Enzyme-linked immunosorbent assay Microtiter well EEEEE Specimen 2nd antibody E Substrate SP.

Enzyme-linked immunosorbent assay

Microtiter well

E E E E E

Specimen 2nd antibodyE

Substrate

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HAMA “bridging” interference

E E E E

2nd antibodyESubstrate

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HAMA blocking interference

E E E E

Distinguishing between Health and Disease: The role of the clinical laboratory in the

diagnostic process

Clinical Biochemistry 3H3

What is normal???• Normal Health

– choice between defining an ‘ideal state’ or determining an ‘average’ state in people considered healthy

– more practical to analyze ‘average’ state --with respect to a biological parameter results in a symmetric (Gaussian) distribution

The Disease State

• A population having a specific disease will usually have an asymmetric (nonparametric) distribution.

Diagnostic process involves gathering information until, ideally, the probability of the disease approaches 100%.in practice, this value is much lower at the time of the decision.

Defining the value of a Diagnostic Test• The clinical performance of a laboratory test defines how well it

predicts disease• The sensitivity of a test indicates the likelihood that it will be

positive when disease is present• The specificity of a test indicates the likelihood that it will be

negative when disease is absent• Distinction between a test being a true positive (TP) or true

negative (TN) is usually determined with reference to a selected “normal range” based on 95% confidence. This range is referred to as a Reference Range (RR). Test focuses on the upper or lower limit often use a Reference Value (RV).

• False Positive (FP) Normal people falling outside RR• False Negative (FN) Diseased individual falling inside RR

Defining the value of a Diagnostic Test

Defining the value of a Diagnostic Test• Reference state (RS): conditions in which the RR is assumed to apply

– “Ideal world” RS would include sex, ethnicity, weight range, diet – In practice RR are applied to a much larger population

• distinction made between neonate, pediatric, obstetrics and geriatric practices• Establishing a Reference Range

– min 100 subjects – Test should be validated under the following conditions:

• in healthy subjects• in patients with the disease

– no symptoms– full symptoms

• subjects who not have the disease but whose signs and symptoms mimic the disease

• subjects having a pathologic conditions associated with the same organ system

Laboratory Test Characteristics•Sensitivity(SENS)- the test “positivity”SENS= TP X 100

TP +FN=% of disease cases that give a positive result with the RV selected

•Specificity(SPEC)- the test “negativity”SPEC= TN X 100

TN +FP=% of non-disease cases that give a negative result with the RV selected

ExampleExample

Of 25 admitted cocaine abusers, 23 tested positive for urinary benzoylecgonine and 2 tested negative. What is the sensitivity of the urine screen?

23

23 2100 92%

Mar

ker

con

cen

trat

ion

- +Disease

Sensitivity and specificity are inversely related.

Do you prefer a sensitive test or a specific test?

• Choice of test characteristic is a function of diagnostic need– Discovery tests are often applied to asymptomatic

patients.

• requires good sensitivity

– Confirmatory tests require high specificity

• establish presence of disease

– Test to exclude a disease require high sensitivity

• little chance of false negatives

Evaluating Clinical Performance of laboratory tests

Evaluating Clinical Performance of laboratory tests

• The sensitivity of a test indicates the likelihood that it will be positive when disease is present

• The specificity of a test indicates the likelihood that it will be negative when disease is absent

• The predictive value of a test indicates the probability that the test result correctly classifies a patient

Laboratory Test Characteristics(Cont)• Prevalence of a disease is the number of positive cases in the

population being tested at a designated point in time.

– 1 per X people, number per 100, 000, or expressed as percentage

• Predictive Value (PV)- essential characteristic of any lab test. Depends on: SENS, SPEC and prevalence

– indicates info that can be gained from by conducting test under a giving set of conditions

PV(+) = TP X 100

TP +FP

PV(-) = TN X 100

TN +FN

Predictive ValuePredictive Value

The predictive value of a clinical laboratory test takes into account the prevalence of a certain disease, to quantify the probability that a positive test is associated with the disease (PV+) in a randomly-selected individual, or alternatively, that a negative test is associated with health (PV-).

Laboratory Test CharacteristicsNew test devoloped for Myocardial infarction (cTnI)

Research Data1) Test was positive in 99 out 100 patients with MI2) Test was positive for 12 out 100 in normal controls

SENS= TP X 100

TP +FN

99 X 100= 99%

99 +1

SPEC= TN X 100

TN +FP

88 X 100= 88%

88 +12 PV(+) = 3465 X 100 =81%

3465 +780

Positive Negative Total

Disease Population

TP 3465

FN 35

3500

Control Population

FP 780

TN 5720

6500

Totals 4245 5755 10000

Test is used in to test 10,000 patients in CCU (35% prevalence)

3500 patients are positive. 3465 are TP

PV(+) = TP X 100

TP +FP

35% prevalence of MI

Test is then used in to test 10,000 ER patients ( 4% prevalence)400 patients are positive. 396 are TP

PV(+) = TP X 100

TP +FP

PV(+) = 396 X 100 =26%

1152 +396

Positive Negative Total

Disease Population

TP 396

FN 4

400

Control Population

FP 1152

TN 8448

9600

Totals 1548 8452 10000

4% prevalence of MI

Laboratory Test Characteristics

Efficiency and Receiver Operating Characteristics (ROC) curves

Efficiency = TP + TN X 100 TP +FP+FN+TN

• Used to differentiate between tests when Sensitivity and Specificity are equally important.

• Test with an efficiency of <80 % should not be usedROC curves plots True positive rate to False positive rate for a series of reference

values• Useful for assessing the clinical value of different tests• Useful for selecting best Reference value for a test• Recall True positive rate =Sensitivity = TP

TP +FN

• False Positive rate = FP = 100-specificity FP +TN

ROC Curves

1-specificity

sens

itiv

ity

Shows trade off between specificity and sensitivityCloser the curve follows left-hand border and top border the more accurate the testThe closer the test comes to a 45 degree angle the less accurate the test

Area under the curve.9-1= excellent.8-.9=good.7-.8= fair.6-.7=poor.5-.6=fail

The Diagnostic Test

The view from the laboratory

The Expectation• Clinicians depend on the the laboratory to provide

results that are– Accurate– Precise– Timely

• Result compared to reference interval and patient is treated accordingly– Result also compared to previous patient results

How does the laboratory meet this expectation?

Quality Control (QC)• Quality Control (QC)

– The use of statistics, techniques and activities to achieve, sustain and improve the quality of a product or service

-Product or Service is the test result

The focus of QC in the lab is the method which used to determine the result

QC is part of the “Big Picture” of Quality Assurance• Quality Assurance (QA)

– Focuses on all aspects of laboratory performance• Analytical results• Overall laboratory Services

– Specimen labeling, specimen handling, accurate reporting of test results, TAT, incident reports, patient, nurse or clinician surveys

QC in the Laboratory involves Evaluating method performanceQC in the Laboratory involves

Evaluating method performance

Constant

Long term

Short term

So what are we evaluating?

Evaluating method performanceEvaluating method performance

• Accuracy

• Precision

• Sensitivity

• Linearity


• Accuracy

• The closeness of the agreement between the measured value of an analyte and True Value• Gold standard • Comparison to Reference Laboratory• Average of a number of labs


• Precision

• The ability of an analytical method to produce the same value for replicate measurements of the same sample• With-in run• Between run

Method SensitivityMethod Sensitivity• The analytical sensitivity of a method refers

to the lowest concentration of analyte that can be reliably detected.

• The most common definition of sensitivity is the analyte concentration that will result in a signal two or three standard deviations above background.

Clinical Sensitivity Vs Analytical Sensitivity

Signal

time

Signal/Noise threshold

Clinical Sensitivity Vs Analytical Sensitivity

Other measures of sensitivityOther measures of sensitivity• Limit of Detection (LOD) is sometimes defined as the

concentration producing an S/N > 3.– In drug testing, LOD is customarily defined as the lowest

concentration that meets all identification criteria.

• Limit of Quantitation (LOQ) is sometimes defined as the concentration producing an S/N >5.– In drug testing, LOQ is customarily defined as the lowest

concentration that can be measured within ±20%.

Method LinearityMethod Linearity

• A linear relationship between concentration and signal is not absolutely necessary, but it is highly desirable.

• Ways to evaluate linearity– Visual/linear regression

Sig

nal

Concentration

The Application of QC to Laboratory Methods

We base the validity of our patient test result by comparison to other samples analyzed by the same method

• Sample Types Analyzed by the Lab– Patient Samples

– QC samples

– Proficiency samples (PT)


• QC Samples• Samples selected by the laboratory and purchased from

an external company

• Tested each day of patient testing to mimic patient and proficiency samples

• Indicates if the lab’s analytical processes are performing in an acceptable manner, thereby producing clinically acceptable patient and proficiency results

• QC samples provide data about accuracy and precision of each methods at the level of analyte present in the control

• We interpret the data when making daily decisions about the acceptability of each batch of patient or PT samples


• Proficiency (PT) Samples• External agencies (mandated legislative bodies or voluntary

organizations)

• QMP LS -Quality Management Program Laboratory Services

• Part of Ontario Medical Association (OMA)

• CAP College of American Pathologists

• Samples are sent to see how well laboratory performs relative to peers and to a defined quality specification. This is usually referred to as a total error allowable (TES) from a target value for each sample.

• For many analytes measured a specific license is required

• The ability to continue measuring an analyte hinges upon maintaining proficiency


• Running QC and PT samples reflects how well the lab is doing but does not modify or correct or control analytical problems

• Require QC system to “drive” the system:– QC data

– Rules of acceptability

– Tools for monitoring and documenting daily QC and corrective actions

Rules of Acceptability are based upon:• Performance specifications

– Numerical limits established by each laboratory for each analyte and each testing system, which often include accuracy, precision, analytical sensitivity (minimum reportable amount), analytical specificity (interfering substances), the reportable range of patient test results and the reference range.

• Action Limits– Ranges set for QC samples that if exceeded signal a possible

deterioration of the quality of the testing system and requires an investigation by a technologists.


• QC Tools– Levy-Jennings Control Chart

• A simple graphical display in which the observed values are plotted versus an acceptable range of values as indicated on the chart by lines for upper and lower control limits

– Control Rules• A decision criterion used to interpret QC data and make judgment on

the control status

– Statistical QC program• Software part of specific analyzer and/or laboratory information

system (LIS) which analyzes QC data and provides appropriate feedback

– warnings– flags


Levey-Jennings Control Chart

mean

+1sd

+2sd

+3sd

-1sd

-2sd

-3sd

mean

+1sd

+2sd

+3sd

-1sd

-2sd

-3sd

Levey-Jennings Control Chart

• Control Rules– Westgard Multirule

• A control procedure that uses a series of control rules to test the control measurement.

– A 12s rule being used as a warning, followed by the use of 13s, 22s, R4s, 41s and 10x as rejection rules


13s refers to a control rule that is

commonly used with a Levey-Jennings chart when the control limits are set as measurement exceeds the mean plus 3s or the mean minus 3s control the mean plus 3s and the mean minus 3s. A run is rejected when a single control limit.

12s refers to the control rule that is

commonly used with a Levey-Jennings chart when the control limits are set as the mean plus/minus 2s. In the original Westgard multirule QC procedure, this rule is used as a warning rule to trigger careful inspection of the analyte

Westgard Rules

http://westgard.com/images/mrf2.gif


22s - reject when 2

consecutive control measurements exceed the same mean plus 2s or the same mean minus 2s control limit.

R4s - reject when 1 control

measurement in a group exceeds the mean plus 2s and another exceeds the mean minus 2s.

Westgard Rules





41s - reject when 4

consecutive control measurements exceed the same mean plus 1s or the same mean minus 1s control limit.

10x - reject when 10

consecutive control measurements fall on one side of the mean.

Westgard Rules





QC algorithm utilizing Westgard Rules

Enzyme-linked immunosorbent assay Microtiter well EEEEE Specimen 2nd antibody E Substrate SP.

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