<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>8(1)</volume><submitter>Seum T</submitter><funding>German Federal Ministry of Education and Research</funding><pubmed_abstract>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 precurso</pubmed_abstract><journal>NPJ precision oncology</journal><pagination>244</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11514036</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Potential of pre-diagnostic metabolomics for colorectal cancer risk assessment or early detection.</pubmed_title><pmcid>PMC11514036</pmcid><pubmed_authors>Bhardwaj M</pubmed_authors><pubmed_authors>Cardoso R</pubmed_authors><pubmed_authors>Seum T</pubmed_authors><pubmed_authors>Brenner H</pubmed_authors><pubmed_authors>Frick C</pubmed_authors><pubmed_authors>Hoffmeister M</pubmed_authors></additional><is_claimable>false</is_claimable><name>Potential of pre-diagnostic metabolomics for colorectal cancer risk assessment or early detection.</name><description>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 precurso</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Oct</publication><modification>2026-07-15T14:44:54.638Z</modification><creation>2026-07-06T03:08:33.059Z</creation></dates><accession>S-EPMC11514036</accession><cross_references><pubmed>39462072</pubmed><doi>10.1038/s41698-024-00732-5</doi></cross_references></HashMap>