Literature DB >> 27085335

How 'Optimal' are Optimal Sampling Times for Tyrosine Kinase Inhibitors in Cancer? Practical Considerations.

Michael B Ward1,2, Stephanie E Reuter1,2,3, Jennifer H Martin4.   

Abstract

Tyrosine kinase inhibitors have been marketed as a fixed dose, 'one size fits all' treatment strategy. Physicians have also been interested in this method of dosing, knowing the complex planning of other current cancer therapies administered on a mg/m(2) or mg/kg basis and subsequent occurrence of dosing error or concern for underdosing. The 'simple and safe' strategy of a single dose of tyrosine kinase inhibitor for cancer has thus been widely adopted. However, the benefits purported to exist in the clinical trials do not appear to be borne out in clinical practice, particularly in solid tumours. In order to investigate whether pharmacokinetic variability is a contributor to the variable outcomes, pharmacokinetic targets to enable individualisation of tyrosine kinase inhibitor administration are now emerging. Evidence suggests there is not a clear relationship of a single dose to maximum plasma concentration (C max), steady-state trough concentration (C trough) or area under the curve (AUC). Furthermore, a significant number of questions remain related to the specific timing and frequency of sample collection required to achieve optimal outcomes. This article reviews the wide variability in the literature on this topic, specifically the different pharmacokinetic targets of the same drug for different cancers, for different states of cancer, and changing pharmacokinetic parameters over a treatment interval in cancer. It appears the optimal sampling times to enable appropriate dose recommendations across patients and diseases may vary, and are not always trough concentrations at steady state. Importantly, the need to be pragmatic in a clinical setting is paramount. Lastly, international collaborations to increase sample size are highly recommended to ensure enough patients are sampled to be sure of a clinical benefit from this concentration-directed methodology.

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Year:  2016        PMID: 27085335     DOI: 10.1007/s40262-016-0394-3

Source DB:  PubMed          Journal:  Clin Pharmacokinet        ISSN: 0312-5963            Impact factor:   6.447


  32 in total

1.  Phase II trial of erlotinib in patients with advanced non‑small‑cell lung cancer harboring epidermal growth factor receptor mutations: additive analysis of pharmacokinetics.

Authors:  Kohei Motoshima; Yoichi Nakamura; Kazumi Sano; Yoji Ikegami; Takaya Ikeda; Kosuke Mizoguchi; Shinnosuke Takemoto; Minoru Fukuda; Seiji Nagashima; Tetsuya Iida; Kazuhiro Tsukamoto; Shigeru Kohno
Journal:  Cancer Chemother Pharmacol       Date:  2013-12       Impact factor: 3.333

2.  Therapeutic drug monitoring of imatinib: Bayesian and alternative methods to predict trough levels.

Authors:  Verena Gotta; Nicolas Widmer; Michael Montemurro; Serge Leyvraz; Amina Haouala; Laurent A Decosterd; Chantal Csajka; Thierry Buclin
Journal:  Clin Pharmacokinet       Date:  2012-03-01       Impact factor: 6.447

3.  Trough plasma concentration of imatinib reflects BCR-ABL kinase inhibitory activity and clinical response in chronic-phase chronic myeloid leukemia: a report from the BINGO study.

Authors:  Yuichi Ishikawa; Hitoshi Kiyoi; Keisuke Watanabe; Koichi Miyamura; Yasuyuki Nakano; Kunio Kitamura; Akio Kohno; Isamu Sugiura; Toshiya Yokozawa; Akitoshi Hanamura; Kazuhito Yamamoto; Hiroatsu Iida; Nobuhiko Emi; Ritsuro Suzuki; Kazunori Ohnishi; Tomoki Naoe
Journal:  Cancer Sci       Date:  2010-07-01       Impact factor: 6.716

4.  Variability of sorafenib toxicity and exposure over time: a pharmacokinetic/pharmacodynamic analysis.

Authors:  Pascaline Boudou-Rouquette; Stanislas Ropert; Olivier Mir; Romain Coriat; Bertrand Billemont; Michel Tod; Laure Cabanes; Nathalie Franck; Benoit Blanchet; François Goldwasser
Journal:  Oncologist       Date:  2012-07-02

Review 5.  Relationship between exposure to sunitinib and efficacy and tolerability endpoints in patients with cancer: results of a pharmacokinetic/pharmacodynamic meta-analysis.

Authors:  Brett E Houk; Carlo L Bello; Bill Poland; Lee S Rosen; George D Demetri; Robert J Motzer
Journal:  Cancer Chemother Pharmacol       Date:  2009-12-05       Impact factor: 3.333

6.  Imatinib plasma levels: correlation with clinical benefit in GIST patients.

Authors:  N Widmer; L A Decosterd; C Csajka; M Montemurro; A Haouala; S Leyvraz; T Buclin
Journal:  Br J Cancer       Date:  2010-02-23       Impact factor: 7.640

7.  Imatinib plasma levels are correlated with clinical benefit in patients with unresectable/metastatic gastrointestinal stromal tumors.

Authors:  George D Demetri; Yanfeng Wang; Elisabeth Wehrle; Amy Racine; Zariana Nikolova; Charles D Blanke; Heikki Joensuu; Margaret von Mehren
Journal:  J Clin Oncol       Date:  2009-05-18       Impact factor: 44.544

8.  Nilotinib population pharmacokinetics and exposure-response analysis in patients with imatinib-resistant or -intolerant chronic myeloid leukemia.

Authors:  Francis J Giles; Ophelia Q P Yin; William M Sallas; Philipp D le Coutre; Richard C Woodman; Oliver G Ottmann; Michele Baccarani; Hagop M Kantarjian
Journal:  Eur J Clin Pharmacol       Date:  2012-10-05       Impact factor: 2.953

9.  Sorafenib in advanced melanoma: a critical role for pharmacokinetics?

Authors:  N Pécuchet; C Lebbe; O Mir; B Billemont; B Blanchet; N Franck; M Viguier; R Coriat; M Tod; M-F Avril; F Goldwasser
Journal:  Br J Cancer       Date:  2012-07-05       Impact factor: 7.640

10.  Pharmacokinetically guided sunitinib dosing: a feasibility study in patients with advanced solid tumours.

Authors:  N A G Lankheet; J S L Kloth; C G M Gadellaa-van Hooijdonk; G A Cirkel; R H J Mathijssen; M P J K Lolkema; J H M Schellens; E E Voest; S Sleijfer; M J A de Jonge; J B A G Haanen; J H Beijnen; A D R Huitema; N Steeghs
Journal:  Br J Cancer       Date:  2014-04-15       Impact factor: 7.640

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