Outcomes of robotic nipple-sparing mastectomy versus conventional nipple-sparing mastectomy in women with breast cancer: a systematic review and meta-analysis.
Gabriel De La Cruz KuDiego Chambergo-MichilotArmando PerezBryan ValcarcelLarissa PamenDavid LinshawAbhishek ChatterjeeJennifer LaFeminaJudy C BougheyPublished in: Journal of robotic surgery (2023)
The promising results of the robotic approach for multiple cancer operations has led to interest in the potential of robotic nipple-sparing mastectomy (R-NSM); however, further studies are required to compare the benefits and complications of this approach with those of conventional open nipple-sparing mastectomy (C-NSM). We performed a meta-analysis to compare surgical complications of R-NSM versus C-NSM. We performed a review of literature through June 2022 in PubMed, Scopus, and EMBASE. We included randomized controlled trials (RCTs), cohorts, case-control studies, and case series with > 50 patients comparing the two techniques. Separate meta-analyses were conducted according to study design. From 80 publications, we identified six studies. The sample size ranged from 63 to 311 mastectomies from 63 to 275 patients. The tumor size and disease stage were similar between groups. The positive margin rate was 0-4.6% in the R-NSM arm and 0-2.9% in the C-NSM arm. Four studies reported early recurrence data, which were similar between groups (R-NSM: 0%, C-NSM: 0-8%). The R-NSM group had a lower rate of overall complications compared to the C-NSM group in cohorts/RCTs (RR = 0.68, 95%CI 0.49-0.96). In case-control studies, rate of necrosis was lower with R-NSM. Operative time was significantly longer in the R-NSM group in cohort/RCTs. In early experience with R-NSM, R-NSM had a lower overall complication rate compared to C-NSM in cohorts/RCTs. While these data are promising, our results show variability and heterogeneity limiting definitive conclusions. Additional trials are needed to guide the role of R-NSM and its oncologic outcomes.
Keyphrases
- case control
- breast reconstruction
- robot assisted
- end stage renal disease
- minimally invasive
- randomized controlled trial
- chronic kidney disease
- ejection fraction
- risk factors
- systematic review
- risk assessment
- prognostic factors
- electronic health record
- adipose tissue
- skeletal muscle
- papillary thyroid
- machine learning
- study protocol
- deep learning
- weight loss
- big data
- artificial intelligence
- rectal cancer
- patient reported outcomes