Evidence map›Paper›PMID 41510108›Full record

ArticleTranslational cancer research2025

Preoperative prediction of breast cancer Ki-67 status via multimodal ultrasound-clinical nomogram: a single-center study.

Xiao-Kai Lu, Nian-Qiu Liu, Yi-Hang Li, Zhi-Yao Li, Dong Chen, Zhi-Rui Chuan, Yin-Xi Qu, Ying-Xian Zhang, Hai-Tao Chen, Xiao-Mao Luo

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Article in Translational cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing 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

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper 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

10 authors.

Xiao-Kai Lu *Department of Ultrasonography, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China.
Nian-Qiu Liu *Mammary Gland Center Second Ward, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China.
Yi-Hang Li *Department of Ultrasonography, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Zhi-Yao LiDepartment of Ultrasonography, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China.
Dong ChenDepartment of Ultrasonography, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China.
Zhi-Rui ChuanDepartment of Ultrasonography, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China.
Yin-Xi QuDepartment of Ultrasonography, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China.
Ying-Xian ZhangDepartment of Ultrasonography, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China.
Hai-Tao Chen *Department of Ultrasonography, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China.
Xiao-Mao Luo *Department of Ultrasonography, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Breast cancer is a highly heterogeneous malignancy that poses a major health threat to women. Contemporary clinical management relies heavily on molecular subtyping, in which the Ki-67 proliferation index serves as a critical biomarker for assessing tumor aggressiveness and recurrence risk. However, conventional Ki-67 evaluation depends on invasive biopsy and immunohistochemical analysis, whose accuracy can be compromised by tumor heterogeneity-induced sampling errors and inter-observer variability. Therefore, this study aimed to develop and validate a preoperative nomogram that integrates multimodal ultrasound features with clinical parameters to enable non-invasive preoperative assessment of Ki-67 expression status in breast cancer. Methods: We retrospectively enrolled 142 consecutive breast cancer patients from The Third Affiliated Hospital of Kunming Medical University's Breast Center (March 2022 to August 2024). Preoperative multimodal ultrasound parameters (including B-mode, Doppler, and shear-wave elastography) and clinical variables were systematically documented using standardized protocols. Variables demonstrating univariate associations (P<0.10) underwent forward stepwise multivariate regression using likelihood ratio criteria. Model performance was assessed through: (I) calibration curves with Hosmer-Lemeshow test; (II) discrimination via area under the curve (AUC); and (III) clinical utility by decision curve analysis. Internal validation employed bootstrap resampling (1,000 replicates) with optimism correction using Harrell's method. Results: Univariate analysis identified six predictors associated with Ki-67 status (P<0.10): maximum lesion diameter, hyperechoic halo presence, Adler grade, Eratio, posterior echo reduction, and calcifications. Multivariate analysis confirmed four independent predictors of Ki-67 status (P<0.05): hyperechoic halo presence [adjusted odds ratio (aOR) =7.934; 95% confidence interval (CI): 2.604-24.173], posterior echo reduction (aOR =0.245; 95% CI: 0.099-0.601), calcifications (aOR =3.524; 95% CI: 1.466-8.472), and Adler grade (aOR =2.334; 95% CI: 1.222-4.456). The resulting nomogram demonstrated good discrimination (AUC =0.797; 95% CI: 0.722-0.872), with bootstrap-corrected AUC of 0.771 (95% CI: 0.673-0.879). Conclusions: The validated nomogram provides clinically useful preoperative prediction of Ki-67 status (AUC =0.797; bootstrap-corrected 0.771), with hyperechoic halo presence, posterior echo reduction, calcifications, and high Adler grade as key predictors.

Indexed as

Breast cancerKi-67multimodal ultrasoundshear-wave elastography (SWE)

Identifiers

PMID41510108
PMCPMC12776185

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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.