Evaluation of a panel of 28 biomarkers for the non-invasive diagnosis of endometriosis
Abstract
BACKGROUND: At present, the only way to conclusively diagnose endometriosis is laparoscopic inspection, preferably with histological confirmation. This contributes to the delay in the diagnosis of endometriosis which is 6-11 years. So far non-invasive diagnostic approaches such as ultrasound (US), MRI or blood tests do not have sufficient diagnostic power. Our aim was to develop and validate a non-invasive diagnostic test with a high sensitivity (80% or more) for symptomatic endometriosis patients, without US evidence of endometriosis, since this is the group most in need of a non-invasive test. METHODS: A total of 28 inflammatory and non-inflammatory plasma biomarkers were measured in 353 EDTA plasma samples collected at surgery from 121 controls without endometriosis at laparoscopy and from 232 women with endometriosis (minimal-mild n = 148; moderate-severe n = 84), including 175 women without preoperative US evidence of endometriosis. Surgery was done during menstrual (n = 83), follicular (n = 135) and luteal (n = 135) phases of the menstrual cycle. For analysis, the data were randomly divided into an independent training (n = 235) and a test (n = 118) data set. Statistical analysis was done using univariate and multivariate (logistic regression and least squares support vector machines (LS-SVM) approaches in training- and test data set separately to validate our findings. RESULTS: In the training set, two models of four biomarkers (Model 1: annexin V, VEGF, CA-125 and glycodelin; Model 2: annexin V, VEGF, CA-125 and sICAM-1) analysed in plasma, obtained during the menstrual phase, could predict US-negative endometriosis with a high sensitivity (81-90%) and an acceptable specificity (68-81%). The same two models predicted US-negative endometriosis in the independent validation test set with a high sensitivity (82%) and an acceptable specificity (63-75%). CONCLUSIONS: In plasma samples obtained during menstruation, multivariate analysis of four biomarkers (annexin V, VEGF, CA-125 and sICAM-1/or glycodelin) enabled the diagnosis of endometriosis undetectable by US with a sensitivity of 81-90% and a specificity of 63-81% in independent training- and test data set. The next step is to apply these models for preoperative prediction of endometriosis in an independent set of patients with infertility and/or pain without US evidence of endometriosis, scheduled for laparoscopy.
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Proinflammatory cytokines may not be suitable candidates for a noninvasive biomarker for endometriosis, unless proper control subjects can be established.
“This inappropriate selection of control led to their inability to discriminate endometriosis patients from others with nonendometriosisrelated pelvic inflammation and pain (115), effectively demonstrating that proinflammatory cytokines may not be suitable candidates for a noninvasive biomarker for endometriosis, unless proper control subjects can be established.”
From Biomarkers in endometriosis: Challenges and opportunities (2017) · cites this paper as [115]
In Vodolazkaia et al.'s training data set, increased levels of proinflammatory markers including TNF-a, IL-6, and IL-1b were found in the control group rather than the endometriosis group.
“Interestingly, though, they found increased levels of proinflammatory markers, including TNF-a, IL-6, and IL-1b, in the control group rather than the endometriosis group in the training data set, remarking on the possibility of nonendometriotic pelvic pathology contributing to the increase in the control group of women.”
From Biomarkers in endometriosis: Challenges and opportunities (2017) · cites this paper as [115]
Inappropriate selection of control led to the inability to discriminate endometriosis patients from others with nonendometriosis-related pelvic inflammation and pain.
“This inappropriate selection of control led to their inability to discriminate endometriosis patients from others with nonendometriosisrelated pelvic inflammation and pain (115), effectively demonstrating that proinflammatory cytokines may not be suitable candidates for a noninvasive biomarker for endometriosis, unless proper control subjects can be established.”
From Biomarkers in endometriosis: Challenges and opportunities (2017) · cites this paper as [115]
Since May et al., 2010, research in endometriosis biomarkers has accomplished successful validation of biomarkers in an independent sample dataset, but still no test for endometriosis is commercially available.
“Since the extensive review of May et al., 2010, research in endometriosis biomarkers has accomplished the successful validation of biomarkers in an independent sample dataset [24], but still no test for endometriosis is commercially available.”
From Update on biomarkers for the detection of endometriosis (2015) · cites this paper as [24]
No consensus exists on whether cytokines are suitable to discriminate endometriosis patients from patients with other pelvic pathology.
“However, no consensus exists on whether cytokines are suitable to discriminate endometriosis patients from patients with other pelvic pathology [24].”
From Update on biomarkers for the detection of endometriosis (2015) · cites this paper as [24]
sICAM-I has been included in a panel with three other markers to diagnose endometriosis cases that could not be identified by preoperative ultrasound.
“Correspondingly, sICAM-I has been included in a panel with three other markers to diagnose endometriosis cases that could not be identified by preoperative ultrasound [24].”
From Update on biomarkers for the detection of endometriosis (2015) · cites this paper as [24]
A panel of 4 biomarkers (CA-125, VEGF, Annexin V, and glycodelin/sICAM-1) showed sensitivity of 74-94% and specificity of 55-75% in a training set and after initial validation in an independent test set.
“Recently, a panel of 4 biomarkers (CA-125, VEGF, Annexin V, and glycodelin/soluble intercellular adhesion molecule (sICAM)-1) showed a sensitivity of 74–94% and a specificity of 55–75% in a training set and after initial validation in an independent test set [24].”
From Update on biomarkers for the detection of endometriosis (2015) · cites this paper as [24]
In Vodolazkaia et al., univariate analysis showed differential expression of several cytokines and chemokines in 232 women with endometriosis and 121 controls, but no cytokines or chemokines were included in the final proposed panel after multivariate analysis.
“In a study by Vodolazkaia et al., univariate analysis showed the differential expression of several cytokines and chemokines in 232 women with endometriosis and 121 controls [24]. However, no cytokines or chemokines were included in the final proposed panel of biomarkers after multivariate analysis [24].”
From Update on biomarkers for the detection of endometriosis (2015) · cites this paper as [24]
A recent study proposing a panel of biomarkers included VEGF in two panels to detect minimal/mild endometriosis with 80% sensitivity.
“Despite these contrasting results, a recent study proposing a panel of biomarkers included VEGF in two panels to detect minimal/mild endometriosis with 80% sensitivity [24].”
From Update on biomarkers for the detection of endometriosis (2015) · cites this paper as [24]
A first step toward validation of biomarkers has been made.
“A first step toward validation of biomarkers has been made [24, 140]; however, further studies are needed to develop a clinically useful test.”
From Update on biomarkers for the detection of endometriosis (2015) · cites this paper as [24]
In plasma samples obtained during menstruation, multivariate analysis of 4 biomarkers (annexin V, VEGF, CA-125, and sICAM-1/or glycodelin) enabled the diagnosis of endometriosis undetectable by ultrasound with a sensitivity of 81% to 90% and a specificity of 63% to 81% in independent training and test data sets.
“More recently it was reported that in plasma samples obtained during menstruation, multivariate analysis of 4 biomarkers (annexin V, VEGF, CA-125, and sICAM-1/or glycodelin) enabled the diagnosis of endometriosis undetectable by ultrasound with a sensitivity of 81% to 90% and a specificity of 63% to 81% in independent training and test data sets.19”
From Defining Future Directions for Endometriosis Research: Workshop Report From the 2011 World Congress of Endometriosis in Montpellier, France (2013) · cites this paper as [19]
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Self-citationDetermination of HGF concentration in serum and peritoneal fluid in women with endometriosis.
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Unexpected increase of the CA 19-9 tumour marker in patients with endometriosis.
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Biomarkers in endometriosis: Challenges and opportunities
Ahn, S. H., Singh, V., & Tayade, C. (2017) · Fertility and Sterility · doi:10.1016/j.fertnstert.2017.01.009 · Cited by 242 · see citing works
The link between immunity, autoimmunity and endometriosis: a literature update
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“biomarkers has beenmade [24, 140]; however, further studies”
InfluentialSelf-citationCirculating microRNAs as potential biomarkers for endometriosis
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Molecular classification of endometriosis and disease stage using high-dimensional genomic data
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Diagnostic accuracy of cancer antigen 125 for endometriosis: A systematic review and meta-analysis
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An integrated multi-tissue approach for endometriosis candidate biomarkers: a systematic review
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Nezhat, C. R., Oskotsky, T. T., Robinson, J. F., Fisher, S. J., Tsuei, A., Liu, B., Irwin, J. C., Gaudilliere, B., Sirota, M., Stevenson, D. K., et al. (2025) · npj Women s Health · doi:10.1038/s44294-024-00052-w · Cited by 25 · see citing works
Evaluation of elevated urinary enolase I levels in patients with endometriosis
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Biomarker development in endometriosis
Burney, R. O. (2014) · Scandinavian Journal of Clinical and Laboratory Investigation · doi:10.3109/00365513.2014.936692 · Cited by 16 · see citing works
- Authors
- Vodolazkaia, A., El-Aalamat, Y., Popovic, D., Mihalyi, A., Bossuyt, X., Kyama, C. M., Fassbender, A., Bokor, A., Schols, D., Huskens, D., Meuleman, C., Peeraer, K., Tomassetti, C., Gevaert, O., Waelkens, E., Kasran, A., De Moor, B., & D'Hooghe, T. M.
- Affiliations
- Universitair Ziekenhuis Leuven (BE)
- KU Leuven (BE)
- Jomo Kenyatta University of Agriculture and Technology (KE)
- Semmelweis University (HU)
- Rega Institute for Medical Research (BE)
- ORCID
- Venue
- Human Reproduction
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-06-26
- Volume
- 27
- Issue
- 9
- Pages
- 2698-2711
- ISSN
- 0268-1161 (ISSN-L)
- 1460-2350
- OpenAlex
- W2130807780
- Semantic Scholar
- 5f325892de937d4294ff10563a742f0011c75a59
- Cited by
- 189
- References
- 85
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 16 · 2023: 13 · 2022: 11 · 2021: 16 · 2020: 14 · 2019: 11 · 2018: 13 · 2017: 12 · 2016: 15 · 2015: 18 · 2014: 15 · 2013: 18 · 2012: 3
- FWCI
- 20.12
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Human Reproduction (publishedVersion)
- PubMed (publishedVersion)
- Lirias (submittedVersion)
- Topics
- Health Sciences › Medicine › Reproductive Medicine › Endometriosis Research and Treatment
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ectopic Pregnancy Diagnosis and Management
- Health Sciences › Medicine › Obstetrics and Gynecology › Endometrial and Cervical Cancer Treatments
- Keywords
- endometriosis, non-invasive diagnosis, plasma biomarkers, biomarker panel, annexin V, vascular endothelial growth factor, CA125, sICAM-1, glycodelin, menstrual cycle phases, sensitivity and specificity, least squares support vector machine, inflammatory markers, delayed diagnosis, laparoscopic surgery
- MeSH terms
- Adult, Edetic Acid, Endometriosis, Female, Humans, Inflammation, Menstrual Cycle, Middle Aged, Laparoscopy, Regression Analysis, ROC Curve, Sensitivity and Specificity, Models, Statistical, Biomarkers, Least-Squares Analysis, Case-Control Studies
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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