Meta-Analysis:
Diffusion-weighted imaging in identifying breast cancer pathological response to neoadjuvant chemotherapy: A meta-analysis
PDF | HTML | Supplementary Files | How to cite
Metrics: PDF 1778 views | HTML 3111 views | ?
Abstract
Wei Chu1,*, Weiwei Jin2,*, Daihong Liu3, Jian Wang3, Chengjun Geng4, Lihua Chen4 and Xuequan Huang3
1Department of Radiology, Wuxi Huishan District People’s Hospital, Jiangsu Province, 214187, China
2Department of Radiology, Wuxi Second Traditional Chinese Medicine Hospital, Jiangsu Province, 214121, China
3Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing, 400038, China
4Department of Radiology, PLA No.101 Hospital, Wuxi, Jiangsu Province, 214044, China
*These authors contributed equally to this work
Correspondence to:
Xuequan Huang, email: [email protected]
Lihua Chen, email: [email protected]
Keywords: magnetic resonance imaging; diffusion-weighted imaging; neoadjuvant chemotherapy; breast cancer; meta-analysis
Received: October 27, 2017 Accepted: December 01, 2017 Published: December 11, 2017
ABSTRACT
Background: Diffusion-weighted imaging (DWI) is increasingly used to identify pathological complete responses (pCRs) to neoadjuvant chemotherapy (NAC) in breast cancer. The aim of the present study was to assess the utility of DWI using a pooled analysis.
Materials and Methods: Literature databases were searched prior to July 2017. Fifteen studies with a total of 1181 patients were included. The data were extracted to perform pooled analysis, heterogeneity testing, threshold effect testing, sensitivity analysis, publication bias analysis and subgroup analyses.
Result: The methodological quality was moderate. Remarkable heterogeneity was detected, primarily due to a threshold effect. The pooled weighted values were a sensitivity of 0.88 (95% confidence interval (CI): 0.81, 0.92), a specificity of 0.79 (95% CI: 0.70, 0.86), a positive likelihood ratio of 4.1 (95% CI: 2.9, 5.9), a negative likelihood ratio of 0.16 (95% CI: 0.10, 0.24), and a diagnostic odds ratio of 26 (95% CI: 15, 46). The area under the receiver operator characteristic curve was 0.91 (95% CI: 0.88, 0.93). In the subgroup analysis, the pooled specificity of change in the apparent diffusion coefficient (ADC) subgroup was higher than that in the pre-treatment ADC subgroup (0.80 [95% CI: 0.71, 087] vs. 0.63 [95% CI: 0.52, 0.73], P = 0.027).
Conclusions: DWI may be an accurate and nonradioactive imaging technique for identifying pCRs to NAC in breast cancer. Nonetheless, there are a variety of issues when assessing DWI techniques for estimating breast cancer responses to NAC, and large scale and well-designed clinical trials are needed to assess the technique’s diagnostic value.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 4.0 License.
PII: 23195