Does severe obesity define a threshold over which robotic sentinel lymph node mapping outperforms laparoscopic mapping in endometrial cancer?

BACKGROUND: Obesity is a major determinant of technical difficulty in sentinel lymph node (SLN) mapping for endometrial cancer and has been associated with reduced bilateral detection and increased risk of empty nodal dissections. Whether a clinically relevant body mass index (BMI) threshold exists beyond which robotic assistance may preserve SLN mapping reliability remains unclear. METHODS: We conducted a retrospective cohort study including consecutive women with apparent early-stage endometrial cancer (FIGO 2009 I-II) and BMI ≥30 kg/m2 undergoing minimally invasive hysterectomy with bilateral salpingo-oophorectomy and indocyanine green-guided SLN mapping. Patients were stratified into class I obesity (BMI 30-34.9 kg/m2) and class II-III obesity (BMI ≥35 kg/m2). The primary endpoint was bilateral SLN detection at final pathology. Secondary endpoints included empty package dissection. Logistic regression models were fitted within the BMI ≥35 subgroup to explore independent predictors of bilateral detection and empty package dissection. RESULTS: A total of 109 patients were included (70 laparoscopic, 39 robotic). In class I obesity, bilateral SLN detection rates were comparable between approaches (70.0% vs 78.6%). In patients with BMI ≥35 kg/m2, robotic surgery showed higher bilateral detection compared with laparoscopy (88% vs 53.3%, p = 0.008). Empty package dissection occurred less frequently with robotics in this subgroup (8% vs 33.3%, p = 0.046). In multivariable analysis restricted to BMI ≥35 kg/m2, robotic approach was associated with increased odds of bilateral detection (OR 9.24, 95% CI 1.64-52.19, p = 0.012). CONCLUSIONS: In women with severe obesity, robotic surgery was associated with meaningful improvements in SLN mapping completeness compared with laparoscopy. These findings support the hypothesis that a BMI threshold may exist beyond which robotic assistance helps preserve nodal staging reliability, warranting validation in larger prospective studies.