| Literature DB >> 35935572 |
Daixiong Tian1, Ying Chu1, Ge Zhang2, Dan Huang1, Jialin Huang1, Jin Zeng1.
Abstract
Background: Autologous fat transfer (AFT) is a minimally invasive technique that employs a patient's own fat to correct disfiguring sequelae for breast reconstruction in postoperative breast cancer patients. However, the results of studies on this topic were controversial. In order to explore the effect of AFT on breast reconstruction after breast cancer surgery, we included cohort studies and conducted a meta-analysis.Entities:
Keywords: Autologous fat transfer (AFT); after breast cancer operation; breast reconstruction; meta-analysis
Year: 2022 PMID: 35935572 PMCID: PMC9346223 DOI: 10.21037/gs-22-297
Source DB: PubMed Journal: Gland Surg ISSN: 2227-684X
Figure 1Flow diagram of literature search.
Details of included studies
| Author | Year | Country | Group | Total patients | Age [range or ± SD] | Type of surgery | Histology | Outcomes | NOS scores | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mastectomy | BCS | Quadrantectomy | Invasive |
| |||||||||
| Petit | 2012 | Italy | AFT | 321 | 45 [22–71] | 196 | 125 | 284 | 37 | ABCDF | 6 | ||
| NFT | 642 | 46 [26–69] | 392 | 250 | 568 | 74 | |||||||
| Seth | 2012 | USA | AFT | 90 | 49.4±8.8 | 90 | 50 | B | 6 | ||||
| NFT | 1,112 | 48.0±10.6 | 1,112 | 587 | |||||||||
| Petit | 2013 | Italy | AFT | 59 | 49 [33–65] | 47 | 12 | B | 7 | ||||
| NFT | 118 | 50 [29–72] | 94 | 24 | |||||||||
| Kim | 2014 | Korea | AFT | 102 | 46.3 [22–63] | 102 | 42 | A | 5 | ||||
| NFT | 449 | 449 | |||||||||||
| Gale | 2015 | USA | AFT | 211 | 52.2 [30–76] | 176 | 35 | 184 | 27 | ABCDF | 7 | ||
| NFT | 422 | 52.7 [30–72] | 358 | 64 | 368 | 54 | |||||||
| Laporta | 2015 | Italy | AFT | 20 | 44.8 [35–57] | 20 | B | 6 | |||||
| NFT | 20 | 44.95 [35–59] | 20 | ||||||||||
| Masia | 2015 | Italy | AFT | 107 | 49.19 [31–65] | 107 | 0 | 75 | 16 | B | 6 | ||
| NFT | 107 | 48.98 [31–71] | 107 | 0 | 72 | 14 | |||||||
| Pinell-White | 2015 | USA | AFT | 51 | 49.6 [32–68] | 51 | 0 | A | 5 | ||||
| NFT | 51 | 48.9 [32–66] | 51 | 0 | |||||||||
| Mestak | 2016 | Czech | AFT | 32 | 53 [39–67] | 0 | 32 | 24 | 4 | AD | 6 | ||
| NFT | 45 | 64 [37–84] | 0 | 45 | 41 | 3 | |||||||
| Kronowitz | 2016 | USA | AFT | 719 | 47.7±9.6 | 639 | 79 | 552 | 108 | AE | 7 | ||
| NFT | 670 | 46.5±10.5 | 591 | 73 | 548 | 61 | |||||||
| Cohen | 2017 | USA | AFT | 414 | 52.6±11.1 | 414 | 319 | 83 | BD | 7 | |||
| NFT | 162 | 47.8±8.7 | 162 | 111 | 51 | ||||||||
| Fertsch | 2017 | Germany | AFT | 100 | 49.6 | 100 | 0 | 73 | 9 | A | 7 | ||
| NFT | 100 | 50.7 | 100 | 0 | 73 | 9 | |||||||
| Khan | 2017 | UK | AFT | 35 | 49 [35–70] | 0 | 35 | B | 5 | ||||
| NFT | 64 | 54 [36–73] | 0 | 64 | |||||||||
| Petit | 2017 | Italy | AFT | 322 | 0 | 322 | 322 | BCDF | 6 | ||||
| NFT | 322 | 0 | 322 | 322 | |||||||||
| Silva-Vergara | 2017 | Spain | AFT | 205 | 49.1 [23–72] | 147 | 58 | 161 | 44 | BCDF | 7 | ||
| NFT | 410 | 49.7 [24–72] | 286 | 124 | 335 | 75 | |||||||
| Stumpf | 2017 | Brazil | AFT | 27 | 53.6±10.9 | 0 | 27 | 27 | 0 | BE | 6 | ||
| NFT | 167 | 56.4±12.0 | 0 | 167 | 167 | 0 | |||||||
| Calabrese | 2018 | Italy | AFT | 64 | 50.3 [33–69] | 64 | 0 | 23 | AE | 7 | |||
| NFT | 64 | 47.7 [33–60] | 64 | 0 | 25 | ||||||||
| Krastev | 2019 | Netherlands | AFT | 300 | 48.1 [9.0] | 161 | 139 | 261 | 39 | ADF | 6 | ||
| NFG | 300 | 49.4 [8.4] | 150 | 150 | 260 | 40 | |||||||
| Sorrentino | 2019 | Italy | AFT | 233 | 49.4 [±9.0] | 179 | 54 | 207 | 26 | ADF | 6 | ||
| NFT | 597 | 50.7 [±8.9] | 53 | 444 | 535 | 62 | |||||||
| Hanson | 2020 | USA | AFT | 72 | 53 [46.0–61.0] | A | 7 | ||||||
| NFT | 72 | 54 [46.5–64.0] | |||||||||||
| Stumpf | 2020 | Brazil | AFT | 65 | 53 [46.0–61.0] | 0 | 65 | 65 | BCD | 6 | |||
| NFT | 255 | 54 [46.5–64.0] | 0 | 255 | 255 | ||||||||
| Vyas | 2020 | USA | 73 | 48.6±8.8 | A | 6 | |||||||
| 200 | 50.2±9.2 | ||||||||||||
AFT, autologous fat transfer; NFT, non-autologous fat transfer; BCS, breast-conserving surgery; A, locoregional recurrence rate; B, local recurrence rate; C, regional recurrence rate; D, distant metastasis rate; E, systemic recurrence rate; F, total death rate; NOS, Newcastle-Ottawa Scale.
Results of overall meta-analysis
| Characteristics | RR (95% CI) | P value | I2 |
|---|---|---|---|
| LR rate | |||
| Overall | 0.92 (0.70–1.19) | 0.514 | 0.0 |
| Sensitivity analysis | 0.92 (0.70–1.19) | ||
| Publication bias | t=1.04 | 0.310 | |
| RRR rate | |||
| Overall | 1.17 (0.77–1.79) | 0.451 | 0.4 |
| Sensitivity analysis | 1.17 (0.77–1.79) | ||
| LRR rate | |||
| Overall | 0.79 (0.62–1.01) | 0.056 | 0.0 |
| Sensitivity analysis | 0.79 (0.62–1.01) | ||
| Publication bias | t=1.08 | 0.315 | |
| Distant metastasis rate | |||
| Overall | 1.13 (0.91–1.42) | 0.248 | 0.0 |
| Sensitivity analysis | 1.13 (0.91–1.42) | ||
| Publication bias | t=1.27 | 0.225 | |
| SR rate | |||
| Overall | 0.67 (0.49–0.92) | 0.012 | 0.0 |
| Sensitivity analysis | 0.67 (0.49–0.92) | ||
| Total death rate | |||
| Overall | 0.75 (0.54–1.05) | 0.096 | 0.0 |
| Sensitivity analysis | 0.75 (0.54–1.05) |
LR, local recurrence; RRR, regional recurrence; LRR, locoregional recurrence; SR, systemic recurrence; RR, relative ratio.
Figure 2Forest plot of local recurrence rate. P value represents the P value of I2. RR, relative risk; CI, confidence intervals.
Figure 3Forest plot of regional recurrence rate. P value represents the P value of I2. RR, relative risk; CI, confidence intervals.
Figure 4Forest plot of locoregional recurrence rate. P value represents the P value of I2. RR, relative risk; CI, confidence intervals.
Figure 5Forest plot of systemic recurrence rate. P value represents the P value of I2. RR, relative risk; CI, confidence intervals.
Figure 6Forest plot of distant metastasis rate. P value represents the P value of I2. RR, relative risk; CI, confidence intervals.
Figure 7Forest plot of total death rate. P value represents the P value of I2. RR, relative risk; CI, confidence intervals.