Development and validation of a risk assessment model for post-surgical scar formation in pediatric melanocytic nevus excision: a retrospective cohort study

Scar-related complications remain a significant concern following melanocytic nevus excision in children. However, validated risk prediction tools for this specific population are lacking. This study aimed to develop and validate a prediction model for unfavorable scar formation after pediatric melanocytic nevus excision. A retrospective cohort study was conducted at Plastic Surgery Hospital, Chinese Academy of Medical Sciences from March 2024 to August 2024. Pediatric patients who underwent melanocytic nevus excision were included. Patients were classified into favorable and unfavorable scar groups based on morphological characteristics, POSAS scores, and persistent symptoms. Multivariable logistic regression identified independent risk factors, and a nomogram was constructed. Model performance was evaluated using discrimination, calibration, and decision curve analysis, with internal validation via bootstrap resampling. Among 300 patients, 73 (24.3%) developed unfavorable scars. Six independent predictors were identified: older age was protective (OR = 0.871), while congenital nevus type (OR = 2.280), larger diameter (OR = 1.818), trunk location (OR = 4.536), extremity location (OR = 3.314), high wound tension (OR = 8.365), moderate wound tension (OR = 2.971), and junctional depth (OR = 2.050) increased the risk. The model demonstrated good discrimination (AUC = 0.839; bootstrap-corrected AUC = 0.821) and calibration (Brier score = 0.132, calibration slope = 0.968). At the optimal threshold, sensitivity was 0.753 and specificity was 0.834. Decision curve analysis confirmed clinical utility across threshold probabilities of 0.10–0.80. This prediction model incorporating six clinical factors may facilitate perioperative risk stratification and informed consent discussions for pediatric patients undergoing melanocytic nevus excision. External validation is warranted before clinical implementation.