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Author Spotlight: Engineering Molecular Tools for Disease Detection and Imaging
Published on: December 8, 2023
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Diagnostic validation and interpretation of longitudinal circulating biomarkers using a biomarker response
R Moritz1, M Muller2, C M Korse1
1Department of Laboratory Medicine, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
Clinica Chimica Acta; International Journal of Clinical Chemistry
|September 12, 2018
Summary
A new graphical tool, the biomarker response characteristic (BReC) plot, aids in interpreting longitudinal tumor biomarker data for cancer treatment monitoring. This method supports diagnostic accuracy studies and clinical decision-making for biomarkers like CEA and Cyfra 21.1.
Area of Science:
- Oncology
- Biomarker Research
- Medical Diagnostics
Background:
- Serum tumor biomarkers are crucial for monitoring cancer treatment efficacy.
- Clinical guidance for interpreting longitudinal biomarker data is often insufficient.
- Graphical presentations can enhance the diagnostic accuracy and clinical utility of biomarker data.
Purpose of the Study:
- To introduce and demonstrate the application of a novel graphical tool, the biomarker response characteristic (BReC) plot.
- To develop software for dynamic generation of BReC plots and diagnostic accuracy studies.
- To evaluate the utility of BReC plots using longitudinal biomarker data in non-small cell lung cancer patients.
Main Methods:
- Designed a biomarker response characteristic (BReC) plot.
- Developed software for dynamic BReC plot generation and diagnostic accuracy assessment.
- Applied the BReC plot to serial carcinoembryonic antigen (CEA) and Cyfra 21.1 data from 216 metastatic non-small cell lung cancer patients treated with Nivolumab.
Main Results:
- The software successfully generated BReC plots and diagnostic metrics (sensitivity, specificity, predictive values).
- BReC plots revealed a clear correlation between clinical outcomes and CEA/Cyfra 21.1 responses.
- CEA and Cyfra 21.1 based tests designed using BReC plots showed high specificity (0.96) for detecting treatment failure.
Conclusions:
- The BReC plot shows promise in supporting diagnostic validation studies for biomarkers.
- This graphical tool aids in the clinical interpretation of longitudinal biomarker data.
- Further validation studies are recommended to confirm the utility of BReC plots.
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