Clues to revising the conventional diagnostic algorithm for endometriosis

Andrew Spiers, Andrew J. Spiers, Horace Roman, Megan Wasson, Charles Chapron, Pascal Rousset, François Golfier, Raffaele Fauvet, R. Fauvet, Léa Delbos, Mathieu Poilblanc, Vincent Lavoué, E. Petit, Erick Petit, Frédérique Perotte, Mikhael Benjoar, Chérif Akladios, Cherif Akladios, Benjamin Merlot, Thomas Dennis, Anne Sophie Boudy, Anne‐Sophie Boudy, Benjamin Fedida, Pierre Leguevaque, Pierre Lèguevaque, Ludivine Genre, Clothilde Hennetier, Morgane Perrin, Patrice Crochet, Nicolas Lucas, Claire-Marie Roger, Claire‐Marie Roger, Elodie Chantalat, Élodie Chantalat, Pierre Collinet, Hervé Fernandez, H. Fernandez, Philippe Descamps, Sofiane Bendifallah
International Journal of Gynecology & Obstetrics · 2024 · vol. 168(1) , pp. 101–111 · doi:10.1002/ijgo.15840 · PMID:39161277 · W4401715698
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This review synthesizes evidence on diagnostic tools for endometriosis, finding limited impact from traditional methods but highlighting potential for novel biomarkers like salivary noncoding RNAs to revise current algorithms.

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Abstract

Endometriosis is a complex gynecologic disorder characterized primarily by symptoms of pelvic pain, infertility, and altered quality of life. National and international guidelines highlight the diagnostic difficulties and lack of conclusive diagnostic tools for endometriosis. Furthermore, guidelines are becoming questionable at an increasingly rapid rate as new diagnostic techniques emerge. This work aims to provide a knowledge synthesis of the relevance of various diagnostic tools and to assess areas of improvement of conventional algorithms. MEDLINE and Cochrane Library databases were searched from January 2021 to December 2023 using relevant key words. Articles evaluating the diagnostic relevance and performance of various tools were included and independently reviewed by the authors for eligibility. Included studies were assessed using the GRADE and QUADAS-2 tools. Of the 4204 retrieved articles, 26 were included. While anamnesis and clinical examination do contribute to diagnostic accuracy, their level of evidence and impact on the diagnostic process remains limited. Although imaging techniques are recommended to investigate endometriosis, ultrasonography remains highly operator dependent. Magnetic resonance imaging appears to exhibit higher sensitivities than ultrasound. However, concerns persist with regards to the terminology, anatomical definition of lesions, and accuracies of both ultrasound and magnetic resonance imaging. Recently, several biological markers have been studied and cumulative evidence supports the contribution of noncoding RNAs to the diagnosis of endometriosis. Marginal improvements have been suggested for anamnesis, clinical examination, and imaging examinations. Conversely, some biomarkers, including the saliva microRNA signature for endometriosis, have emerged as diagnostic tools which inspire reflection on the revision of conventional diagnostic algorithms.

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Condition tags

mesh:D004715endometriosisinfertility

MeSH descriptors

Algorithms Algorithms Algorithms Algorithms Algorithms Algorithms Algorithms Algorithms Algorithms Algorithms Algorithms Algorithms Algorithms Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

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