Robotic hysterectomy versus expert 3D laparoscopy: A risk-adjusted learning curve analysis from a prospective single-surgeon study

Minimally invasive hysterectomy is preferred for benign gynaecologic conditions. Robotic-assisted hysterectomy (RAH) offers ergonomic and technical advantages over conventional laparoscopy, but whether it enhances performance beyond expert-level 3D laparoscopy remains uncertain. This prospective, single-surgeon study compared 50 RAH cases with 147 3D total laparoscopic hysterectomies (3D-TLH) by the high volume surgeon experienced in 3D laparoscopy and started robotic surgery soon after certification for DaVinci Xi robotic platform. A risk-adjusted cumulative sum (CUSUM) model, using operative time predicted from the surgeon's own 3D-TLH regression (Duration ∼ Uterine weight), was applied to assess proficiency. Outcomes were stratified by uterine weight (<250 g vs ≥ 250 g). Proficiency in RAH was achieved after 19 cases. The robotic cohort included more complex pathologies (adenomyosis, endometriosis) compared with the laparoscopic group (leiomyomas, polyps; p = 0.04). For uteri <250 g, outcomes were similar between approaches. For uteri ≥250 g, RAH offered reduced blood loss and shorter hospital stay while maintaining operative times. RAH demonstrates a shorter learning curve for experienced laparoscopists and offers distinct advantages in complex hysterectomies. Structured training and credentialing are essential for safe implementation in Malaysia. • Robotic-assisted hysterectomy achieved proficiency after only 19 cases. • Robotics maintained performance despite higher case complexity than 3D laparoscopy. • For uteri ≥250 g, robotics reduced blood loss and hospital stay. • Robotic platform delivered more consistent operative outcomes across all case types. • Benchmarking against the surgeon's own 3D TLH outcomes strengthened internal validity.