Evidence map›Paper›PMID 37187159›Full record

ArticleHuman reproduction (Oxford, England)2023

TGFBI as a candidate biomarker for non-invasive diagnosis of early-stage endometriosis.

Vid Janša, Maja Pušić Novak, Helena Ban Frangež, Tea Lanišnik Rižner

Open access · hybridAbstract readMulticenter Study
In one paragraph

Article in Human reproduction (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
6.8field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Endometriosis: Challenges in Clinical Molecular Diagnostics and Treatment.International journal of molecular sciences · 2025
    Review
  8. Serum Metabolites as Diagnostic Biomarkers in Patients with Endometriosis.Reproductive sciences (Thousand Oaks, Calif.) · 2024
    Article
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Vid JanšaDepartment of Obstetrics and Gynaecology, University Medical Centre Ljubljana, Ljubljana, Slovenia.
Maja Pušić NovakInstitute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.ORCID 0000-0003-0458-7729
Helena Ban FrangežDepartment of Obstetrics and Gynaecology, University Medical Centre Ljubljana, Ljubljana, Slovenia.
Tea Lanišnik RižnerInstitute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.ORCID 0000-0002-3453-4081
University of Ljubljana · SILjubljana University Medical Centre · SI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

study questionCan cartilage oligomeric matrix protein (COMP) and transforming growth factor-β-induced protein ig-h3 (TGFBI) alone or in combination with cancer antigen 125 (CA-125) be considered as potential blood biomarkers of endometriosis? SUMMARY ANSWER: The results of this study indicate that COMP has no diagnostic value. TGFBI has potential as a non-invasive biomarker of the early stages of endometriosis, while TGFBI together with CA-125 has similar diagnostic characteristics as CA-125 alone for all stages of endometriosis. WHAT IS KNOWN ALREADY: Endometriosis is a common, chronic gynecological disease that significantly affects patient quality of life by causing pain and infertility. The gold standard for diagnosis is visual inspection of pelvic organs by laparoscopy, therefore there is an urgent need for discovery of non-invasive biomarkers for endometriosis to reduce diagnostic delays and allow earlier treatment of patients. The potential biomarkers for endometriosis evaluated in this study (COMP and TGFBI) were previously identified by our proteomic analysis of peritoneal fluid samples. STUDY DESIGN, SIZE, DURATION: This is a case-control study divided into a discovery (n = 56 patients) and a validation phase (n = 237 patients). All patients were treated between 2008 and 2019 in a tertiary medical center. PARTICIPANTS/MATERIALS, SETTING,

methodPatients were stratified based on the laparoscopic findings. The discovery phase included 32 endometriosis patients (cases) and 24 patients with confirmed absence of endometriosis (controls). The validation phase included 166 endometriosis and 71 control patients. Concentrations of COMP and TGFBI were measured by ELISA in plasma samples, whereas concentration of CA-125 was measured using a clinically validated assay for serum samples. Statistical and receiver operating characteristic (ROC) curve analyses were performed. The classification models were built using the linear support vector machine (SVM) method with the SVM built-in feature ranking method. MAIN RESULTS AND THE ROLE OF CHANCE: The discovery phase revealed significantly increased concentration of TGFBI, but not COMP, in plasma samples of patients with endometriosis compared to controls. In this smaller cohort, univariate ROC analysis showed fair diagnostic potential of TGFBI, with an AUC value of 0.77, sensitivity of 58%, and specificity of 84%. The classification model built using linear SVM and combining TGFBI and CA-125 showed an AUC value of 0.91, sensitivity of 88% and specificity of 75% in distinguishing patients with endometriosis from controls. The validation phase results revealed similar diagnostic characteristics of the SVM model combining TGFBI and CA-125, with an AUC value of 0.83, sensitivity of 83% and specificity of 67% and CA-125 alone with AUC value of 0.83, sensitivity of 73% and specificity of 80%. TGFBI exhibited good diagnostic potential for early-stage endometriosis (revised American Society for Reproductive Medicine stage I-II), with an AUC value of 0.74, sensitivity of 61% and specificity of 83% compared to CA-125, which had an AUC value of 0.63, sensitivity of 60% and specificity of 67%. An SVM model combining TGFBI and CA-125 showed a high AUC value of 0.94 and sensitivity of 95% for diagnosing moderate-to-severe endometriosis. LIMITATIONS, REASONS FOR CAUTION: The diagnostic models were built and validated from a single endometriosis center, and thus further validation and technical verification in a multicenter study with a larger cohort is needed. Additional limitation was lack of histological confirmation of disease for some patients in the validation phase. WIDER IMPLICATIONS OF THE

findingsThis study revealed for the first time increased concentration of TGFBI in plasma samples of patients with endometriosis, particularly those with minimal-to-mild endometriosis, compared to controls. This is the first step in considering TGFBI as a potential non-invasive biomarker for the early stages of endometriosis. It also opens a path for new basic research to investigate the importance of TGFBI in the pathophysiology of endometriosis. Further studies are needed to confirm the diagnostic potential of a model based on TGFBI and CA-125 for the non-invasive diagnosis of endometriosis. STUDY FUNDING/COMPETING INTEREST(S): The preparation of this manuscript was supported by grant J3-1755 from the Slovenian Research Agency to T.L.R and EU H2020-MSCA-RISE project TRENDO (grant 101008193). All authors declare that they have no conflicts of interest. TRIAL REGISTRATION NUMBER: NCT0459154.

Indexed as

EndometriosisbetaIG-H3 ProteinBiomarkersCase-Control StudiesFemaleHumansProteomicsQuality of LifebetaIG-H3 ProteinBiomarkersblood biomarkerscancer antigen 125cartilage oligomeric matrix proteindiagnostic algorithmendometriosisnon-invasive diagnosisreceiver operating characteristic curvesensitivityspecificitytransforming growth factor-β-induced protein ig-h3

Identifiers

PMID37187159
PMCPMC10320490
OpenAlexW4376602177

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.