{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:49:12Z","timestamp":1786978152633,"version":"build-2736575974"},"reference-count":27,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T00:00:00Z","timestamp":1761264000000},"content-version":"vor","delay-in-days":23,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["JGH Open"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background\/Aims<\/jats:title>\n                    <jats:p>Tacrolimus is an effective treatment option for refractory ulcerative colitis; however, some patients still require colectomy due to insufficient response. Early assessment of surgical risk is clinically important, as delayed decision\u2010making may worsen the patient's condition and increase the risk of postoperative complications. This study aimed to identify predictors of colectomy within 3\u2009months of initiating tacrolimus therapy and to develop a clinically applicable prediction model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective analysis of hospitalized patients with severe ulcerative colitis treated with tacrolimus between 2011 and 2025. Fourteen clinical background variables were evaluated using LASSO\u2010penalized logistic regression with cross\u2010validation to construct the prediction model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among 114 patients, 24 (21.1%) underwent colectomy, including 16 (14.0%) within 3\u2009months of treatment initiation. The LASSO regression identified three predictive variables: serum albumin level, hemoglobin level, and age at tacrolimus initiation. The resulting model demonstrated good discriminative performance, with an area under the curve of 0.78. Using a cutoff value of logit(\n                      <jats:italic>p<\/jats:italic>\n                      ), the model achieved a sensitivity of 87.5% and a specificity of 63.4%. Kaplan\u2013Meier analysis revealed a significantly higher cumulative colectomy rate in the high\u2010risk group (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), supporting the model's predictive utility.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We developed a clinical prediction model that accurately estimates the risk of early colectomy based on baseline clinical factors at the start of tacrolimus therapy. This model may serve as a practical tool to guide decision\u2010making regarding surgical timing and overall treatment strategy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jgh3.70297","type":"journal-article","created":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T06:17:18Z","timestamp":1761373038000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Clinical Prediction Model for Early Colectomy in Patients With Severe Ulcerative Colitis Treated With Tacrolimus"],"prefix":"10.1002","volume":"9","author":[{"given":"Hikaru","family":"Shimizu","sequence":"first","affiliation":[{"name":"2nd Department of Internal Medicine Osaka Medical and Pharmaceutical University  Takatsuki 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