Evidence Hub

Breast fat grafting and cancer: a systematic review of the science behind enhancements and concerns

Valente DS, Ely PB, Kieling L, Konzen AT, Steffen LP, Lazzaretti GS, Zanella RK

Translational breast cancer research : a journal focusing on translational research in breast cancer, 2024

Abstract

BACKGROUND: Autologous fat transfer (AFT) is gaining popularity in breast surgery, offering a natural-looking and minimally invasive approach for augmentation, reconstruction, and contouring. However, concerns about its impact on breast cancer necessitate an understanding of the interplay between transplanted adipose-derived stem cells (ADSCs) and the breast tissue microenvironment. Renowned for regeneration, ADSCs raise questions about their role in cancer promotion. This systematic review delves into the complex relationship between AFT and breast cancer, exploring how ADSCs may influence development, growth, and metastasis.

METHODS: A systematic search of electronic databases, including PubMed, Embase, and BVS was conducted to identify relevant studies. The search strategy employed a combination of keywords, including "breast augmentation", "fat grafting", "breast enhancement", "mammoplasty", "cancer", "neoplasm" and related terms. Two reviewers independently screened titles and abstracts. Full-text articles were then retrieved for further evaluation based on their potential contribution to the review objectives.

RESULTS: Two hundred and forty records were identified. Among these, 104 duplicates were removed, resulting in 136 reports available for title and abstract screening. Subsequently, 54 papers were deemed potentially eligible for inclusion, and all reports were retrieved.

CONCLUSIONS: In vitro studies reveal ADSCs dual role in breast cancer, influencing…

How strong is the evidence?

Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free