Literature DB >> 15691265

Immunosuppressive drug monitoring - what to use in clinical practice today to improve renal graft outcome.

Dirk R J Kuypers1.   

Abstract

Therapeutic drug monitoring (TDM) of immunosuppressive therapy is becoming an increasingly complex matter as the number of compounds and their respective combinations are continuously expanding. Unfortunately, in clinical practice, monitoring predose trough blood concentrations is often not sufficient for guiding optimal long-term dosing of these drugs. The excellent short-term results obtained nowadays in renal transplantation confer a misleading feeling of safety despite the fact that long-term results have not substantially improved, definitely not to a point where longer graft survival could counteract the increasing need for transplant organs and less toxicity and side-effects could ameliorate patient survival. It is therefore a challenging task to try to tailor immunosuppressive drug therapy to the individual patient profile and this in a time-dependent manner. For the majority of currently used immunosuppressive drugs, measurement of total drug exposure by determination of the dose-interval area under the concentration curve (AUC) seems to provide more useful information for clinicians in terms of concentration-exposure and exposure-response as well as reproducibility. To simplify this laborious way of measuring drug exposure, several validated abbreviated AUC profiles, accurately predicting the dose-interval AUC, have been put forward. Together with an increasing knowledge of the time-related pharmacokinetic behaviour of immunosuppressive drug and their metabolites, studies are focusing on how to apply abbreviated AUC sampling methods in clinical transplantation, taking into account the numerous factors affecting drug pharmacokinetics. Eventually, TDM using abbreviated AUC profiles has to be prospectively tested against classic methods of drug monitoring in terms of cost-effectiveness, feasibility and clinical relevance with the ultimate goal of improving patient and graft survival.

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Year:  2005        PMID: 15691265     DOI: 10.1111/j.1432-2277.2004.00041.x

Source DB:  PubMed          Journal:  Transpl Int        ISSN: 0934-0874            Impact factor:   3.782


  19 in total

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Review 2.  Clinical pharmacokinetics and pharmacodynamics of mycophenolate in solid organ transplant recipients.

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4.  Incidence and impact of adverse drug events contributing to hospital readmissions in kidney transplant recipients.

Authors:  Michelle A Arms; James Fleming; Deep B Sangani; Satish N Nadig; John W McGillicuddy; David J Taber
Journal:  Surgery       Date:  2017-11-22       Impact factor: 3.982

5.  The interactions of age, sex, body mass index, genetics, and steroid weight-based doses on tacrolimus dosing requirement after adult kidney transplantation.

Authors:  P Stratta; M Quaglia; T Cena; R Antoniotti; R Fenoglio; A Menegotto; D Ferrante; A Genazzani; S Terrazzino; C Magnani
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Review 6.  Maximum a posteriori Bayesian estimation of mycophenolic Acid area under the concentration-time curve: is this clinically useful for dosage prediction yet?

Authors:  Christine E Staatz; Susan E Tett
Journal:  Clin Pharmacokinet       Date:  2011-12-01       Impact factor: 6.447

Review 7.  The evolution of population pharmacokinetic models to describe the enterohepatic recycling of mycophenolic acid in solid organ transplantation and autoimmune disease.

Authors:  Catherine M T Sherwin; Tsuyoshi Fukuda; Hermine I Brunner; Jens Goebel; Alexander A Vinks
Journal:  Clin Pharmacokinet       Date:  2011-01       Impact factor: 6.447

8.  Evaluation of tacrolimus abbreviated area-under-the-curve monitoring in renal transplant patients who are potentially at risk for adverse events.

Authors:  Yuen Yi Hon; Christine E Chamberlain; David E Kleiner; Michael S Ring; Douglas A Hale; Allan D Kirk; Roslyn B Mannon
Journal:  Clin Transplant       Date:  2010 Jul-Aug       Impact factor: 2.863

9.  Pharmacokinetics of mycophenolic acid and estimation of exposure using multiple linear regression equations in Chinese renal allograft recipients.

Authors:  Pei-Jun Zhou; Da Xu; Zi-Cheng Yu; Xiang-Hui Wang; Kun Shao; Ju-Ping Zhao
Journal:  Clin Pharmacokinet       Date:  2007       Impact factor: 6.447

10.  Gender-dependent predictable pharmacokinetic method for tacrolimus exposure monitoring in kidney transplant patients.

Authors:  Radmila Velickovic-Radovanovic; Momir Mikov; Aleksandra Catic-Djordjevic; Nikola Stefanovic; Branka Mitic; Goran Paunovic; Tatjana Cvetkovic
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2014-03-05       Impact factor: 2.441

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