亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Comparison of ultrasound features and establishment of a predictive nomogram for triple-negative and non-triple-negative breast cancer

作者
Liyang Su,Qiaojie Xie,Jiaohong Chen,Qingquan Zhang,Nian Li,Chuntian Hong
出处
期刊:Research Square
标识
DOI:10.21203/rs.3.rs-3936899/v1
摘要

Abstract Objective: The objective of this study was to compare ultrasound features and establish a predictive nomogram for distinguishing between triple-negative breast cancer (TNBC) and non-triple-negative breast cancer (non-TNBC). Materials and Methods: The study included a total of 205 patients with confirmed TNBC and 574 patients with non-TNBC, randomly divided into a training set and a validation set at a ratio of 7:3. All patients underwent ultrasound examination and received a confirmatory pathological diagnosis. Nodules were classified according to the Breast Imaging-Reporting and Data System (BI-RADS) standard. Subsequently, the study conducted a comparative analysis of clinical characteristics and ultrasonic features. Results: A statistically significant difference was observed in multiple clinical and ultrasonic features between TNBC and non-TNBC. Specifically, in the logistic regression analysis conducted on the training set, indicators such as posterior echo, lesion size, presence of clinical symptoms, margin characteristics, internal blood flow signals, halo, and microcalcification were found to be statistically significant (P<0.05). These significant indicators were then effectively incorporated into a static and dynamic nomogram model, demonstrating high predictive performance in distinguishing TNBC from non-TNBC. Conclusion: The results of our study demonstrated that ultrasound features can be valuable in distinguishing between TNBC and non-TNBC. The presence of posterior echo, size, clinical symptoms, margin, internal flow, halo and microcalcification were identified as predictive factors for this differentiation. Microcalcification, hyperechoic halo, internal flow, and clinical symptoms emerged as the strongest predictive factors, indicating their potential as reliable indicators for identifying TNBC and non-TNBC.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
直率的宛丝完成签到,获得积分10
5秒前
高山流水完成签到,获得积分10
15秒前
完美的飞兰完成签到,获得积分10
34秒前
34秒前
41秒前
灵宝宝完成签到,获得积分10
43秒前
嘻嘻哈哈的应助被科研通管家采纳,获得10
1分钟前
1分钟前
1分钟前
SciGPT的应助被l1563358采纳,获得10
1分钟前
成就云朵完成签到,获得积分10
1分钟前
火星上雨南完成签到,获得积分10
1分钟前
汉堡包的应助被l1563358采纳,获得10
1分钟前
完美世界的应助被l1563358采纳,获得10
1分钟前
1分钟前
JamesPei的应助被l1563358采纳,获得10
1分钟前
楚科研完成签到 ,获得积分10
1分钟前
打打的应助被l1563358采纳,获得10
1分钟前
我是老大的应助被l1563358采纳,获得10
1分钟前
吴彬完成签到,获得积分10
1分钟前
李健的应助被l1563358采纳,获得10
1分钟前
脑洞疼的应助被QIQI采纳,获得10
1分钟前
GingerF的应助被Ali采纳,获得50
1分钟前
清爽小凡完成签到,获得积分10
1分钟前
冷艳的紫完成签到,获得积分10
2分钟前
2分钟前
烂漫的半雪完成签到,获得积分10
2分钟前
loii给真是个小机灵鬼呢的求助进行了留言
2分钟前
科研通AI6.4的应助被lxwctking采纳,获得10
3分钟前
嘻嘻哈哈的应助被科研通管家采纳,获得10
3分钟前
成就舞仙完成签到,获得积分10
3分钟前
无私的碧玉完成签到,获得积分10
3分钟前
3分钟前
缥缈雯完成签到,获得积分10
3分钟前
他有篮完成签到 ,获得积分10
3分钟前
畅快的夜云完成签到,获得积分10
3分钟前
QIQI发布了新的文献求助10
3分钟前
tamtam发布了新的文献求助10
3分钟前
包容雁菡完成签到,获得积分10
3分钟前
3分钟前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Organizational Behavior 510
A Silent Apostrophe:The Fayum Portraits 350
Sing with Understanding: Introduction to Theology in Christian Congregational Song, 3rd ed 330
Auslegung und Untersuchung einer invers ausgelegten Beschaufelung eines einstufigen Axialverdichters mit Vorleitrad (German) 300
AI-Contracting 300
四川大学学位论文.郭瑞昂. 基于高压热扩散的n型磷掺杂金刚石半导体制备研究 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 有机化学 化学工程 内科学 物理 生物化学 复合材料 催化作用 细胞生物学 人工智能 心理学 无机化学 基因 遗传学
热门帖子
关注 科研通微信公众号,转发送积分 7840603
求助须知:如何正确求助?哪些是违规求助? 9362225
关于积分的说明 20624829
捐赠科研通 7435223
什么是DOI,文献DOI怎么找? 3339702
关于科研通互助平台的介绍 2484209
邀请新用户注册赠送积分活动 2361495