QC_FB01

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Definitions (1)

s Quality Control - QC refers to the measures that must be included

during each assay run to verify that the method is working properly.

s

Quality Assurance - QA is defined as the overall program that ensuresthat the final results reported by the laboratory are correct.

s The aim of quality control is simply to ensure that the results

generated by the method are reliable. However, quality assurance is

concerned with much more: that the right method is carried out on the

right specimen, and that the right result and right interpretation isdelivered to the right personat the right time

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Definitions (2)

s Quality Assessment - quality assessment (also known as

proficiency testing) is a means to determine the quality of

the results generated by the laboratory. Quality assessmentis a challenge to the effectiveness of the QA and QC

programs.

s Quality Assessment may be external or internal, examples

of external programs include regulatory agencies andreference laboratories.

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Variables that affect the quality of results

The educational background and training of the

laboratory personnel

The condition of the specimensThe controls used in the test runsReagentsEquipmentThe interpretation of the resultsThe transcription of resultsThe reporting of results

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Errors in measurement

s True value - this is an ideal concept which cannot be

achieved.

s Accepted true value - the value approximating the true

value, the difference between the two values is

negligible (within acceptance criteria).

s Error - the discrepancy between the result of ameasurement and the true (or accepted true value).

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Sources of error

Input data required - such as standards used, calibration values, andvalues of physical constants.

Inherent characteristics of the quantity being measured

Instruments used - accuracy, repeatability.

Observer fallibility - reading errors, blunders, equipment selection,analysis and computation errors.

Environment - any external influences affecting the measurement.

Theory assumed - validity of mathematical methods andapproximations.

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Random Error

An error which varies in an unpredictable manner, in magnitude

and sign, when a large number of measurements of the same

quantity are made under effectively identical conditions.

Random errors create a characteristic spread of results for any test

method and cannot be accounted for by applying corrections.Random errors are difficult to eliminate but repetition reduces the

influences of random errors.

Examples of random errors include errors in pipetting and changes

in incubation period. Random errors can be minimized by training,

supervision and adherence to standard operating procedures.

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Random Errors

x

x x

x x

True x x x x

Value x x x

x x x

x

x

x

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Systematic Error

An error which, in the course of a number of measurements of

the same value of a given quantity, remains constant when

measurements are made under the same conditions, or varies

according to a definite law when conditions change.

Systematic errors create a characteristic bias in the test results

and can be accounted for by applying a correction.

Systematic errors may be induced by factors such as variations in

incubation temperature, blockage of plate washer, change in the

reagent batch or modifications in testing method.

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Systematic Errors

x

x x x x x x x

True x

Value

Systematic + BIAS

Strongly suggest a process error

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Internal Quality Control Program

An internal quality control program depend on the use of internal

quality control (IQC) specimens and the use of statistical methods

for interpretation.

Internal Quality Control Specimens

IQC specimens comprises either (1) in-house sera (single or pooled

samples), or (2) Reference samples provided by a reference

laboratory with values within significant analytical ranges (MRL

minimally but Idealy; 0.5*MRL, MRL and 2*MRL).

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Quality Control Scheme

The quality control scheme depend on the use of IQC specimens and isdeveloped in the following manner:

Use IQC specimen analysed in duplicate for each analytical runs and

record the individual values.

Weekly/Monthly/yearly, Calculate the mean and standard deviations(SD) of the individual values obtained

Make a plot with the assay run number on the x-axis, and measured

values on the y axis.

Draw the following lines across the y-axis: mean, -3SD, -2SD, -2SD,

1SD, 2SD, and 3 SD. (based on normal gaussian distribution) Plot the concentration obtained for the IQC specimen for all analytical

runs (trend analysis)

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Statistical Basis for Evaluation

Mean

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Objectives of an analytical procedure

s Able to quantify as accurately as possible each unknownquantity to be determined.

s After analysis: the difference between returned result xreturned result x and the

unknown true value true value TT be small or < acceptance limitacceptance limit :

-- < x - < x - TT

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Mesured Accuracy profile

bias (%)

concentration

+

C1 C2 C3 C4

LLQ ULQRANGE

a

ccept a

ncelim

its

dosage interval

0

+ BIAS

- BIAS

Acceptable BIAS

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Intra Batch Quality Control Estimator

+15%

-15%

0.5*MRL MRL 2*MRL

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Inter Batch Quality Control Trend Analysis

1.98 SD

- 1.98 * SD

95%CI

Trend analysis and performance evaluation are vital to assess if the

method performed with an acceptable accuracy.

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Warning rules

Warning 1 : It is violated if 1/3 of IQC bias exceeds 15%

Warning 2 : It detects systematic. BIAS is systematicaly negative

or positive.

Warning 3 : It is violated if consecutive IQC bias lead from apositif to a negative Bias of from a negative to a positive bias.

This observation may indicate the need to perform instrument

verification or maintenance.

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Follow-up action in the event of a violation

There are three options as to the action to be taken in the event of aviolation of a pre-established QC rules:

Accept the test run in its entirety - this usually applies when

only a warning rule is violated.

Reject the whole test run - this applies only when a mandatoryrule is violated.

Accept only results that are within the analytical range that is

not affected by a violation of either a warning or mandatory

rule. Re-analyse samples that are affected by rule violation

(this is always risky)