Suppr超能文献

凯泽评分在使用MRI评估乳腺癌中的诊断性能:一项系统评价和荟萃分析。

Diagnostic performance of Kaiser score in the evaluation of breast cancer using MRI: A systematic review and meta-analysis.

作者信息

Mohammadzadeh Saeed, Mohebbi Alisa, Moradi Zahra, Abdi Ali, Mohammadi Afshin, Hakim Peyman Kamali, Ahmadinejad Nasrin, Zeinalkhani Fahimeh

机构信息

Department of Radiology, Tehran University of Medical Sciences, Imam Khomeini Hospital, Tehran, Iran; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

出版信息

Eur J Radiol. 2025 May;186:112055. doi: 10.1016/j.ejrad.2025.112055. Epub 2025 Mar 15.

Abstract

PURPOSE

To assess the performance of Kaiser score (KS) in detecting and characterizing breast cancer on magnetic resonance imaging (MRI).

METHODS

The protocol was pre-registered at (https://osf.io/83c6j/). We performed a comprehensive search in PubMed, Embase, Cochrane Library, and Web of Science until 30 October 2024 for studies that used KS for detection of breast cancer on MRI. The risk of bias in the included studies was evaluated utilizing Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Diagnostic values of area under the curve (AUC), sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio were calculated using a random-effects bivariate model. Meta-regression was used to explore the source of heterogeneity when I2 was ≥ 50 %. P-value < 0.05 was considered statistically significant.

RESULTS

A total of 29 studies with 7918 patients and 8451 breast lesions were included. The pooled sensitivity, specificity, and AUC of KS for detecting malignant breast lesions on MRI were 95 % (95 % CI = 94 % to 96 %), 70 % (95 % CI = 64 % to 75 %), and 0.94 (95 % CI = 0.91 to 0.96), while for Breast Imaging Reporting and Data System (BI-RADS), they were 97 % (95 % CI = 92 % to 99 %), 46 % (95 % CI = 30 % to 62 %), and 0.89 (95 % CI = 0.86 to 0.91). Sensitivity difference was not statistically significant (p-value = 0.803), but specificity difference was significant (p-value = 0.001). Also, KS demonstrated slightly better diagnostic accuracy for mass lesions with a sensitivity of 96 % (95 % CI = 94 % to 97 %), specificity of 69 % (95 % CI = 60 % to 77 %), and AUC of 0.96 (95 % CI = 0.94 to 0.97) compared to non-mass lesions with 93 % (95 % CI = 88 % to 96 %), 68 % (95 % CI = 58 % to 77 %), and 0.91 (95 % CI = 0.88 to 0.94) values, respectively. KS showed better performance in larger lesions.

CONCLUSION

The KS's superior diagnostic performance compared to BI-RADS, particularly its ability to avoid unnecessary biopsies, makes it valuable for diagnostic and clinical decision-making.

摘要

目的

评估凯泽评分(KS)在磁共振成像(MRI)检测和表征乳腺癌中的性能。

方法

该方案已在(https://osf.io/83c6j/)预先注册。我们在PubMed、Embase、Cochrane图书馆和Web of Science中进行了全面检索,直至2024年10月30日,以查找使用KS在MRI上检测乳腺癌的研究。采用诊断准确性研究质量评估2(QUADAS - 2)对纳入研究的偏倚风险进行评估。使用随机效应双变量模型计算曲线下面积(AUC)、敏感性、特异性、阳性和阴性似然比以及诊断比值比的诊断值。当I2≥50%时,使用Meta回归探索异质性来源。P值<0.05被认为具有统计学意义。

结果

共纳入29项研究,涉及7918例患者和8451个乳腺病变。KS在MRI上检测恶性乳腺病变的合并敏感性、特异性和AUC分别为95%(95%CI = 94%至96%)、70%(95%CI = 64%至75%)和0.94(95%CI = 0.91至0.96),而乳腺影像报告和数据系统(BI - RADS)的相应值分别为97%(95%CI = 92%至99%)、46%(95%CI = 30%至62%)和0.89(95%CI = 0.86至0.91)。敏感性差异无统计学意义(P值 = 0.803),但特异性差异有统计学意义(P值 = 0.001)。此外,KS对肿块病变的诊断准确性略高,其敏感性为96%(95%CI = 94%至97%),特异性为69%(95%CI = 60%至77%),AUC为0.96(95%CI = 0.94至0.97),相比之下,非肿块病变的相应值分别为93%(95%CI = 88%至96%)、68%(95%CI = 58%至77%)和0.91(95%CI = 0.88至0.94)。KS在较大病变中表现更佳。

结论

与BI - RADS相比,KS具有卓越的诊断性能,尤其是其避免不必要活检的能力,使其在诊断和临床决策中具有重要价值。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验