{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Tamm A"],"funding":["National Institute for Health Research (NIHR)"],"pagination":["e101521"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12458752"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["32(1)"],"pubmed_abstract":["Objectives
The 'tumour, node, metastasis' (TNM) classification of colorectal cancer (CRC) predicts prognosis and so is vital to consider in analyses of patterns and outcomes of care when using electronic health records. Unfortunately, it is often only available in free-text reports. This study aimed to develop regex-based text-processing algorithms that identify the reports describing CRC and extract the TNM staging at a low computational cost.Methods
The CRC and TNM extraction algorithms were iteratively developed using 58 634 imaging and pathology reports of patients with CRC from the Oxford University Hospitals (OUH) and Royal Marsden (RMH) NHS Foundation Trusts (FT), with additional input from Imperial College Healthcare and Christie NHS FTs. The algorithms were evaluat"],"journal":["BMJ health & care informatics"],"pubmed_title":["Supporting cancer research on real-world data: extracting colorectal cancer status and explicitly written TNM stages from free-text imaging and histopathology reports."],"pmcid":["PMC12458752"],"funding_grant_id":["NIHR203314","NIHR203323","NIHR203308"],"pubmed_authors":["Doshi N","Roadknight G","Woods K","Withers J","Little S","Mercuri L","Glampson B","Cunningham C","Salih H","Matharu S","Wasan H","O'Hara C","Renehan A","Nicholson BD","Jones HJS","Galdikas A","Teare M","Starling N","Scanlon LA","Morris EJA","Noble T","Campell D","Tamm A","Perry W","Varnai KA","Davies J","Malcomson L","Papadimitriou D"],"additional_accession":[]},"is_claimable":false,"name":"Supporting cancer research on real-world data: extracting colorectal cancer status and explicitly written TNM stages from free-text imaging and histopathology reports.","description":"Objectives
The 'tumour, node, metastasis' (TNM) classification of colorectal cancer (CRC) predicts prognosis and so is vital to consider in analyses of patterns and outcomes of care when using electronic health records. Unfortunately, it is often only available in free-text reports. This study aimed to develop regex-based text-processing algorithms that identify the reports describing CRC and extract the TNM staging at a low computational cost.Methods
The CRC and TNM extraction algorithms were iteratively developed using 58 634 imaging and pathology reports of patients with CRC from the Oxford University Hospitals (OUH) and Royal Marsden (RMH) NHS Foundation Trusts (FT), with additional input from Imperial College Healthcare and Christie NHS FTs. The algorithms were evaluat","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Sep","modification":"2026-06-03T19:36:06.219Z","creation":"2026-04-30T03:12:21.575Z"},"accession":"S-EPMC12458752","cross_references":{"pubmed":["40983364"],"doi":["10.1136/bmjhci-2025-101521"]}}