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Accreditation and Quality Assurance: Journal for Quality, Comparability and Reliability in Chemical Measurement (v.11, #6)
The European Conference on quality in the spotlight in medical laboratories, Antwerp Belgium, 7–8 March 2005
by J. C. Libeer; H. M. J. Goldschmidt (pp. 263-264).
The European Conference on quality in the spotlight in medical laboratories, Antwerp Belgium, 7–8 March 2005
by J. C. Libeer; H. M. J. Goldschmidt (pp. 263-264).
Regulatory compliance vs. NEXUS quality for laboratory tests by Sharon S. Ehrmeyer; Ronald H. Laessig (pp. 265-268).
In the U.S., all clinical laboratory testing is regulated by the Clinical Laboratory Improvement Amendments (CLIA) ( http://www.phppo.cdc.gov/clia/regs/toc.aspx ). The CLIA link test quality and adherence to a body of testing regulations intended to ensure accurate, reliable, and timely patient test results. The goal of the CLIA legislation was to ensure a minimum, fundamental level of quality. In the context of “NEXUS,” quality must “go beyond getting the ‘right’ answer on the ‘right’ patient that can be interpreted against ‘right’ reference values. CLIA regulations with specific minimum, performance requirements, or safeguards, are designed to prevent testing errors. The US Institute of Medicine found that testing processes fail as a result of human error, lack of documentation, and lack of test management. In the latest (2004) interpretations of CLIA regulations, the minimum quality control requirement continues to be analyzing at least two external, liquid quality control materials per test per day. In 1995, we proposed that the responsibility for achieving quality test results shifts from the sole purview of the laboratory director to an “alliance” of laboratory professionals, manufacturers, and regulators. The EQC (equivalent quality control) concept as proposed is a positive step in achieving this alliance. With the obvious lack of scientific and statistical robustness, EQC falls far short of ensuring quality. Achieving the “NEXUS Vision” for quality laboratory testing will not come solely from laboratory professionals. The NEXUS is about how to ensure the full-quality assessment of the testing process – pre-analytical, analytical, and post-analytical.
Keywords: Clinical laboratory improvement amendments (CLIA); Laboratory quality regulations; Medical errors; Quality; Quality control; Equivalent quality control
Regulatory compliance vs. NEXUS quality for laboratory tests by Sharon S. Ehrmeyer; Ronald H. Laessig (pp. 265-268).
In the U.S., all clinical laboratory testing is regulated by the Clinical Laboratory Improvement Amendments (CLIA) ( http://www.phppo.cdc.gov/clia/regs/toc.aspx ). The CLIA link test quality and adherence to a body of testing regulations intended to ensure accurate, reliable, and timely patient test results. The goal of the CLIA legislation was to ensure a minimum, fundamental level of quality. In the context of “NEXUS,” quality must “go beyond getting the ‘right’ answer on the ‘right’ patient that can be interpreted against ‘right’ reference values. CLIA regulations with specific minimum, performance requirements, or safeguards, are designed to prevent testing errors. The US Institute of Medicine found that testing processes fail as a result of human error, lack of documentation, and lack of test management. In the latest (2004) interpretations of CLIA regulations, the minimum quality control requirement continues to be analyzing at least two external, liquid quality control materials per test per day. In 1995, we proposed that the responsibility for achieving quality test results shifts from the sole purview of the laboratory director to an “alliance” of laboratory professionals, manufacturers, and regulators. The EQC (equivalent quality control) concept as proposed is a positive step in achieving this alliance. With the obvious lack of scientific and statistical robustness, EQC falls far short of ensuring quality. Achieving the “NEXUS Vision” for quality laboratory testing will not come solely from laboratory professionals. The NEXUS is about how to ensure the full-quality assessment of the testing process – pre-analytical, analytical, and post-analytical.
Keywords: Clinical laboratory improvement amendments (CLIA); Laboratory quality regulations; Medical errors; Quality; Quality control; Equivalent quality control
Predictive values instead of normal ranges: less data, more information by Nico P. van Duijn (pp. 269-272).
Diagnostic strategies can have various goals at two levels: to facilitate the diagnostic process on the cognitive level, and to serve considerations on the level of the doctor–patient relationship. Requests for laboratory tests could be intended to exclude a disease or to affirm the presence of disease. Thirdly, tactical motives to smoothen the negotiations between doctor and patient probably seem to be important as well. These three intentions differ in prior probability, should lead to different sets of tests, and to different interpretations. Even the cut-off points should differ. This leads to three different decision strategies, both at requesting, as at interpreting the results. Following this line of thought, post-test probabilities are more suitable than normal ranges. Excluding strategy: this is the most prevalent. However, the disadvantage of an excluding strategy (prior 1–5%) is a false-positive result. A positive test result should lead to follow-up by wait and see or by repeated testing. More extensive testing usually is not a very sensible strategy. In practice, physicians simply ignore slightly abnormal values. Mentally they put the cut-off points for normality more broader. The number of tests is small. Confirmative strategy: the disadvantage of a confirmative intention (prior 10–30%) is a false-negative result. Follow-up without testing, repeated testing, or even accepting marginal normal results as abnormal is a proper strategy. The number of tests is moderate to high. Tactical strategy: the tactical intention strategy to reassure the patient – or avoid referrals – could lead to ignoring all slightly positive test results by choosing a higher cut-off point. Actually, considering the usual insignificant diagnostic gain when testing for tactical reasons, all test results are clinically insignificant, unsuspected outliers excluded. Here, a very limited set of tests should be chosen. The laboratory test is the currency in mutual trading medical expectations and relationship considerations between doctor and patient. The number of tests is minimal. If the physician chooses a strategy, a limited range of prior probability is chosen. Then a possibly computerized algorithm produces a “Value (posterior probability)” as test result, replacing “Value (normal ranges)”. Thus one number less on the lab form, yielding more significant information.
Keywords: Physician behaviour; Diagnostic strategy; Outcome quality
Predictive values instead of normal ranges: less data, more information by Nico P. van Duijn (pp. 269-272).
Diagnostic strategies can have various goals at two levels: to facilitate the diagnostic process on the cognitive level, and to serve considerations on the level of the doctor–patient relationship. Requests for laboratory tests could be intended to exclude a disease or to affirm the presence of disease. Thirdly, tactical motives to smoothen the negotiations between doctor and patient probably seem to be important as well. These three intentions differ in prior probability, should lead to different sets of tests, and to different interpretations. Even the cut-off points should differ. This leads to three different decision strategies, both at requesting, as at interpreting the results. Following this line of thought, post-test probabilities are more suitable than normal ranges. Excluding strategy: this is the most prevalent. However, the disadvantage of an excluding strategy (prior 1–5%) is a false-positive result. A positive test result should lead to follow-up by wait and see or by repeated testing. More extensive testing usually is not a very sensible strategy. In practice, physicians simply ignore slightly abnormal values. Mentally they put the cut-off points for normality more broader. The number of tests is small. Confirmative strategy: the disadvantage of a confirmative intention (prior 10–30%) is a false-negative result. Follow-up without testing, repeated testing, or even accepting marginal normal results as abnormal is a proper strategy. The number of tests is moderate to high. Tactical strategy: the tactical intention strategy to reassure the patient – or avoid referrals – could lead to ignoring all slightly positive test results by choosing a higher cut-off point. Actually, considering the usual insignificant diagnostic gain when testing for tactical reasons, all test results are clinically insignificant, unsuspected outliers excluded. Here, a very limited set of tests should be chosen. The laboratory test is the currency in mutual trading medical expectations and relationship considerations between doctor and patient. The number of tests is minimal. If the physician chooses a strategy, a limited range of prior probability is chosen. Then a possibly computerized algorithm produces a “Value (posterior probability)” as test result, replacing “Value (normal ranges)”. Thus one number less on the lab form, yielding more significant information.
Keywords: Physician behaviour; Diagnostic strategy; Outcome quality
Quality in point-of-care testing: taking POC to the next level by James H. Nichols (pp. 273-277).
Point-of-care testing (POCT) is a complex system with many opportunities for error. Delivering quality POCT requires multidisciplinary coordination and an understanding of the preanalytic, analytic, and postanalytic processes that are necessary to deliver a test result and take clinical action. Most errors in laboratory testing occur in the pre and postanalytical phases and many mistakes that are referred to as lab error are actually due to poor communication, actions by others involved in the testing process, or poorly designed processes outside the laboratory's control. POCT requires significant operator interaction with analysis and documentation of calibration and quality control, unlike other medical devices. Clinicians often interpret POCT as equivalent to core laboratory testing, only faster, and mistakenly utilize the results interchangeably despite the differences in test methodologies. Taking quality of POCT to the next level involves looking beyond the analytical phase and integration of POCT into the entire pathway of patient care to understand how POCT relates to medical decision-making at specific points during the patient's care. A systematic review of the literature by the National Academy of Clinical Biochemistry is currently being conducted to draft guidelines for best practice that link the use of POCT to improved patient outcomes.
Keywords: Point of care testing; Quality; Medical errors
Quality in point-of-care testing: taking POC to the next level by James H. Nichols (pp. 273-277).
Point-of-care testing (POCT) is a complex system with many opportunities for error. Delivering quality POCT requires multidisciplinary coordination and an understanding of the preanalytic, analytic, and postanalytic processes that are necessary to deliver a test result and take clinical action. Most errors in laboratory testing occur in the pre and postanalytical phases and many mistakes that are referred to as lab error are actually due to poor communication, actions by others involved in the testing process, or poorly designed processes outside the laboratory's control. POCT requires significant operator interaction with analysis and documentation of calibration and quality control, unlike other medical devices. Clinicians often interpret POCT as equivalent to core laboratory testing, only faster, and mistakenly utilize the results interchangeably despite the differences in test methodologies. Taking quality of POCT to the next level involves looking beyond the analytical phase and integration of POCT into the entire pathway of patient care to understand how POCT relates to medical decision-making at specific points during the patient's care. A systematic review of the literature by the National Academy of Clinical Biochemistry is currently being conducted to draft guidelines for best practice that link the use of POCT to improved patient outcomes.
Keywords: Point of care testing; Quality; Medical errors
Quality improvement in wellness reports in patients with Crohn’s disease by Lone G. M. Jørgensen; Henrik Hey; Ivan Brandslund; Martin Eivindson; Ida Vind; Henning Grønbæk; Søren Jensen; Per Hyltoft Petersen (pp. 278-283).
Quality-of-life tests are used because they provide information about symptoms, potential complications, and response to treatment with patients as active participants. We took Crohn’s disease (CD) during diet supplement with omega 3 or 6 fatty acids (ω-3FA vs. ω-6FA) Impact® as an example and assessed three quality-of-life tests: The inflammatory bowel disease questionnaire (IBDQ), the Beck depression inventory (BDI), and the visual analogue scale (VAS). These tests have been found inconvenient, not informative in daily clinical use, and inhomogeneous in international studies.We used the body mass index (BMI) (kg/m2) as a clinical quantitative effect parameter and the patient self-rated quality of life as qualitative variables during recovery. All ratings were converted into numeric standardized percent point before isolation of optimized ratings.BMI increased on average 2 BMI units in both diet groups. The classical wellness tests or their traditional sub-scores identified improved outcome during recovery, primarily in the ω-3FA group. Separate items on bowel function, wellness, and asthenia possessed the best item responsiveness – (30–35 percent point). A new selective scale with the six most responsive items is proposed as a specific optimized questionnaire.Based on CD as an example, we described a method to isolate responsive items from quality-of-life tests and described a method to optimize their sensitivity. We propose for validation a new optimized disease – specific VAS scale for rating of wellness during treatment in inflammatory bowel disease, in which ω-3FA seemed superior in improving outcome.
Keywords: Quality of life; Sensitivity; Standardization of medical scoring scales
Quality improvement in wellness reports in patients with Crohn’s disease by Lone G. M. Jørgensen; Henrik Hey; Ivan Brandslund; Martin Eivindson; Ida Vind; Henning Grønbæk; Søren Jensen; Per Hyltoft Petersen (pp. 278-283).
Quality-of-life tests are used because they provide information about symptoms, potential complications, and response to treatment with patients as active participants. We took Crohn’s disease (CD) during diet supplement with omega 3 or 6 fatty acids (ω-3FA vs. ω-6FA) Impact® as an example and assessed three quality-of-life tests: The inflammatory bowel disease questionnaire (IBDQ), the Beck depression inventory (BDI), and the visual analogue scale (VAS). These tests have been found inconvenient, not informative in daily clinical use, and inhomogeneous in international studies.We used the body mass index (BMI) (kg/m2) as a clinical quantitative effect parameter and the patient self-rated quality of life as qualitative variables during recovery. All ratings were converted into numeric standardized percent point before isolation of optimized ratings.BMI increased on average 2 BMI units in both diet groups. The classical wellness tests or their traditional sub-scores identified improved outcome during recovery, primarily in the ω-3FA group. Separate items on bowel function, wellness, and asthenia possessed the best item responsiveness – (30–35 percent point). A new selective scale with the six most responsive items is proposed as a specific optimized questionnaire.Based on CD as an example, we described a method to isolate responsive items from quality-of-life tests and described a method to optimize their sensitivity. We propose for validation a new optimized disease – specific VAS scale for rating of wellness during treatment in inflammatory bowel disease, in which ω-3FA seemed superior in improving outcome.
Keywords: Quality of life; Sensitivity; Standardization of medical scoring scales
Laboratory guidelines and standards in clinical and forensic toxicology by Joris Penders; Alain Verstraete (pp. 284-290).
An overview is given of the existing standards and guidelines for analytical toxicology. Details about guidelines concerning forensic toxicology, clinical toxicology, point-of-care testing, and an area of overlap are provided. Guidelines and standards exist for forensic toxicological analysis in general and for specific situations, e.g., workplace drug testing and driving under the influence of drugs and alcohol. For workplace drug testing, detailed guidelines exist in the U.S.A., Australia, and Europe describing for example the methods used, their cut-off and the process of sample handling. Some governments describe the methods and quality requirements for blood alcohol testing for driving under the influence of alcohol in detail in their laws. In the area of clinical toxicology, guidelines not only focus on the analytical aspects of analysis but also on the timeliness of results. According to the US- and UK-based practice guidelines for the emergency department, the turn-around time should be 1 or 2 h, respectively, for a specific set of analytes. Guidelines are either being developed now or already available (e.g., workplace drug testing, breath alcohol analysis) for point-of-care testing in analytical toxicology. In the context of brain death and sexual assault cases, specific demands need to be imposed because of the unique aspects of drug analysis in these situations (variety of drugs used, low concentrations). Many guidelines and standards are available and it is up to every laboratory to choose the best ones depending on the area of activity and the legal and regulatory environment.
Keywords: Guideline; Quality assurance; Standard; Substance abuse; Toxicology
Laboratory guidelines and standards in clinical and forensic toxicology by Joris Penders; Alain Verstraete (pp. 284-290).
An overview is given of the existing standards and guidelines for analytical toxicology. Details about guidelines concerning forensic toxicology, clinical toxicology, point-of-care testing, and an area of overlap are provided. Guidelines and standards exist for forensic toxicological analysis in general and for specific situations, e.g., workplace drug testing and driving under the influence of drugs and alcohol. For workplace drug testing, detailed guidelines exist in the U.S.A., Australia, and Europe describing for example the methods used, their cut-off and the process of sample handling. Some governments describe the methods and quality requirements for blood alcohol testing for driving under the influence of alcohol in detail in their laws. In the area of clinical toxicology, guidelines not only focus on the analytical aspects of analysis but also on the timeliness of results. According to the US- and UK-based practice guidelines for the emergency department, the turn-around time should be 1 or 2 h, respectively, for a specific set of analytes. Guidelines are either being developed now or already available (e.g., workplace drug testing, breath alcohol analysis) for point-of-care testing in analytical toxicology. In the context of brain death and sexual assault cases, specific demands need to be imposed because of the unique aspects of drug analysis in these situations (variety of drugs used, low concentrations). Many guidelines and standards are available and it is up to every laboratory to choose the best ones depending on the area of activity and the legal and regulatory environment.
Keywords: Guideline; Quality assurance; Standard; Substance abuse; Toxicology
Towards quality specifications in extra-analytical phases of laboratory services: What information on quality specifications should be communicated to clinicians, and how? by Mario Plebani (pp. 291-296).
Quality specifications, the level of performance required to facilitate clinical decision-making, not only have a central role in quality management in clinical laboratories, but are also essential for assuring the interpretation and utilization of laboratory information by clinicians. Laboratory tests have been grouped into five categories and the most suitable ways to communicate quality specifications to clinicians have been proposed. In particular, for tests with a uni-modal distribution, decision limits should replace the traditional reference values. For tests with a bi-modal distribution, in addition to reference values, some flags based on the uncertainty of laboratory data, can be included in the report. For tests used in patients monitoring and in evaluating the response to therapy, the reference change value or the most effective threshold of the difference between two consecutive results should be indicated. For tests/test batteries that require interpretative comments, these should be added on a regular basis. Lastly, pre- and post-test counseling is mandatory for genetic testing.
Keywords: Quality specifications; Appropriateness; Test request; Interpretation; Interpretative comments
Towards quality specifications in extra-analytical phases of laboratory services: What information on quality specifications should be communicated to clinicians, and how? by Mario Plebani (pp. 291-296).
Quality specifications, the level of performance required to facilitate clinical decision-making, not only have a central role in quality management in clinical laboratories, but are also essential for assuring the interpretation and utilization of laboratory information by clinicians. Laboratory tests have been grouped into five categories and the most suitable ways to communicate quality specifications to clinicians have been proposed. In particular, for tests with a uni-modal distribution, decision limits should replace the traditional reference values. For tests with a bi-modal distribution, in addition to reference values, some flags based on the uncertainty of laboratory data, can be included in the report. For tests used in patients monitoring and in evaluating the response to therapy, the reference change value or the most effective threshold of the difference between two consecutive results should be indicated. For tests/test batteries that require interpretative comments, these should be added on a regular basis. Lastly, pre- and post-test counseling is mandatory for genetic testing.
Keywords: Quality specifications; Appropriateness; Test request; Interpretation; Interpretative comments
Sensitivity and significance of disease outcome measures in inflammatory bowel disease by Lone G. M. Jørgensen (pp. 297-302).
In inflammatory bowel disease (IBD), proxy measures of clinical outcome are often collected into summary indices of qualitative self-rated disease markers, clinical observations, and quantitative biochemical analyses. In Crohn's disease (CD), a frequently used index is the Crohn's disease activity index (DCAI). This index consists of six qualitative variables and two quantitative variables. The aim of this presentation is to illustrate the use of this index to calculate its range, to estimate errors in the index, its sensitivity, and the number of significant steps in the index. The measure of sensitivity of the summary index was analyzed for the signal-to-noise ratio (SNR), the reference change value (RCV) and the confidence interval (CI). If identical errors were assumed in patient self-rated health and clinically judged disease manifestations, such as tumours and fistulas, the majority of the variance of the index was caused by the self-rated experience of health, the number of days over which the individual variable was rated, and the prognostic multiplier of each variable.The range of the index has no upper limit, but can be estimated to 403 units, of which patient self-rating of well-being account for up to one-third of the summary index maximal score range. The median signal noise measure of index sensitivity was 18 SDs. The two disease classification limits of 150 units for moderate disease and 450 for severe disease on average cover an interval of limit ±41.5 units vs. ±60.5 units. In judgments on change in clinical outcome the RCV interval of steps of 121 units are valid. Conclusion: Both variance and range of the CDAI summary score are primarily decided by the self-rated experience of well-being. Variables on disease signs have a minor impact on the index. Rating of the two important outcome parameters: Self-experienced health and medical outcome would favourably be given in two individual scores.
Keywords: Clinical outcome; Crohn's disease; Inflammatory bowel disease; Prognostic factors; Quality assessment; Signal-to-noise ratio; Ulcerative colitis
Sensitivity and significance of disease outcome measures in inflammatory bowel disease by Lone G. M. Jørgensen (pp. 297-302).
In inflammatory bowel disease (IBD), proxy measures of clinical outcome are often collected into summary indices of qualitative self-rated disease markers, clinical observations, and quantitative biochemical analyses. In Crohn's disease (CD), a frequently used index is the Crohn's disease activity index (DCAI). This index consists of six qualitative variables and two quantitative variables. The aim of this presentation is to illustrate the use of this index to calculate its range, to estimate errors in the index, its sensitivity, and the number of significant steps in the index. The measure of sensitivity of the summary index was analyzed for the signal-to-noise ratio (SNR), the reference change value (RCV) and the confidence interval (CI). If identical errors were assumed in patient self-rated health and clinically judged disease manifestations, such as tumours and fistulas, the majority of the variance of the index was caused by the self-rated experience of health, the number of days over which the individual variable was rated, and the prognostic multiplier of each variable.The range of the index has no upper limit, but can be estimated to 403 units, of which patient self-rating of well-being account for up to one-third of the summary index maximal score range. The median signal noise measure of index sensitivity was 18 SDs. The two disease classification limits of 150 units for moderate disease and 450 for severe disease on average cover an interval of limit ±41.5 units vs. ±60.5 units. In judgments on change in clinical outcome the RCV interval of steps of 121 units are valid. Conclusion: Both variance and range of the CDAI summary score are primarily decided by the self-rated experience of well-being. Variables on disease signs have a minor impact on the index. Rating of the two important outcome parameters: Self-experienced health and medical outcome would favourably be given in two individual scores.
Keywords: Clinical outcome; Crohn's disease; Inflammatory bowel disease; Prognostic factors; Quality assessment; Signal-to-noise ratio; Ulcerative colitis
The DNSev™ expert system in the auto-verification of tumour markers and hormones results by Romolo M. Dorizzi; Beatrice Caruso; Sandra Meneghelli; Paolo Rizzotti (pp. 303-307).
Most of the immunoassays workload is processed in clinical laboratories within a time span comparable to the clinical chemistry and the haematology assays and the analytical work is usually completed between 1:00 and 2:00 p.m. In order to accelerate the auto-verification of the results of tumour markers (Total and free PSA, CEA, CA 125, CA 15-3, CA 19-9, TPA, AFP, NSE, S 100 protein), and hormones (TSH, FT4, FT3, Prolactin, total testosterone) and Procalcitonin (PCT) we used DNSevTM expert system implementing 13 rules based on decision levels/reference intervals and reference change values. The auto-verification procedure has been implemented after a 6-month trial in June 2004 and in 2005 the immunoassays section supervisor was able to verify about 500 results in about 30 min 5 days/week. We conclude that the auto-verification of immunoassays implemented in our laboratory is fast and consistent among different supervisors and leaves more time for an effective and timely interaction with clinicians and general practitioners.
Keywords: Auto-verification; Auto-validation; Tumour markers; Hormones; Reference change value
The DNSev™ expert system in the auto-verification of tumour markers and hormones results by Romolo M. Dorizzi; Beatrice Caruso; Sandra Meneghelli; Paolo Rizzotti (pp. 303-307).
Most of the immunoassays workload is processed in clinical laboratories within a time span comparable to the clinical chemistry and the haematology assays and the analytical work is usually completed between 1:00 and 2:00 p.m. In order to accelerate the auto-verification of the results of tumour markers (Total and free PSA, CEA, CA 125, CA 15-3, CA 19-9, TPA, AFP, NSE, S 100 protein), and hormones (TSH, FT4, FT3, Prolactin, total testosterone) and Procalcitonin (PCT) we used DNSevTM expert system implementing 13 rules based on decision levels/reference intervals and reference change values. The auto-verification procedure has been implemented after a 6-month trial in June 2004 and in 2005 the immunoassays section supervisor was able to verify about 500 results in about 30 min 5 days/week. We conclude that the auto-verification of immunoassays implemented in our laboratory is fast and consistent among different supervisors and leaves more time for an effective and timely interaction with clinicians and general practitioners.
Keywords: Auto-verification; Auto-validation; Tumour markers; Hormones; Reference change value
Estimation of the biological variation of glucose-6-phosphate dehydrogenase in dried blood spots by George J. Reclos; Tijen Tanyalcin; Kenneth A. Pass (pp. 308-312).
Models based on biological variation provide a well-accepted database with reliable information for clinical laboratories for all purposes including screening, diagnosis and follow-up. Newborn screening laboratories use a blood spotted paper matrix to measure the analytes. This matrix medium is certainly different than body fluid matrix medium. After long-term monitoring of the performance of the Glucose-6-Phosphate Dehydrogenase Kit (R&D Diagnostics OSMMR 2000-D G6PD), the results obtained from the variation analysis were statistically evaluated. Analytical coefficient of variation, CV A, was found to be 5.41%. The CV A derived from between run assays was 5.32%, while within-subject biological coefficient of variation, CV I, was 7.26%. Since minimum performance is defined as CV A< 0.750 CV I , CV A should be lower than 5.44%. The analytical bias in calculation of total error $$B_{
m A} < 0.375reak sqrt {left( {it CV_{
m I}}
ight)^2 + left( {it CV_{
m G}}
ight)^2}$$ was chosen to evaluate the performance of this assay. In this aspect, CV G, between-subject biological coefficient of variation, was found to be equal to 10.35%. B A was found to be 4.12%, which is lower than 4.74%, which means that it is acceptable. Therefore, the minimum quality specification for total error allowable is $${it TE}_{
m a} < 1.65(0.75,CV_{
m I} ) + {
m }0.375sqrt {left( {
m CV_{
m I}}
ight)^2 + left( {
m CV_{
m G}}
ight)^2 }$$ . When the relevant results obtained in this study were substituted in this formula, TE a was found to be 13.7% for G6PD measurement in dried blood spots on paper filter matrix. It is expected that this figure will be helpful for the performance evaluation of newborn screening laboratories performing G6PD screening. We have been using error grid graphs for the evaluation of our external quality assurance survey results for the last two years, only because there was no data for assays employing filter matrix. Even the TE a already reported for EDTA whole blood samples used in G6PD assays has been remarkably high, which can easily create the wrong impression that G6PD is not a reliable test to perform from blood spot cards. The present study shows that this assay is adequately reliable even when performed from dried blood spot matrix. However, we believe that the combination of total allowable error, error grid graphs with a well-defined cut off is the best approach to obtain an accurate performance evaluation for this test.
Keywords: Biological variation; Glucose-6-phosphate dehydrogenase; Total allowable error; Error grid graph; Index of individuality
Estimation of the biological variation of glucose-6-phosphate dehydrogenase in dried blood spots by George J. Reclos; Tijen Tanyalcin; Kenneth A. Pass (pp. 308-312).
Models based on biological variation provide a well-accepted database with reliable information for clinical laboratories for all purposes including screening, diagnosis and follow-up. Newborn screening laboratories use a blood spotted paper matrix to measure the analytes. This matrix medium is certainly different than body fluid matrix medium. After long-term monitoring of the performance of the Glucose-6-Phosphate Dehydrogenase Kit (R&D Diagnostics OSMMR 2000-D G6PD), the results obtained from the variation analysis were statistically evaluated. Analytical coefficient of variation, CV A, was found to be 5.41%. The CV A derived from between run assays was 5.32%, while within-subject biological coefficient of variation, CV I, was 7.26%. Since minimum performance is defined as CV A< 0.750 CV I , CV A should be lower than 5.44%. The analytical bias in calculation of total error $$B_{
m A} < 0.375reak sqrt {left( {it CV_{
m I}}
ight)^2 + left( {it CV_{
m G}}
ight)^2}$$ was chosen to evaluate the performance of this assay. In this aspect, CV G, between-subject biological coefficient of variation, was found to be equal to 10.35%. B A was found to be 4.12%, which is lower than 4.74%, which means that it is acceptable. Therefore, the minimum quality specification for total error allowable is $${it TE}_{
m a} < 1.65(0.75,CV_{
m I} ) + {
m }0.375sqrt {left( {
m CV_{
m I}}
ight)^2 + left( {
m CV_{
m G}}
ight)^2 }$$ . When the relevant results obtained in this study were substituted in this formula, TE a was found to be 13.7% for G6PD measurement in dried blood spots on paper filter matrix. It is expected that this figure will be helpful for the performance evaluation of newborn screening laboratories performing G6PD screening. We have been using error grid graphs for the evaluation of our external quality assurance survey results for the last two years, only because there was no data for assays employing filter matrix. Even the TE a already reported for EDTA whole blood samples used in G6PD assays has been remarkably high, which can easily create the wrong impression that G6PD is not a reliable test to perform from blood spot cards. The present study shows that this assay is adequately reliable even when performed from dried blood spot matrix. However, we believe that the combination of total allowable error, error grid graphs with a well-defined cut off is the best approach to obtain an accurate performance evaluation for this test.
Keywords: Biological variation; Glucose-6-phosphate dehydrogenase; Total allowable error; Error grid graph; Index of individuality