{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T05:11:36Z","timestamp":1777957896978,"version":"3.51.4"},"reference-count":23,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T00:00:00Z","timestamp":1776297600000},"content-version":"vor","delay-in-days":15,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["ascpt.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clinical Translational Sci"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Tacrolimus is a key immunosuppressant used to prevent allograft rejection in kidney transplant recipients. Intra\u2010patient variability (IPV) in tacrolimus trough concentrations has been recognized as a useful biomarker for predicting clinical outcomes in kidney transplantation. Tacrolimus therapeutic drug monitoring traditionally relies on whole\u2010blood concentration measurements. However, the pharmacological effect of tacrolimus is likely directly influenced by the unbound fraction in plasma, suggesting that IPV derived from plasma concentrations might be a more accurate predictor of clinical outcomes. This study aimed to compare the predictive performance of tacrolimus IPV calculated from whole\u2010blood versus imputed plasma concentrations for biopsy\u2010proven kidney allograft rejection. Plasma tacrolimus concentrations were imputed from measured whole\u2010blood levels in 1302 adult recipients using an established saturable hematocrit\u2010binding model. Tacrolimus whole\u2010blood and plasma IPV were calculated as time\u2010weighted coefficients of variation. The association between IPV and biopsy\u2010proven rejection occurring 60\u2013730\u2009days posttransplant was assessed using Kaplan\u2013Meier analysis and Cox proportional hazards models. We found that higher tacrolimus IPV was significantly associated with increased rejection risk, irrespective of the matrix used. Model performance analysis using the concordance index (\n                    <jats:italic>C<\/jats:italic>\n                    \u2010index) and bootstrap revealed that the plasma\u2010derived IPV model did not outperform the whole\u2010blood IPV model, indicating that calculating IPV from hematocrit\u2010imputed plasma concentrations offers no significant predictive advantage over the standard whole\u2010blood method. While our results indicate no predictive advantage of hematocrit\u2010imputed plasma IPV over whole\u2010blood IPV, it remains unknown whether IPV obtained from direct plasma tacrolimus measurement or more advanced plasma prediction models will outperform blood tacrolimus IPV in predicting rejection risk.\n                  <\/jats:p>","DOI":"10.1111\/cts.70543","type":"journal-article","created":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T06:22:27Z","timestamp":1776406947000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Comparing Whole\u2010Blood and Plasma Tacrolimus Intra\u2010Patient Variability for Predicting Allograft Rejection in Kidney Transplantation"],"prefix":"10.1111","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-2735-274X","authenticated-orcid":false,"given":"Zeyu","family":"Xia","sequence":"first","affiliation":[{"name":"Department of Clinical Pharmacy University of Michigan  Ann Arbor Michigan USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-1957-4622","authenticated-orcid":false,"given":"Hui","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Sciences University of Michigan  Ann Arbor Michigan USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7961-494X","authenticated-orcid":false,"given":"Jeong M.","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Clinical Pharmacy University of Michigan  Ann Arbor Michigan USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2248-4419","authenticated-orcid":false,"given":"Hao\u2010Jie","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Clinical Pharmacy University of Michigan  Ann Arbor Michigan 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