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Monte Carlo simulations of the clinical benefits from therapeutic drug monitoring of sunitinib in patients with gastrointestinal stromal tumours

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Abstract

Purpose

Therapeutic drug monitoring (TDM) is being considered as a tool to individualise sunitinib treatment of gastrointestinal stromal tumours (GIST). Here, we used computer simulations to assess the expected impact of sunitinib TDM on the clinical outcome of patients with GIST.

Methods

Monte Carlo simulations were performed in R, based on previously published pharmacokinetic–pharmacodynamic models. Clinical trials with dose-limiting toxicity and patient dropout were simulated to establish the study size required to obtain sufficient statistical power for comparison of TDM-guided and fixed dosing.

Results

The simulations revealed that TDM might increase time to tumour progression by about 1–2 months (15–31 %) in eligible patients. However, the number of subjects required for a sufficient statistical power to quantify clinical benefit of TDM guided is likely to be prohibitively high (>1000).

Conclusion

Although data from randomised clinical trials on the clinical impact of sunitinib TDM are lacking, our findings support implementation of sunitinib TDM in clinical practice. For rare cancers with well-defined exposure–response relationships, modelling and simulation might allow the optimisation of dosing strategies when clinical trials cannot be performed due to low number of patients.

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References

  1. European Medicines Agency (2015) Sutent: EPAR—product information. http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Product_Information/human/000687/WC500057737.pdf. Accessed 26 Oct 2015

  2. Yu H, Steeghs N, Nijenhuis CM, Schellens JH, Beijnen JH, Huitema AD (2014) Practical guidelines for therapeutic drug monitoring of anticancer tyrosine kinase inhibitors: focus on the pharmacokinetic targets. Clin Pharmacokinet 53(4):305–325. doi:10.1007/s40262-014-0137-2

    Article  CAS  PubMed  Google Scholar 

  3. Lankheet NA, Knapen LM, Schellens JH, Beijnen JH, Steeghs N, Huitema AD (2014) Plasma concentrations of tyrosine kinase inhibitors imatinib, erlotinib, and sunitinib in routine clinical outpatient cancer care. Ther Drug Monit 36(3):326–334. doi:10.1097/FTD.0000000000000004

    Article  CAS  PubMed  Google Scholar 

  4. Terada T, Noda S, Inui K (2015) Management of dose variability and side effects for individualized cancer pharmacotherapy with tyrosine kinase inhibitors. Pharmacol Ther 152:125–134. doi:10.1016/j.pharmthera.2015.05.009

    Article  CAS  PubMed  Google Scholar 

  5. Escudier B, Roigas J, Gillessen S, Harmenberg U, Srinivas S, Mulder SF, Fountzilas G, Peschel C, Flodgren P, Maneval EC, Chen I, Vogelzang NJ (2009) Phase II study of sunitinib administered in a continuous once-daily dosing regimen in patients with cytokine-refractory metastatic renal cell carcinoma. J Clin Oncol 27(25):4068–4075. doi:10.1200/JCO.2008.20.5476

    Article  CAS  PubMed  Google Scholar 

  6. Houk BE, Bello CL, Poland B, Rosen LS, Demetri GD, Motzer RJ (2010) Relationship between exposure to sunitinib and efficacy and tolerability endpoints in patients with cancer: results of a pharmacokinetic/pharmacodynamic meta-analysis. Cancer Chemother Pharmacol 66(2):357–371. doi:10.1007/s00280-009-1170-y

    Article  CAS  PubMed  Google Scholar 

  7. Lankheet NA, Kloth JS, Gadellaa-van Hooijdonk CG, Cirkel GA, Mathijssen RH, Lolkema MP, Schellens JH, Voest EE, Sleijfer S, de Jonge MJ, Haanen JB, Beijnen JH, Huitema AD, Steeghs N (2014) Pharmacokinetically guided sunitinib dosing: a feasibility study in patients with advanced solid tumours. Br J Cancer 110(10):2441–2449. doi:10.1038/bjc.2014.194

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Houk BE, Bello CL, Kang D, Amantea M (2009) A population pharmacokinetic meta-analysis of sunitinib malate (SU11248) and its primary metabolite (SU12662) in healthy volunteers and oncology patients. Clin Cancer Res 15(7):2497–2506. doi:10.1158/1078-0432.CCR-08-1893

    Article  CAS  PubMed  Google Scholar 

  9. Yu H, Steeghs N, Kloth JS, de Wit D, van Hasselt JG, van Erp NP, Beijnen JH, Schellens JH, Mathijssen RH, Huitema AD (2015) Integrated semi-physiological pharmacokinetic model for both sunitinib and its active metabolite SU12662. Br J Clin Pharmacol 79(5):809–819. doi:10.1111/bcp.12550

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Food and Drug Administration (1999) Guidance for industry population pharmacokinetics. http://www.fda.gov/downloads/Drugs/…/Guidances/UCM072137.pdf. Accessed 26 Oct 2015

  11. Food and Drug Administration (2003) Guidance for industry: exposure–response relationships-study design, data analysis, and regulatory applications. http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm072109.pdf. Accessed 22 Oct 2015

  12. Holford N, Ma SC, Ploeger BA (2010) Clinical trial simulation: a review. Clin Pharmacol Ther 88(2):166–182. doi:10.1038/clpt.2010.114

    Article  CAS  PubMed  Google Scholar 

  13. Kowalski KG, Hutmacher MM (2001) Design evaluation for a population pharmacokinetic study using clinical trial simulations: a case study. Stat Med 20(1):75–91

    Article  CAS  PubMed  Google Scholar 

  14. Bernstein M (2006) Ethical guideposts to clinical trials in oncology. Curr Oncol 13(2):55–60

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Suresh K, Chandrashekara S (2012) Sample size estimation and power analysis for clinical research studies. J Hum Reprod Sci 5(1):7–13. doi:10.4103/0974-1208.97779

    Article  PubMed  PubMed Central  Google Scholar 

  16. Halpern SD, Karlawish JH, Berlin JA (2002) The continuing unethical conduct of underpowered clinical trials. JAMA 288(3):358–362

    Article  PubMed  Google Scholar 

  17. Rinne H (2008) Definition and properties of the WEIBULL distribution. The Weibull distribution: a handbook. CRC Press, Boca Raton, pp 27–97

    Chapter  Google Scholar 

  18. Bonate PL (2011) Principles of simulation. In: Pharmacokinetic–pharmacodynamic modeling and simulation, 2nd edn. Springer, New York, pp 489–581. doi:10.1007/978-1-4419-9485-1

  19. Demetri GD, van Oosterom AT, Garrett CR, Blackstein ME, Shah MH, Verweij J, McArthur G, Judson IR, Heinrich MC, Morgan JA, Desai J, Fletcher CD, George S, Bello CL, Huang X, Baum CM, Casali PG (2006) Efficacy and safety of sunitinib in patients with advanced gastrointestinal stromal tumour after failure of imatinib: a randomised controlled trial. Lancet 368(9544):1329–1338. doi:10.1016/S0140-6736(06)69446-4

    Article  CAS  PubMed  Google Scholar 

  20. Reichardt P, Kang YK, Rutkowski P, Schuette J, Rosen LS, Seddon B, Yalcin S, Gelderblom H, Williams CC, Fumagalli E, Biasco G, Hurwitz HI, Kaiser PE, Fly K, Matczak E, Chen L, Lechuga MJ, Demetri GD (2015) Clinical outcomes of patients with advanced gastrointestinal stromal tumors: safety and efficacy in a worldwide treatment-use trial of sunitinib. Cancer 121(9):1405–1413. doi:10.1002/cncr.29220

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Li J, Gao J, Hong J, Shen L (2012) Efficacy and safety of sunitinib in Chinese patients with imatinib-resistant or -intolerant gastrointestinal stromal tumors. Future Oncol 8(5):617–624. doi:10.2217/fon.12.29

    Article  CAS  PubMed  Google Scholar 

  22. George S, Blay JY, Casali PG, Le Cesne A, Stephenson P, Deprimo SE, Harmon CS, Law CN, Morgan JA, Ray-Coquard I, Tassell V, Cohen DP, Demetri GD (2009) Clinical evaluation of continuous daily dosing of sunitinib malate in patients with advanced gastrointestinal stromal tumour after imatinib failure. Eur J Cancer 45(11):1959–1968. doi:10.1016/j.ejca.2009.02.011

    Article  CAS  PubMed  Google Scholar 

  23. Åsberg A, Bjerre A, Neely M (2014) New algorithm for valganciclovir dosing in pediatric solid organ transplant recipients. Pediatr Transplant 18(1):103–111. doi:10.1111/petr.12179

    Article  PubMed  Google Scholar 

  24. del Mar Fernández de Gatta M, Martin-Suarez A, Lanao JM (2013) Approaches for dosage individualisation in critically ill patients. Expert Opin Drug Metab Toxicol 9(11):1481–1493. doi:10.1517/17425255.2013.822486

    Article  PubMed  Google Scholar 

  25. van Hest R, Mathot R, Vulto A, Weimar W, van Gelder T (2005) Predicting the usefulness of therapeutic drug monitoring of mycophenolic acid: a computer simulation. Ther Drug Monit 27(2):163–167

    Article  PubMed  Google Scholar 

  26. Booth BP, Rahman A, Dagher R, Griebel D, Lennon S, Fuller D, Sahajwalla C, Mehta M, Gobburu JV (2007) Population pharmacokinetic-based dosing of intravenous busulfan in pediatric patients. J Clin Pharmacol 47(1):101–111. doi:10.1177/0091270006295789

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Discipline of Clinical Pharmacology, School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia

    Sebastiaan C. Goulooze, Peter Galettis & Jennifer H. Martin

  2. Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden, The Netherlands

    Sebastiaan C. Goulooze

  3. Faculty of Pharmacy, University of Sydney, Sydney, NSW, Australia

    Alan V. Boddy

  4. Calvary Mater Hospital, Waratah, NSW, Australia

    Jennifer H. Martin

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  1. Sebastiaan C. Goulooze
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  2. Peter Galettis
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Correspondence to Jennifer H. Martin.

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Goulooze, S.C., Galettis, P., Boddy, A.V. et al. Monte Carlo simulations of the clinical benefits from therapeutic drug monitoring of sunitinib in patients with gastrointestinal stromal tumours. Cancer Chemother Pharmacol 78, 209–216 (2016). https://doi.org/10.1007/s00280-016-3071-1

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  • DOI: https://doi.org/10.1007/s00280-016-3071-1

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