Because endometriosis is a chronic and heterogeneous disease, its symptoms, extent, progression, localizations, treatment responsiveness and recurrence potential vary from one patient to another.
As a consequence it is often difficult for the doctor to know which class of treatment will better benefit the patient to relieve pain, to predict if and when the disease may recur after surgery, or to make informed decisions regarding the best fertility treatment plan.
Current endometriosis classification, the revised American Fertility Society (rAFS) system to grade endometriosis into different stages based on size and localization of the lesions (I to IV), does not always correlate with underlying symptoms (notably pain and infertility).
Additionally this classification has limited prognostic or predictive value. Disease recurrence is frequent and poses an underestimated ongoing medical unmet need. A biomarker-based approach would add specificity to patient management if it could predict which patients will respond to therapy, or which patients will develop aggressive forms of the disease.
There’s a clear lack of such biomarkers that would improve disease classification, patient stratification and guide treatment decisions.
Endodiag together with several expert gynecologists has developed EndoGram®, a 10-biomarker test based on the analysis of biopsies taken during surgery. Thanks to a proprietary algorithm combining other patient clinical factors, EndoGram® provides for each patient a risk of disease recurrence score and a biological profile aimed to help the physician discard unsuitable treatments.
EndoGram is currently under clinical validation.
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