Development and Validation of a Nomogram for Prediction of Risks of Hypertrophic Scar Outcomes According to Burn Location

Abstract

Purpose: To develop and validate a nomogram for prediction of postburn hypertrophic scar according to burn location. Method: The prediction model was developed in a primary cohort that consisted of 125patients with 309 burn sites. and data were collected from June 2017 to December 2019. Lasso regression model was used for data feature selection and prediction model building. Signature risk factors were used to develop a nomogram to assess the individualized risk of postburn hypertrophic scar. The performance of the nomogram was assessed with respect to its calibration, discrimination and clinical usefulness and was developed decision curve analysis. Result: Predictors contained in the prediction nomogram included use of sex, age, burn causes, burn sites, burn depth, total body sur-face area, surgical treatment, and healing time. The model displayed good discrimination with a C-index of 0.852 (95% CI: 0.811-0.893) and good calibration. High C-index value of 0.814 could still be reached in the interval validation. Decision curve analysis showed that the nomogram was clinically useful when intervention was decided at the postburn hypertrophic scar possibility threshold between 0.3% and 87%. Conclusion: A simple-to-use nomogram could be conveniently used to facilitate individual hypertrophic scar risk prediction in postburn patients. Funding: This work was funded by the Guangxi medical High-level Leading Talents Training “139” Project (No: GWKJ [2018]22#) Declaration of Interest: None to declare. Ethical Approval: Research approval was obtained from the Youjiang Medical University for Nationalities’ Ethics Committee.