MC on BJOG-20-0227.R2 Prevalence of Endometriosis: how close are we to the truth?
Notice bibliographique
Résumé
Endometriosis is a common health condition affecting women of reproductive age who often present with chronic pelvic pain and/or infertility. There is wide variation in the estimates of endometriosis prevalence. Accurate reporting of the disease prevalence is hampered by multiple factors including long delay in diagnosis due to natural fluctuation in symptoms severity, lack of a reliable non-surgical diagnostic tool, polymorphic appearance of endometriosis lesions at laparoscopy, inability to achieve histological confirmation is all suspected cases and tendency for disease recurrence. Therefore, a longitudinal, rather than cross-sectional, cohort study design spanning an extended follow-up period is better suited to assess endometriosis prevalence. In this issue of BJOG, Rowlands and colleagues (2020) linked longitudinal survey data to three administrative health databases to identify the prevalence of endometriosis among 13,508 young Australian women followed up for nearly 20 years. The study reported a 6% cumulative prevalence of clinically-confirmed endometriosis and an additional 5.4% of clinically-suspected endometriosis. If these figures reflect the true prevalence of endometriosis, then one in nine women will be diagnosed with endometriosis at some point during their reproductive years up to the age of 44 with a peak at 30-34 years, thus underscoring the significant impact of the disease on the well-being and quality of life in young women and the enormous burden on healthcare resources needed to diagnose and treat endometriosis and its sequelae.The data presented in the study of Rowlands and colleagues (BJOG 2020) included patients who could have been diagnosed with adenomyosis but their condition was coded as endometriosis. This is unlikely to have significantly over-estimated the prevalence of endometriosis as recent evidence suggests adenomyosis prevalence to be only 1% with a considerable proportion of those patients having co-existing endometriosis (Yu et al, Am J Obstet Gynecol 2020; 223: 94.e1-10). The same can not be said about the 5.4% of clinically-suspected endometriosis cases. Symptoms review, clinical examination and various imaging modalities, including ultrasound scanning and magnetic resonance imaging, represent the cornerstone of non-invasive diagnosis of endometriosis. Current evidence suggests that the predictive accuracy of those non-invasive methods in the diagnosis of endometriosis compared to laparoscopy and histological confirmation is modest (Nisenblat et al, Cochrane Database Syst Rev, 2016 (2): CD009591) and depends on the combination of diagnostic tools used as well as the site and extent of the endometriosis lesions (Reid et al, Eur J Obstet Gynecol Reprod Biol 2019; 234: 171-178). These data are not provided in the study of Rowlands and colleagues. It is therefore difficult to accurately estimate the prevalence of endometriosis whether it’s the 6% clinically-confirmed rate or the full 11.4% confirmed and suspected rate. The truth probably lies somewhere in the middle! Future epidemiological studies should endeavour to elucidate on the distinction between the different methods used in the diagnosis of endometriosis with reference to the predictive accuracy of each diagnostic modality to help advance our understanding of the incidence and risk factors associated with this debilitating gynaecological condition.Mr. Tarek A El-ToukhyAssisted Conception Unit, Guys and St. Thomas Hospital NHS Trust11th Floor, Tower Wing,Guys Hospital,St. Thomas Street tarekeltoukhy@hotmail.com
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,005 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,884 | 0,730 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».