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More nuanced stratification could lead to enrichment of these referral pathways.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Population-based cohort study of adults aged 30\u201385 years at type 2 diabetes diagnosis (2010\u20132021) using the QResearch primary care database in England linked to secondary care data, the national cancer registry and mortality registers. Clinical prediction models were developed to estimate risks of pancreatic cancer diagnosis within 2 years and evaluated using internal\u2013external cross-validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Seven hundred and sixty-seven of 253,766 individuals were diagnosed with pancreatic cancer within 2 years. Models included age, sex, BMI, prior venous thromboembolism, digoxin prescription, HbA1c, ALT, creatinine, haemoglobin, platelet count; and the presence of abdominal pain, weight loss, jaundice, heartburn, indigestion or nausea (previous 6 months). The Cox model had the highest discrimination (Harrell\u2019s\n                      <jats:italic>C<\/jats:italic>\n                      -index 0.802 (95% CI: 0.797\u20130.817)), the highest clinical utility, and was well calibrated. The model\u2019s highest 1% of predicted risks captured 12.51% of pancreatic cancer cases. NICE guidance had 3.95% sensitivity.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>A new prediction model could have clinical utility in identifying individuals with recent onset diabetes suitable for fast-track abdominal imaging.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1038\/s41416-024-02693-9","type":"journal-article","created":{"date-parts":[[2024,5,3]],"date-time":"2024-05-03T07:01:59Z","timestamp":1714719719000},"page":"1969-1978","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Predicting the risk of pancreatic cancer in adults with new-onset diabetes: development and internal\u2013external validation of a clinical risk prediction model"],"prefix":"10.1038","volume":"130","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0061-979X","authenticated-orcid":false,"given":"Ash Kieran","family":"Clift","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pui San","family":"Tan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martina","family":"Patone","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiqi","family":"Liao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carol","family":"Coupland","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rachael","family":"Bashford-Rogers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shivan","family":"Sivakumar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2479-7283","authenticated-orcid":false,"given":"Julia","family":"Hippisley-Cox","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,3]]},"reference":[{"key":"2693_CR1","unstructured":"CRUK. 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JH-C has a 50% shareholding in ClinRisk Ltd, co-owning it with her husband, who is a director. As a shareholder and spouse of a director, she has a financial and family interest in the ongoing and future success of the company. The company licences software both to the private sector and to NHS bodies or bodies that provide services to the NHS (through GP electronic health record providers, pharmacies, hospital providers and other NHS providers). This software implements algorithms developed from access to the QResearch database during her time at the University of Nottingham. CC reports previous consultancy with ClinRisk Ltd outside the current work. PST reports previous consultation with AstraZeneca and Duke-NUS outside the current work. RB-R is a co-founder of Alchemab Therapeutics Ltd and consultant for Alchemab Therapeutics Ltd, Roche, GSK and UCB outside the current work. SS holds research funding from Bristol Myers Squibb, received fees for ad board for AstraZeneca, received speakers fees from AstraZeneca and received support from AstraZeneca and Novartis for online attendance at meetings. The other authors declare that they do not have any competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"This study was approved by the QResearch Scientific board (project reference OX153); ethical approval for the QResearch database is with the Derby Research Ethics Committee (reference: 18\/EM\/0400). Anonymised data sharing from general practices contributing to QResearch is on an individual \u2018opt-out\u2019 basis\u2014individual patient consent was not required for this analysis of anonymised, routinely collected clinical data.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}}]}}