Objective: Tumor markers are used to monitor disease progression and determine the responsiveness to cancer treatment. However, there are no standardized criteria for monitoring serial tumor marker measurements. Herein, we have developed a monitoring system for interpreting changes in tumor markers using overlapping 95% confidence intervals (CIs).
Methods: Two-year data, including 117,289 results for 11 tumor markers in our laboratory, were analyzed. CI ranges for each tumor marker were set based on biological variation, and data were analyzed for each patient assessed at health check-ups and clinics, individually and overall.
Results: The 95th percentile cut-offs for each tumor marker were much higher in the clinic group than in the health check-up group. In decreasing order, the percentages of results with no overlap in 95% CIs were thyroglobulin antigen, 14.9%; protein induced by vitamin K absence-II (PIVKA), 11.9%; and prostate-specific antigen, 9.8%. After correction using the reference interval, the percentages decreased to less than 5%, except for PIVKA (10.9%).
Conclusion: We suggest that our monitoring system can serve as a criterion for the auto-verification of tumor markers. Further studies are required to validate and demonstrate this concept in real clinical situations using actual clinical data reflecting disease progression in cancer patients and responsiveness to cancer treatment.
Keywords: Biological variation; Cancer treatment; Confidence interval; Delta check; Intra-individual variation; Tumor marker.
© 2021 by the Association of Clinical Scientists, Inc.