인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Pancreatic cancer is often detected at a late stage and usually leads to significant morbidity and deaths1. The 5-year survival rate for those with pancreatic cancer detected at a resectable stage is 25%, compared with a 5-year survival rate of 3% for those with pancreatic cancer that is not resectable2–4. Some 20% of patients have resectable disease at the time of diagnosis, underscoring the necessity to develop novel early detection tools2.The timeline for the development of pancreatic cancer is controversial. The evolution of pancreatic cancer is probably a slow process, involving sequential, independent accumulation of mutations in both oncogenes and tumour suppressor genes, with progression from precancerous stages to increasingly invasive and metastatic stages over many years5. An alternative evolution might be driven by punctuated equilibrium, a process that encompasses intervals of stability and rapid transformation with molecular changes6. Epidemiological data suggest that, once clinically apparent, pancreatic cancer may progress from category T1 to T4 in 1 year7. Methods must be developed to detect the disease before the onset of clinical symptoms.Liquid biopsy approaches have garnered substantial interest for pancreatic cancer screening, either as single-cancer tests or as part of multi-cancer early detection tests. A wide range of blood-based biomarkers have been investigated, including proteins, metabolites, microRNAs (miRs), circulating tumour DNA, circulating tumour cells, and exosomes8. Previous studies have focused on biomarkers at the time of clinical diagnosis. It remains unknown whether such biomarkers could be used for longitudinal screening in asymptomatic individuals.The aim of this meta-analysis was to evaluate the use of blood-based biomarkers for the detection of pancreatic cancer in prediagnostic settings, with a particular focus on diagnostic accuracy at different time points up to 5 years before clinical diagnosis
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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