Evidence map›Paper›PMID 39045652›Full record

ArticleThe oncologist2024

18F-FDG PET/CT for early prediction of pathological complete response in breast cancer neoadjuvant therapy: a retrospective analysis.

Yilin Wu, Yanling Li, Bin Chen, Ying Zhang, Wanying Xing, Baoliang Guo, Wan Wang

Abstract read
In one paragraph

Article in The oncologist, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Prospective comparison of [European journal of nuclear medicine and molecular imaging · 2026
    Trial
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Resistance to neoadjuvant chemotherapy in breast cancers: a metabolic perspective.Journal of experimental & clinical cancer research : CR · 2025
    Review
  11. Gland surgery · 2025
    Article
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

7 authors.

Yilin WuDepartment of Breast Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, People's Republic of China.
Yanling LiDepartment of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin 150001, People's Republic of China.
Bin ChenDepartment of Breast Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, People's Republic of China.
Ying ZhangDepartment of Breast Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, People's Republic of China.
Wanying XingDepartment of Breast Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, People's Republic of China.
Baoliang GuoDepartment of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin 150001, People's Republic of China.
Wan WangDepartment of Breast Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, People's Republic of China.

Funding

Jilin Scientific and Technological Development Program 20210101323JC
6 · The paper itself

Abstract

backgroundNeoadjuvant treatment has been developed as a systematic approach for patients with early breast cancer and has resulted in improved breast-conserving rate and survival. However, identifying treatment-sensitive patients at the early phase of therapy remains a problem, hampering disease management and raising the possibility of disease progression during treatment.

methodsIn this retrospective analysis, we collected 2-deoxy-2-[F-18] fluoro-d-glucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) images of primary tumor sites and axillary areas and reciprocal clinical pathological data from 121 patients who underwent neoadjuvant treatment and surgery in our center. The univariate and multivariate logistic regression analyses were performed to investigate features associated with pathological complete response (pCR). An 18F-FDG PET/CT-based prediction model was trained, and the performance was evaluated by receiver operating characteristic curves (ROC).

resultsThe maximum standard uptake values (SUVmax) of 18F-FDG PET/CT were a powerful indicator of tumor status. The SUVmax values of axillary areas were closely related to metastatic lymph node counts (R = 0.62). Moreover, the early SUVmax reduction rates (between baseline and second cycle of neoadjuvant treatment) were statistically different between pCR and non-pCR patients. The early SUVmax reduction rates-based model showed great ability to predict pCR (AUC = 0.89), with all molecular subtypes (HR+HER2-, HR+HER2+, HR-HER2+, and HR-HER2-) considered.

conclusionOur research proved that the SUVmax reduction rate of 18F-FDG PET/CT contributed to the early prediction of pCR, providing rationales for utilizing PET/CT in NAT in the future.

Indexed as

Breast NeoplasmsFluorodeoxyglucose F18Neoadjuvant TherapyPositron Emission Tomography Computed TomographyAdultAgedFemaleHumansMiddle AgedRadiopharmaceuticalsRetrospective StudiesFluorodeoxyglucose F18Radiopharmaceuticals18F-FDG PET/CTbreast cancerdrug responseneoadjuvant therapy

Identifiers

PMID39045652
PMCPMC11630790

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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.