Meta-analysis and Systematic Review of the Diagnostic Value of Contrast-enhanced Spectral Mammography for the Detection of Breast Cancer

Overview

Journal BMJ Open

Specialty General Medicine

Date 2024 Sep 4

PMID 39231551

Authors

Jiulin Liu

Ran Xiao

Huijia Yin

Ying Hu

Siyu Zhen

Shihao Zhou

Dongming Han

Affiliations

Soon will be listed here.

Abstract

Objective: The objective is to evaluate the diagnostic effectiveness of contrast-enhanced spectral mammography (CESM) in the diagnosis of breast cancer.

Design: DATA SOURCES: PubMed, Embase and Cochrane libraries up to 18 June 2022.

Eligibility Criteria For Selecting Studies: We included trials studies, compared the results of different researchers on CESM in the diagnosis of breast cancer, and calculated the diagnostic value of CESM for breast cancer.

Data Extraction And Synthesis: Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) evaluated the methodological quality of all the included studies. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses specification. In addition to sensitivity and specificity, other important parameters were explored in an analysis of CESM accuracy for breast cancer diagnosis. For overall accuracy estimation, summary receiver operating characteristic curves were calculated. STATA V.14.0 was used for all analyses.

Results: This meta-analysis included a total of 12 studies. According to the summary estimates for CESM in the diagnosis of breast cancer, the pooled sensitivity and specificity were 0.97 (95% CI 0.92 to 0.98) and 0.76 (95% CI 0.64 to 0.85), respectively. Positive likelihood ratio was 4.03 (95% CI 2.65 to 6.11), negative likelihood ratio was 0.05 (95% CI 0.02 to 0.09) and the diagnostic odds ratio was 89.49 (95% CI 45.78 to 174.92). Moreover, there was a 0.95 area under the curve.

Conclusions: The CESM has high sensitivity and good specificity when it comes to evaluating breast cancer, particularly in women with dense breasts. Thus, provide more information for clinical diagnosis and treatment.

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PMID: 39975646 PMC: 11835552. DOI: 10.1016/j.radcr.2024.06.009.

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