R Moritz1, M Muller2, C M Korse1, D van den Broek1, P Baas2, V van den Noort3, J J Ten Hoeve4, M M van den Heuvel5, H H van Rossum6. 1. Department of Laboratory Medicine, The Netherlands Cancer Institute, Amsterdam, the Netherlands. 2. Department of Thoracic Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands. 3. Department of Biometrics, The Netherlands Cancer Institute, Amsterdam, the Netherlands. 4. Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, the Netherlands. 5. Department of Thoracic Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Respiratory Diseases, Radboud Medical Center, Nijmegen, the Netherlands. 6. Department of Laboratory Medicine, The Netherlands Cancer Institute, Amsterdam, the Netherlands. Electronic address: h.v.rossum@nki.nl.
Abstract
BACKGROUND: Serum-based tumor biomarkers are used to monitor cancer treatment, while clear guidance on the clinical usage is often lacking. We describe a graphical presentation to support diagnostic accuracy studies and clinical interpretation of longitudinal biomarker data. METHODS: A biomarker response characteristic (BReC) plot was designed. To allow demonstration of the BReC plot application, software was developed that supported 1) dynamic generation of BReC plots, and 2) diagnostic accuracy studies of biomarker response-based medical tests. The BReC plot application was demonstrated using serial carcinoembryonic antigen (CEA) and Cyfra 21.1 results from 216 patients with metastasized non-small cell lung cancer, treated with Nivolumab in routine clinical practice. RESULTS: The developed software supported the generation of BReC plots and diagnostic validation of biomarker response-based medical tests by generating the sensitivity, specificity and predictive values. Obtained BReC plots showed a clear relationship between clinical outcome and CEA and Cyfra 21.1 responses. Furthermore, using BReC plots, CEA and Cyfra 21.1 based medical tests were designed with a sensitivity for detection of treatment failure of 0.34 and 0.35 and a specificity of 0.96. CONCLUSIONS: The BReC plot appears to support diagnostic validation studies and the interpretation of longitudinal biomarkers though further validation is warranted.
BACKGROUND: Serum-based tumor biomarkers are used to monitor cancer treatment, while clear guidance on the clinical usage is often lacking. We describe a graphical presentation to support diagnostic accuracy studies and clinical interpretation of longitudinal biomarker data. METHODS: A biomarker response characteristic (BReC) plot was designed. To allow demonstration of the BReC plot application, software was developed that supported 1) dynamic generation of BReC plots, and 2) diagnostic accuracy studies of biomarker response-based medical tests. The BReC plot application was demonstrated using serial carcinoembryonic antigen (CEA) and Cyfra 21.1 results from 216 patients with metastasized non-small cell lung cancer, treated with Nivolumab in routine clinical practice. RESULTS: The developed software supported the generation of BReC plots and diagnostic validation of biomarker response-based medical tests by generating the sensitivity, specificity and predictive values. Obtained BReC plots showed a clear relationship between clinical outcome and CEA and Cyfra 21.1 responses. Furthermore, using BReC plots, CEA and Cyfra 21.1 based medical tests were designed with a sensitivity for detection of treatment failure of 0.34 and 0.35 and a specificity of 0.96. CONCLUSIONS: The BReC plot appears to support diagnostic validation studies and the interpretation of longitudinal biomarkers though further validation is warranted.
Authors: Frederik A van Delft; Milou Schuurbiers; Mirte Muller; Sjaak A Burgers; Huub H van Rossum; Maarten J IJzerman; Hendrik Koffijberg; Michel M van den Heuvel Journal: Heliyon Date: 2022-10-04
Authors: Hao Chen; Yan Jiang; Keyi Jia; Kaixuan Zhang; Natsumi Matsuura; Jin Yong Jeong; Bo Su; Xiao Zhou Journal: Transl Lung Cancer Res Date: 2021-10