Background: Patients with chest keloids undergoing surgery and adjuvant radiotherapy still have a high recurrence rate, which is a critical problem. The level of keloid activity has not been studied, and a nomogram model for predicting keloid recurrence has not been established in previous studies.
Methods: A total of 145 patients with chest keloids who underwent surgery and radiotherapy between January 2015 and January 2019 at Peking Union Medical College Hospital were included in our study. Demographic and clinical features and the score of KAAS were analyzed. We compared the area under the curve (AUC) and decision curve analysis (DCA) between KAAS and the Vancouver scar scale (VSS) and established a nomogram model for predicting the risk of recurrence. We used bootstrap and calibration plots to evaluate the performance of the nomogram.
Results: The KAAS can predict recurrence in patients with chest keloids after surgery and radiotherapy. Areas under the curve (AUCs) of KAAS and VSS were 0.858 and 0.711, respectively (p < 0.001). Decision curve analysis (DCA) demonstrated that the KAAS was better than the VSS. Complications after treatment may be risk factors for keloid recurrence. We created a nomogram by using complications and KAAS. The AUC was 0.871 (95% CI 0.812-0.930). The ROC of the model's bootstrap was 0.865 and was well calibrated.
Conclusions: The KAAS can be used to predict the recurrence and we developed a nomogram for predicting the recurrence of chest keloids after surgery and adjuvant radiotherapy.
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Keywords: Chest keloids; Nomogram; Prognostic factors; Recurrence; Risk factors.
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