O-214 Incidence and factors associated with premature ovarian insufficiency: a population-based cohort study
Notice bibliographique
Résumé
Abstract Study question What is the incidence and associated risk factors for premature ovarian insufficiency (POI) in Ontario, Canada between 1995 and 2019? Summary answer The incidence of POI has been rising since 2011; those with history of endometriosis had the highest incidence of POI compared to other associated factors. What is known already Recent estimates of POI suggest a global prevalence of 3.7% with increased rates over time. The underlying etiology of POI is variable and can range from genetic, to autoimmune, to infectious or iatrogenic. Nonetheless, in about 70% of cases, the etiology of spontaneous POI remains unknown. Prior studies on the incidence of POI are limited by study designs that may lead to recall bias, including self-report and cross-sectional data on age at menopause, small sample size, and inability to assess factors associated with POI. Study design, size, duration Population-based cohort study including all females in Ontario ≤ 39 years between 1995 and 2019. Follow-up was until development of POI, age 40, death, loss of Insurance Plan, or end of the study period. The primary outcome was a diagnosis of POI from a minimum of one of two sources occurring before the age of 40: a) records of surgical menopause, or b) 1 or more physician consultations billed as menopause diagnosis (ICD-9 627). Participants/materials, setting, methods Annual incidence rates (IR) of POI diagnosis were calculated using census data with the whole female Ontario population aged 39 years or younger as the denominator. Diagnosis type were defined as non-iatrogenic, surgical, post-chemotherapy and/or radiotherapy, or post-surgery in combination with chemotherapy and/or radiotherapy. Potential associated factors in relation to POI were quantified by incidence rate ratios (IRR) derived by modified Poisson regression. Main results and the role of chance Of all 3,635,702 eligible women, 168,173 had newly diagnosed POI due to any etiology (IR 389.4 per 100,000 person-years). Participants were followed for a median (IQR) of 11 (6-18) years. The mean (IQR) age at POI diagnosis was 31 (25-26) years. IRs by type of POI diagnosis were: 351.4 per 100,000 person-years for non-iatrogenic, 30.2 per 100,000 person-years for surgical, 5.5 per 100,000 person-years post-chemotherapy and/or radiotherapy, and 2.3 per 100,000 person-years post-surgery in combination with chemotherapy and/or radiotherapy. Overall incidence of POI decreased from 2002 to 2008, followed by an increase to 2019, primarily driven by non-iatrogenic POI which followed this trend. The IR of surgically induced POI decreased from 60 per 100,000 person-years in 1995 to 20 per 100,000 person-years in 2019. The IR of POI related to chemotherapy and radiation +/- surgery show a steady increase 1995 to 2019. Age adjusted IRR of POI by potential associated factors were 1.19 (1.17-1.22) for autoimmune disorders, 1.50 (1.42 - 1.59) for genetic disorders, 1.59 (1.51-1.67) for drug/tobacco use, 2.01 (1.89 -2.14) for cancer, chemotherapy or radiotherapy, and 3.45 (3.39 - 3.52) for endometriosis. Limitations, reasons for caution This study is limited by the use of administrative health data, namely misclassification and residual confounding. Wider implications of the findings These results may help guide clinician counselling for those with co-morbidities associated with POI, particularly patients with endometriosis. These results also indicate that ovarian-preserving surgical approaches have led to greatly reduced incidence of surgically-induced POI since 1995 in Ontario, Canada. Trial registration number No
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».