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Validation of tacrolimus equation to predict troughs using genetic and clinical factors.

ABSTRACT: Tacrolimus is an immunosuppressant used in transplantation. This article reports the validation of the authors' recently developed genetics-based tacrolimus equation that predicts troughs.Validation was performed in an independent cohort of 795 kidney transplant recipients receiving tacrolimus. The performance of the equation to predict initial troughs was assessed by calculating the bias and precision of the equation. For all troughs in the first 6 months post-transplant, a comparison was made between the troughs predicted using the equation versus those predicted using a basic apparent clearance model with no covariates.For initial troughs, the equation had a low bias (0.2 ng/ml) and high precision (1.8 ng/ml). For all troughs, the equation predicted troughs significantly better than the basic apparent clearance model.The tacrolimus equation had good bias and precision in predicting initial troughs and performed better than a basic apparent clearance model for all the troughs.

SUBMITTER: Passey C

PROVIDER: S-EPMC3579500 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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Validation of tacrolimus equation to predict troughs using genetic and clinical factors.

Passey Chaitali C Birnbaum Angela K AK Brundage Richard C RC Schladt David P DP Oetting William S WS Leduc Robert E RE Israni Ajay K AK Guan Weihua W Matas Arthur J AJ Jacobson Pamala A PA

Pharmacogenomics 20120701 10

<h4>Aim</h4>Tacrolimus is an immunosuppressant used in transplantation. This article reports the validation of the authors' recently developed genetics-based tacrolimus equation that predicts troughs.<h4>Methods</h4>Validation was performed in an independent cohort of 795 kidney transplant recipients receiving tacrolimus. The performance of the equation to predict initial troughs was assessed by calculating the bias and precision of the equation. For all troughs in the first 6 months post-transp ...[more]

PMID: 22909204

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Project description:BackgroundThe kidney failure risk equation (KFRE) predicts the 2- and 5-year risk of needing kidney replacement therapy (KRT) using four risk factors - age, sex, urine albumin-to-creatinine ratio (ACR) and creatinine-based estimated glomerular filtration rate (eGFR). Although the KFRE has been recalibrated in a UK cohort, this did not consider minority ethnic groups. Further validation of the KFRE in different ethnicities is a research priority. The KFRE also does not consider the competing risk of death, which may lead to overestimation of KRT risk. This study externally validates the KFRE for patients of South Asian ethnicity and compares methods for accounting for ethnicity and the competing event of death.MethodsData were gathered from an established UK cohort containing 35,539 individuals diagnosed with chronic kidney disease. The KFRE was externally validated and updated in several ways taking into account ethnicity, using recognised methods for time-to-event data, including the competing risk of death. A clinical impact assessment compared the updated models through consideration of referrals made to secondary care.ResultsThe external validation showed the risk of KRT differed by ethnicity. Model validation performance improved when incorporating ethnicity and its interactions with ACR and eGFR as additional risk factors. Furthermore, accounting for the competing risk of death improved prediction. Using criteria of 5 years ≥ 5% predicted KRT risk, the competing risks model resulted in an extra 3 unnecessary referrals (0.59% increase) but identified an extra 1 KRT case (1.92% decrease) compared to the previous best model. Hybrid criteria of predicted risk using the competing risks model and ACR ≥ 70 mg/mmol should be used in referrals to secondary care.ConclusionsThe accuracy of KFRE prediction improves when updated to consider South Asian ethnicity and to account for the competing risk of death. This may reduce unnecessary referrals whilst identifying risks of KRT and could further individualise the KFRE and improve its clinical utility. Further research should consider other ethnicities.

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Validation of tacrolimus equation to predict troughs using genetic and clinical factors.

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Validation of tacrolimus equation to predict troughs using genetic and clinical factors.

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