Development and Validation of an Endometriosis Diagnostic Method Based on Serum Biomarkers and Clinical Variables

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Abstract

Endometriosis affects more than 10% of women of reproductive age, significantly impacting their quality of life. Diagnosis typically takes 4 to 11 years from symptom onset. The gold standard for diagnosing this disease, laparoscopy, is invasive, contributing to this delay in diagnosis. Two studies were conducted to develop a diagnostic test based on the combination of serum biomarkers and clinical variables. Study 1, the development study, aimed to: (i) confirm the ability of CA125, BDNF and clinical variables to differentiate between cases and controls, and (ii) develop a diagnostic algorithm based on these results. Study 2 validated the clinical performance of the developed in vitro diagnostic (IVD) test in diagnosing endometriosis. Serum samples and clinical variables extracted from psychometric questionnaires were obtained from the Oxford Endometriosis CaRe Centre biobank (UK). Case/control classification was performed based on laparoscopy and histological verification of the excised lesions. Studies 1 and 2 included n = 204 and n = 79 patients, respectively. Study 1 found a statistically significant difference between cases and controls for levels of both biomarkers. Of the assessed clinical variables from the patients’ medical histories, six were found to be significantly different between endometriosis cases and controls. CA125, BDNF and these six clinical variables were combined into a multivariable prediction model. In Study 2, the IVD test demonstrated sensitivity and specificity values of 46.2% (25.5–66.8%) and 100% (86.7–100%), respectively. Due to its high specificity, this IVD test is a simple and accurate rule-in test for early disease identification, even in the presence of non-specific symptoms.

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Herranz-Blanco, B., Daoud, E., Viganò, P., García-Velasco, J. A., & Colli, E. (2023). Development and Validation of an Endometriosis Diagnostic Method Based on Serum Biomarkers and Clinical Variables. Biomolecules, 13(7). https://doi.org/10.3390/biom13071052

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