Use risk-adjusted cumulative sum (RA-CUSUM) analysis to account for case-mix heterogeneity in learning curve assessment¶

Strategy · All strategies
Evidence · 4 claims (4 for) · 1 study (1 review), q2 · 0 of 1 report an effect size · 4 claims rest on one study

Description¶

The review recommends using risk-adjusted cumulative sum (RA-CUSUM) analysis to adjust for confounding variables that may influence operative performance, providing a more accurate representation of a surgeon's progression over time. This addresses the tendency to perform fewer complex cases early in learning followed by more challenging cases later, which distorts standard learning curve assessments. The authors note that effective application requires large datasets, which remains challenging given that LLND is not yet widely adopted globally.

Design Implications¶

Context¶

Requirements¶

• Large datasets to support the risk-adjustment model

Constraints¶

• LLND is not yet widely adopted globally, limiting dataset availability

Target Learners¶

• Surgical trainees learning LLND

Target Learning Goals¶

• Acquiring surgical competence in lateral lymph node dissection

Claims¶

• Laparoscopic LLND competence is achieved after 19 cases [+W]
• No learning curve inflection point was identified for open LLND [+W]
• Surgical competence in robotic LLND is achieved after 12–53 cases regardless of learning outcome [+W]
• Blood loss, urinary complications, and morbidity decreased during the proficiency phase of robotic LLND [+W]

Related Strategies¶

• Incorporate quality control measures with standardized photographic or video-based assessments using predefined anatomic landmarks
• Use performance thresholds that meaningfully measure surgeon performance alongside standardized terminology when assessing surgical learning curves

Examples¶

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Key Sources¶

• Kehagias D., Baldari L., Cassinotti E., Boni L., Lampropoulos C., Kehagias I. (2025). Learning curve for lateral lymph node dissection in rectal cancer – a systematic review of literature. Techniques in Coloproctology. https://doi.org/10.1007/s10151-025-03214-3