Analytical Performance Flashcards
Difference between analytical performance & diagnostic performance
Analytical assesses how well an instrument/method measures analyte of interest
Diagnostic assesses the ability of a test to discriminate between a healthy & unhealthy patient
Why monitor analytical performance
- Ensure reliability of data
- Meet requirements of regulatory bodies
- Validation of assay/method
- Calibration to maintain accuracy
- Comparison of assays on diff instruments/labs
How can precision be evaluated (3)
- With-in-run precision study (intra assay)
- Between-run precision study (inter assay)
- Precision profile
What can precision be numerically defined by (2)
- Standard deviation
- Coefficient of variation (CV)
What does a low SD mean
Data points close to the mean/expected value
What does a high SD mean
Data point spread from the mean/expected value (high variation)
SD formula
Coefficient of variation formula
%CV = (SD/Mean) x (100/1)
What does it mean if % CV is high
Data is more imprecise
What is involved in running a precision profile
- It examines the variation of a method over a number of analyte concentrations, days, and optionall over one/two runs per day
- Its a plot of %CV vs Concentration
- Cab be used to establish working reference ranges
2 Requirements of precision profile
- At least 3 replicates must be observed for each run, and each run must have the same number of replicates
- Analyte conc must be known
% error formula
(nominal value - experimental value / nominal value) x 100
Difference between what accuracy & precision indicate
- Accuracy indicates proximity of measured results to true value
- Precision indicates repeatability or reproducability of the measurement
What does a recovery study test
Ability of an assay to recover / measure a known amount of analyte from a sample matrix
Specificity formula (remember; its the measure of the ability to identify neg results)
Specificity = ( Number true negatives / Number true negatives + Number false positives )
Difference between specificity and sensitivity
- Specitivity measures ability to identify negative results
- Sensitivity measures ability to identify positive results correctly
Sensitivity formula
Sensitivity = (Number true positives / Number true positives + Number false negatives)
