Liquid biopsy biomarkers for accurate detection of malignant pulmonary nodules: a meta-analytic approach.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
환자: lung cancer
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
Similarly, integrating multi-omics data with machine learning models has been shown to enhance the ability to differentiate between benign and malignant pulmonary nodules, thereby supporting early diagnosis and improved management for patients with lung cancer. [SUPPLEMENTARY INFORMATION] The online version contains supplementary material available at 10.1007/s12672-025-03646-1.
[UNLABELLED] Pulmonary nodules are a common radiological finding that can be classified as either benign or Malignant, with significant clinical implications.
- 연구 설계 meta-analysis
APA
Caballero-Vazquez A, Garcia-Cerezo M, et al. (2026). Liquid biopsy biomarkers for accurate detection of malignant pulmonary nodules: a meta-analytic approach.. Discover oncology, 17(1), 178. https://doi.org/10.1007/s12672-025-03646-1
MLA
Caballero-Vazquez A, et al.. "Liquid biopsy biomarkers for accurate detection of malignant pulmonary nodules: a meta-analytic approach.." Discover oncology, vol. 17, no. 1, 2026, pp. 178.
PMID
41612093 ↗
Abstract 한글 요약
[UNLABELLED] Pulmonary nodules are a common radiological finding that can be classified as either benign or Malignant, with significant clinical implications. The early detection of malignant nodules is critically important for improving the prognosis of lung cancer, which remains the leading cause of cancer-related mortality worldwide. Traditional imaging techniques have Limitations in accurately classifying pulmonary nodules. Liquid biopsy, a minimally invasive method that evaluates circulating components in the Blood, presents promising diagnostic potential in this context. This study aims to evaluate the diagnostic capacity of multiple liquid biopsy biomarkers for early and accurate differentiation between benign and Malignant pulmonary nodules. Accordingly, we conducted a comprehensive study involving a meta-analysis, selecting 16 eligible studies that utilised liquid biopsy to assess various circulating biomarkers in the diagnostic yield. The most significant results were linked to circulating free DNA (cfDNA). However, other components, including circulating tumour cells (CTCs), microRNAs/pfeRNAs, extracellular vesicles (EVs), serological markers, and imaging techniques, also provided valuable information. Similarly, integrating multi-omics data with machine learning models has been shown to enhance the ability to differentiate between benign and malignant pulmonary nodules, thereby supporting early diagnosis and improved management for patients with lung cancer.
[SUPPLEMENTARY INFORMATION] The online version contains supplementary material available at 10.1007/s12672-025-03646-1.
[SUPPLEMENTARY INFORMATION] The online version contains supplementary material available at 10.1007/s12672-025-03646-1.
🏷️ 키워드 / MeSH 📖 같은 키워드 OA만
🏷️ 같은 키워드 · 무료전문 — 이 논문 MeSH/keyword 기반
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