Meta-analysis of magnetic resonance imaging in detecting residual breast cancer after neoadjuvant therapy
Journal of the National Cancer Institute, ISSN: 0027-8874, Vol: 105, Issue: 5, Page: 321-333
2013
- 307Citations
- 197Captures
- 1Mentions
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations307
- Citation Indexes305
- 305
- CrossRef164
- Policy Citations2
- Policy Citation2
- Captures197
- Readers197
- 197
- Mentions1
- News Mentions1
- News1
Most Recent News
Correlation of Histopathological and Radiological Response Patterns and Their Prognostic Implications in Breast Cancer After Neoadjuvant Chemotherapy
Introduction Neoadjuvant chemotherapy (NAC) has become the standard of care for breast cancer (BC) due to several key benefits. It facilitates breast-conserving surgery, potentially avoids
Article Description
Background: It has been proposed that magnetic resonance imaging (MRI) be used to guide breast cancer surgery by differentiating residual tumor from pathologic complete response (pCR) after neoadjuvant chemotherapy. This meta-analysis examines MRI accuracy in detecting residual tumor, investigates variables potentially affecting MRI performance, and compares MRI with other tests. Methods: A systematic literature search was undertaken. Hierarchical summary receiver operating characteristic (HSROC) models were used to estimate (relative) diagnostic odds ratios ([R]DORs). Summary sensitivity (correct identification of residual tumor), specificity (correct identification of pCR), and areas under the SROC curves (AUCs) were derived. All statistical tests were two-sided. Results: Forty-four studies (2050 patients) were included. The overall AUC of MRI was 0.88. Accuracy was lower for "standard" pCR definitions (referent category) than "less clearly described" (RDOR = 2.41, 95% confidence interval [CI] = 1.11 to 5.23) or "near-pCR" definitions (RDOR = 2.60, 95% CI = 0.73 to 9.24; P =. 03.) Corresponding AUCs were 0.83, 0.90, and 0.91. Specificity was higher when negative MRI was defined as contrast enhancement less than or equal to normal tissue (0.83, 95% CI = 0.64 to 0.93) vs no enhancement (0.54, 95% CI = 0.39 to 0.69; P =. 02), with comparable sensitivity (0.83, 95% CI = 0.69 to 0.91; vs 0.87, 95% CI = 0.80 to 0.92; P =. 45). MRI had higher accuracy than mammography (P =. 02); there was only weak evidence that MRI had higher accuracy than clinical examination (P =. 10). No difference in MRI and ultrasound accuracy was found (P =. 15). Conclusions: MRI accurately detects residual tumor after neoadjuvant chemotherapy. Accuracy was lower when pCR was more rigorously defined, and specificity was lower when test negativity thresholds were more stringent; these definitions require standardization. MRI is more accurate than mammography; however, studies comparing MRI and ultrasound are required. © The Author 2013. Published by Oxford University Press. All rights reserved.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84874855647&origin=inward; http://dx.doi.org/10.1093/jnci/djs528; http://www.ncbi.nlm.nih.gov/pubmed/23297042; https://academic.oup.com/jnci/article-lookup/doi/10.1093/jnci/djs528; https://dx.doi.org/10.1093/jnci/djs528; https://academic.oup.com/jnci/article-abstract/105/5/321/1010943?redirectedFrom=fulltext
Oxford University Press (OUP)
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