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Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging-a systematic review and meta-analysis

Rejmer, Cornelia LU orcid ; Hjärtström, Malin LU orcid ; Bendahl, Pär-Ola LU ; Dihge, Looket LU ; Skarping, Ida LU orcid ; Zhang, Daqu LU ; Dustler, Magnus LU orcid and Rydén, Lisa LU orcid (2025) In Systematic Reviews
Abstract

BACKGROUND: Prediction models for sentinel lymph node (SLN) status could potentially substitute surgical axillary staging in patients with early breast cancer. Several imaging modalities have been used with various feature extraction and selection approaches. This systematic review and meta-analysis aimed to evaluate prediction models for SLN status based on breast imaging in patients with early breast cancer to summarize the current evidence and to identify areas requiring additional research.

METHODS: The systematic literature search strategy was based on the Population, Intervention, Comparison, and Outcome (PICO) framework: P: female patients with clinically node-negative invasive breast cancer scheduled to undergo primary... (More)

BACKGROUND: Prediction models for sentinel lymph node (SLN) status could potentially substitute surgical axillary staging in patients with early breast cancer. Several imaging modalities have been used with various feature extraction and selection approaches. This systematic review and meta-analysis aimed to evaluate prediction models for SLN status based on breast imaging in patients with early breast cancer to summarize the current evidence and to identify areas requiring additional research.

METHODS: The systematic literature search strategy was based on the Population, Intervention, Comparison, and Outcome (PICO) framework: P: female patients with clinically node-negative invasive breast cancer scheduled to undergo primary surgery; I: breast imaging; C: upfront sentinel lymph node biopsy; and O: prediction model performance regarding SLN status. The search was conducted in the PubMed, Embase, Web of Science, Cochrane, and Cumulative Index to Nursing and Allied Health Literature databases in March 2024. The screening of records, data collection, and bias assessments were performed independently by two reviewers. The risk of bias was assessed via the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool and the Prediction Model Study Risk of Bias Assessment Tool. A meta-analysis was performed using the random-effects model to assess performance and heterogeneity overall and in subgroups.

RESULTS: The literature search resulted in the inclusion of 32 articles with 11,464 patients in total. Five imaging categories were included: ultrasound (n = 8), magnetic resonance imaging (MRI) (n = 17), mammography (n = 1), positron emission tomography computed tomography (n = 1), and multiple modalities (n = 5). Four studies, assessed as having a high risk of bias, were excluded from the meta-analysis. The meta-analysis revealed heterogeneity in overall performance, except for MRI-based studies, with a pooled area under the curve of 0.85 (95% confidence interval 0.82-0.87). Meta-regression indicated that MRI and model calibration assessment upon validation contributed to heterogeneity.

CONCLUSIONS: This systematic review and meta-analysis revealed that prediction models using breast imaging-particularly MRI-could serve as a noninvasive alternative to surgical axillary staging in patients with early breast cancer. The results illustrate the heterogeneity between studies and the need for additional high-quality studies.

SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022301852, available at https://www.crd.york.ac.uk/PROSPERO.

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Systematic Reviews
publisher
BioMed Central (BMC)
external identifiers
  • pmid:41287043
ISSN
2046-4053
DOI
10.1186/s13643-025-03005-9
language
English
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yes
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© 2025. The Author(s).
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3d26c7b4-3e52-4984-88d5-7af82e7ed143
date added to LUP
2025-12-03 17:56:14
date last changed
2025-12-04 09:01:39
@article{3d26c7b4-3e52-4984-88d5-7af82e7ed143,
  abstract     = {{<p>BACKGROUND: Prediction models for sentinel lymph node (SLN) status could potentially substitute surgical axillary staging in patients with early breast cancer. Several imaging modalities have been used with various feature extraction and selection approaches. This systematic review and meta-analysis aimed to evaluate prediction models for SLN status based on breast imaging in patients with early breast cancer to summarize the current evidence and to identify areas requiring additional research.</p><p>METHODS: The systematic literature search strategy was based on the Population, Intervention, Comparison, and Outcome (PICO) framework: P: female patients with clinically node-negative invasive breast cancer scheduled to undergo primary surgery; I: breast imaging; C: upfront sentinel lymph node biopsy; and O: prediction model performance regarding SLN status. The search was conducted in the PubMed, Embase, Web of Science, Cochrane, and Cumulative Index to Nursing and Allied Health Literature databases in March 2024. The screening of records, data collection, and bias assessments were performed independently by two reviewers. The risk of bias was assessed via the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool and the Prediction Model Study Risk of Bias Assessment Tool. A meta-analysis was performed using the random-effects model to assess performance and heterogeneity overall and in subgroups.</p><p>RESULTS: The literature search resulted in the inclusion of 32 articles with 11,464 patients in total. Five imaging categories were included: ultrasound (n = 8), magnetic resonance imaging (MRI) (n = 17), mammography (n = 1), positron emission tomography computed tomography (n = 1), and multiple modalities (n = 5). Four studies, assessed as having a high risk of bias, were excluded from the meta-analysis. The meta-analysis revealed heterogeneity in overall performance, except for MRI-based studies, with a pooled area under the curve of 0.85 (95% confidence interval 0.82-0.87). Meta-regression indicated that MRI and model calibration assessment upon validation contributed to heterogeneity.</p><p>CONCLUSIONS: This systematic review and meta-analysis revealed that prediction models using breast imaging-particularly MRI-could serve as a noninvasive alternative to surgical axillary staging in patients with early breast cancer. The results illustrate the heterogeneity between studies and the need for additional high-quality studies.</p><p>SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022301852, available at https://www.crd.york.ac.uk/PROSPERO.</p>}},
  author       = {{Rejmer, Cornelia and Hjärtström, Malin and Bendahl, Pär-Ola and Dihge, Looket and Skarping, Ida and Zhang, Daqu and Dustler, Magnus and Rydén, Lisa}},
  issn         = {{2046-4053}},
  language     = {{eng}},
  month        = {{11}},
  publisher    = {{BioMed Central (BMC)}},
  series       = {{Systematic Reviews}},
  title        = {{Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging-a systematic review and meta-analysis}},
  url          = {{http://dx.doi.org/10.1186/s13643-025-03005-9}},
  doi          = {{10.1186/s13643-025-03005-9}},
  year         = {{2025}},
}