Seum Teresa, Frick Clara, Cardoso Rafael, Bhardwaj Megha, Hoffmeister Michael, Brenner Hermann
Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Medical Faculty Heidelberg, Heidelberg University, Im Neuenheimer Feld 672, 69120, Heidelberg, Germany.
NPJ Precis Oncol. 2024 Oct 27;8(1):244. doi: 10.1038/s41698-024-00732-5.
This systematic review investigates the efficacy of metabolite biomarkers for risk assessment or early detection of colorectal cancer (CRC) and its precursors, focusing on pre-diagnostic biospecimens. Searches in PubMed, Web of Science, and SCOPUS through December 2023 identified relevant prospective studies. Relevant data were extracted, and the risk of bias was assessed with the QUADAS-2 tool. Among the 26 studies included, significant heterogeneity existed for case numbers, metabolite identification, and validation approaches. Thirteen studies evaluated individual metabolites, mainly lipids, while eleven studies derived metabolite panels, and two studies did both. Nine panels were internally validated, resulting in an area under the curve (AUC) ranging from 0.69 to 0.95 for CRC precursors and 0.72 to 1.0 for CRC. External validation was limited to one panel (AUC = 0.72). Metabolite panels and lipid-based biomarkers show promise for CRC risk assessment and early detection but require standardization and extensive validation for clinical use.
本系统评价研究了代谢物生物标志物在结直肠癌(CRC)及其癌前病变风险评估或早期检测中的有效性,重点关注诊断前生物样本。通过检索截至2023年12月的PubMed、科学网和Scopus数据库,确定了相关的前瞻性研究。提取相关数据,并使用QUADAS-2工具评估偏倚风险。在纳入的26项研究中,病例数量、代谢物鉴定和验证方法存在显著异质性。13项研究评估了单个代谢物,主要是脂质,11项研究得出了代谢物面板,2项研究两者都做了。9个面板进行了内部验证,CRC癌前病变的曲线下面积(AUC)范围为0.69至0.95,CRC的AUC范围为0.72至1.0。外部验证仅限于一个面板(AUC = 0.72)。代谢物面板和基于脂质的生物标志物在CRC风险评估和早期检测方面显示出前景,但临床应用需要标准化和广泛验证。