Logistic regression analysis of risk factors influencing postoperative keloid scar recurrence

OBJECTIVE: To identify risk factors of postoperative keloid scar recurrence in patients using logistic regression analysis. METHODS: A retrospective analysis was conducted with the use of clinical data collected from 132 keloid scars patients undergoing keloidectomy under local anaesthesia between January 2020 and June 2023 at The First Affiliated Hospital of the WANNAN Medical College. The recurrence of keloid scars in the included patients was analyzed, and their clinical data were subjected to univariate analysis. Factors showing significant differences were included in the multivariate logistic regression analysis. A receiver operating characteristics (ROC) curve was generated based on the independent risk factors to explore the predictive performance of joint-factor prediction for postoperative recurrence of keloid scars, and a corresponding Nomogram was generated. RESULTS: Out of the 132 patients, 38 experienced keloid scar recurrence, accounting for 28.79% of the total cases. Logistic regression analysis identified infection, family history of keloid scars, relatively large scar size and the absence of radiotherapy and local hormone therapy as independent risk factors influencing postoperative recurrence of keloid scars. The prediction for postoperative recurrence of keloid scars based on the joint independent risk factors yielded an area under the ROC curve of 0.889, with a sensitivity, a specificity, and an accuracy of 78.72%, 86.84%, and 81.06%, respectively. CONCLUSION: Infection, family history of keloid scars, relatively large scar size, and the absence of radiotherapy and local hormone treatment have been identified as independent risk factors for postoperative recurrence of keloid scars in patients.