Introduction/Background Determination of appropriate surgical approach for each cervical cancer (CC) patient between open radical hysterectomy (RH) and laparoscopic RH without compromising survival outcome is an important issue. Thus, we aimed to develop nomograms predicting disease recurrence according to the surgical approach in early-stage CC.

Methodology We retrospectively identified 724 patients with FIGO stage IB1-IB2 CC who received either open or laparoscopic Type C RH at two tertiary institutional hospitals between 2000 and 2017. Among them, those who underwent pre-operative MRI were included. Patients‘ clinicopathologic characteristics and survival outcomes were collected. Considering only the variables that could be obtained before surgery, we constructed predictive models for the 2-year progression-free survival (PFS) rate using logistic regression and a machine learning method called xgBoost.

Results In total, 572 patients were included; 343 and 229 received open RH and laparoscopic RH, respectively. The median length of observation was 54.7 months during which 79 patients (13.8%) experienced disease recurrence. Similar PFS was observed between the open and laparoscopic RH groups (2-year rate, 90.5% vs. 86.8%; P=0.068). The AUCs of the newly developed nomograms predicting 2-year PFS were up to 0.64 for open RH group and up to 0.65 for laparoscopic RH group.

Conclusion We preliminarily developed surgical approach-based two independent nomograms predicting disease recurrence in early-stage CC. These nomograms are expected to aid decision-making on the surgical approach of RH in individualized counselling practices. Further studies tailoring the nomograms with large cohorts are warranted.

Disclosure Nothing to disclose.