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Technical Verification and Assessment of Independent Validation of Biomarker Models for Endometriosis.
Biomed Res Int. 2019; 2019:3673060.BR

Abstract

There is a great need for a noninvasive diagnosis for endometriosis. Several biomarkers and biomarker panels have been proposed. Biomarker models consisting of CA-125, VEGF, Annexin V, and glycodelin/sICAM-1 were previously developed by our group. The objective of our current study was to assess the impact of technical and biological variability on the performance of those previously developed prediction models in a technical verification and a validation setting. The technical verification cohort consisted of peripheral blood plasma samples from a subset of the patients included in the original study of Vodolazkaia et al. (99 women with and 37 women without endometriosis). The validation study was done in plasma samples of an independent patient cohort (170 women with and 86 women without endometriosis). Single immunoassays were used for CA-125, VEGF-A, sICAM-1, Annexin V, and glycodelin. Statistical analyses were done using univariate and multivariate (logistic regression) approaches. The previously reported prediction models for endometriosis had a low performance in both the technical verification and validation setting. New prediction models were developed, which included CA-125, Annexin V, and sICAM-1, but CA-125 was the only marker that was retained in the models across the technical verification and validation study. Overall, successful validation of a biomarker model depends on several factors such as patient selection, collection methods, assay selection/handling, stability of the marker, and statistical analysis and interpretation. There is a need for standardized studies in large, well-defined patient cohorts with robust assay methodologies.

Authors+Show Affiliations

KU Leuven Department of Development and Regeneration, Woman and Child, 3000 Leuven, Belgium. Department of Obstetrics and Gynecology, Leuven University Fertility Center, University Hospital Leuven, 3000 Leuven, Belgium.KU Leuven Department of Development and Regeneration, Woman and Child, 3000 Leuven, Belgium.KU Leuven Department of Development and Regeneration, Woman and Child, 3000 Leuven, Belgium.KU Leuven Department of Public Health and Primary Care, Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat), 3000 Leuven, Belgium.KU Leuven Department of Development and Regeneration, Woman and Child, 3000 Leuven, Belgium.KU Leuven Department of Development and Regeneration, Woman and Child, 3000 Leuven, Belgium. Department of Obstetrics and Gynecology, Leuven University Fertility Center, University Hospital Leuven, 3000 Leuven, Belgium.SYBIOMA, Facility for Systems Biology Based Mass Spectrometry, 3000 Leuven, Belgium. KU Leuven Department of Cellular and Molecular Medicine, 3000 Leuven, Belgium.KU Leuven Department of Development and Regeneration, Woman and Child, 3000 Leuven, Belgium.

Pub Type(s)

Clinical Trial
Journal Article
Validation Study

Language

eng

PubMed ID

31428634

Citation

O, Dorien F., et al. "Technical Verification and Assessment of Independent Validation of Biomarker Models for Endometriosis." BioMed Research International, vol. 2019, 2019, p. 3673060.
O DF, Fassbender A, Van Bree R, et al. Technical Verification and Assessment of Independent Validation of Biomarker Models for Endometriosis. Biomed Res Int. 2019;2019:3673060.
O, D. F., Fassbender, A., Van Bree, R., Laenen, A., Peterse, D. P., Vanhie, A., Waelkens, E., & D'Hooghe, T. M. (2019). Technical Verification and Assessment of Independent Validation of Biomarker Models for Endometriosis. BioMed Research International, 2019, 3673060. https://doi.org/10.1155/2019/3673060
O DF, et al. Technical Verification and Assessment of Independent Validation of Biomarker Models for Endometriosis. Biomed Res Int. 2019;2019:3673060. PubMed PMID: 31428634.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Technical Verification and Assessment of Independent Validation of Biomarker Models for Endometriosis. AU - O,Dorien F, AU - Fassbender,Amelie, AU - Van Bree,Rita, AU - Laenen,Annouschka, AU - Peterse,Daniëlle P, AU - Vanhie,Arne, AU - Waelkens,Etienne, AU - D'Hooghe,Thomas M, Y1 - 2019/07/25/ PY - 2019/04/02/received PY - 2019/06/13/accepted PY - 2019/8/21/entrez PY - 2019/8/21/pubmed PY - 2020/1/16/medline SP - 3673060 EP - 3673060 JF - BioMed research international JO - Biomed Res Int VL - 2019 N2 - There is a great need for a noninvasive diagnosis for endometriosis. Several biomarkers and biomarker panels have been proposed. Biomarker models consisting of CA-125, VEGF, Annexin V, and glycodelin/sICAM-1 were previously developed by our group. The objective of our current study was to assess the impact of technical and biological variability on the performance of those previously developed prediction models in a technical verification and a validation setting. The technical verification cohort consisted of peripheral blood plasma samples from a subset of the patients included in the original study of Vodolazkaia et al. (99 women with and 37 women without endometriosis). The validation study was done in plasma samples of an independent patient cohort (170 women with and 86 women without endometriosis). Single immunoassays were used for CA-125, VEGF-A, sICAM-1, Annexin V, and glycodelin. Statistical analyses were done using univariate and multivariate (logistic regression) approaches. The previously reported prediction models for endometriosis had a low performance in both the technical verification and validation setting. New prediction models were developed, which included CA-125, Annexin V, and sICAM-1, but CA-125 was the only marker that was retained in the models across the technical verification and validation study. Overall, successful validation of a biomarker model depends on several factors such as patient selection, collection methods, assay selection/handling, stability of the marker, and statistical analysis and interpretation. There is a need for standardized studies in large, well-defined patient cohorts with robust assay methodologies. SN - 2314-6141 UR - https://www.unboundmedicine.com/medline/citation/31428634/Technical_Verification_and_Assessment_of_Independent_Validation_of_Biomarker_Models_for_Endometriosis_ L2 - https://dx.doi.org/10.1155/2019/3673060 DB - PRIME DP - Unbound Medicine ER -