Evidence map›Paper›PMID 39844103›Full record

SynthesisBMC cancer2025

Multiple time points for detecting circulating tumor DNA to monitor the response to neoadjuvant therapy in breast cancer: a meta-analysis.

Shuyi Niu, Tie Sun, Mozhi Wang, Litong Yao, Tianyi He, Yusong Wang, Hengjun Zhang, Xiang Li, Yingying Xu

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

  1. Pooled it
  2. Observational
  3. Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Review
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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

9 authors.

Shuyi Niu *Department of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China.
Tie Sun *The Third Department of General Surgery, People's Hospital of China Medical University (Liaoning Provincial People's Hospital), Shenyang, Liaoning, 110001, China.
Mozhi WangDepartment of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China.
Litong YaoDepartment of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China.
Tianyi HeDepartment of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China.
Yusong WangDepartment of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China.
Hengjun ZhangDepartment of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China.
Xiang LiDepartment of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China. lixiangcmu@163.com.
Yingying XuDepartment of Breast Surgery, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China. xuyingying@cmu.edu.cn.

Funding

Chinese Young Breast Experts Research Project CYBER-2021-A02Chinese Young Breast Experts Research Project CYBER-2022-001the National Natural Science Foundation of China 82203786the National Natural Science Foundation of China 82373231the Natural Science Foundation of Liaoning Province of China 2022-YGJC-68the Natural Science Foundation of Liaoning Province of China 2023-BS-105
6 · The paper itself

Abstract

backgroundNot all breast cancer (BC) patients can benefit from neoadjuvant therapy (NAT). A poor response may result in patients missing the best opportunity for treatment, ultimately leading to a poor prognosis. Thus, to identify an effective predictor that can assess and predict patient response at early time points, we focused on circulating tumor DNA (ctDNA), which is a vital noninvasive liquid biopsy biomarker. We performed a meta-analysis to explore the predictive value of response by monitoring ctDNA at four time points of NAT using pathologic complete response (pCR) and residual cancer burden (RCB).

methodsBy searching Embase, PubMed, the Cochrane Library, and the Web of Science until December 24, 2023, we selected studies concerning the relationship between ctDNA and response or prognosis. We analysed the results at the following various time points: baseline (T0), first cycle of NAT (T1), mid-treatment (MT), and end of NAT (EOT). pCR and RCB were used to evaluate the response as the primary endpoint. The secondary endpoint was to investigate the relationship between ctDNA and prognosis. Odds ratios (ORs) and hazard ratios (HRs) were used as effect indicators.

resultsThirteen reports from twelve studies were eligible for inclusion in this meta-analysis. The results demonstrated that ctDNA negativity was associated with pCR at T1 (OR = 0.34; 95% CI: 0.21-0.57), MT (OR = 0.35; 95% CI: 0.20-0.60), and EOT (OR = 0.38; 95% CI: 0.22-0.66). When RCB was used to evaluate responses, ctDNA negativity was associated with RCB-0/I at the MT (OR = 0.34; 95% CI: 0.21-0.55) and EOT (OR = 0.26; 95% CI: 0.15-0.46). Furthermore, ctDNA positivity at T1 predicted a worse prognosis for patients (HR = 2.73; 95% CI: 1.29-5.75). We also performed a subgroup analysis to more accurately assess the predictive value of ctDNA for triple-negative breast cancer.

conclusionsOur meta-analysis suggested that the ctDNA status at the early stage of NAT can predict patient response, which provides evidence for adjusting personalized treatment strategies and improving patient survival. PROSPERO REGISTRATION NUMBER: CRD42024496465.

Indexed as

Biomarkers, TumorBreast NeoplasmsCirculating Tumor DNANeoadjuvant TherapyFemaleHumansLiquid BiopsyPrognosisTime FactorsTreatment OutcomeBiomarkers, TumorCirculating Tumor DNABiomarkersBreast cancerCirculating tumor DNANeoadjuvant therapyPrognosisResponse

Identifiers

PMID39844103
PMCPMC11752932

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.