Abstract

Clinical trials have suggested that the serologic cytokeratin tumor marker tissue polypeptide antigen (TPA) may be important as a monitor of metastatic breast cancer (1)(2)(3). The usefulness of this marker depends on the ability to identify, predict, and exclude tumor growth before the changes are detectable by imaging techniques and routine biochemistry (4)(5)(6). It is, however, difficult to compare results because the investigated patient populations have been heterogeneous. It remains unknown how TPA assessment criteria perform in situations with different ( a ) time intervals between measurements, ( b ) numbers of measurements, ( c ) rates of increase during progression, and ( d ) analytical quality. The time and expense required to investigate these issues in new studies will be considerable. Recently, computer-simulated marker data have been suggested to compare the diagnostic accuracy of assessment criteria used to interpret longitudinal cancer antigen (CA) 15.3 and carcinoembryonic antigen (CEA) data (7)(8). The computer-based approach was useful because the descriptive variables described above could be standardized and changed individually according to the simulated clinical and laboratory situation. The procedure-identified criteria must have a high ability to detect early CA 15.3 and CEA progression and at the same time maintain robustness against false-positive signals. Because TPA measurements among patients are frequently performed in combination with CA 15.3 and CEA, we consider it relevant to investigate whether computer-simulated data can be used to identify reliable criteria to interpret sequential TPA concentrations. However, because the typical background variability of TPA and the rate of TPA increase during progression are different as compared with CA 15.3 and CEA (7), we generated new data sets in the present simulation procedure to test our …

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