data to learn if the data points agree with adequate precision throughout the analytical measurement range
• ANOVA computes and reports the sum of squares within and between groups, the total sum of squares, the mean squares within and between groups, and the F-statistic
• Spreadsheet programs compare the F-statistic to the table of critical F-values and report the P-value, which the operator then compares with the selected P-value limit to determine significance
• Pearson correlation coefficient


  A measure of how two data sets vary together while documenting dispersion
• Calculating Pearson correlation coefficient


  1. Σxy/n-XY

  2. SDxSDx
• Pearson r-values


  • 0 to +1.0 represent positive correlation, 1.0 equals perfect correlation
  • Laboratory professionals employ the Pearson formula to assess the range of values from two like assays or to compare assay results to previously assigned standard or calibrator results
  • Most operators set an r-value of 0.975 (or r²-value of 0.95) as the lower limit of correlation
• Linear regression equation


  1. y=a+bx

  2. Slope (b)=[nΣXY−(ΣX)(ΣY)] / [nΣx²-(Σ×)²]

  3. Intercept (a) = [ΣY -b (Σx)] /n
• Perfect correlation


  • Generates a slope of 1 and a y intercept of 0
• Slope


  Measures proportional systematic error
• Intercept


  Measures constant systematic error (or bias)
• Regression analysis gains sufficient power when 40 or more specimens (calibrators and/or patients) are tested using both the new and reference assay
• Bland-Altman difference plot


  Provides a graphical representation of agreement between two assays
• Calculating Bland-Altman difference


  (S1+S2)/2, and S1 – S2
• In a normal (Gaussian) distribution, 95.5% of the values are expected to fall within the Bland-Altman difference limits