The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Meta-Analysis of Magnetic Resonance Imaging in Detecting Residual Breast Cancer After Neoadjuvant Therapy
Abstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Whiting, P., Rutjes, A. W., Reitsma, J. B., Bossuyt, P. M., & Kleijnen, J. (2003) · BMC Medical Research Methodology · doi:10.1186/1471-2288-3-25 · Cited by 3,592
von Minckwitz, G., Untch, M., Blohmer, J.-U., Costa, S. D., Eidtmann, H., Fasching, P. A., Gerber, B., Eiermann, W., Hilfrich, J., Huober, J., et al. (2012) · Journal of Clinical Oncology · doi:10.1200/jco.2011.38.8595 · Cited by 2,659
Self-citationThe diagnostic odds ratio: a single indicator of test performance
Glas, A. S., Lijmer, J. G., Prins, M. H., Bonsel, G. J., & Bossuyt, P. M. M. (2003) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(03)00177-x · Cited by 2,261
Effect of preoperative chemotherapy on the outcome of women with operable breast cancer.
Fisher, B., Bryant, J., Wolmark, N., Mamounas, E., Brown, A., Fisher, E. R., Wickerham, D. L., Begovic, M., DeCillis, A., Robidoux, A., et al. (1998) · Journal of Clinical Oncology · doi:10.1200/jco.1998.16.8.2672 · Cited by 2,165
Self-citationA hierarchical regression approach to meta‐analysis of diagnostic test accuracy evaluations
Rutter, C. M., & Gatsonis, C. A. (2001) · Statistics in Medicine · doi:10.1002/sim.942 · Cited by 1,505
Magnetic resonance imaging of the breast: Recommendations from the EUSOMA working group
Sardanelli, F., Boetes, C., Borisch, B., Decker, T., Federico, M., Gilbert, F. J., Helbich, T., Heywang-Köbrunner, S. H., Kaiser, W. A., Kerin, M. J., et al. (2010) · European Journal of Cancer · doi:10.1016/j.ejca.2010.02.015 · Cited by 992
Self-citationOgston, K. N., Miller, I. D., Payne, S., Hutcheon, A. W., Sarkar, T. K., Smith, I., Schofield, A., & Heys, S. D. (2003) · The Breast · doi:10.1016/s0960-9776(03)00106-1 · Cited by 982
Houssami, N., Ciatto, S., Macaskill, P., Lord, S. J., Warren, R. M., Dixon, J. M., & Irwig, L. (2008) · Journal of Clinical Oncology · doi:10.1200/jco.2007.15.2108 · Cited by 831
Self-citationEvaluation of QUADAS, a tool for the quality assessment of diagnostic accuracy studies
Whiting, P. F., Weswood, M. E., Rutjes, A. W., Reitsma, J. B., Bossuyt, P. N., & Kleijnen, J. (2006) · BMC Medical Research Methodology · doi:10.1186/1471-2288-6-9 · Cited by 769
Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy
(2023) · doi:10.1002/9781119756194 · Cited by 757
Cited by
Harbeck, N., Penault-Llorca, F., Cortes, J., Gnant, M., Houssami, N., Poortmans, P., Ruddy, K., Tsang, J., & Cardoso, F. (2019) · Nature Reviews Disease Primers · doi:10.1038/s41572-019-0111-2 · Cited by 3,024
Self-citationMann, R. M., Cho, N., & Moy, L. (2019) · Radiology · doi:10.1148/radiol.2019182947 · Cited by 917
Houssami, N., Turner, R. M., & Morrow, M. (2017) · Breast Cancer Research and Treatment · doi:10.1007/s10549-017-4324-3 · Cited by 243
Self-citationGu, Y.-L., Pan, S.-M., Ren, J., Yang, Z.-X., & Jiang, G.-Q. (2017) · Clinical Breast Cancer · doi:10.1016/j.clbc.2016.12.010 · Cited by 128
Metadata
- Authors
- Marinovich, M. L., Houssami, N., Macaskill, P., Sardanelli, F., Irwig, L., Mamounas, E. P., von Minckwitz, G., Brennan, M. E., & Ciatto, S.
- Venue
- JNCI: Journal of the National Cancer Institute
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-01-07
- Volume
- 105
- Issue
- 5
- Pages
- 321-333
- ISSN
- 0027-8874 (ISSN-L)
- 1460-2105
- OpenAlex
- W2150539933
- Cited by
- 382
- References
- 60
- FWCI
- 3.80
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Meta-Analysis of Magnetic Resonance Imaging in Detecting Residual Breast Cancer After Neoadjuvant Therapy. https://app.cochat.ai/papers/10.1093/jnci/djs528
- The paper
- Marinovich, M. L., Houssami, N., Macaskill, P., Sardanelli, F., Irwig, L., Mamounas, E. P., von Minckwitz, G., Brennan, M. E., & Ciatto, S. (2013). Meta-Analysis of Magnetic Resonance Imaging in Detecting Residual Breast Cancer After Neoadjuvant Therapy. JNCI: Journal of the National Cancer Institute. https://doi.org/10.1093/jnci/djs528
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.