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<p>The adoption of robotic-assisted surgery (RAS) for rectal cancer is governed by a steep learning curve (LC). This systematic review evaluates the "Price of Proficiency" by comparing RAS to conventional laparoscopic surgery (CLS) across temporal, oncological, and ergonomic dimensions. A systematic search of PubMed, Embase, and Scopus (2014–2026) identified 24 studies utilizing Cumulative Sum (CUSUM) or Risk-Adjusted CUSUM (RA-CUSUM) modeling. Methodological quality was appraised using MINORS and Cochrane RoB 2.0 tools. Synthesis of &gt;3,500 procedures revealed a triphasic LC. Phase I (Learning: cases 1–25) demonstrated high operative times but remarkably low conversion rates (1.0%–3.2%) compared to historical CLS averages (12.2%– 15.0%). Technical proficiency (Phase II) stabilized by case 35, while Phase III (Mastery: &gt;50 cases) was characterized by "Complexity Drift," where surgeons tackled high-BMI and post-radiation cases without compromising outcomes. Oncological quality, including TME completeness (91.9%–97.0%) and CRM negativity, remained stable throughout all LC phases. Mastery was associated with higher nodal yield and an increased likelihood of achieving a “Textbook Outcome”. The robotic platform decouples procedural speed from surgical safety, providing an immediate “safety net” that protects oncological integrity during the initial learning phase. While RAS requires a significant temporal investment, its superior ergonomics and lower conversion rates support its transition as the standard for minimally invasive rectal cancer resection.</p>

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The Multi-Dimensional Learning Curve in Robotic-Assisted vs. Laparoscopic Rectal Cancer Resection: A Systematic Review of Procedural Efficiency, Pathological Integrity, and Ergonomic Impact

  • 期刊论文

  • 发表日期：

    2026年7月20日

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  • Greeshma Arun Kumar,
  • Gargi Sharma,
  • Brahmini Arun Kumar

摘要

The adoption of robotic-assisted surgery (RAS) for rectal cancer is governed by a steep learning curve (LC). This systematic review evaluates the "Price of Proficiency" by comparing RAS to conventional laparoscopic surgery (CLS) across temporal, oncological, and ergonomic dimensions. A systematic search of PubMed, Embase, and Scopus (2014–2026) identified 24 studies utilizing Cumulative Sum (CUSUM) or Risk-Adjusted CUSUM (RA-CUSUM) modeling. Methodological quality was appraised using MINORS and Cochrane RoB 2.0 tools. Synthesis of >3,500 procedures revealed a triphasic LC. Phase I (Learning: cases 1–25) demonstrated high operative times but remarkably low conversion rates (1.0%–3.2%) compared to historical CLS averages (12.2%– 15.0%). Technical proficiency (Phase II) stabilized by case 35, while Phase III (Mastery: >50 cases) was characterized by "Complexity Drift," where surgeons tackled high-BMI and post-radiation cases without compromising outcomes. Oncological quality, including TME completeness (91.9%–97.0%) and CRM negativity, remained stable throughout all LC phases. Mastery was associated with higher nodal yield and an increased likelihood of achieving a “Textbook Outcome”. The robotic platform decouples procedural speed from surgical safety, providing an immediate “safety net” that protects oncological integrity during the initial learning phase. While RAS requires a significant temporal investment, its superior ergonomics and lower conversion rates support its transition as the standard for minimally invasive rectal cancer resection.