{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:48:31Z","timestamp":1786978111018,"version":"build-2736575974"},"reference-count":46,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2024,2,8]],"date-time":"2024-02-08T00:00:00Z","timestamp":1707350400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["accp1.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["The Journal of Clinical Pharma"],"published-print":{"date-parts":[[2024,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    The determination of the appropriate initial dose for tacrolimus is crucial in achieving the target concentration promptly and avoiding adverse effects and poor prognosis. However, the trial\u2010and\u2010error approach is still common practice. This study aimed to establish a prediction model for an initial dosing algorithm of tacrolimus in patients receiving a lung transplant. A total of 210 lung transplant recipients were enrolled, and 26 single nucleotide polymorphisms (SNP) from 18 genes that could potentially affect tacrolimus pharmacokinetics were genotyped. Associations between SNPs and tacrolimus concentration\/dose ratio were analyzed. SNPs that remained significant in pharmacogenomic analysis were further combined with clinical factors to construct a prediction model for tacrolimus initial dose. The dose needed to reach steady state tacrolimus concentrations and achieve the target range was used to validate model prediction efficiency. Our final model consisted of 7 predictors\u2014\n                    <jats:italic>CYP3A5<\/jats:italic>\n                    rs776746,\n                    <jats:italic>SLCO1B3<\/jats:italic>\n                    rs4149117,\n                    <jats:italic>SLC2A2<\/jats:italic>\n                    rs1499821,\n                    <jats:italic>NFATc4<\/jats:italic>\n                    rs1955915, alanine aminotransferase, direct bilirubin, and hematocrit\u2014and explained 41.4% variance in the tacrolimus concentration\/dose ratio. It achieved an area under the receiver operating characteristic curve of 0.804 (95% confidence interval, 0.746\u20100.861). The Hosmer\u2010Lemeshow test yielded a nonsignificant\n                    <jats:italic>P<\/jats:italic>\n                    value of .790, suggesting good fit of the model. The predicted dose exhibited good correlation with the observed dose in the early postoperative period (r\u00a0=\u00a00.748,\n                    <jats:italic>P<\/jats:italic>\n                    less than .001). Our study provided a genotype\u2010guided prediction model for tacrolimus initial dose, which may help to guide individualized dosing of tacrolimus in the lung transplant population in clinical practice.\n                  <\/jats:p>","DOI":"10.1002\/jcph.2411","type":"journal-article","created":{"date-parts":[[2024,2,8]],"date-time":"2024-02-08T03:28:26Z","timestamp":1707362906000},"page":"719-727","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Genotype\u2010Guided Model for Prediction of Tacrolimus Initial Dosing After Lung Transplantation"],"prefix":"10.1002","volume":"64","author":[{"given":"Wenwen","family":"Du","sequence":"first","affiliation":[{"name":"Department of Pharmacy China\u2010Japan Friendship Hospital  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoxing","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Pharmacy China\u2010Japan 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