Algorithm of chest wall keloid treatment. Issue 35 (August 2016)

• Record Type: Journal Article
• Authors: Long, Xiao; Zhang, Mingzi; Wang, Yang; Zhao, Ru; Wang, Youbin; Wang, Xiaojun
• Other Names: Maatouk. Ismael section editor.
• Is Part Of: Medicine. Volume 95:Issue 35(2016)
• Publication Date: 2016-08
• Subjects: algorithm -- chest wall -- keloid -- surgery; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000004684
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: Keloids are common in the Asian population. Multiple or huge keloids can appear on the chest wall because of its tendency to develop acne, sebaceous cyst, etc. It is difficult to find an ideal treatment for keloids in this area due to the limit of local soft tissues and higher recurrence rate. This study aims at establishing an individualized protocol that could be easily applied according to the size and number of chest wall keloids. A total of 445 patients received various methods (4 protocols) of treatment in our department from September 2006 to September 2012 according to the size and number of their chest wall keloids. All of the patients received adjuvant radiotherapy in our hospital. Patient and Observer Scar Assessment Scale (POSAS) was used to assess the treatment effect by both doctors and patients. With mean follow-up time of 13 months (range: 6–18 months), 362 patients participated in the assessment of POSAS with doctors. Both the doctors and the patients themselves used POSAS to evaluate the treatment effect. The recurrence rate was 0.83%. There was an obvious significant difference ( P < 0.001) between the before-surgery score and the after-surgery score from both doctors and patients, indicating that both doctors and patients were satisfied with the treatment effect. Our preliminary clinical result indicates that good clinical results could be achieved by choosing the proper method in this algorithm for Chinese patients with chest wall keloids. This algorithm could play a guiding role for surgeons when dealing with chest wall keloid treatment.