The incidence of unexpected gynaecological malignancies in hysterectomies carried out for benign indications

Abstract

The aim of the present study was to determine the incidence of unexpected gynaecological malignancies in patients undergoing hysterectomy for benign indications and to evaluate their clinical characteristics. Data from 6448 cases who had undergone hysterectomy for benign indications between the dates of 01.01.2008–01.01.2018 were recorded retrospectively from the database of the institution. The mean age of the cases with malignancy was 59.2 ± 9.66 (45–80) and 76,31% were (29/38) postmenopausal. The mean gravidity was 3.94 ± 1.73 and parity was 3.31 ± 1.45. Their mean BMI was 29.6 ± 4.26 kg/m² (22.4–41.9 kg/m² range). These patients were followed for a mean duration of 60.68 ± 37.66 months and during this period death associated with malignancy occurred in 4/38 (%10.52) cases, all of whom had leiomyosarcoma. The benign indications of procedure were as follows: myoma uteri (2675, 41.48%), abnormal uterine bleeding (1508, 23.38%), uterine prolapsus (793, 12.29%), ovarian cyst (619, 9.59%), endometriosis (303, 4.69%), endometrial polyp (264, 4.09%), pelvic pain (238, 3.69%) and other benign causes (48, 0.74%). Unexpected gynaecological malignancy was found in 20 cases (0.31%) with endometrial cancer, in eight cases (0.12%) with uterine sarcoma, in seven cases (0.10%) with ovarian cancer, in one case (0.01%) with tubal cancer and in two (0.03%) with cervical cancer. Gynaecological malignancy was found in 38 of 6648 cases who underwent hysterectomy for benign indications, yielding an incidence rate of 0.58%.

IMPACT STATEMENT

• What is already known on this subject? Hysterectomy is the most common gynaecological surgery in the world and although most are performed for benign indications, unexpected gynaecological malignancy is possible in the final pathology results.

• Although there are available publications investigating unexpected gynaecological malignancy incidences after hysterectomies for benign reasons, the incidence is still not clear. We aimed to contribute to the existing literature with this study, which includes a large number of cases.

• What do the results of this study add? Our study adds new findings to the body of the knowledge on the incidence of unexpected gynaecological malignancies in hysterectomies for benign indications. Gynaecological malignancy was found in 38 of 6648 cases who underwent hysterectomy for benign indications, yielding an incidence rate of 0.58%.

• What are the implications of these findings for clinical practice and/or further research? There is an unexpected possibility of gynaecological malignancy even in cases where it is expected to be benign with current diagnostic methods. In cases that are expected to be benign, detailed preoperative evaluation should be performed in all patients to prevent unexpected gynaecological malignancies. More sensitive screening methods should be developed especially in the preoperative differential diagnosis of leiomyoma and leiomyosarcoma.

Keywords:

• Benign indication
• hysterectomy
• unexpected gynaecological malignancy

Acknowledgement

We want to say special thanks to the nurses of operation room, anaesthesia technicians, anaesthesiologists and worker of Istanbul Kartal Dr. Lütfi Kırdar Training and Research Hospital.

Ethics approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee (Istanbul Kartal Dr. Lütfi Kırdar Training and Research Hospital, date of approval: 06.12.2019, reference number: 2019/514/167/25) and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Disclosure statement

We declare that we have no conflict of interest.

Author contributions

Gazi Yildiz, MD: Corresponding author, study design, writing, statistical analysis. Emre Mat, MD: Data collection, interpretation of data. Pinar Yildiz, MD: Analysis and interpretation of data, writing. Elif Cansu Gundogdu, MD: Data collection, revising article critically. Gulfem Basol, MD: Analysis and interpretation of data, data collection, statistical analysis. Didar Kurt, MD: Statistical analysis, revising article critically. Ahmet Kale, Prof. Dr: Study design, concept, revising article critically.