Plasma creatinine medians from patients partitioned by gender and age used as a tool for assessment of analytical stability at different concentrations.

Background Monthly medians of patient results are useful in assessment of analytical quality in medical laboratories. Separate medians by gender makes it possible to generate two independent estimates of contemporaneous errors. However, for plasma creatinine, reference intervals (RIs) are different by gender and also higher over 70 years of age. Methods Daily, weekly and monthly patient medians were calculated from the raw data of plasma creatinine concentrations for males between 18 and 70 years, males >70 years, females between 18 and 70 years and females >70 years. Results The medians of the four groups were all closely associated, with similar patterns. The mean of percentage bias from each group defined the best estimate of bias. The maximum half-range (%) of the bias evaluations provided an estimate of the uncertainty comparable to the analytical performance specifications: thus, bias estimates could be classified as optimum, desirable or minimum quality. Conclusions Medians by gender and age are useful in assessment of analytical stability for plasma creatinine concentration ranging from 60 to 90 µmol/L. The daily medians are valuable in rapid detection of large systematic errors, the weekly medians in detecting minor systematic errors and monthly medians in assessment of long-term analytical stability.

Gender-partitioned patient medians of serum albumin requested by general practitioners for the assessment of analytical stability.

BACKGROUND: Recently, the use of separate gender-partitioned patient medians of serum sodium has revealed potential for monitoring analytical stability within the optimum analytical performance specifications for laboratory medicine. The serum albumin concentration depends on whether a patient is sitting or recumbent during phlebotomy. We therefore investigated only examinations requested by general practitioners (GPs) to provide data from sitting patients. METHODS: Weekly and monthly patient medians of serum albumin requested by GP for both male and female patients were calculated from the raw data obtained from three analysers in the hospital laboratory on examination of samples from those >18 years. The half-range of medians were applied as an estimate of the maximum bias. Further, the ratios between the two medians were calculated (females/males). RESULTS: The medians for male and female patients were closely related despite considerable variation due to the current analytical variation. This relationship was confirmed by the calculated half-range for the monthly ratio between the genders of 0.44%, which surpasses the optimum analytical performance specification for bias of serum albumin (0.72%). The weekly ratio had a half-range of 1.83%, which surpasses the minimum analytical performance specifications of 2.15%. CONCLUSIONS: Monthly gender-partitioned patient medians of serum albumin are useful for monitoring of long-term analytical stability, where the gender medians are two independent estimates of changes in (delta) bias: only results requested by GP are of value in this application to ensure that all patients are sitting during phlebotomy.

Within-subject biological variation of activated partial thromboplastin time, prothrombin time, fibrinogen, factor VIII and von Willebrand factor in pregnant women.

BACKGROUND: During pregnancy, interpretation of results from coagulation parameters can be difficult as the physiological changes that occur may affect the biochemical parameters. The aim of this study was to describe the normal course of five coagulation parameters in healthy pregnancies, and to estimate the within-subject biological variation (CVI). METHODS: Blood samples were obtained every 4th week during pregnancy and three samples after delivery in 20 healthy women and every 4th week during a 40-week period in 19 healthy non-pregnant women. Activated partial thromboplastin time (APTT), prothrombin time (PT), PT International Normalized Ratio (INR), fibrinogen, factor VIII clot (FVIII:C) and von Willebrand factor antigen (vWF:Ag) were analyzed. The physiological changes during pregnancy were compensated by transformation into multiples of the median (MoM) and it is natural logarithm (lnMoM) in order to establish a kind of steady state, and CVI was calculated from the standard deviation. RESULTS: During pregnancy, APTT, PT and INR remained unchanged or decreased, depending upon the reagent used, while fibrinogen, FVIII:C and vWF:Ag increased gradually until delivery. The CVI in pregnancy were 2.2 and 3.0% for APTT, 2.3 and 2.6% for PT, 2.2 and 2.3% for INR, 7.2% for fibrinogen, 12.2% for FVIII:C and 11.3% for vWF:Ag, and corresponded with the CVI in non-pregnant women. CONCLUSIONS: Transformation of coagulation parameters in healthy pregnancies to MoM is a tool to establish a kind of steady state. Although there is a physiological change in these coagulation parameters during pregnancy, the CVI after lnMoM transformation was comparable with the CVI of non-pregnant women.

Separate patient serum sodium medians from males and females provide independent information on analytical bias.

BACKGROUND: During monitoring of monthly medians of results from patients undertaken to assess analytical stability in routine laboratory performance, the medians for serum sodium for male and female patients were found to be significantly related. METHODS: Daily, weekly and monthly patient medians of serum sodium for both male and female patients were calculated from results obtained on samples from the population >18 years on three analysers in the hospital laboratory. The half-range of medians was applied as an estimate of the maximum bias. Further, the ratios between the two medians were calculated. RESULTS: The medians of both genders demonstrated dispersions over time, but they were closely connected in like patterns, which were confirmed by the half-range of the ratios of medians for males and females that varied from 0.36% for daily, 0.14% for weekly and 0.036% for monthly ratios over all instruments. CONCLUSIONS: The tight relationship between the gender medians for serum sodium is only possible when raw laboratory data are used for calculation. The two patient medians can be used to confirm both and are useful as independent estimates of analytical bias during constant calibration periods. In contrast to the gender combined median, the estimate of analytical bias can be confirmed further by calculation of the ratios of medians for males and females.

Biological Variation: The Effect of Different Distributions on Estimated Within-Person Variation and Reference Change Values.

BACKGROUND: Good estimates of within-person biological variation, CVI, are essential for diagnosing and monitoring patients and for setting analytical performance specifications. The aim of the present study was to use computer simulations to evaluate the impact of various measurement distributions on different methods for estimating CVI and reference change value (RCV). METHOD: Data were simulated on the basis of 3 models for distributions of the within-person effect. We evaluated 3 different methods for estimating CVI: standard ANOVA, ln-ANOVA, and CV-ANOVA, and 3 different methods for calculating RCV: classic, ln-RCV, and a nonparametric method. We estimated CVI and RCV with the different methods and compared the results with the true values. RESULTS: The performance of the methods varied, depending on both the size of the CVI and the type of distributions. The CV-ANOVA model performed well for the estimation of CVI with all simulated data. The ln-RCV method performed best if data were ln-normal distributed or CVI was less than approximately 12%. The nonparametric RCV method performed well for all simulated data but was less precise. CONCLUSIONS: The CV-ANOVA model is recommended for both calculation of CVI and the step-by-step approach of checking for outliers and homogeneity in replicates and samples. The standard method for calculation of RCV should not be used when using CVs.

Clinical Use of Cancer Biomarkers in Epithelial Ovarian Cancer: Updated Guidelines From the European Group on Tumor Markers.

OBJECTIVE: To present an update of the European Group on Tumor Markers guidelines for serum markers in epithelial ovarian cancer. METHODS: Systematic literature survey from 2008 to 2013. The articles were evaluated by level of evidence and strength of recommendation. RESULTS: Because of its low sensitivity (50-62% for early stage epithelial ovarian cancer) and limited specificity (94-98.5%), cancer antigen (CA) 125 (CA125) is not recommended as a screening test in asymptomatic women. The Risk of Malignancy Index, which includes CA125, transvaginal ultrasound, and menopausal status, is recommended for the differential diagnosis of a pelvic mass. Because human epididymis protein 4 has been reported to have superior specificity to CA125, especially in premenopausal women, it may be considered either alone or as part of the risk of ovarian malignancy algorithm, in the differential diagnosis of pelvic masses, especially in such women. CA125 should be used to monitor response to first-line chemotherapy using the previously published criteria of the Gynecological Cancer Intergroup, that is, at least a 50% reduction of a pretreatment sample of 70 kU/L or greater. The value of CA125 in posttherapy surveillance is less clear. Although a prospective randomized trial concluded that early administration of chemotherapy based on increasing CA125 levels had no effect on survival, European Group on Tumor Markers state that monitoring with CA125 in this situation should occur, especially if the patient is a candidate for secondary cytoreductive surgery. CONCLUSIONS: At present, CA125 remains the most important biomarker for epithelial ovarian cancer, excluding tumors of mucinous origin.

The variation in high sensitive cardiac troponin concentration during haemodialysis treatment is not similar to the biological variation observed in stable end stage renal disease patients.

BACKGROUND: Cardiovascular mortality is high in end stage renal disease (ESRD). This study aimed to: (1) calculate within-week within- and between-subject biological variation (CVI and CVG) for hs-cTn in ESRD; (2) determine the magnitude of hs-cTn concentration changes during haemodialysis (HD) treatment; and (3) compare the CVI and CVG to the within and between-subject variation of cTn concentration changes during HD treatments (CVDIFF-I and CVDIFF-G). METHODS: Serum samples were collected from 20 patients before and after 10 consecutive HD treatments. cTn were measured using the hs-cTnT (Roche Diagnostics) and the hs-cTnI (Abbott Diagnostics). The CVA, CVI, CVG, CVDIFF-I and CVDIFF-G, were estimated using nested ANOVA. RESULTS: The within-week data showed hs-cTnT CVA, CVI and CVG of 1.6, 7.3 and 94.4%. Reference change values (RCV) were estimated to -18.7-23.0%. The Index of individuality (II) was 0.08. Corresponding values for hs-cTnI were 5.3, 13.2 and 142.4%, whilst the RCV was -32.5-48.2% and the II was 0.10. The mean concentration of cTn decreased by -6.4% (hs-cTnT) and -7.6% (hs-cTnI) during HD treatment. The CVDIFF-I and CVDIFF-G was 4.2 and 6.3% for hs-cTnT, and 10.7 and 9.4% for hs-cTnI. The RCVDIFF was -18.2-5.4% (hs-cTnT) and -39.0-23.8% (hs-cTnI), respectively, and the IIDIFF-values were 0.7 and 1.3. CONCLUSIONS: The CVI and CVG are similar to earlier findings. Mean hs-cTn concentrations decreased during HD. The within-subject hs-cTn variation during HD is similar to the between-subject variation, i.e. determining a cut-off value for hs-cTn changes during HD may be useful.

Performance criteria based on true and false classification and clinical outcomes. Influence of analytical performance on diagnostic outcome using a single clinical component.

BACKGROUND: In the general classical model for diagnoses based on a single analytic component, distributions of healthy and diseased are compared and several investigations of varying analytical performance on the percentage of misclassifications have been published. A new concept based on an alternative type of diagnosing, based on sharp decision limits has been introduced in diagnostic guidelines, but only a few publications on investigation of analytical performance have been seen. METHODS: The two diagnostic models (bimodal and unimodal) based on natural logarithmic Gaussian distributions are simulated. RESULTS: In the bimodal model it is possible to evaluate the influence of prevalence of disease in combination with varying analytical performances. In the unimodal model the prevalence is pre-decided by the chosen decision limit. In this model the influence of analytical performance is investigated for diagnosing diabetes using haemoglobin A1c (HbA1c), and for patients with high and low risk for coronary heart disease defined by serum-cholesterol concentrations. CONCLUSIONS: For HbA1c the guidelines and recommendations define a maximum inter-laboratory coefficient of variation of 3.5%, but this is in DCCT units (without a true zero-point), so after transformation to IFCC units (which are proportional) it was 5.2%, which allows for analytical bias as high as approximately ±9%. Consequently, analytical quality specifications should be separated as maximum bias and imprecision.

Weekly and 90-minute biological variations in cardiac troponin T and cardiac troponin I in hemodialysis patients and healthy controls.

BACKGROUND: Myocardial infarction (MI) is diagnosed by the finding of a single cardiac troponin value above the 99th percentile and a significant time-dependent change in cardiac troponin concentration. The aim of this study was to determine the 90-min and weekly biological variations, the reference change value (RCV), and the index of individuality (II) of high-sensitivity cardiac troponin T (hs-cTnT) (Roche Diagnostics) and hs-cTnI (Abbott Diagnostics) in patients receiving hemodialysis (HD) and in healthy individuals. METHOD: Blood samples were collected from 19 HD patients (on an HD-free day) and 20 healthy individuals at 90-min intervals over a 6-h period (between 08:30 and 14:30) and before the midweek HD treatment for 10 weeks. The within-person variation (CVi), between-person variation, RCV, and II were calculated. RESULTS: During the 6-h sampling period, the concentrations of hs-cTnT (both groups) and hs-cTnI (HD patients only) decreased on average by 0.8% to 1.7% per hour, respectively. These declining trends were included in the calculation of a 90-min asymmetric RCV: -8%/+5% in HD patients (hs-cTnT), -18%/+21% in HD patients (hs-cTnI), -27%/+29% in healthy individuals (hs-cTnT), and -39%/+64% in healthy individuals (hs-cTnI). The II was low in both groups for both assays. The weekly CVi values were approximately 8% (hs-cTnT) and 15% (hs-cTnI) in both groups. CONCLUSIONS: When using a cardiac troponin change of 20%-50% to diagnose an MI, the false-positive rate is likely to be lower for the hs-cTnT assay than for the hs-cTnI assay. The low II suggests that use of a diagnostic cutoff value can be omitted.

Changing from glucose to HbA1c for diabetes diagnosis: predictive values of one test and importance of analytical bias and imprecision.

BACKGROUND: In Denmark, the use of HbA1c in the diagnosis of diabetes was adopted from March 2012. We evaluated the change in the number of diabetes cases diagnosed by haemoglobin A1c (HbA1c) versus fasting venous plasma glucose (FPG), and estimated the influence of analytical variation and bias on the HbA1c-based prevalence of diabetes. METHODS: The study population constituted 4239 individuals not known to have diabetes randomly selected from all inhabitants aged 25-75 years in the former County of Vejle, Denmark. The number of undiagnosed patients with diabetes in the study population using FPG or HbA1c as the diagnostic criterion was estimated. Furthermore, changes in the analytical bias and coefficient of variation (CV) for HbA1c analysis were simulated and the effect on the number of diabetes cases was observed. RESULTS: Changing the diagnostic test from FPG to HbA1c reduced the number of patients with diabetes by approximately 46% based on one measurement. The predictive value of one test of HbA1c was 91% versus only 66% for one test of FPG. Analytical variation had a much greater impact on the number of patients with diabetes than bias. At a bias of 0%, an increase of CVanalytical from 2.7% to 3.7% increased the number of diabetes cases by 90%. CONCLUSIONS: In the study population, the percentage of undiagnosed patients with diabetes aged 25-75 years was reduced from 3.6% (95% CI 3.0%-4.2%) based on one FPG measurement (FPG ≥7.0 mmol/L) to only 1.9% (95% CI 1.5%-2.3%) if the diagnosis of diabetes was based on the criterion of HbA1c ≥48 mmol/mol (6.5% DCCT).

External quality assessment of point-of-care methods: model for combined assessment of method bias and single-participant performance by the use of native patient samples and noncommutable control materials.

BACKGROUND: An important objective in external quality assessment (EQA) is to evaluate systematic deviations between methods. However, this is not possible when noncommutable control materials are used. The aim of this study was to develop an EQA model that incorporates a method bias evaluation using native patient samples into EQA schemes in which noncommutable materials are used. METHODS: The model was applied twice in a point-of-care (POC) international normalized ratio survey among 1341 and 1578 participants. To estimate bias, about 100 native patient samples for each POC method were analyzed by a selected group of "expert" primary healthcare centers and on a designated comparison method. In addition, the expert centers as well as all the other EQA participants analyzed 2 noncommutable control materials, and method-specific target values were established. Both method bias and the deviation of a single-participant result from the method target value were evaluated against analytical quality specifications, making combined assessment possible. The best-case scenario occurred when both results were within the quality specifications. RESULTS: Two POC methods fulfilled the quality specification for bias, whereas one did not. The best-case scenario was achieved by more than 90% of the participants using the methods with no bias, whereas none of the participants using the method with unacceptable bias achieved this result. CONCLUSIONS: We propose an EQA model for which the bias of POC methods can be evaluated in situations in which commutable control materials are not available.

Effect of coagulation factors on discrepancies in International Normalized Ratio results between instruments.

BACKGROUND: The reasons for discrepancies between International Normalized Ratio (INR) results determined by point-of-care-instruments and laboratory measurements are not fully understood. In this study we investigated whether different levels of coagulation factors in the plasma of patients can explain some of the systematic and/or random parts of the difference in INR between the instruments. METHODS: Blood samples were collected at four different patient visits from each of 34 outpatients on warfarin treatment. INR was determined on a laboratory instrument (STA Compact(®)) and on three point-of-care instruments (Simple Simon(®)PT, CoaguChek(®)XS and INRatio™). In addition, the level of fibrinogen, coagulation factors II, V, VII and X was determined. INR instruments were compared in pairs. Simple linear regressions as well as multiple linear regressions and nested ANOVA analyses were used to examine the data. RESULTS: The coagulation factors, especially fibrinogen, factors II and VII, could explain between 16% and 45% of the total variance of the differences in INR between instruments dependent on instruments compared. After correction for factors no systematic difference was seen for four of the six comparisons and the between- and within-subject variation of the differences were reduced by up to 69% and 52%, respectively. CONCLUSIONS: By correcting for the appropriate coagulation factors, especially the systematic differences, but also the between- and within-subject variation of the differences between instruments, were reduced. This indicates that different levels of coagulation factors in the plasma of the patients play an important role in explaining discrepancies between INR instruments.

Do new concepts for deriving permissible limits for analytical imprecision and bias have any advantages over existing consensus?

The Stockholm conference held in 1999 on "Strategies to set global analytical quality specifications (AQS) in laboratory medicine" reached a consensus and advocated the ubiquitous application of a hierarchical structure of approaches to setting AQS. This approach has been widely used over the last decade, although several issues remain unanswered. A number of new suggestions have been recently proposed for setting AQS. One of these recommendations is described by Haeckel and Wosniok in this issue of Clinical Chemistry and Laboratory Medicine. Their concept is to estimate the increase in false-positive results using conventional population-based reference intervals, the delta false-positive rate due to analytical imprecision and bias, and relate the results directly to the current analytical quality attained. Thus, the actual estimates in the laboratory for imprecision and bias are compared to the AQS. These values are classified in a ranking system according to the closeness to the AQS, and this combination is the new idea of the proposal. Other new ideas have been proposed recently. We wait, with great interest, as should others, to see if these newer approaches become widely used and worthy of incorporation into the hierarchy.

Analytical performance, reference values and decision limits. A need to differentiate between reference intervals and decision limits and to define analytical quality specifications.

With the increasing use of decision limits (action limits, cut-off points) specified for a number of analytical components in diagnosis and for action in critical situations, formulated in national or international recommendations, the traditional interpretation of reference intervals has been uncertain, and sometimes the two concepts are being mixed up by incorporating risk calculations in the reference intervals. There is, therefore, a need to clarify the two concepts and to keep them definitely separated. Reference intervals are the 95% limits for the descriptions of the distributions of the values of analytical components measured on reference samples from reference individuals. Decision limits are based on guidelines from national and international expert groups defining specific concentrations of certain components as limits for decision about diagnosis or well-defined specific actions. Analytical quality specifications for reference intervals have been defined for bias since the 1990s, but in the recommendations specified in the clinical guidelines analytical quality specifications are only scarcely defined. The demands for negligible biases are, however, even more essential for decision limits, as the choice is no longer left to the clinician, but emerge directly from the concentration. Even a small bias will change the number of diseased individuals, so the demands for negligible biases are obvious. A view over the analytical quality as published gives a variable picture of bias for many components, but with many examples of considerable bias which must be critical--yet no specifications have been stipulated until now.

Within-subject biological variation of glucose and HbA(1c) in healthy persons and in type 1 diabetes patients.

BACKGROUND: Several articles describing within-subject biological variation of fasting glucose and HbA(1c) in healthy populations have been published, but information about biological variation of glucose and HbA(1c) in patients with type 1 diabetes is scarce. It is reasonable to assume that type 1 diabetics differ from their healthy counterparts in this matter. The aim of our study was to estimate the biological variation of glucose and HbA(1c) in healthy subjects and in patients with type 1 diabetes. METHODS: Fifteen healthy individuals and 15 type 1 diabetes patients were included. Biological variations were calculated based on blood samples collected weekly for 10 consecutive weeks from the healthy and the eligible of the type 1 diabetes patients. RESULTS: The within-subject variations of glucose were approximately 5% in healthy individuals and 30% in diabetes patients, and for HbA(1c) they were 1.2% in healthy individuals and 1.7% in diabetes patients. CONCLUSIONS: In conclusion, we found a high within-subject biological variation of glucose in diabetes patients as expected compared to healthy individuals (30% vs. 5%). The short-term (2 months) within-subject biological variation of HbA(1c) did not differ significantly between well regulated type 1 diabetes patients and healthy individuals (1.7% vs. 1.2%).

Interpretation of increments in serial tumour biomarker concentrations depends on the distance of the baseline concentration from the cut-off.

BACKGROUND: In the management of breast cancer, several algorithms for interpretation of measured concentrations during monitoring have been introduced, without objective evaluation of their performance regarding the distance of the starting concentration from the cut-off concentration. METHODS: A computer simulation model has developed using parameters for the tumour biomarker CA 15-3 regarding biological variation and different rates of increase during progressive disease. Seven different algorithms, which include the cut-off point in the calculations, are applied to the simulated data corresponding to 1000 surrogate patients. Steady-state variation (CV-within-subject=14.9%) is based on Gaussian random numbers and an exponential increase in tumour growth (λ=0.009, 0.021, and 0.090 kU/day). RESULTS: The main outcome of the simulations was that low starting concentrations (baseline concentrations) delay the detection of progressive disease (true-positive), whereas, baseline concentrations just below the cut-off value results in false-positive results of progression during steady-state situations. The algorithms investigated show varying susceptibility for baseline concentrations approaching the cut-off. Thus, three of the algorithms show > 90% false-positives and three algorithms < 5% false-positives when baseline concentrations were just below the cut-off point. CONCLUSIONS: Based on the simulations, it is possible to select the optimal algorithms for early detection of progressive disease and a low percentage of false-positives.

Internal quality control of prothrombin time in primary care: comparing the use of patient split samples with lyophilised control materials.

Many primary care laboratories use point-of-care (POC) instruments to monitor patients on anticoagulant treatment. The internal analytical quality control of these instruments is often assessed by analysing lyophilised control materials and/or by sending patient samples to a local hospital laboratory for comparison (split sample). The aim of this study was to evaluate the utility of these two models of prothrombin time quality control. The models were evaluated by power functions created by computer simulations based on empirical data from 18 primary care laboratories using the POC instruments Thrombotrack, Coagu-Chek S, or Hemochron Jr. Signature. The control rules 1(2S), 1(3S), exponential weighted moving average, and the deviation limits of +/- 10% and +/- 20% were evaluated by their probability of error detection and false rejections. The total within-lab coefficient of variation was 3.8% and 6.9% for Thrombotrack, 8.9% and 10.5% for CoaguChek S, and 9.4% and 14.8% for Hemochron Jr. Signature for the control sample measurements and the split sample measurements, respectively. The probability of error detection was higher using a lyophilised control material than a patient split sample for all three instruments, whereas the probability of false rejection was similar. A higher probability of error detection occurred when lyophilised control material was used compared with the patient split samples; therefore, lyophilised control material should be used for internal analytical quality control of prothrombin time in primary health care.