Improved sensitivity of a thyrotropin receptor antibody assay.
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Antibodies↗
Biomedical subjects
Esther Jensen
Publications and source records attributed to Esther Jensen.
Reference change values and power functions.
Repeated samplings and measurements in the monitoring of patients to look for changes are common clinical problems. The "reference change value", calculated as zp x [2 x (CVI2 + CVA2)](1/2), where zp is the z-statistic and CVI and CVA are within-subject and analytical coefficients of variation, respectively, has been used to detect whether a measured difference between measurements is statistically significant. However, a reference change value only detects the probability of false-positives (type I error), and for this reason, a model to calculate the risk of missing significant changes in serial results from individuals (probability of false-negatives) is investigated in this work by means of power functions. Therefore, when an analyte is being monitored in a patient, power functions estimate the probability of detecting a defined real change by measuring the difference. Thus, when a measured difference is the same as the calculated reference change value, then it will be detected in only 50% of situations.
Analysis of Variance↗
Graphical interpretation of confidence curves in rankit plots.
A well-known transformation from the bell-shaped Gaussian (normal) curve to a straight line in the rankit plot is investigated, and a tool for evaluation of the distribution of reference groups is presented. It is based on the confidence intervals for percentiles of the calculated Gaussian distribution and the percentage of cumulative points exceeding these limits. The process is to rank the reference values and plot the cumulative frequency points in a rankit plot with a logarithmic (In=log(e)) transformed abscissa. If the distribution is close to In-Gaussian the cumulative frequency points will fit to the straight line describing the calculated In-Gaussian distribution. The quality of the fit is evaluated by adding confidence intervals (CI) to each point on the line and calculating the percentage of points outside the hyperbola-like CI-curves. The assumption was that the 95% confidence curves for percentiles would show 5% of points outside these limits. However, computer simulations disclosed that approximate 10% of the series would have 5% or more points outside the limits. This is a conservative validation, which is more demanding than the Kolmogorov-Smirnov test. The graphical presentation, however, makes it easy to disclose deviations from In-Gaussianity, and to make other interpretations of the distributions, e.g., comparison to non-Gaussian distributions in the same plot, where the cumulative frequency percentage can be read from the ordinate. A long list of examples of In-Gaussian distributions of subgroups of reference values from healthy individuals is presented. In addition, distributions of values from well-defined diseased individuals may show up as In-Gaussian. It is evident from the examples that the rankit transformation and simple graphical evaluation for non-Gaussianity is a useful tool for the description of sub-groups.
Blood Chemical Analysis↗
Establishment of a serum thyroid stimulating hormone (TSH) reference interval in healthy adults. The importance of environmental factors, including thyroid antibodies.
It has previously been shown that thyroid antibodies affect thyroid stimulating hormone (TSH) concentrations in men and women and that TSH levels are predictive of future thyroid disease. We investigated the validity of the National Academy of Clinical Biochemistry (NACB) guidelines regarding the TSH reference interval by studying 1512 individuals. Two hundred and fifty had at least one thyroid antibody, 121 were taking medications other than estrogens and occasional analgesics, and 105 reported a family history of thyroid disease. Serum TSH, thyroid peroxidase antibodies (TPOab) and thyroglobulin antibodies (Tgab) were determined on AutoDELFIA and TSHRab by a radioreceptor assay (RRA) from Brahms Diagnostica. For individuals without thyroid antibodies and other risk factors, no effect of age and gender was seen for serum TSH. Neither medication nor the presence of Tgab alone had any influence on serum TSH. TPOab alone or in combination with Tgab were associated with an increased serum TSH level. The 'cumulative percentage distributions' of subgroups, as well as the combined population, was In-Gaussian distributed. The central 95% of the population was within the 95% CI in rankit-plots. Consequently, a common reference interval for serum TSH of 0.58-4.07 mlU/l for all adults between 17 and 66 years of age was established. This reference interval is much higher than expected from the NACB-guidelines.
Adolescent↗