Evidence map›Paper›PMID 36855131›Full record

ArticleWorld journal of surgical oncology2023

How to accurately preoperative screen nipple-sparing mastectomy candidate-a nomogram for predicting nipple-areola complex involvement risk in breast cancer patients.

Yuanbing Xu, Dai Pan, Yi Liu, Hanzhong Liu, Xing Sun, Wenjie Zhang, Chaohua Hu

Abstract read
In one paragraph

Article in World journal of surgical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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

What it found

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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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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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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

7 authors.

Yuanbing Xu *Department of Breast Surgery of Xiaogan Hospital affiliated to Wuhan University of Science and Technology, Xiaogan, 432100, Hubei Province, China.
Dai Pan *Department of Ultrasound of Xiaogan Hospital affiliated to Wuhan University of Science and Technology, Xiaogan, 432100, Hubei Province, China.
Yi LiuDepartment of Cancer Statistics of Xiaogan Hospital affiliated to Wuhan University of Science and Technology, Xiaogan, 432100, Hubei Province, China.
Hanzhong LiuDepartment of Pathology of Xiaogan Hospital affiliated to Wuhan University of Science and Technology, Xiaogan, 432100, Hubei Province, China.
Xing SunDepartment of Breast Surgery of Xiaogan Hospital affiliated to Wuhan University of Science and Technology, Xiaogan, 432100, Hubei Province, China.
Wenjie ZhangDepartment of Breast Surgery of Xiaogan Hospital affiliated to Wuhan University of Science and Technology, Xiaogan, 432100, Hubei Province, China.
Chaohua HuDepartment of Breast Surgery of Xiaogan Hospital affiliated to Wuhan University of Science and Technology, Xiaogan, 432100, Hubei Province, China. hch_xgzy@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNipple-sparing mastectomy (NSM) offers superior cosmetic outcomes and has been gaining wide acceptance. It has always been difficult to objectively quantify the risk of nipple-areola complex involvement (NACi). The goal was to develop a prediction model for clinical application.

methodsPatients who had a total mastectomy (TM) between January 2016 and January 2020 at a single institute formed the development cohort (n = 578) and those who had NSM + immediate breast reconstruction (IBR) between January 2020 and January 2021 formed the validation cohort (n = 112). The prediction model was developed using univariate and multivariate logistic regression studies. Based on NACi risk variables identified in the development cohort, a nomogram was created and evaluated in the validation cohort. Meanwhile, stratified analysis was performed based on the model's risk levels and was combined with intraoperative frozen pathology (IFP) to optimize the model.

resultsTumor central location, clinical tumor size (CTS) > 4.0 cm, tumor-nipple distance (TND) ≤ 1.0 cm, clinical nodal status positive (cN +), and KI-67 ≥ 20% were revealed to be good predictive indicators for NACi. A nomogram based on these major clinicopathologic variables was employed to quantify preoperative NACi risk. The accuracy was verified internally and externally. The diagnostic accuracy of IFP was 92.9%, sensitivity was 64.3%, and specificity was 96.9% in the validation group. Stratified analysis was then performed based on model risk. The diagnostic accuracy rates of IFP and NACiPM in low-risk, intermediate-risk, and high-risk respectively were 96.0%, 93.3%, 83.9%, 61.3%, 66.7%, and 83.3%.

conclusionWe created a visual nomogram to predict NACi risk in breast cancer patients. The NACiPM can be used to distinguish the low, intermediate, and high risk of NAC before surgery. Combined with IFP, we can develop a decision-making system for the implementation of NSM.

Indexed as

Breast NeoplasmsMammaplastyFemaleHumansMastectomyNipplesNomogramsImmediate breast reconstructionNipple-areola complex involvementNipple-areola sparing mastectomyNomogramPredictive model

Identifiers

PMID36855131
PMCPMC9976364

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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.