Abbreviated tacrolimus area-under-the-curve monitoring for renal transplant recipients

Wong, K.M.; Shek, Chi Chung; Chau, Kwong Wing; Li, Chun Sang

doi:10.1016/s0272-6386(00)70013-8

Cited by 116 publications

(128 citation statements)

References 17 publications

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“…Based on our previous pilot study in stable patients on tacrolimus, AUC 0-12 value was kept at around 100-150 ng · h/ml in first 3 months and around 80-100 ng · h/ml after 3 months. Some centers also found very high coefficients of correlation between three time-point strategy and the complete AUC 0-12 [9][10][11][12][13]. The regression equation using three time-point derived in our group was: 13.3 + 1.2 · C 0 + 2.4 · C 2 + 5.6 · C 4 .…”

Section: Methodsmentioning

confidence: 50%

“…It has been shown that C 0 has a poor correlation with AUC 0-12 [7,8]. Our center favors the use of limited sampling strategy and abbreviated formula to estimate the AUC 0-12 , which allows better prediction of drug exposure [9]. However, it is inconvenient for the patients because they have to stay in the center for at least 2-h waiting for blood sampling.…”

Section: Discussionmentioning

confidence: 99%

“…Limited sampling strategy and abbreviated AUC 0-12 estimation were used in our center for tacrolimus monitoring. Calculation of tacrolimus AUC 0-12 was by the formula: 16.2 + C 2 · 2.4 + C 4 · 5.9 (C 2 : 2-h postdose tacrolimus level; C 4 : 4-h postdose tacrolimus level) [9]. Based on our previous pilot study in stable patients on tacrolimus, AUC 0-12 value was kept at around 100-150 ng · h/ml in first 3 months and around 80-100 ng · h/ml after 3 months.…”

Section: Methodsmentioning

confidence: 99%

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Dried blood spot measurement: application in tacrolimus monitoring using limited sampling strategy and abbreviated AUC estimation

et al. 2007

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Section: Methodsmentioning

confidence: 50%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Dried blood spot measurement: application in tacrolimus monitoring using limited sampling strategy and abbreviated AUC estimation

et al. 2007

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“…Trough levels of both CsA and tacrolimus are not closely correlated with drug exposure (17,18,(32)(33)(34), the risk for allograft rejection (35,36), or their adverse effects (37,38). The AUC 0-12h and derived parameters, such as absorption profiles, have been shown to correlate more closely with clinical outcome also in patients who received prophylaxis with basiliximab (39).…”

Section: Discussionmentioning

confidence: 99%

Untreated Rejection in 6-Month Protocol Biopsies Is Not Associated with Fibrosis in Serial Biopsies or with Loss of Graft Function

Scholten

Rowshani²,

Cremers³

et al. 2006

Journal of the American Society of Nephrology

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Donor age, calcineurin inhibitor nephrotoxicity, and acute rejection are the most significant predictors of chronic allograft nephropathy. Protocol biopsies, both in deceased-and living-donor renal grafts, have shown that cortical tubulointerstitial fibrosis correlates with graft survival and function. The impact of not treating subclinical acute rejection (SAR) is less clear. In this study, 126 de novo renal transplant recipients were randomly assigned to receive area-under-the-curve-controlled exposure of either a cyclosporine or a tacrolimus-based immunosuppressive regimen that included steroids, mycophenolate mofetil, and basiliximab induction. Protocol biopsies were taken before and 6 and 12 mo after transplantation. The prevalence of SAR was determined retrospectively. Fibrosis was evaluated by quantitative digital analysis of Sirius red staining in serial biopsies. Donor age correlated significantly with tubulointerstitial fibrosis in pretransplantation biopsies and inferior graft function at month 6 (r ‫؍‬ ؊0.26; P ‫؍‬ 0.033). Acute rejection incidence was 11.5%, and no clinical late rejection occurred. The prevalence of SAR at 6 mo was 30.8% but was not associated with differences in serial quantitative Sirius red staining at 6 or 12 mo, proteinuria, or progressive loss of GFR up to 2 yr. No differences were found in donor variables, histocompatibility, rejection history, or exposure of immunosuppressants. Controlled individualized calcineurin inhibitor exposure and subsequent tapering resulted in a low early acute rejection rate and prevented late acute rejection. Because, by design, we did not treat SAR, these results provide evidence that asymptomatic infiltrates in 6-mo surveillance biopsies may not be deleterious in the intermediate term. There is need for reliable biomarkers to prove that not all cell infiltrates are equivalent or that infiltrates may change with time.

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“…Therefore, TAC was examined to show which blood sampling point is the best correlated with AUC as CYA. One study reported that C o is the best correlated with AUC 27) , whereas another study suggested that a formula with fewer blood sampling points, and not C o , is the most closely correlated with AUC (limited sampling strategy) [28][29][30][31] .…”

Section: Tacrolimusmentioning

confidence: 99%

Optimal Pharmacokinetics of Cyclosporine and Tacrolimus Based Relationship Among AUC, Trough and Peak Concentration

Takeuchi¹

2012

Readings in Advanced Pharmacokinetics - Theory, Methods and Applications

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Abbreviated tacrolimus area-under-the-curve monitoring for renal transplant recipients

Cited by 116 publications

References 17 publications

Dried blood spot measurement: application in tacrolimus monitoring using limited sampling strategy and abbreviated AUC estimation

Dried blood spot measurement: application in tacrolimus monitoring using limited sampling strategy and abbreviated AUC estimation

Untreated Rejection in 6-Month Protocol Biopsies Is Not Associated with Fibrosis in Serial Biopsies or with Loss of Graft Function

Optimal Pharmacokinetics of Cyclosporine and Tacrolimus Based Relationship Among AUC, Trough and Peak Concentration

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