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- W2898039622 abstract "Liquid biopsies using circulating tumor DNA (ctDNA) and cell-free DNA (cfDNA) have been developed for early cancer detection and patient monitoring. To investigate the clinical usefulness of ctDNA aberrations and cfDNA levels in patients with breast cancer (BC), we conducted a meta-analysis of 69 published studies on 5736 patients with BC.The relevant publications were identified by searching PubMed and Embase databases. The effect sizes of outcome parameters were pooled using a random-effects model.The ctDNA mutation rates of TP53, PIK3CA, and ESR1 were approximately 38%, 27%, and 32%, respectively. High levels of cfDNA were associated with BCs rather than with healthy controls. However, these detection rates were not satisfactory for BC screening. Although the precise mechanisms have been unknown, high cfDNA levels were significantly associated with axillary lymph node metastasis (odds ratio [OR] = 2.148, P = .030). The ctDNA mutations were significantly associated with cancer recurrence (OR = 3.793, P < .001), short disease-free survival (univariate hazard ratio [HR] = 5.180, P = .026; multivariate HR = 3.605, P = .001), and progression-free survival (HR = 1.311, P = .013) rates, and poor overall survival outcomes (HR = 2.425, P = .007).This meta-analysis demonstrates that ctDNA mutation status predicts disease recurrence and unfavorable survival outcomes, while cfDNA levels can be predictive of axillary lymph node metastasis in patients with BC." @default.
- W2898039622 created "2018-10-26" @default.
- W2898039622 creator A5046495710 @default.
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- W2898039622 date "2018-10-01" @default.
- W2898039622 modified "2023-10-10" @default.
- W2898039622 title "Liquid biopsy prediction of axillary lymph node metastasis, cancer recurrence, and patient survival in breast cancer" @default.
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- W2898039622 doi "https://doi.org/10.1097/md.0000000000012862" @default.
- W2898039622 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6211877" @default.
- W2898039622 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30334995" @default.
- W2898039622 hasPublicationYear "2018" @default.
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