Evidence map›Paper›PMID 42218349›Full record

ArticleAnnals of surgical oncology2026

Early Oncologic Outcomes of Robot-Assisted Versus Conventional Nipple-Sparing Mastectomy: A Propensity Score-Matching Analysis.

Seung Ah Lee, Ki Jo Kim, Doyoun Woen, Su Min Lee, Kawon Oh, Cho Eun Lee, Woong Ki Park, Se Kyung Lee, Byung Joo Chae, Jonghan Yu and 9 more

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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. Not yet cited in PubMed.

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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

19 authors.

Seung Ah LeeDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Ki Jo KimDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Doyoun WoenDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Su Min LeeDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Kawon OhDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Cho Eun LeeDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Woong Ki ParkDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Se Kyung LeeDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Byung Joo ChaeDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Jonghan YuDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Jeong Eon LeeDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Seok Won KimDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Seok Jin NamDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Goo Hyun MunDepartment of Plastic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Jai Kyong PyonDepartment of Plastic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Byung Joon JeonDepartment of Plastic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Kyong Je WooDepartment of Plastic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Kyeong Tae LeeDepartment of Plastic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Jai Min RyuDivision of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. jaimin.ryu@samsung.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRobot-assisted nipple-sparing mastectomy (R-NSM) was developed to minimize visible scarring and improve the quality of life in patients with breast cancer. However, despite its increasing adoption, evidence regarding its oncologic outcomes remains sparse. This study aimed to compare the oncologic outcomes of R-NSM and conventional nipple-sparing mastectomy (C-NSM).

methodsWe retrospectively reviewed patients who underwent NSM with immediate breast reconstruction for breast cancer between 2019 and 2022. Risk-reducing cases were excluded. R-NSM and C-NSM groups were compared after propensity score matching using a nearest-neighbor algorithm, matching each patient in the R-NSM group to up to five controls without replacement.

resultsBefore matching, the R-NSM group more frequently had hormone receptor-positive/human epidermal growth factor receptor 2-negative tumors, lower Ki-67 indices, and no neoadjuvant chemotherapy. After propensity score matching, most clinicopathologic variables were well balanced between groups. During a median follow-up of 37.5 months for R-NSM and 42.6 months for C-NSM, no locoregional recurrence, distant metastasis, or death occurred in the R-NSM group, whereas all seven recurrences (3.5%) occurred in the C-NSM group. Kaplan-Meier analysis showed no significant differences in locoregional recurrence-free survival, distant metastasis-free survival, or disease-free survival between groups, although all observed oncologic events occurred in the C-NSM group.

conclusionR-NSM demonstrated oncologic outcomes comparable to those of C-NSM, with no recurrence or mortality despite a sufficiently long follow-up. These findings support R-NSM as a feasible and oncologically sound surgical option for appropriately selected patients with early-stage breast cancer.

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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.