| Literature DB >> 30982056 |
Pengfei Sun1, Yanjin Wang1, Minglei Bi1, Zhenyu Chen1.
Abstract
BACKGROUND Axillary osmidrosis (AO) is common in plastic surgery. But there is no perfect way to treat AO. We systematically compared the efficacy of 10 AO treatments with network meta-analysis in order to provide reference for the clinical treatment of axillary odor. MATERIAL AND METHODS Chinese and English databases were searched by computer. Some relevant studies were collected for network meta-analysis. RESULTS We identified 56 studies, including a total of 8618 patients for meta-analysis. The network meta-analysis showed that 21 out of 45 pairs of 10 AO treatments had no statistical significance. In statistical comparison, subcutaneous curettage and swelling suction subcutaneous pruning were better than a single treatment. In addition, the effects of both laser and electric ion therapy were inferior to those of other treatments. The order of therapeutic effects predicted by surface under the cumulative ranking (SUCRA), curve was swelling aspiration+subcutaneous pruning >subcutaneous pruning >subcutaneous curettage+subcutaneous pruning >spindle excision >botulinum toxin A injection >swelling aspiration >subcutaneous curettage >YAG laser therapy >CO2 laser therapy >electric ion therapy. CONCLUSIONS In operative treatment of AO, swelling aspiration+subcutaneous pruning is the best operative treatment, and botulinum toxin A injection is the best in non-operative treatment. Overall, the effect of surgical treatment was more significant than that of non-surgical treatment.Entities:
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Year: 2019 PMID: 30982056 PMCID: PMC6478402 DOI: 10.12659/MSM.913932
Source DB: PubMed Journal: Med Sci Monit ISSN: 1234-1010
Figure 1PRISMA flow diagram.
Characteristics of the 56 included studies.
| First author | Year | Country | Surgery type | No. patients | Age | Follow-up (months) | Research type | Literature quality (star) |
|---|---|---|---|---|---|---|---|---|
| Zong Yanxia | 2005 | China | a | 88 | 25 | 6 | Non-RCT | 6 |
| b | 9 | |||||||
| Wang Jin | 2014 | China | c | 52 | 27.2 | 3 | Non-RCT | 6 |
| d | 68 | |||||||
| Cai Tiequan | 1994 | China | c | 48 | 23.2 | 8.2 | Non-RCT | 6 |
| e | 56 | 24.5 | ||||||
| Chen Mingxing | 2002 | China | c | 58 | 18–35 | 1 | RCT | 7 |
| d | 58 | |||||||
| Wang Shuhua | 2003 | China | c | 140 | 25 | 12 | RCT | 6 |
| b | 140 | |||||||
| Yang Shulan | 2008 | China | c | 50 | 13–60 | 3–8 | RCT | 8 |
| e | 50 | |||||||
| Li Chaohui | 2005 | China | e | 90 | 18–30 | 3–12 | RCT | 6 |
| f | 90 | |||||||
| Wang Weiping | 2007 | China | f | 165 | 27 | 3 | Non-RCT | 5 |
| a+d | 145 | |||||||
| b | 115 | |||||||
| Gu Shuguang | 2010 | China | b | 47 | 18–40 | 4–60 | Non-RCT | 6 |
| c | 40 | |||||||
| d | 52 | |||||||
| Jiang Wei | 2010 | China | f | 26 | 28.6 | 6–18 | Non-RCT | 6 |
| g | 30 | |||||||
| d | 50 | |||||||
| a+d | 50 | |||||||
| Zhang Likang | 2014 | China | a | 60 | 23.4 | 2–6 | Non-RCT | 7 |
| b | 80 | |||||||
| Guo Xiaochuan | 2008 | China | a | 114 | 15–47 | 6–18 | Non-RCT | 6 |
| b | 42 | |||||||
| g | 30 | |||||||
| Zhang Xiaotao | 2013 | China | b | 45 | 23.98 | 6–12 | Non-RCT | 7 |
| d | 45 | 23.26 | ||||||
| Zhang Hui | 2010 | China | b | 65 | 29.6 | 3 | Non-RCT | 6 |
| d | 65 | |||||||
| Xie Qixuan | 2004 | China | a+d | 85 | 25.7 | 3 | RCT | 5 |
| f | 70 | |||||||
| Zhang Zhanzhao | 2012 | China | d | 47 | 25.4 | 3 | Non-RCT | 6 |
| h | 39 | 21.1 | ||||||
| Gu Tingmin | 2012 | China | b | 113 | 24.5 | 6–12 | Non-RCT | 7 |
| d | 205 | |||||||
| Qian Jiang | 2003 | China | a | 31 | 25 | 6 | Non-RCT | 6 |
| b | 18 | 23.8 | ||||||
| Wang Wanzhi | 2006 | China | b | 23 | 28.6 | 3 | Non-RCT | 5 |
| d | 19 | 27.4 | ||||||
| Jing Liangyu | 2010 | China | a | 46 | 27 | 6–60 | RCT | 7 |
| b | 54 | 25 | ||||||
| Lei Tianbing | 2014 | China | a | 60 | 16–40 | 6 | RCT | 6 |
| d | 50 | |||||||
| Li Li | 2015 | China | d | 45 | ––– | 6 | Non-RCT | 5 |
| g | 45 | |||||||
| Zhang Jianzhuo | 2014 | China | d | 40 | 22.51 | 6 | RCT | 6 |
| g | 40 | 22.7 | ||||||
| Wang Qian | 2011 | China | d | 90 | 23.53 | 6–12 | RCT | 6 |
| h | 100 | 20.65 | ||||||
| Zheng Ruo | 2013 | China | a | 64 | 27.6 | 3 | RCT | 6 |
| d | 64 | 27.2 | ||||||
| Jiang Bin | 2012 | China | a | 136 | 28.7 | 3 | RCT | 7 |
| b | 97 | |||||||
| c | 101 | |||||||
| Zhang Kaiheng | 2012 | China | b | 33 | 24 | 5–72 | Non-RCT | 6 |
| d | 115 | |||||||
| g | 21 | |||||||
| Liu Cheng | 2017 | China | d | 38 | 23.3 | 6–9 | Non-RCT | 6 |
| h | 23 | |||||||
| g | 23 | |||||||
| Guo Qun | 2007 | China | b | 67 | 28 | 6–72 | RCT | 7 |
| d | 112 | |||||||
| a+d | 177 | |||||||
| Mo Lue | 2007 | China | a | 42 | 19–27 | 6 | RCT | 5 |
| b | 47 | |||||||
| d | 61 | |||||||
| Chen Jie | 2011 | China | a+d | 82 | 15–40 | 6–12 | Non-RCT | 5 |
| b | 58 | |||||||
| c | 40 | |||||||
| Chen Hui | 2011 | China | b | 23 | 25 | 6 | Non-RCT | 6 |
| g | 30 | |||||||
| Jing Liangyu | 2010 | China | b | 54 | 27 | 6–60 | RCT | 6 |
| c | 51 | 28 | ||||||
| Liu Jianyi | 2004 | China | b | 40 | 29.6 | 6 | RCT | 7 |
| d | 102 | |||||||
| Wu Weiping | 2016 | China | d | 50 | 27.61 | 3 | RCT | 7 |
| g | 50 | 27.56 | ||||||
| Lin Xia | 2012 | China | d | 45 | 26 | 6 | RCT | 5 |
| g | 33 | 28 | ||||||
| Huang Haiyan | 2011 | China | a | 105 | 24.6 | 6–12 | Non-RCT | 6 |
| g | 51 | |||||||
| Liang Haisheng | 2014 | China | a+d | 75 | 25.5 | 12 | RCT | 6 |
| b | 75 | |||||||
| Luo Wenyue | 2010 | China | c | 69 | ––– | 6–24 | Non-RCT | 5 |
| d | 54 | |||||||
| Wu Shuang | 2014 | China | d | 50 | 37.2 | 12 | Non-RCT | 6 |
| f | 50 | 43.6 | ||||||
| Zhou Jinghe | 2015 | China | d | 108 | 17–39 | 3–12 | RCT | 5 |
| g | 108 | 18–36 | ||||||
| Yang Xingang | 2013 | China | b | 120 | 23.5 | 6–12 | Non-RCT | 6 |
| d | 120 | 25 | ||||||
| Zhang Binyu | 2012 | China | c | 32 | 29 | 3 | Non-RCT | 6 |
| d | 58 | |||||||
| g | 48 | |||||||
| Zhao Guilan | 2010 | China | a | 90 | 18–40 | 6 | Non-RCT | 5 |
| f | 85 | |||||||
| Shen Bin | 2012 | China | a | 140 | 24 | 6 | Non-RCT | 6 |
| d | 140 | |||||||
| Tan Jianping | 2003 | China | a | 62 | 16–49 | 3–60 | Non-RCT | 5 |
| b | 76 | |||||||
| f | 48 | |||||||
| Cai Mei | 2008 | China | b | 79 | 24.3 | 6 | Non-RCT | 5 |
| d | 82 | |||||||
| Huang Xiaodong | 2012 | China | b | 68 | 28.5 | 6 | RCT | 6 |
| d | 68 | |||||||
| Wu Hailong | 2005 | China | b | 70 | 26 | 6 | Non-RCT | 5 |
| c | 30 | 29 | ||||||
| Liu Xiaofeng | 2014 | China | d | 58 | 18–45 | 3–6 | Non-RCT | 5 |
| g | 36 | 18–43 | ||||||
| Liu Jianzhong | 2008 | China | d | 138 | 28 | 3–6 | Non-RCT | 5 |
| g | 55 | 26 | ||||||
| He J | 2018 | China | g | 91 | 20 | 6–36 | Non-RCT | 6 |
| d+g | 80 | 21 | ||||||
| Chen YT | 2015 | China | e | 66 | 29.8 | 56.8 | Non-RCT | 6 |
| g | 19 | 37.5 | ||||||
| Cao Han | 2016 | China | a | 71 | 26.8 | 6–24 | Non-RCT | 6 |
| d | 73 | |||||||
| Li Weiwei | 2010 | China | d | 180 | ––– | 3–24 | Non-RCT | 5 |
| g | 120 | |||||||
| h | 50 | |||||||
| Yu Kefeng | 2015 | China | a+d | 29 | 26.4 | ––– | RCT | 7 |
| g | 29 | 25.3 |
a – subcutaneous curettage; b – fusiform skin excision; c – CO2 laser treatment; d – subcutaneous pruning; e – YAG laser treatment; f – electric ion therapy; g – Swelling aspiration; h – botulinum toxin A injection; RCT – randomized controlled trial; non-RCT – non-randomized controlled trial.
Figure 2Network graph: a) subcutaneous curettage; b) fusiform skin excision; c) CO2 laser treatment; d) subcutaneous pruning; e) YAG laser treatment; f) electric ion therapy; g) swelling aspiration; h) botulinum toxin A injection.
Figure 3Inconsistency test results.
Figure 4Funnel plot.
The network meta-analysis results.
| a | 1.29 (0.92,1.80) | 1.21 (0.97,1.51) | 0.68 (0.50,0.92) | 1.34 (1.07,1.69) | 2.78 (1.21,6.37) | 0.76 (0.48,1.21) | 0.61 (0.44,0.87) | 1.05 (0.80,1.36) | 1.10 (0.72,1.67) |
| 0.78 (0.56,1.08) | a+d | 0.94 (0.71,1.24) | 0.53 (0.37,0.75) | 1.04 (0.78,1.39) | 2.16 (0.92,5.04) | 0.59 (0.36,0.96) | 0.48 (0.33,0.68) | 0.81 (0.59,1.11) | 0.85 (0.54,1.35) |
| 0.83 (0.66,1.03) | 1.07 (0.81,1.41) | b | 0.56 (0.43,0.73) | 1.11 (0.94,1.32) | 2.30 (1.01,5.22) | 0.63 (0.41,0.98) | 0.51 (0.37,0.70) | 0.87 (0.69,1.09) | 0.91 (0.61,1.35) |
| 1.48 (1.08,2.01) | 1.90 (1.33,2.71) | 1.78 (1.38,2.31) | c | 1.98 (1.52,2.59) | 4.10 (1.76,9.56) | 1.12 (0.71,1.77) | 0.91 (0.62,1.33) | 1.55 (1.14,2.10) | 1.62 (1.04,2.53) |
| 0.74 (0.59,0.93) | 0.96 (0.72,1.28) | 0.90 (0.76,1.07) | 0.50 (0.39,0.66) | d | 2.07 (0.92,4.65) | 0.57 (0.37,0.87) | 0.46 (0.33,0.63) | 0.78 (0.64,0.95) | 0.82 (0.57,1.17) |
| 0.36 (0.16,0.83) | 0.46 (0.20,1.08) | 0.43 (0.19,0.99) | 0.24 (0.10,0.57) | 0.48 (0.21,1.09) | d+g | 0.27 (0.11,0.68) | 0.22 (0.09,0.52) | 0.38 (0.17,0.83) | 0.40 (0.16,0.95) |
| 1.32 (0.83,2.09) | 1.69 (1.04,2.76) | 1.59 (1.02,2.46) | 0.89 (0.57,1.40) | 1.77 (1.15,2.72) | 3.65 (1.48,9.01) | e | 0.81 (0.51,1.29) | 1.38 (0.89,2.14) | 1.45 (0.83,2.52) |
| 1.63 (1.15,2.30) | 2.10 (1.47,2.99) | 1.96 (1.43,2.70) | 1.10 (0.75,1.61) | 2.19 (1.59,3.02) | 4.52 (1.91,10.69) | 1.24 (0.78,1.97) | f | 1.70 (1.21,2.41) | 1.79 (1.11,2.88) |
| 0.96 (0.73,1.24) | 1.23 (0.90,1.68) | 1.15 (0.92,1.45) | 0.65 (0.48,0.88) | 1.28 (1.06,1.56) | 2.65 (1.21,5.84) | 0.73 (0.47,1.13) | 0.59 (0.42,0.83) | g | 1.05 (0.71,1.54) |
| 0.91 (0.60,1.38) | 1.17 (0.74,1.85) | 1.10 (0.74,1.63) | 0.62 (0.40,0.96) | 1.22 (0.85,1.75) | 2.53 (1.05,6.07) | 0.69 (0.40,1.20) | 0.56 (0.35,0.90) | 0.95 (0.65,1.40) | h |
Figure 5Ranking of therapeutic effects of axillary osmidrosis.