A team consisting of researchers from Seoul National University Bundang Hospital (SNUBH) and Kyung Hee University Medical Center (KHUMC) have developed a predictive model to evaluate the necessity of radiotherapy in early-stage cervical cancer patients.

Cervical cancer is the fourth most common malignant tumor-related disease affecting women globally. While overall incidence has decreased due to early detection screenings, there is a rising trend among young women who need to preserve their reproductive functions.

Postoperative tissue examination determines whether cervical cancer patients require radiotherapy, with patients with cancer cells invading surrounding uterine tissue or lymph nodes are indicated for radiotherapy, while others may not need it.

As radiotherapy can lead to loss or impairment of ovarian function, ovarian transposition surgery, which relocates the ovaries outside the radiation field, is recommended during surgery.

However, this procedure itself can diminish ovarian function and cause complications such as abdominal pain, cyst formation, and vascular damage. Consequently, it is advisable to perform ovarian transposition surgery only on patients anticipated to undergo radiotherapy.

Currently, there are no standardized guidelines for deciding whether to perform ovarian transposition surgery preoperatively, and decisions are primarily based on the attending physician’s experience, sometimes resulting in unnecessary ovarian transposition surgeries when tissue examination later reveals no need for radiotherapy.

To address this issue, the team, led by Professors Kim Ki-dong of the Department of Obstetrics and Gynecology at SNUBH and Hwang Woo-yeon of the Department of Obstetrics and Gynecology at KHUMC, conducted a retrospective study to derive a model that predicts the necessity of radiotherapy before surgery.

The study analyzed data from 886 cervical cancer patients, aged 20-45, who underwent either modified radical hysterectomy or radical hysterectomy between 2000 and 2008, collected by the Korean Gynecologic Oncology Group.

The dataset included various preoperative variables such as age, medical history, tumor size, and tumor type.

Patients with larger tumors or those invading surrounding tissues were defined as having a positive risk for radiotherapy, while those without these characteristics were defined as negative.

Using machine learning analysis, the researchers stratified the patients into four subgroups based on tumor size and age for comparative analysis.

The analysis revealed that patients with tumors 2.45 cm or smaller had a 13.4 percent risk of needing radiotherapy, and tumors between 2.45 cm and 3.85 cm had a 43.3 percent risk.

The team also found that tumors larger than 3.85 cm in patients aged 39.5 years or younger had an 84.4 percent risk, while patients with tumors larger than 3.85 cm and older than 39.5 years had an 88.5 percent risk.

"Based on the results of this study, we can now determine the necessity of ovarian transposition surgery in premenopausal cervical cancer patients according to the preoperative predicted risk,” Professor Kim said. “We hope that by applying this model in clinical practice, we can implement patient-centered treatment and enhance the standard of care in gynecologic oncology.”

The results of the research were published in Obstetrics & Gynecology Science.