Costs and Benefits of Opportunistic Salpingectomy as an Ovarian Cancer Prevention Strategy
Notice bibliographique
Résumé
Evidence accumulated over the past decade suggests that the majority of ovarian cancers arise in the fallopian tube and not the ovary. This led to the recommendation that opportunistic salpingectomy be offered as an elective concurrent procedure for premenopausal women at average risk of ovarian cancer who undergo either hysterectomy for benign gynecologic conditions or surgical sterilization. It has been estimated that opportunistic salpingectomy could reduce the ovarian cancer risk by 20% to 40% over the next 20 years. There are few hard data, however, on the long-term risks and benefits associated with this procedure. Because a clinical trial is not feasible, a population-based cohort study is essential to establish the long-term risks, benefits, and cost-effectiveness of opportunistic salpingectomy. Such a cohort study would take many years to yield results; more timely data on the likely costs and benefits of this strategy could be obtained from a decision analytic model. The aim of this study was to conduct a cost-effectiveness analysis of opportunistic salpingectomy as an ovarian cancer prevention strategy in the general population. A Markov Monte Carlo simulation model was used to estimate the costs and benefits of opportunistic salpingectomy in a hypothetical cohort of premenopausal Canadian women undergoing hysterectomy for benign gynecologic conditions or surgical sterilization as permanent contraception. Three strategies were compared: hysterectomy alone, hysterectomy with salpingectomy, and hysterectomy with bilateral salpingo-oophorectomy (BSO). The main outcome measure was the incremental cost-effectiveness ratio. Effectiveness was calculated in terms of average years of life expectancy gain. Multiple sensitivity analyses accounted for uncertainty around various parameters, including treatment costs, age at surgery, and estimates of risk reduction attributable to salpingectomy. The number of ovarian cancer cases associated with each strategy was estimated in the simulation model. The model predicted that salpingectomy with hysterectomy would be less costly ($11,044 ± $1.56) and more effective (21.12 ± 0.02 years) than either hysterectomy alone ($11,207 ± $29.81, 21.10 ± 0.03 years) or BSO ($12,627 ± $13.11, 20.94 ± 0.03 years), respectively. The model also predicted that salpingectomy for sterilization would be marginally more costly than tubal ligation ($9720 ± $3.74 vs $9339 ± $26.74) but more effective (22.45 ± 0.02 vs 22.43 ± 0.02 years of life expectancy), with an incremental cost-effectiveness ratio of $27,278 per year of life gained. Results were stable over a wide range of treatment costs and estimates of risk reduction. In the Monte Carlo simulation model, salpingectomy reduced the risk of ovarian cancer by 38.1% (95% confidence interval, 36.5%–41.3%) compared with hysterectomy alone and 29.2% (95% confidence interval, 28.0%–31.4%) compared with tubal ligation. This analytic model shows that opportunistic salpingectomy with hysterectomy for benign conditions has the potential to decrease ovarian cancer risk at acceptable cost and that salpingectomy is a cost-effective alternative to use of tubal ligation for sterilization. These findings suggest that prophylactic salpingectomy should be considered in all women undergoing these procedures.
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 | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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) | 0,001 | 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 ».