Evidence map›Paper›PMID 41724918›Full record

ArticleAnnals of surgical oncology2026

Single-Port Robot-Assisted Nipple-Sparing Mastectomy: Main Analysis of a Retrospective Multicenter Study (SPROUT, KoREa-BSG 09).

Jung Eun Choi, Young-Won Lee, Sungchan Gwark, Se Hyun Paek, Young Woo Chang, Hee Jun Choi, Young Joo Lee, Moo Hyun Lee, Joo Heung Kim, Sung Gwe Ahn and 2 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Annals of surgical oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Jung Eun Choi *Department of Surgery, Yeungnam University College of Medicine, Daegu, Korea.
Young-Won Lee *Division of Breast and Endocrine Surgery, Department of Surgery, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea.
Sungchan GwarkDepartment of Surgery, Ewha Woman's University College of Medicine, Ewha Woman's University Seoul Hospital, Seoul, Korea.
Se Hyun PaekDepartment of Surgery, Ewha Woman's University College of Medicine, Ewha Woman's University Seoul Hospital, Seoul, Korea.
Young Woo ChangDivision of Breast and Endocrine Surgery, Department of Surgery, Korea University Ansan Hospital, Korea University College of Medicine, Seoul, Korea.
Hee Jun ChoiDepartment of Surgery, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Republic of Korea.
Young Joo LeeDivision of Breast Surgery, Department of Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Moo Hyun LeeDepartment of Surgery, Keimyung University School of Medicine, Daegu, Korea.
Joo Heung KimDepartment of Surgery, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Korea.
Sung Gwe AhnDepartment of Surgery, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
Hyung Seok ParkDepartment of Surgery, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Korea. imgenius@yuhs.ac.
Sae Byul LeeDivision of Breast Surgery, Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea. newstar153@hanmail.net.ORCID http://orcid.org/0000-0002-3370-6937

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe emergence of single-port robotic systems has enabled their application in breast surgery, offering minimally invasive, cosmetically favorable options for mastectomy. This study aimed to evaluate surgical outcomes and operative efficiency of single-port robotic-assisted nipple-sparing mastectomy (SP-RNSM) across multiple institutions in Korea based on early experiences.

methodsThis multicenter retrospective study included the patients with primary breast cancer who underwent SP-RNSM with or without axillary surgery and immediate reconstruction between January 2018 and November 2023 at 12 institutions in Korea. Clinicopathologic characteristics, operative variables, including operative time, and postoperative outcomes were collected.

resultsA total of 428 patients were included in this study. Among them, 81.5% were diagnosed with invasive carcinoma, and 18.5% with ductal carcinoma in situ. The mean age was 45.7 years, and 78.5% were premenopausal. Direct-to-implant was the most common reconstruction method (66.1%). The mean breast surgeon's operative time, plastic surgeon's operative time, and total operative time were 160.5 ± 54.1, 167.1 ± 116.1, and 333.5 ± 132.6 minutes. Multivariable analysis identified lymph node metastasis, heavier breast weight, and absence of tumescent solution use as independent predictors of longer BS time, with breast weight showing the strongest association. Postoperatively, 80% of patients recovered without complications. The most common complication was seroma (10.5%), and the reoperation rate was 2.8%. In the learning curve analysis, no consistent or marked decrease in operative time was observed with increasing case numbers.

conclusionsThe SP-RNSM is a feasible and safe approach for breast cancer surgery with favorable surgical outcomes and minimal complications.

Indexed as

Breast NeoplasmsCarcinoma, Ductal, BreastCarcinoma, Intraductal, NoninfiltratingMastectomyNipplesOrgan Sparing TreatmentsRobotic Surgical ProceduresAdultFemaleFollow-Up StudiesHumansMiddle AgedOperative TimePrognosisRepublic of KoreaRetrospective StudiesBreast neoplasmsLearning curveRobot-assisted surgerySubcutaneous mastectomySurgical time

Identifiers

PMID41724918

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.