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.

With the aim to shorten the time for diagnosis and accelerate access to correct management, a non-invasive diagnostic test for endometriosis was developed and validated. The IVD test combines an ELISA test kit to quantify CA125 and BDNF concentrations in serum and a data treatment algorithm hosted in medical software processing results from the ELISA test and responses to six clinical variables. Serum samples and clinical variables extracted from psychometric questionnaires from 77 patients were collected from the Oxford Endometriosis CaRe Centre biobank (UK). Case/control classification was performed based on laparoscopy and histological verification of the excised lesions. Biomarkers serum concentrations and clinical variables were introduced to the software, which generates the qualitative diagnostic result (“positive” or “negative”). This test allowed the detection of 32% of cases with superficial endometriosis, which is an added value given the limited efficacy of existing imaging techniques. Even in the presence of various confounding medical conditions, the test maintained a specificity of 100%, supporting its suitability for use in patients with underlying medical conditions.

STRUCTURED Objective: To develop a non-invasive diagnostic test for endometriosis. Design: We conducted two studies: the development study (study 1) aimed at (i) evaluating the ability of CA125, brain-derived neurotrophic factor (BDNF) and clinical variables in segregating between cases and controls and (ii) developing a diagnostic algorithm based on those results. In the validation study (study 2), the clinical performance of the developed in vitro diagnostic (IVD) test, in diagnosing endometriosis was validated. Interventions: Serum samples and clinical variables extracted from psychometric questionnaires were collected from the Oxford Endometriosis CaRe Centre biobank (UK). Case/control classification was performed based on laparoscopy and histological verification of endometrial glands and/or stroma in the excised lesions. Main outcome measures: Study 1 and 2 included n =204 and n =79 patients, respectively. CA125 and BDNF concentrations were determined using the endometriosis IVD ELISA kit. In study 2, serum CA125 and BDNF concentrations and clinical variables were introduced into the IVD test software hosting the data treatment algorithm, which generates the qualitative diagnostic result (“positive” or “negative”). Results: Results from study 1 showed that, for both biomarkers levels, a statistically significant difference was found between cases and controls. Among all clinical variables related to patients’ medical history considered, six were significantly different between cases and controls: record of a previous surgery to investigate endometriosis presence, painful periods leading to referral for endometriosis presence, severity of menstrual pain during last cycle, age at first experience of intercourse pain, age at first regular use of painkillers and age at first diagnosis of ovarian cyst. In study 2, the novel endometriosis IVD test demonstrated sensitivity and specificity values of 46.2% (25.5-66.8%) and 100% (86.7-100%), respectively. Conclusion: BDNF and CA125, together with patient’s clinical variables allowed efficient segregation between controls and endometriosis cases. Due to its high specificity, the novel endometriosis IVD test is an accurate rule-in non-invasive method, potentially contributing to diagnose endometriosis.

With the aim to shorten the time for diagnosis and accelerate access to correct management, a non-invasive diagnostic test for endometriosis was developed and validated. The IVD test combines an ELISA test kit to quantify CA125 and BDNF concentrations in serum and a data treatment algorithm hosted in medical software processing results from the ELISA test and responses to six clinical variables. Serum samples and clinical variables extracted from psychometric questionnaires from 77 patients were collected from the Oxford Endometriosis CaRe Centre biobank (UK). Case/control classification was performed based on laparoscopy and histological verification of the excised lesions. Biomarkers serum concentrations and clinical variables were introduced to the software, which generates the qualitative diagnostic result (“positive” or “negative”). This test allowed the detection of 32% of cases with superficial endometriosis, which is an added value given the limited efficacy of existing imaging techniques. Even in the presence of various confounding medical conditions, the test maintained a specificity of 100%, supporting its suitability for use in patients with underlying medical conditions.