Breast cancer risk after hysterectomy with and without salpingo-oophorectomy for benign indications

Chow, Stephanie; Raine‐Bennett, Tina; Samant, Navendu; Postlethwaite, Debbie; Holzapfel, Marie

doi:10.1016/j.ajog.2020.06.040

Cited by 12 publications

(13 citation statements)

References 27 publications

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“…However, the hysterectomy feature was used along with other risk factors that could influence the performance of models. The study by Chow et al assessed the risk of breast cancer after hysterectomy and showed a statistical significance between hysterectomy and breast cancer [ 50 ].…”

Section: Discussionmentioning

confidence: 99%

Prediction of Breast Cancer using Machine Learning Approaches

Rabiei

2022

J Biomed Phys Eng

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Background: Breast cancer is considered one of the most common cancers in women caused by various clinical, lifestyle, social, and economic factors. Machine learning has the potential to predict breast cancer based on features hidden in data. Objective: This study aimed to predict breast cancer using different machine-learning approaches applying demographic, laboratory, and mammographic data. Material and Methods: In this analytical study, the database, including 5,178 independent records, 25% of which belonged to breast cancer patients with 24 attributes in each record was obtained from Motamed cancer institute (ACECR), Tehran, Iran. The database contained 5,178 independent records, 25% of which belonged to breast cancer patients containing 24 attributes in each record. The random forest (RF), neural network (MLP), gradient boosting trees (GBT), and genetic algorithms (GA) were used in this study. Models were initially trained with demographic and laboratory features (20 features). The models were then trained with all demographic, laboratory, and mammographic features (24 features) to measure the effectiveness of mammography features in predicting breast cancer. Results: RF presented higher performance compared to other techniques (accuracy 80%, sensitivity 95%, specificity 80%, and the area under the curve (AUC) 0.56). Gradient boosting (AUC=0.59) showed a stronger performance compared to the neural network. Conclusion: Combining multiple risk factors in modeling for breast cancer prediction could help the early diagnosis of the disease with necessary care plans. Collection, storage, and management of different data and intelligent systems based on multiple factors for predicting breast cancer are effective in disease management.

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Section: Discussionmentioning

confidence: 99%

Prediction of Breast Cancer using Machine Learning Approaches

Rabiei

2022

J Biomed Phys Eng

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“…In the USA, an estimated 45% of women have a hysterectomy in their lifetime [1] . Of the 600,000 hysterectomies performed yearly, 90% are performed for benign indications including uterine fibroids, endometriosis, uterine polyp, abnormal uterine bleeding (AUB), pelvic infection, and/or adnexal pathology [2,3] . For women with elder ages, genital prolapse and leiomyoma were frequent indications and responsible for a big part of their benign hysterectomies [4,5] .Unlike malignant tumors, hysterectomy is not imperative for most patients with benign indications.…”

Section: Introductionmentioning

confidence: 99%

Association of age at benign hysterectomy with leukocyte telomere length in a nationally representative population

Wan¹,

Zhao²,

Pei³

et al. 2022

Maturitas

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…However, recent literature questions the acceptability of this approach among average-risk women such as those without a familial or genetic predisposition to ovarian cancer. This is particularly true when performed in premenopausal women 1,2,5,6 . Specifically, ovarian preservation has been shown to confer a benefit with respect to cardiovascular disease, non-gynecologic cancer, and all-cause mortality risk in certain populations such as premenopausal women 2,5 .…”

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confidence: 99%

“…This is particularly true when performed in premenopausal women. 1,2,5,6 Specifically, ovarian preservation has been shown to confer a benefit with respect to cardiovascular disease, non-gynecologic cancer, and all-cause mortality risk in certain populations such as premenopausal women. 2,5 Conversely, removal of the ovaries at the time of hysterectomy has been associated with lower risk of developing ovarian cancer 4 and breast cancer.…”

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confidence: 99%

“…For example, the average lifetime risk of developing ovariancancer is 1.4%, 4 whereas the average lifetime risk of developing breast cancer is 12%. 1 In a retrospective review of 2,656 hysterectomies at 6 Ontario, Canada hospitals, 4 Wong et al found BSOs were performed concomitantly in 28% of hysterectomies with 32% lacking a preoperative diagnosis indicating BSO. Overall, 8% were deemed unnecessary-in this group, patient age was less than 51 years and there was no pre-or intraoperative indication for BSO.…”

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confidence: 99%

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Avoidable bilateral salpingo-oophorectomy at hysterectomy: a large retrospective study

et al. 2022

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Objectives: Evaluate the proportion of justified bilateral salpingo-oophorectomy (BSO) at hysterectomy, based on pathologic diagnosis, and determine prevalence of avoidable BSO based on pre-and intraoperative considerations and pathologic diagnosis.Methods: Retrospective review of hysterectomies at seven Ontario, Canada hospitals from 2016 to 2019. Surgeries completed by oncologists or for invasive placentation were excluded. Patient, case, and surgeon characteristics were recorded along with pathologic diagnoses. Avoidable BSO criteria were: preoperative diagnosis of cervical dysplasia or benign diagnosis other than endometriosis, gender dysphoria, risk reduction or premenstrual dysphoric disorder; age < 51 years; absence of intraoperative endometriosis and adhesions; unjustified pathology (where ``justified'' pathology was endometriosis or (pre)malignant diagnosis except for cervical dysplasia). Patients with avoidable BSO were compared to those having at least one criterion for BSO. Binary logistic regression identified factors most strongly associated with avoidable BSO.Results: Four thousand one hundred ninety-one hysterectomies were completed with 1,422 (33.9%) patients having concomitant BSO. Pathologic diagnosis justified BSO in most patients (1,035/1,422, 72.8%) with endometrial cancer being most common (439/1,422, 30.9%). When preoperative characteristics, intraoperative findings, and pathologic diagnoses were considered, 79 of 1,422 (5.6%) BSOs were avoidable. Compared to cases with at least one criterion for BSO, avoidable BSOs were more frequently completed by generalists (OR 1.80, 95% CI 1.10-2.99, P ¼ 0.021), for preoperative diagnoses of abnormal uterine bleeding/menorrhagia (OR 3.82, 95% CI 2.35-6.30, P ¼ 0.001) and fibroids (OR 4.25, 95% CI 2.63-6.92, P < 0.001).Conclusion: Pathologic diagnosis justified most BSOs at hysterectomy. BSO was avoidable in 5.6% of patients, underscoring the need to standardize practice of BSO.

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Breast cancer risk after hysterectomy with and without salpingo-oophorectomy for benign indications

Cited by 12 publications

References 27 publications

Prediction of Breast Cancer using Machine Learning Approaches

Prediction of Breast Cancer using Machine Learning Approaches

Association of age at benign hysterectomy with leukocyte telomere length in a nationally representative population

Avoidable bilateral salpingo-oophorectomy at hysterectomy: a large retrospective study

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