Assessment of CA 15.3, CEA and TPA Concentrations during Monitoring of Breast Cancer

Abstract

The variability of the tumor markers cancer antigen (CA) 15.3, carcinoembryonic antigen (CEA) and tissue polypeptide antigen (TPA) during steady state concentrations and the rate of increase during progression is described. One hundred and ninety-two patients were monitored during first-line chemotherapy for metastatic breast cancer and during follow-up. Blood specimens were sampled approximately every four weeks. Steady state concentrations were registered for 77 (CA 15.3), 96 (CEA), and 127 (TPA) patients with below cutoff level values and for 28 (CA 15.3), 25 (CEA), and 11 (TPA) patients with above cutoff level values. Clinical and marker progression was registered for 75 (CA 15.3), 62 (CEA), and 57 (TPA) patients. The coefficients of total variation of steady state concentrations (comprising the intra- and interassay analytical imprecision and the within subject biological variation) were higher below (14.9% CA 15.3, 15.4% CEA, 25.9% TPA) than above cutoffs (9.6% CA 15.3,6.0% CEA, 19.9% TPA). The variability was similar for CA 15.3 and CEA but higher for TPA. During progression the rates of increase in concentrations were similar for CA 15.3 (0.0257) and CEA (0.0214) and lower than for TPA (0.0346). Our data indicate that criteria for assessment of sequential tumor marker concentrations should consider the marker in question, the steady state variability, the cutoff value, and the rate of increase during disease progression.

Design of Tumor Biomarker–Monitoring Trials: A Proposal by the European Group on Tumor Markers

“…Data on biological variation can be derived from populations of healthy individuals, patients who have undergone curative surgery and are apparently disease free, patients with advanced but stable disease, or patients with benign disease (19 ); data involving many biomarkers are tabulated separately (21 ). The design of tumor biomarker studies that take account of inherent variation was recently considered in a report that reviewed 27 studies of prostate-specific antigen (22 ) and in publications of studies relating to cancer-associated antigens 15-3 and 125 (CA125), carcinoembryonic antigen, and tissue polypeptide antigen (23,24 ).…”

Computer Simulation Model System for Interpretation and Validation of Algorithms for Monitoring of Cancer Patients by Use of Serial Serum Concentrations of Biomarkers in the Follow-Up After Surgical Procedures and Other Treatments - A Computer Simulation

“…The variations during the stable period of monitoring breast cancer patients are considered as steady-state and expressed as within-subject biological variation (CV B ) and analytical variation (CV A ) according to Sölétormos et al (2000a). However, the within-subject biological variation, CV B , is not homogeneous.…”

“…Based on data from Sölétormos et al (1997Sölétormos et al ( , 2000a, increases in biomarkers are shown to be associated with progression of disease and it is found that the concentrations of biomarkers have an exponential relation with time. However, the rate of tumour growth can vary considerably.…”

“…The rate of increase is expressed as  in the exponential function as a factor in the exponent in e  t or as exp(t). The rate of increase  (also called slope) was calculated for TPA in patients Sölétormos et al (2000a) As a resulting graph the tumour concentration is now added to the steady-state concentration (steady-state concentration + initial tumour (0.95 U/L)). An example is illustrated in Fig 1C. At first, the resulting graph has nearly the same concentration as the steady-state graph, but after some time TPA products from the tumour take over as the dominating contributor.…”

“…If there is variance homogeneity, this pooled coefficient of variance represents all individuals of the reference group and it is correct to use this pooled CV B in the simulations as a factor for the random Gaussian values. This assumption, however, is not fulfilled for TPA (Sölétormos et al 2000a), where the range of coefficients of variation goes from 8.5% and 48.9% and represents individual CV B -values, from which the extreme values used for the challenging of algorithms in the simulations are selected.…”