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Haeckel R.,Bremer Zentrum For Laboratoriumsmedizin | Wosniok W.,University of Bremen | Al Shareef N.,Ministry of Health Laboratory
Clinical Chemistry and Laboratory Medicine | Year: 2011

Method comparisons are indispensable tools for the extensive validation of analytic procedures. Laboratories often only want to know whether an established procedure (x-method) can be replaced by another one (y-method) without interfering with diagnostic purposes. Then split patients' samples are analyzed more or less simultaneously with both procedures designed to measure the same quantity. The measured values are usually presented graphically as a scatter or difference plots. The two methods are considered to be equivalent (comparable) if the data pairs scatter around the line of equality (x=y line) within permissible equivalence lines. It is proposed to derive these limits of permissible imprecision limits which are based on false-positive error rates. If all data pairs are within the limits, both methods lead to comparable false error rates. If one or more data pairs are outside the permissible equivalence limits, the x-method cannot simply be replaced by the y-method and further studies are required. The discordance may be caused either by aberrant values (outliers), non-linearity, bias or a higher variation of e.g., the y-values. The spread around the line of best fit can detect possible interferences if more than 1% of the data pairs are outside permissible spread lines in a scatter plot. Because bias between methods and imprecision can be inter-related, both require specific examinations for their identification. © 2011 by Walter de Gruyter Berlin Boston 2011.

Haeckel R.,Bremer Zentrum For Laboratoriumsmedizin | Wosniok W.,University of Bremen | Streichert T.,Universitatsklinik Cologne
Clinical Chemistry and Laboratory Medicine | Year: 2015

The organizers of the first EFLM Strategic Conference "Defining analytical performance goals" identified three models for defining analytical performance goals in laboratory medicine. Whereas the highest level of model 1 (outcome studies) is difficult to implement, the other levels are more or less based on subjective opinions of experts, with models 2 (based on biological variation) and 3 (defined by the state-of-the-art) being more objective. A working group of the German Society of Clinical Chemistry and Laboratory Medicine (DGKL) proposes a combination of models 2 and 3 to overcome some disadvantages inherent to both models. In the new model, the permissible imprecision is not defined as a constant proportion of biological variation but by a non-linear relationship between permissible analytical and biological variation. Furthermore, the permissible imprecision is referred to the target quantity value. The biological variation is derived from the reference interval, if appropriate, after logarithmic transformation of the reference limits. © 2015 by De Gruyter.

Haeckel R.,Bremer Zentrum For Laboratoriumsmedizin | Wosniok W.,University of Bremen | Kratochvila J.,SEKK Pardubice | Carobene A.,Universitario ffaele
Clinical Chemistry and Laboratory Medicine | Year: 2012

Permissible limits for internal and external quality assurance are either based on biological variation or on the state of the art (technical feasibility). The former approach has a scien-tific basis, but, in some cases, leads to limits which are either not achievable under the present technology, or which are not stringent enough. If proficiency testing is mandatory, stringent limits which cannot be fulfilled by the majority of laboratories could lead to juristic consequences. Therefore, most national guidelines were based on the state of the art, however, without providing the underlying reasoning. A simple algorithm for permissible limits in external quality assessment schemes (EQAS) is proposed based on biological variation, technical feasibility and correlated to the rate of false positive results. The proposed limits are compared with some limits from several EQAS (RiliBÄK, SEKK, RCPA, CLIA, PROLARIT). The suggested limits are slightly more stringent than the German RiliBÄK, less stringent than the Australasian guidelines and agreed best with the Czech SEKK and the Italian PROLARIT scheme. The graphical presentation of permissible limits strictly derived of biological variation with the proposed limits led to straight lines with different slopes and a cross-over at the limits for quantities with a medium biological variation (e.g., trijodthyronine). The greatest discordance between the various recommendations was observed for calcium, chloride, hemoglobin A1c and sodium. © 2012 by Walter de Gruyter • Berlin • Boston.

Haeckel R.,Bremer Zentrum For Laboratoriumsmedizin | Wosniok W.,University of Bremen
Clinical Chemistry and Laboratory Medicine | Year: 2011

Background: Permissible limits of analytical imprecision and bias are usually derived either from biological variability or from the state of the art. Both concepts require information from external sources which often lack transparency and are difficult to integrate in medical decision-making. Additionally, physicians may be interested in knowing the probability of decision errors due to analytical uncertainty. Therefore, an approach was developed which combines all three concepts. Methods: The empirical (observed) biological variation was derived from reference ranges used by the laboratory (CVE). CVE was corrected to get the biological variation in the theoretical absence of analytical imprecision (CVC). Relatively simple equations were derived from the relationship between biological variation and the analytical imprecision (CVA) to calculate permissible imprecision and bias. Five quality classes are proposed for the various analytes reflecting the false-positive error rates (FPR). These classes characterize analytical procedures according to their theoretical specificity (FPR). Thus, the new approach combines the theoretical base of biological variation with the technical state-of-the-art. Results and conclusions: As practical examples, the permissible imprecision and bias limits were estimated for a selection of quantities. The limits found were more realistic than present proposals based on Cotlove's rule (fixed fraction of biological variation), but slightly more stringent than national consensus values based on the state-of-the-art. Imprecision and bias do not affect FPR equally, and, therefore, should be assessed separately. It is proposed to insert monthly imprecision and bias results calculated after each control cycle in a table with five quality classes. This table provides a simple overview of the analytical quality performance of the entire laboratory with one glance and can be handled on the Excel platform. © 2011 by Walter de Gruyter Berlin New York.

Zierk J.,Friedrich - Alexander - University, Erlangen - Nuremberg | Arzideh F.,University of Bremen | Rechenauer T.,Friedrich - Alexander - University, Erlangen - Nuremberg | Haeckel R.,Bremer Zentrum For Laboratoriumsmedizin | And 3 more authors.
Clinical Chemistry | Year: 2015

BACKGROUND: Pediatric laboratory test results must be interpreted in the context of interindividual variation and age- and sex-dependent dynamics. Reference intervals as presently defined for separate age groups can only approximate the age-related dynamics encountered in pediatrics. Continuous reference intervals from birth to adulthood are not available for most laboratory analytes because of the ethical and practical constraints of defining reference intervals using a population of healthy community children. We applied an indirect method to generate continuous reference intervals for 22 hematologic and biochemical analytes by analyzing clinical laboratory data from blood samples taken during clinical care of patients. METHODS: We included samples from 32 000 different inpatients and outpatients (167 000 samples per analyte) from a German pediatric tertiary care center. Measurements were performed on a Sysmex-XE 2100 and a Cobas Integra 800 during clinical care over a 6-year period. The distribution of samples considered normal was estimated with an established indirect statistical approach and used for the calculation of reference intervals. RESULTS: We provide continuous reference intervals from birth to adulthood for 9 hematology analytes (hemoglobin, hematocrit, red cell indices, red cell count, red cell distribution width, white cell count, and platelet count) and 13 biochemical analytes (sodium, chloride, potassium, calcium, magnesium, phosphate, creatinine, aspartate transaminase, alanine transaminase, γ-glutamyltransferase, alkaline phosphatase, lactate dehydrogenase, and total protein). CONCLUSIONS: Continuous reference intervals capture the population changes in laboratory analytes during pediatric development more accurately than age groups. After local validation, the reference intervals provided should allow a more precise consideration of these dynamics in clinical decision making. © 2015 American Association for Clinical Chemistry.

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