control ofcontrol of analytical quality - iacld.ircontrol ofcontrol of analytical quality r. r....
TRANSCRIPT
CONTROL OFCONTROL OFCONTROL OF CONTROL OF ANALYTICALANALYTICAL QUALITYQUALITYANALYTICAL ANALYTICAL QUALITYQUALITY
R. R. MohammadiMohammadiBiochemist (Ph D )Biochemist (Ph D )Biochemist (Ph.D.)Biochemist (Ph.D.)
Faculty member of Medical FacultyFaculty member of Medical Faculty
STATISTICAL QUALITY CONTROL (SQC)STATISTICAL QUALITY CONTROL (SQC)STATISTICAL QUALITY CONTROL (SQC)STATISTICAL QUALITY CONTROL (SQC)
SQC evaluates the measurementSQC evaluates the measurementSQC evaluates the measurement SQC evaluates the measurement procedure by periodically assaying QC procedure by periodically assaying QC materials for which the correct result ismaterials for which the correct result ismaterials for which the correct result is materials for which the correct result is known.known.IQC assumes a Gaussian (normal)IQC assumes a Gaussian (normal)IQC assumes a Gaussian (normal) IQC assumes a Gaussian (normal) distribution of QC results in whichdistribution of QC results in which
6868..22% results are in % results are in ±± 1 1 SDSD9494..55% % results are in results are in ±± 2 2 SDSD9999..77% % results are in results are in ±± 3 3 SDSD
Statistical Process Control (SPCStatistical Process Control (SPC))Statistical Process Control (SPCStatistical Process Control (SPC))
Statistical Process Control (SPC)Statistical Process Control (SPC)Statistical Process Control (SPC)Statistical Process Control (SPC)
ANALYTICALANALYTICALERRORSERRORSERRORSERRORS
R d ER d ERandom ErrorsRandom Errors
Systematic ErrorsSystematic ErrorsSystematic ErrorsSystematic Errors
ProblemProblem 11Problem Problem 11
+ 3 SD
+ 2 SD
+ 1 SD
2 SD
- 1 SDX
- 2 SD
- 3 SD
ProblemProblem 22Problem Problem 22
+ 3 SD
+ 2 SD
+ 1 SD
2 SD
- 1 SDX
- 2 SD
- 3 SD
Performance Characteristics of A Performance Characteristics of A C t l P dC t l P dControl ProcedureControl Procedure
We HaveWe HaveWe HaveWe HaveInherent or background random errorInherent or background random error
hi h d ihi h d iwhich produce noisewhich produce noiseAnalytical errors which produce signalsAnalytical errors which produce signalsWe must considerWe must considerProbability of false rejection (Probability of false rejection (PPff ))Probability of false rejection (Probability of false rejection (PPfrfr))Probability of error detection (Probability of error detection (PPeded))
Factors Affecting on Factors Affecting on SQC R lt I t t tiSQC R lt I t t tiSQC Results InterpretationSQC Results Interpretation
QC MaterialQC MaterialQC MaterialQC MaterialMean and SDMean and SDR lR lRulesRulesMethod Sigma Quality MetricsMethod Sigma Quality Metrics
QC MAERIALSQC MAERIALS
SELECTON OF QC MATERIALSSELECTON OF QC MATERIALSSELECTON OF QC MATERIALSSELECTON OF QC MATERIALS
Nature (Matrix & Source) of MaterialNature (Matrix & Source) of MaterialNature (Matrix & Source) of MaterialNature (Matrix & Source) of MaterialAnalyteAnalyte Stability (Before and After Opening)Stability (Before and After Opening)VolumeVolumeVolumeVolumeAmountAmountInclude Whole ProcessInclude Whole ProcessInclude Whole ProcessInclude Whole ProcessAnalyteAnalyte ConcentrationConcentrationAssayed orAssayed or UnassayedUnassayedAssayed or Assayed or UnassayedUnassayedDependent and IndependentDependent and Independent
DETERMINATION OF MEAN ANDDETERMINATION OF MEAN ANDDETERMINATION OF MEAN AND DETERMINATION OF MEAN AND STANDARD DEVIATIONSTANDARD DEVIATION
نالیز ابتدایــی ماده کنترلی جهت تعییننالیز ابتدایــی ماده کنترلی جهت تعییناا
میزان هدف و انحراف معیارمیزان هدف و انحراف معیار
نياز به آناليز تعداد کافی نمونه طی دوره ای وجود دارد که سيستم بخوبی نياز به آناليز تعداد کافی نمونه طی دوره ای وجود دارد که سيستم بخوبی ) ) ١١ ی)) و م ي ر و و ور ی و ی يز ز یي و م ي ر و و ور ی و ی يز ز ي..کاليبره است و عدم دقت مورد انتظار مربوط به شرايط پايدار وجود داردکاليبره است و عدم دقت مورد انتظار مربوط به شرايط پايدار وجود دارد
) ) روز مختلفروز مختلف ٢٠٢٠طی طی ((زمان متفاوت زمان متفاوت ٢٠٢٠آناليز طی حداقل آناليز طی حداقل ٢٠٢٠حداقل نياز به حداقل نياز به ) ) ٢٢ا ز ا خ ا ت آنال ا ا ان ت که اش نه ن ال اک ز ا خ ا ت آنال ا ا ان ت که اش نه ن ال بر روی يک ويال نمونه می باشد که بتواند پايداری آناليت را بخوبی مورد ارزيابی بر روی يک ويال نمونه می باشد که بتواند پايداری آناليت را بخوبی مورد ارزيابی ک
..قرار دھدقرار دھدپروتوکل))٣٣ که صورتی پروتوکلدر که صورتی تعداد٢٠٢٠در با موقتی ھدف مقادير نباشد، عملی تعدادروزه با موقتی ھدف مقادير نباشد، عملی روزه و ) ) ی پرو ور و ر ی پرو ور ی ب ر و ير ب ی ی ب روز و ير ب ی روز
نمونه کمتر تعيين می گردد و با دسترسی به نتايج بيشتر، روزسازی مقادير انجام نمونه کمتر تعيين می گردد و با دسترسی به نتايج بيشتر، روزسازی مقادير انجام ..می شودمی شود
انگ))۴۴ از شگا ا آز ش تفا ا شا ا ا ش از انگقت از شگا ا آز ش تفا ا شا ا ا ش از قت وقتی از شماره جديد ماده مشابھی استفاده می شود ، آزمايشگاه از ميانگين جديد وقتی از شماره جديد ماده مشابھی استفاده می شود ، آزمايشگاه از ميانگين جديد ))۴۴. . بدست آمده به عنوان ميانگين ھدف در کنار انحراف معيار قبلی استفاده می کندبدست آمده به عنوان ميانگين ھدف در کنار انحراف معيار قبلی استفاده می کند
واقعی))۵۵ شرايط از بھتری انعکاس تجمعی معيار انحراف و ميانگين از واقعیاستفاده شرايط از بھتری انعکاس تجمعی معيار انحراف و ميانگين از استفاده ی )) ي و ر ز ری س بھ ی ج ر ي ر ين و ي ز ی ي و ر ز ری س بھ ی ج ر ي ر ين و ي ز استاست
نالیز روتین ماده کنترلی جهت تعییننالیز روتین ماده کنترلی جهت تعییناا
خطاهای احتمالی تصادفی و نظامندخطاهای احتمالی تصادفی و نظامند
توصيه می شود برای ھر آناليت حداقل از دو ماده کنترلی در سطوح متفاوت توصيه می شود برای ھر آناليت حداقل از دو ماده کنترلی در سطوح متفاوت ) ) ١١..تصميم گيری پزشکی استفاده شودتصميم گيری پزشکی استفاده شود
نمونه کنترل ھمانند نمونه بيمار مورد آناليز قرار می گيرد و قبل از گزارش نمونه کنترل ھمانند نمونه بيمار مورد آناليز قرار می گيرد و قبل از گزارش ) ) ٢٢نتايج بيمار، داده ھای نمونه کنترل مورد بررسی و تفسير قرار می گيرند و بعد از نتايج بيمار، داده ھای نمونه کنترل مورد بررسی و تفسير قرار می گيرند و بعد از
نمود گزارش را بيماران نتايج توان م نتايج اين نمودتأييد گزارش را بيماران نتايج توان م نتايج اين ..تأييد اين نتايج می توان نتايج بيماران را گزارش نمودتأييد اين نتايج می توان نتايج بيماران را گزارش نمودتأييدپايداری سيستم اندازه گيری شاخص اصلی تعيين فراوانی نياز به آزمون يک پايداری سيستم اندازه گيری شاخص اصلی تعيين فراوانی نياز به آزمون يک ) ) ٣٣
..نمونه کنترلی استنمونه کنترلی است
رفتغيير شماره ساخت معرفتغيير شماره ساخت معرف ت ر م رفيير ت ر م يير
تغيير شماره ساخت معرفتغيير شماره ساخت معرف
ناليتناليتاستفاده از دو روش براي اندازه گيري يك اياستفاده از دو روش براي اندازه گيري يك ا ي يري ز بري روش و يز ي يري ز بري روش و ز
WESTGARDWESTGARDWESTGARD WESTGARD MULTIRULE SYSTEMMULTIRULE SYSTEM
WESTGRAD RULESWESTGRAD RULESWESTGRAD RULESWESTGRAD RULES
1122SS1122SS1133SS2222SS2222SSRR44SS444411SS1010XX
1122 control rulecontrol rule1122ss control rulecontrol rule
+ 3 SD
+ 2 SD
+ 1 SD
2 SD
- 1 SDX
- 2 SD
- 3 SD
1133 control rulecontrol rule1133ss control rulecontrol rule
+ 3 SD
+ 2 SD
+ 1 SD
2 SD
- 1 SDX
- 2 SD
- 3 SD
2222 control rulecontrol rule2222ss control rulecontrol rule
+ 3 SD
+ 2 SD
+ 1 SD
2 SD
- 1 SDX
- 2 SD
- 3 SD
RR44 control rulecontrol ruleRR44ss control rulecontrol rule
+ 3 SD
+ 2 SD
+ 1 SD
2 SD
- 1 SDX
- 2 SD
- 3 SD
4411 control rulecontrol rule4411ss control rulecontrol rule
+ 3 SD
+ 2 SD
+ 1 SD
2 SD
- 1 SDX
- 2 SD
- 3 SD
1010 control rulecontrol rule1010xx control rulecontrol rule
+ 3 SD
+ 2 SD
+ 1 SD
2 SD
- 1 SDX
- 2 SD
- 3 SD
METHOD SIGMA QUALITYMETHOD SIGMA QUALITYMETHOD SIGMA QUALITY METHOD SIGMA QUALITY METRICSMETRICS
X = 90 mg/dL ; TEa = 10% ; SD = 3 mg/dL ; %CV = %3.3
Lower Spec limit
ProcessMean
UpperSpec.limitSpec.limit Mean Spec.limit
Three SigmaProcessProcess
3 2 1 1 3σσ σ σ 0 σ 2 σ
81 84 87 90 93 96 99
X = 90 mg/dL ; TEa = 10% ; SD = 1.5 mg/dL ; %CV = %1.7
Lower Spec limit
ProcessMean
UpperSpec.limitSpec.limit Mean Spec.limit
Six SigmaProcessProcess
6σ 5σ 4σ 3σ 2σ 1σ 0 1σ 2σ 3σ 4σ 5σ 6σ
81 82.5 84 85.5 87 88.5 90 91.5 93 94.5 96 97.5 99
Lower Spec limit
ProcessMean
UpperSpec.limitSpec.limit Mean Spec.limit
1.5σ 1.5σshift shift
Six SigmaProcessProcess
6σ 5σ 4σ 3σ 2σ 1σ 0 1σ 2σ 3σ 4σ 5σ 6σ
IncreasingIncreasing PPededIncreasing Increasing PPeded
By Using Narrower Control limitsBy Using Narrower Control limitsBy Using Narrower Control limitsBy Using Narrower Control limitse.g. e.g. 1122SS against against 1133SS
B U i M QC M t i lB U i M QC M t i lBy Using More QC MaterialsBy Using More QC Materialse.g. Low, Normal and Highe.g. Low, Normal and HighBy Using Fewer Control DataBy Using Fewer Control Datae ge g 88XX againstagainst 1212XXe.g. e.g. 88XX against against 1212XX
By Using By Using MultirulesMultirulese.g. e.g. 1133SS//2222SS
Recommended Rules For MethodsRecommended Rules For MethodsRecommended Rules For Methods Recommended Rules For Methods with different sigmawith different sigma
Rule(s)NSigma13S26125 12.5S2512.5S or 13S/22S/R4S/41S4413S/2of32SR4S/31S/6x 63
EXTERNAL QUALITY EXTERNAL QUALITY ASSESSMENTASSESSMENTASSESSMENTASSESSMENT
MATRIX EFFECTMATRIX EFFECT
NoncommutableNoncommutable SamplesSamples
EQA organizers often use commercially QC materials specifically prepared to ease transportation and storage, having relatively low cost and exhibits a low vial to vialhaving relatively low cost, and exhibits a low vial to vial variability. For this, control materials are commercially prepared by adding preservatives and other substances which may have adverse effects on the physicochemicalwhich may have adverse effects on the physicochemical properties of samples8.So, QC materials are frequently are noncommutable with clinical patient sample and they may produceclinical patient sample and they may produce significantly differenent results with different assays.
MATRIX EFFECTMATRIX EFFECT
Commutable SamplesCommutable Samples
Commutable Commutable samples are typically prepared by pooling samples are typically prepared by pooling clinical patient samples with minimal processing or clinical patient samples with minimal processing or additives to avoid any alteration ofadditives to avoid any alteration of samplesample matrixmatrixadditives to avoid any alteration of additives to avoid any alteration of sample sample matrixmatrixWhen commutable samples can be prepared, the results When commutable samples can be prepared, the results reflect what would be expected if patient samples were reflect what would be expected if patient samples were sent to each of the different laboratories So Agreementsent to each of the different laboratories So Agreementsent to each of the different laboratories. So. Agreement sent to each of the different laboratories. So. Agreement among different laboratories and methods can be among different laboratories and methods can be correctly evaluated.correctly evaluated.It has been challenging to prepare commutable materialsIt has been challenging to prepare commutable materialsIt has been challenging to prepare commutable materials It has been challenging to prepare commutable materials for use in large PT programs. However, use of for use in large PT programs. However, use of commutable materials adds substantial value to the commutable materials adds substantial value to the information information obtained obtained from the results. from the results.
Matrix EffectMatrix Effect
99thth EQAP HbAEQAP HbA11c Analysisc Analysis
%CVMeannMethod10.46.6580Pars Azmon 10.46.6580Pars Azmon12.05.3227Pishtaz Teb
26.510.81212Biosystem---Roche
8.66.07248NycoCard38.57.75567Total 38.57.75567Total
Matrix EffectMatrix Effect
1111thth EQAP HbAEQAP HbA11c Analysisc Analysis
%CVMeannMethod15.36.0985Pars Azmon 15.36.0985Pars Azmon12.85.4844Pishtaz Teb
21.08.56237Biosystem11.38.2615Roche13.76.33265NycoCard24.57.06646Total 24.57.06646Total
Matrix EffectMatrix Effect
1515thth EQAP HbAEQAP HbA11c Analysisc Analysis
%CVMeannMethod12.58.9035Pars Azmon5.39.0640Pishtaz Teb
11 28 5754Bi t 11.28.5754Biosystem5.69.518Roche5.29.3958NycoCard9.39.01195Total
Matrix EffectMatrix Effect
1717thth EQAP HbAEQAP HbA11c Analysisc Analysis
%CVMeannMethod11 59 4933Pars Azmon 11.59.4933Pars Azmon6.19.6843Pishtaz Teb
10.49.3854Biosystem7.710.3310Roche
12.49.8159NycoCard9 99 61199Total 9.99.61199Total
Matrix EffectMatrix Effect
1818thth EQAP HbAEQAP HbA11c Analysisc Analysis
%CVMeannMethod9 27 1896Pars Azmon 9.27.1896Pars Azmon
10.67.33100Pishtaz Teb
11.97.76229Biosystem4.47.8812Roche8.47.2387NycoCard11 17 49524Total 11.17.49524Total
DATA ANALYSIS FOR DATA ANALYSIS FOR O O S SO O S SINTERPRETATION OF RESULTSINTERPRETATION OF RESULTS
Evaluation of performance of each participant needs Evaluation of performance of each participant needs to establish two values:to establish two values:
11) Assigned (target) value of the test material) Assigned (target) value of the test material22) Acceptable range) Acceptable range
Different methods can be used to establish these Different methods can be used to establish these estimates, but there is no standard protocol estimates, but there is no standard protocol statistical parametersstatistical parametersstatistical parametersstatistical parameters
ESTABLISHING ASSIGNED VALUEESTABLISHING ASSIGNED VALUEESTABLISHING ASSIGNED VALUEESTABLISHING ASSIGNED VALUE
There are three methodsThere are three methods
11) The addition of a known amount or concentration ) The addition of a known amount or concentration ))of of analyteanalyte to a base material containing noneto a base material containing none
22) The use of a Consensus value produced by a group) The use of a Consensus value produced by a group22) The use of a Consensus value produced by a group ) The use of a Consensus value produced by a group of expert or referee laboratories using best possible of expert or referee laboratories using best possible methodsmethods
33) The use of a consensus value produced in each ) The use of a consensus value produced in each round of EQA, and based on the results by round of EQA, and based on the results by participantsparticipantsparticipantsparticipants
ESTABLISHING ASSIGNED VALUEESTABLISHING ASSIGNED VALUEFROM PARTICIPANT RESULTSFROM PARTICIPANT RESULTSFROM PARTICIPANT RESULTS FROM PARTICIPANT RESULTS
assigned value is consensus value (trimmed mean assigned value is consensus value (trimmed mean l ) d i d f ll lt b itt d bl ) d i d f ll lt b itt d bvalue) derived from all results submitted by value) derived from all results submitted by
participants in the scheme of that participants in the scheme of that analyteanalyte
P i l i h h h hP i l i h h h hPractical experiences has shown that the Practical experiences has shown that the consensus value usually agrees closely with the true consensus value usually agrees closely with the true value in schemes with a large number participantsvalue in schemes with a large number participants
Consensus value may not be valid in two conditions:Consensus value may not be valid in two conditions:11) Numbers of laboratories ) Numbers of laboratories is smallis small))22) A large proportion of participants have a significant) A large proportion of participants have a significant
analytical biasanalytical bias
ESTABLISHING ACCEPTABLE RANGEESTABLISHING ACCEPTABLE RANGEESTABLISHING ACCEPTABLE RANGEESTABLISHING ACCEPTABLE RANGE
After calculating method relating consensus value, After calculating method relating consensus value, acceptability criteria must be establishacceptability criteria must be establish
For this, statistical parameters are calculated, For this, statistical parameters are calculated, includingincluding
11) Mean (X)) Mean (X)) ( )) ( )22) Standard Deviation (SD)) Standard Deviation (SD)33) Coefficient of Variation (CV)) Coefficient of Variation (CV)
CV% = SD
Xx 100
X
ESTABLISHING ACCEPTABLE RANGEESTABLISHING ACCEPTABLE RANGEESTABLISHING ACCEPTABLE RANGEESTABLISHING ACCEPTABLE RANGE
Acceptability criteria may beAcceptability criteria may be11) Interval based on group SD (e.g., X ) Interval based on group SD (e.g., X ±± 22SD)SD)22) Fixed percentage (e.g., X ) Fixed percentage (e.g., X ±± constant percent)constant percent)) p g ( g ,) p g ( g , p )p )33) Fixed interval (e.g., X ) Fixed interval (e.g., X ±± constant amount)constant amount)
Alternatively scoring system may be usedAlternatively scoring system may be usedAlternatively, scoring system may be usedAlternatively, scoring system may be used11) ) Bias Index Score (BIS)Bias Index Score (BIS)22) Variance ) Variance Index Score (VISIndex Score (VIS))33) Standard ) Standard Deviation Index or Interval (SDIDeviation Index or Interval (SDI))
Z ScoreZ ScoreZ ScoreZ Score
Z = Xlab - Xpeer
SDSDpeer
BIS =
Xlab - Xpeer
Xpeer x 100SDI = Xlab - Xpeer
SD BIS = CCV%SDpeer
Chosen Coefficient of VariationChosen Coefficient of Variation(CCV)(CCV)(CCV)(CCV)
CCV are the lowest CVs obtained CCV are the lowest CVs obtained for particular determinations for particular determinations d i fi t t f th EQASd i fi t t f th EQASduring first two years of the EQASduring first two years of the EQAS
It is kept constant so that It is kept constant so that improvements in the performance improvements in the performance
f l b t i b d t t df l b t i b d t t dof laboratories can be detectedof laboratories can be detected
Is Numbers of member in peer group adequate?
No
Is CV% of
Data analysis is not valid
Yes
peer group suitable?
YesNo
What Is the result of data analysis?
UnacceptableWarnningExcellent or Good pg
Need error detection and correction
Follow next EQA ResultNeed no action
Peer GROUP PROGRAMPeer GROUP PROGRAMPeer GROUP PROGRAMPeer GROUP PROGRAMPeer Group Program Is A Combination of Peer Group Program Is A Combination of p gp gInternalInternal And And ExternalExternal Quality ControlQuality ControlWhen EQC Is Used In Conjunction With When EQC Is Used In Conjunction With D il IQC Thi P Will GiD il IQC Thi P Will GiDaily IQC, This Program Will Give Daily IQC, This Program Will Give Laboratories Laboratories Added ConfidenceAdded Confidence in Their in Their Patient Test ResultsPatient Test ResultsPatient Test ResultsPatient Test ResultsAll Labs Use The Same Control Material All Labs Use The Same Control Material and Report Their Results and Report Their Results DailyDailyData Are Analyzed And Reported Data Are Analyzed And Reported MonthlyMonthlyAs As SDISDI and and CVRCVR