Clues to revising the conventional diagnostic algorithm for endometriosis.
Andrew Spiers1,2, Horace Roman3, Megan Wasson4
1Department of Obstetrics and Reproductive Medicine, Angers University Hospital, Angers, France.
Summary
Diagnosing endometriosis remains challenging. While current methods offer limited diagnostic accuracy, emerging biomarkers like noncoding RNAs show promise for improving diagnostic algorithms and patient outcomes.
Area of Science:
- Gynecology
- Medical Diagnostics
Background:
- Endometriosis is a complex gynecologic disorder causing pelvic pain and infertility.
- Current diagnostic tools for endometriosis face limitations and are increasingly questioned.
- There is a need to evaluate existing diagnostic methods and explore novel approaches.
Purpose of the Study:
- To synthesize knowledge on the diagnostic relevance of various tools for endometriosis.
- To assess areas for improvement in conventional diagnostic algorithms.
- To evaluate emerging diagnostic techniques and biomarkers.
Main Methods:
- Systematic literature search of MEDLINE and Cochrane Library (Jan 2021-Dec 2023).
- Inclusion of articles evaluating diagnostic relevance and performance of tools.
- Assessment of studies using GRADE and QUADAS-2 tools.
Main Results:
- Anamnesis and clinical examination have limited diagnostic impact.
- Imaging techniques like ultrasonography (operator-dependent) and MRI show potential but have accuracy concerns.
- Noncoding RNAs, particularly saliva microRNA signatures, show promise as diagnostic biomarkers.
Conclusions:
- Conventional diagnostic methods for endometriosis offer limited accuracy.
- Emerging biomarkers, such as noncoding RNAs, represent a significant advancement.
- New diagnostic tools necessitate a revision of current endometriosis diagnostic algorithms.
