Evidence map›Paper›PMID 38183069›Full record

ArticleWorld journal of surgical oncology2024

Reliability of predicting low-burden (≤ 2) positive axillary lymph nodes indicating sentinel lymph node biopsy in primary operable breast cancer - a retrospective comparative study with PET/CT and breast MRI.

Chayanee Sae-Lim, Wen-Pei Wu, Ming-Che Chang, Hung-Wen Lai, Shu-Tian Chen, Chen-Te Chou, Chiung-Ying Liao, Hsin-I Huang, Shou-Tung Chen, Dar-Ren Chen and 1 more

Open access · goldAbstract read
In one paragraph

Article in World journal of surgical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 7 institutions in 2 countries.

Chayanee Sae-LimDepartment of Surgery, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Wen-Pei WuSchool of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Ming-Che ChangDepartment of Nuclear Medicine, Changhua Christian Hospital, Changhua, Taiwan.
Hung-Wen LaiDivision of General Surgery, Changhua Christian Hospital, Changhua, Taiwan. hwlai650420@yahoo.com.tw.
Shu-Tian ChenDepartment of Diagnostic Radiology, Chang Gung Memorial Hospital, Chiayi Branch, Chiayi, Taiwan.
Chen-Te ChouDepartment of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Chiung-Ying LiaoDepartment of Radiology, Changhua Christian Hospital, Changhua, Taiwan.
Hsin-I HuangDepartment of Information Management, National Sun Yat-Sen University, Kaohsiung, Taiwan.
Shou-Tung ChenDivision of General Surgery, Changhua Christian Hospital, Changhua, Taiwan.
Dar-Ren ChenDivision of General Surgery, Changhua Christian Hospital, Changhua, Taiwan.
Che-Lun HungInstitute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan.
Changhua Christian Hospital · TWNational Yang Ming Chiao Tung University · TWChiayi Chang Gung Memorial Hospital · TWChulalongkorn University · THKaohsiung Medical University · TWNational Sun Yat-sen University · TWProvidence University · TW

Funding

Changhua Christian Hospital 109-CCH-IRP-093, 110-CCH-IRP-042, and 110-CCH-ICO-155, 112-CCH-IRP-051 and 112-CCH-IRP-082Ministry of Science and Technology, Taiwan MOST 111-2314-B-371-010
6 · The paper itself

Abstract

backgroundSentinel lymph node biopsy (SLNB) is the standard of care for axillary staging in early breast cancer patients with low-burden axillary metastasis (≤ 2 positive nodes). This study aimed to determine the diagnostic performances of 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) and breast magnetic resonance imaging in detecting axillary lymph node (ALN) metastases and the reliability to predict ALN burden.

methodsA total of 275 patients with primary operable breast cancer receiving preoperative PET/CT and upfront surgery from January 2001 to December 2022 in a single institution were enrolled. A total of 244 (88.7%) of them also received breast MRI. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of PET/CT and breast MRI were assessed. The predictive values to determine ALN burden were evaluated using radio-histopathological concordance.

resultsPET/CT demonstrated a sensitivity of 53.4%, specificity of 82.1%, PPV of 65.5%, NPV of 73.5%, and accuracy of 70.9% for detecting ALN metastasis, and the corresponding values for MRI were 71.8%, 67.8%, 56%, 80.8%, and 69.2%, respectively. Combining PET/CT and MRI showed a significantly higher PPV than MRI (72.7% vs 56% for MRI alone, p = 0.037) and a significantly higher NPV than PET/CT (84% vs 73.5% for PET/CT alone, p = 0.041). For predicting low-burden axillary metastasis (1-2 positive nodes), the PPVs were 35.9% for PET/CT, 36.7% for MRI, and 55% for combined PET/CT and MRI. Regarding patients with 0-2 positive ALNs in imaging, who were indicated for SLNB, the predictive correctness was 96.1% for combined PET/CT and MRI, 95.7% for MRI alone, and 88.6% for PET/CT alone.

conclusionsPET/CT and breast MRI exhibit high predictive values for identifying low-burden axillary metastasis in patients with operable breast cancer with ≦ 2 positive ALNs on imaging.

Indexed as

Breast NeoplasmsSentinel Lymph Node BiopsyFemaleHumansLymphatic MetastasisLymph NodesMagnetic Resonance ImagingPositron Emission Tomography Computed TomographyReproducibility of ResultsRetrospective StudiesAxillary lymph nodeAxillary lymph node disease burdenAxillary stagingBreast cancerMagnetic resonance imagingPositron emission tomography/computed tomographySentinel lymph node biopsy (SLNB)

Identifiers

PMID38183069
PMCPMC10770957
OpenAlexW4390630132

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.