Interpretation of Sequential Measurements of Cancer Antigen 125 (CA 125), Carcinoembryonic Antigen (CEA) and Tissue Polypeptide Antigen (TPA) Based on Analytical Imprecision and Biological Variation in the Monitoring of Ovarian Cancer

Abstract

The main objective with cancer antigen 125 (CA 125), carcinoembryonic antigen (CEA), and tissue polypeptide antigen (TPA) monitoring of ovarian cancer patients is to detect an early change of disease activity with high reliability. We hypothesized that a monitoring scheme for ovarian cancer patients with serological tumor markers should take into account the stochastic variation, i.e. the probability that observed increases and decreases may solely be due to analytical imprecision and normal intra-individual biological variation. The aim of this study was to provide a detailed characteristic of the within-subject mean steady state concentrations and the associated variability in healthy individuals with an age distribution representative for ovarian cancer patients. Thirty-one healthy women with a median age of 55 years comprised the study population. Sixteen blood samples were collected from each subject in four series, with four samples per series, over a period of approximately 1 year. We found that, i) natural logarithmic-transformed concentrations were more homogeneously distributed between individuals than the original concentrations, ii) the within-subject mean steady state levels, the standard deviations, and the coefficients of variation differed among subjects, and iii) the steady state variability differed among the markers. In conclusion, our data indicate that the assessment of sequential CA 125, CEA, and TPA concentrations is more complex than hitherto recognized. We suggest that it is necessary to adjust the assessment criteria to the type of marker, and that assessment may be facilitated if based on natural logarithmic transformed concentrations.

Biological Variation of Tumor Markers and Its Application in the Detection of Disease Progression in Patients with Non-Small Cell Lung Cancer

“…The CV w values for CA 125 and CEA in this study were similar to those reported previously (15)(16)(17). The components of BV for CYFRA 21-1 in healthy individuals are unknown (15 ).…”

Calculation of limits for significant unidirectional changes in two or more serial results of a biomarker based on a computer simulation model

“…2 Within the last decade, discussions about normal and ln-normal distributions of biological parameters have become intense and the tendency is now moving towards the application of ln-distributions. [4][5][6][7][8] One problem with the RCV is that it can only be used in assessment of differences between two serial results, which makes it susceptible to the effect of repeated testing, where the probability of false-positive results increases with the number of results available. Therefore, a new concept to overcome the problems with repeated testing, by keeping the probability of false-positive results constant for several consecutive results and only dependent on the number of results available seems worthwhile.…”

Advantages of the lognormal approach to determining reference change values for N-terminal propeptide B-type natriuretic peptide

“…These results may be extended to other settings, where the lognormal approach was recognized to make a better use of data distribution when assessing biological variation. This was shown by Tuxen et al [16] for cancer antigen 125 (CA 125), carcinoembryonic antigen (CEA), and tissue polypeptide antigen (TPA) in the monitoring of ovarian cancer patients or by van Eyben et al [17] for serum lactate dehydrogenase isoenzyme1 (S-LD-1) in the monitoring of patients with testicular germ cell tumors.…”

“…As component of variation is computed based on nANOVA, the distributional assumptions underlying the use of this method should be satisfied, which is not the case for skewed distributions, as NT-proBNP's. This aspect has been underlined in the literature not only for NTproBNP, but also for other biomarkers in oncologic research [16,17]. Particularly, Fokkema et al [18] showed that the deviation of the mean from the median of week to week measurements was much larger (by a factor of 20) before log-transformation of NT-proBNP concentrations.…”