Plasma ctDNA TP53 Mutation and Breast Cancer Prognosis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
ObjectiveTo analyze the association between plasma circulating tumor DNA (ctDNA) TP53 mutation status and survival outcomes in breast cancer patients.MethodsPubMed, Embase, and the Cochrane Library were searched for relevant literature published between 2000 and 2025, examining the impact of plasma ctDNA TP53 mutations on survival outcomes in breast cancer patients, including overall survival (OS), progression-free survival (PFS), or disease-free survival (DFS).Two researchers independently screened the literature according to predefined inclusion and exclusion criteria and extracted relevant data.The Newcastle-Ottawa scale and Cochrane Risk of Bias Assessment Tool were used to evaluate study quality.Meta-analysis, publication bias assessment, and sensitivity analysis were performed using Review Manager 5.3 and STATA 18.0 software.ResultsA total of 14 studies (13 cohort studies and 1 randomized controlled trial) involving 3521 breast cancer patients were included, among whom 921 had TP53 mutations.All studies were assessed as high-quality or low-risk.The random-effects model demonstrated that TP53 mutations were significantly associated with poorer OS (I2=77%, HR=1.82, 95% CI: 1.15-2.88, P=0.010), PFS (I2=63%, HR=1.68, 95% CI: 1.30-2.17, P < 0.001), and DFS (I2=85%, HR=1.98, 95% CI: 1.05-3.75, P=0.040).Funnel plots indicated no significant publication bias, and sensitivity analysis confirmed the stability and reliability of the results.Subgroup analyses based on study design, breast cancer stage and molecular subtype revealed that TP53 mutations were associated with worse prognosis in prospective studies (OS: HR=2.32, 95% CI: 1.84-2.92, P < 0.001;PFS: HR=1.83, 95% CI: 1.47-2.27, P < 0.001), metastatic/advanced breast cancer (OS: HR=2.03, 95% CI: 1.44-2.87, P < 0.001;PFS: HR=1.90, 95% CI: 1.57-2.31, P < 0.001), and hormone receptor-positive and human epidermal growth factor receptor 2-negative (HR+HER2-) patients (OS: HR=2.11, 95% CI: 1.56-2.85, P < 0.001;PFS: HR=1.94, 95% CI: 1.62-2.33, P < 0.001).Among different treatment regimens, patients with TP53 mutations receiving trastuzumab combined with paclitaxel exhibited relatively better prognosis (PFS: HR=0.08, 95% CI: 0.02-0.30, P < 0.001).ConclusionPlasma ctDNA TP53 mutations are closely associated with survival outcomes in breast cancer patients and may serve as a potential predictor of poor prognosis, providing support for clinical management and prognostic assessment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.034 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".