Performance of seven criteria to assess CA125 increments among ovarian cancer patients monitored during first-line chemotherapy and the post-therapy follow-up period.

AIM: To investigate seven CA125 criteria to monitor progressive ovarian cancer among patients with stage IC-IV disease. MATERIALS & METHODS: Four criteria were used to asses CA125 increments starting from concentrations ≥35 U/ml and three criteria to asses increments starting from concentrations <35 U/ml. RESULTS: A total of 231 patients were allocated to CA125 monitoring. The performances of the CA125 criteria were similar with sensitivities of 30-55%, negative predictive values of 28-46%, positive predictive values of 90-100% and median lead times of 26-87 days. CONCLUSION: The criteria showed low sensitivity and inability to exclude progressive ovarian cancer. The study suggests that CA125 information cannot stand alone but should be considered used in conjunction with other investigative procedures.

Estimates of Within-Subject Biological Variation of Protein C, Antithrombin, Protein S Free, Protein S Activity, and Activated Protein C Resistance in Pregnant Women.

BACKGROUND: In pregnancy, interpretation of results from coagulation parameters can be difficult because of the procoagulant physiological changes. The aim of this study was to describe the course of 5 coagulation parameters (thrombophilia markers) in healthy pregnancies, and to estimate and compare the within-subject biological variation (CVI) of these parameters in healthy pregnant and nonpregnant women. METHODS: Blood samples were obtained every 4th week during pregnancy and 3 samples after delivery in 20 healthy women and every 4th week during 40 weeks in 19 healthy nonpregnant women. Protein C (PC), antithrombin (AT), protein S free (PS free), protein S activity (PS activity), and activated protein C resistance (with factor V-depleted plasma) (APCR) were analyzed. Before the calculation of CVI, results were transformed into multiples of the median (MoM) and natural logarithm of MoM (lnMoM) to adjust for the physiological changes during pregnancy. RESULTS: During pregnancy, PC results showed large variability, AT decreased slightly, and PS free and PS activity decreased significantly. Both activated partial thromboplastin time tests used to calculate APCR decreased, and the APCR ratio was constant. The CVI (lnMoM) in pregnancy were for PC 8.4%, for AT 3.8%, for PS free 11.5%, for PS activity 9.3%, and for APCR 0.5%, and similar to corresponding results in nonpregnant women. CONCLUSIONS: Transformation of coagulation parameters in healthy pregnancies to lnMoM is a tool to establish a kind of steady state. Although there is a physiological change in PC, AT, and PS free and PS activity during pregnancy, the CVI was comparable with the CVI of nonpregnant women.

Analytical performance specifications for changes in assay bias (Δbias) for data with logarithmic distributions as assessed by effects on reference change values.

Background The distributions of within-subject biological variation are usually described as coefficients of variation, as are analytical performance specifications for bias, imprecision and other characteristics. Estimation of specifications required for reference change values is traditionally done using relationship between the batch-related changes during routine performance, described as Δbias, and the coefficients of variation for analytical imprecision (CVA): the original theory is based on standard deviations or coefficients of variation calculated as if distributions were Gaussian. Methods The distribution of between-subject biological variation can generally be described as log-Gaussian. Moreover, recent analyses of within-subject biological variation suggest that many measurands have log-Gaussian distributions. In consequence, we generated a model for the estimation of analytical performance specifications for reference change value, with combination of Δbias and CVA based on log-Gaussian distributions of CVI as natural logarithms. The model was tested using plasma prolactin and glucose as examples. Results Analytical performance specifications for reference change value generated using the new model based on log-Gaussian distributions were practically identical with the traditional model based on Gaussian distributions. Conclusion The traditional and simple to apply model used to generate analytical performance specifications for reference change value, based on the use of coefficients of variation and assuming Gaussian distributions for both CVI and CVA, is generally useful.

Quantifying capital goods for biological treatment of organic waste.

Materials and energy used for construction of anaerobic digestion (AD) and windrow composting plants were quantified in detail. The two technologies were quantified in collaboration with consultants and producers of the parts used to construct the plants. The composting plants were quantified based on the different sizes for the three different types of waste (garden and park waste, food waste and sludge from wastewater treatment) in amounts of 10,000 or 50,000 tonnes per year. The AD plant was quantified for a capacity of 80,000 tonnes per year. Concrete and steel for the tanks were the main materials for the AD plant. For the composting plants, gravel and concrete slabs for the pavement were used in large amounts. To frame the quantification, environmental impact assessments (EIAs) showed that the steel used for tanks at the AD plant and the concrete slabs at the composting plants made the highest contribution to Global Warming. The total impact on Global Warming from the capital goods compared to the operation reported in the literature on the AD plant showed an insignificant contribution of 1-2%. For the composting plants, the capital goods accounted for 10-22% of the total impact on Global Warming from composting.

The influence of coagulation factors on the in-treatment biological variation of international normalized ratio for patients on warfarin.

BACKGROUND: Biological variation is usually estimated in healthy individuals during steady-state conditions. The aim of this study was to estimate the in-treatment biological variation of the International normalised ratio (INR) and to investigate to what extent the different levels of coagulation factors could explain this variation. METHODS: Blood samples were collected from randomly included patients 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(™)). The level of fibrinogen, and the activity of coagulation factors II, V, VII and X were determined. RESULTS: The in-treatment within- and between-subject coefficients of variation of INR were dependent on the method and varied between 18 and 24% and 13 and 19%, respectively, and were reduced to 3.9-5.1% and 2.3-5.8%, after correction for coagulation factors which could explain 91-95% of the variance of INR. CONCLUSIONS: The in-treatment biological variation of INR was higher than reported for healthy individuals as well as patients in a steady-state condition, but by correcting for appropriate coagulation factors it was reduced. The association between INR and coagulation factors was different for the different PT methods mainly due to different sensitivity towards FII and FVII.

A model for calculating the within-subject biological variation and likelihood ratios for analytes with a time-dependent change in concentrations; exemplified with the use of D-dimer in suspected venous thromboembolism in healthy pregnant women.

BACKGROUND: Within-subject biological variation and reference change value (RCV) are difficult to calculate for an analyte with a changing concentration. The aim of this study was to develop a model to examine if it was possible to transform an analyte with a time-dependent change in concentration into a 'steady-state' situation by the use of 'multiples of the median' (MoM) and its natural logarithm (lnMoM). In addition, we wanted to extend the RCV concept, using likelihood and odds ratios, to calculate the post-test probabilities for disease. D-dimer in pregnancy is used as an example. METHODS: Blood samples from 18 healthy pregnant and 18 healthy non-pregnant women were collected every fourth week. MoM of the D-dimer concentrations was calculated for each four-week interval to obtain a 'steady-state' situation for the D-dimer concentrations. The 'normalized' values were then transformed to the lnMoM to obtain a Gaussian distribution, used for the estimation of biological variation. RESULTS: Median D-dimer concentrations increased six-fold during pregnancy. Within-subject variation (SD) of lnMoM D-dimer was 0.27 during pregnancy and 0.23 in non-pregnant women, with RCVs of 0.72 and 0.90, respectively. CONCLUSIONS: By using the lnMoM model, an increasing concentration of an analyte can be transformed to a steady-state situation and the within-subject biological variation and its derived parameters can be calculated.

Confidence intervals and power calculations for within-person biological variation: effect of analytical imprecision, number of replicates, number of samples, and number of individuals.

BACKGROUND: Reliable estimates of within-person biological variation and reference change value are of great importance when interpreting test results, monitoring patients, and setting quality specifications. Little information has been published regarding what experimental design is optimal to achieve the best estimates of within-person biological variation. METHOD: Expected CIs were calculated for different balanced designs for a 2-level nested variance analysis model with varying analytical imprecision. We also simulated data sets based on the model to calculate the power of different study designs for detection of within-person biological variation. RESULTS: The reliability of an estimate for biological variation and a study's power is very much influenced by the study design and by the ratio between analytical imprecision and within-person biological variation. For a fixed number of measurements, it is preferable to have a high number of samples from each individual. Shortcomings in analytical imprecision can be controlled by increasing the number of replicates. CONCLUSIONS: The design of an experiment to estimate biological variation should take into account the analytical imprecision of the method and focus on obtaining the highest possible reliability. Estimates of biological variation should always be reported with CIs.

Discrepancies in international normalized ratio results between instruments: a model to split the variation into subcomponents.

BACKGROUND: Observed differences between results obtained from comparison of instruments used to measure international normalized ratio (INR) have been higher than expected from the imprecision of the instruments. In this study the variation of these differences was divided into subcomponents, and each of the subcomponents was estimated. METHODS: Blood samples were collected at 4 different patient visits from each of 36 outpatients who were receiving warfarin treatment and were included in the study. INR was determined on 1 laboratory instrument (STA Compact®) and 3 point-of-care instruments (Simple Simon®PT, CoaguChek®XS, and INRatio™). All 4 INR instruments were compared in pairs. Linear regression was used to correct for systematic deviations. The remaining variation of the differences was subdivided into between-subject, within-subject, and analytical variation in an ANOVA nested design. RESULTS: The mean difference between instruments varied between 1.0% and 14.3%. Between-subject variation of the differences (expressed as CV) varied between 3.3% and 7.4%, whereas within-subject variation of the differences was approximately 5% for all 6 comparisons. The analytical imprecision of the differences varied between 3.8% and 8.6%. CONCLUSIONS: The differences in INR between instruments were subdivided into calibration differences, between- and within-subject variation, and analytical imprecision. The magnitude of each subcomponent was estimated. Within results for individual patients the difference in INR between 2 instruments varied over time. The reasons for the between- and within-subject variations of the differences can probably be ascribed to different patient-specific effects in the patient plasma. To minimize this variation in a monitoring situation, each site and patient should use results from only 1 type of instrument.

Hypersecretion of the alpha-subunit in clinically non-functioning pituitary adenomas: Diagnostic accuracy is improved by adding alpha-subunit/gonadotropin ratio to levels of alpha-subunit.

BACKGROUND: In vitro, the majority of clinically non-functioning pituitary adenomas (NFPAs) produce gonadotropins or their alpha-subunit; however, in vivo, measurements of alpha-subunit levels may not accurately detect the hypersecretion of the alpha-subunit. AIM: We wanted to estimate the reference intervals and decision limits for gonadotropin alpha-subunit, LH and FSH levels, and aratio (alpha-subunit/LH+FSH), especially taking into consideration patient gender and menstrual status. Furthermore, we wanted to examine if the diagnostic utility of alpha-subunit hypersecretion was improved when the alpha-ratios, rather than simply the alpha-subunit levels, were measured in patients with NFPAs. MATERIAL AND METHODS: Reference intervals for gonadotropin alpha-subunit serum levels and alpha-ratios were established in 231 healthy adults. The estimated cut-off limits were applied to 37 patients with NFPAs. Gonadotropin alpha-subunit, LH and FSH levels were measured and alpha-ratios were calculated. RESULTS: In healthy adults, the cut-offs for alpha-subunit levels were significantly different between men and pre- and postmenopausal women: the cut-offs were 1.10, 0.48 and 3.76 IU/l, respectively. Using these estimated cut-offs, increased alpha-subunit levels were identified in 10 out of 37 (27%) patients with NFPAs. By adding alpha-ratio, in combination with alpha-subunit levels, 23 patients out of 37 (62%) were identified as having elevated alpha-subunit hypersecretion, and 22 out of these 23 patients (96%) had increased alpha-ratios. One premenopausal patient out of 23 had elevated alpha-subunit level but a normal alpha-ratio. CONCLUSION: Our data suggest that adding the simple calculation of alpha-ratio improves the ability of detecting gonadotropin alpha-subunit hypersecretion and thereby indentifying patients with NFPAs.