{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:13:19Z","timestamp":1790727199555,"version":"4.1.0"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T00:00:00Z","timestamp":1717545600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T00:00:00Z","timestamp":1717545600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/http:\/\/dx.doi.org\/10.13039\/501100000664","name":"Health Technology Assessment Programme","doi-asserted-by":"publisher","award":["09\/22\/49"],"award-info":[{"award-number":["09\/22\/49"]}],"id":[{"id":"10.13039\/http:\/\/dx.doi.org\/10.13039\/501100000664","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur Radiol"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Objective<\/jats:title>\n                <jats:p>Improving prognostication to direct personalised therapy remains an unmet need. This study prospectively investigated promising CT, genetic, and immunohistochemical markers to improve the prediction of colorectal cancer recurrence.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Material and methods<\/jats:title>\n                <jats:p>This multicentre trial (ISRCTN 95037515)\u00a0recruited patients with primary colorectal cancer undergoing CT staging from 13 hospitals. Follow-up identified cancer recurrence and death. A baseline model for cancer recurrence at 3 years was developed from pre-specified clinicopathological variables (age, sex, tumour-node\u00a0stage, tumour\u00a0size, location, extramural venous invasion, and treatment). Then, CT perfusion (blood flow, blood volume,\u00a0transit time and permeability), genetic (RAS, RAF, and DNA mismatch repair), and immunohistochemical markers of angiogenesis and hypoxia (CD105, vascular endothelial growth factor, glucose transporter protein, and hypoxia-inducible factor) were added to assess whether prediction improved over tumour-node staging alone as the main outcome measure.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Three hundred twenty-six of 448 participants formed the final cohort (226 male; mean 66\u2009\u00b1\u200910 years. 227 (70%) had \u2265\u2009T3 stage cancers; 151 (46%) were node-positive; 81 (25%) developed subsequent recurrence. The sensitivity and specificity of staging alone for recurrence were 0.56 [95% CI: 0.44, 0.67] and 0.58 [0.51, 0.64], respectively. The baseline clinicopathologic model improved specificity (0.74 [0.68, 0.79], with equivalent sensitivity of 0.57 [0.45, 0.68] for high vs medium\/low-risk participants. The addition of prespecified CT perfusion, genetic, and immunohistochemical markers did not improve prediction over and above the clinicopathologic model (sensitivity, 0.58\u20130.68; specificity, 0.75\u20130.76).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>A multivariable clinicopathological model outperformed staging in identifying patients at high risk of recurrence. Promising CT, genetic, and immunohistochemical markers investigated did not further improve prognostication in rigorous prospective evaluation.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Clinical relevance statement<\/jats:title>\n                <jats:p>A prognostic model based on clinicopathological variables including age, sex, tumour-node stage, size, location, and extramural venous invasion better identifies colorectal cancer patients at high risk of recurrence for neoadjuvant\/adjuvant therapy than stage alone.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Key Points<\/jats:title>\n                <jats:p><jats:list list-type=\"bullet\">\n                  <jats:list-item>\n                    <jats:p><jats:italic>Identification of colorectal cancer patients at high risk of recurrence is an unmet need for treatment personalisation<\/jats:italic>.<\/jats:p>\n                  <\/jats:list-item>\n                  <jats:list-item>\n                    <jats:p><jats:italic>This model for recurrence, incorporating many patient variables, had higher specificity than staging alone<\/jats:italic>.<\/jats:p>\n                  <\/jats:list-item>\n                  <jats:list-item>\n                    <jats:p><jats:italic>Continued optimisation\u00a0of risk stratification schema will help individualise treatment plans and follow-up schedules<\/jats:italic>.<\/jats:p>\n                  <\/jats:list-item>\n                <\/jats:list><\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s00330-024-10803-7","type":"journal-article","created":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T12:15:55Z","timestamp":1717589755000},"page":"6992-7001","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Multivariable prognostic modelling to improve prediction of colorectal cancer recurrence: the PROSPeCT 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VG receives research support from Siemens Healthineers, paid to the institution. The other authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The second author is a Professor of statistics at University College London.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Written informed consent was obtained from all participants in this trial.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Health research authority ethical approval was obtained.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"None of these study subjects have been previously reported.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}