{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T04:49:28Z","timestamp":1791434968554,"version":"4.3.3"},"reference-count":43,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["221854\/Z\/20\/Z"],"award-info":[{"award-number":["221854\/Z\/20\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["R024227"],"award-info":[{"award-number":["R024227"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["S011676"],"award-info":[{"award-number":["S011676"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dom-pubs.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Diabetes Obesity Metabolism"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Diabetes prediction tools are valuable for prevention and resource planning. Few tools exist to predict long\u2010term diabetes risk for British adults. We aim to develop and validate a diabetes prediction tool for short\u2010 and long\u2010term risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>\n                      Prediction model development (Training,\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20094502) and internal validation (Test,\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20091929) used Whitehall II data (WHII); external validation used English Longitudinal Study of Ageing (ELSA) data, with incident diabetes as outcome. Predictors were selected using LASSO\u2010Cox, random survival forests (RSF) and best subset selection. Three candidate Cox models were built from these predictor sets and compared. Performance was assessed with\n                      <jats:italic>C<\/jats:italic>\n                      \u2010indices, calibration and decision curve analysis (DCA). A continuous risk score and quartile\u2010based risk groups were derived; a nomogram was created.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Across WHII Test (235 events) and ELSA (255 events), three models showed broadly similar discrimination, calibration and DCA patterns. LASSO\u2010 and RSF\u2010selected models performed comparably and slightly better than best subset. LASSO and RSF both selected ethnicity, body mass index, waist\u2010to\u2010height ratio, height, triglyceride\u2010glucose index, fasting glucose, family history of diabetes and socioeconomic status; LASSO additionally selected smoking, whereas RSF also included age, triglycerides, high\u2010density lipoprotein cholesterol, systolic and diastolic blood pressure. In ELSA, risk\u2010score\n                      <jats:italic>C<\/jats:italic>\n                      \u2010indices (95% CIs) were 0.800 (0.773\u20130.827) for the LASSO\u2010selected model and 0.801 (0.774\u20130.827) for the RSF\u2010selected model; risk\u2010group\n                      <jats:italic>C<\/jats:italic>\n                      \u2010indices were 0.737 (0.715\u20130.759) and 0.727 (0.707\u20130.748), respectively.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We developed and externally validated a tool to estimate 5\u2010, 10\u2010 and 15\u2010year diabetes risk in British middle\u2010aged adults, which may support primary care decision\u2010making.<\/jats:p>\n                  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