Skip to main content
Log in

Pharmacodynamic analysis of hematologic profiles

  • Published:
Journal of Pharmacokinetics and Biopharmaceutics Aims and scope Submit manuscript

Abstract

We discuss the analysis of the myelosuppressive effects of chemotherapy. Such analyses examine hematologic data that arise by monitoring patients after treatment with high doses of chemotherapy. We propose a flexible approach for modeling such information and, using data collected as part of a Phase I study of an anticancer agent, show some interesting aspects of the data that become available after fitting models this way.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. M. J. Ratain, R. L. Schilsky, B. A. Conley, and M. J. Egorin. Pharmacodynamics in cancer therapy.J. Clin. Oncol. 8:1739–1753 (1990).

    CAS  PubMed  Google Scholar 

  2. J. S. Penta, G. L. Rosner, and D. L. Trump. Choice of starting dose and escalation for Phase I studies of antitumor agents.Cancer Chemother. Pharmacol. 31:247–250 (1992).

    Article  CAS  PubMed  Google Scholar 

  3. R. Mick and M. J. Ratain. Modelling interpatient pharmacodynamic variability of etoposide.J. Natl. Cancer Inst. 83:1560–1564 (1991).

    Article  CAS  PubMed  Google Scholar 

  4. D. L. Trump, M. J. Egorin, A. Forrest, J. K. V. Willson, S. Remick, and K. D. Tutsch. Pharmacokinetic and pharmacodynamic analysis of fluorouracil during 72-hour continous infusion with and without dipyridamole.J. Clin. Oncol. 9:2027–2035 (1991).

    CAS  PubMed  Google Scholar 

  5. S. M. Lichtman, M. J. Ratain, D. A. Van Echo, G. Rosner, M. J. Egorin, D. R. Budman, N. J. Vogelzang, L. Norton, and R. L. Schilsky. Granulocyte-macrophage colony stimulating factor (GM-CSF) plus high-dose biweekly cyclophosphamide: A Cancer and Leukemia Group B phase I study.J. Natl. Cancer Inst. 85:1319–1326 (1993).

    Article  CAS  PubMed  Google Scholar 

  6. W. P. Peters, G. Rosner, M. Ross, J. Vredenburgh, B. Meisenberg, C. Gilbert, and J. Kurtzberg. Comparative effects of granulocyte-macrophage colony stimulating factor (GM-CSF) and granulocyte colony-stimulating factor (G-CSF) on priming peripheral blood progenitor cells for use with autologous bone marrow after high-dose chemotherapy.Blood 81:1709–1719 (1993).

    CAS  PubMed  Google Scholar 

  7. J. Crawford, H. Ozer, R. Stoller, D. Johnson, G. Lyman, I. Tabbara, M. Kris, J. Grous, V. Picozzi, G. Rausch, R. Smith, W. Gradishar, A. Yahanda, M. Vincent, M. Stewart, and J. Glaspy. Reduction by granulocyte colony-stimulating factor of fever and neutropenia induced by chemotherapy in patients with small-cell lung cancer.New Engl. J. Med. 325:164–170 (1991).

    Article  CAS  PubMed  Google Scholar 

  8. M. J. Egorin, D. A. Van Echo, S. J. Tipping, E. A. Olman, M. Y. Whitacre, B. W. Thompson, and J. Aisner. Pharmacokinetics and dosage reduction of cis-diammine(1,1-cyclobutanedicarboxylato)platinum in patients with impaired renal function.Cancer Res. 44:5432–5438 (1984).

    CAS  PubMed  Google Scholar 

  9. R. D. Cook and S. Weisberg.Residuals and Influence in Regression. Chapman and Hall, London, UK, 1982.

    Google Scholar 

  10. G. A. F. Seber and C. J. Wild.Nonlinear Regression, Wiley, New York, 1989.

    Book  Google Scholar 

  11. L. B. Sheiner and T. H. Grasela, Jr.. An introduction to mixed effect modeling: Concepts, definitions, and justification.J. Pharmacokin. Biopharm. 19 (Suppl):11s-24s (1991).

    Article  Google Scholar 

  12. M. J. Crowder and D. J. Hand.Analysis of Repeated Measures, Chapman and Hall, London, UK, 1990.

    Google Scholar 

  13. S. L. Beal and L. B. Sheiner. Estimating population kinetics.CRC Crit. Rev. Biomed. Eng. 8:195–222 (1982).

    CAS  Google Scholar 

  14. M. L. Lindstrom and D. M. Bates. Nonlinear mixed effects models for repeated measures data.Biometrics 46:673–687 (1990).

    Article  CAS  PubMed  Google Scholar 

  15. E. F. Vonesh and R. L. Carter. Mixed effects nonlinear regression for unbalanced repeated measures.Biometrics 48:1–18 (1992).

    Article  CAS  PubMed  Google Scholar 

  16. A. Mallet, F. Mentré, J-L. Steimer, and F. Lokiec. Nonparametric maximum likelihood estimation for population pharmacokinetics, with application to cyclosporine.J. Pharmacokin. Biopharm. 16:311–327 (1988).

    Article  CAS  Google Scholar 

  17. M. Davidian and A. R. Gallant. Smooth nonparametric maximum likelihood estimation for population pharmacokinetics, with application to quinidine.J. Pharmacokin. Biopharm. 20:529–556 (1992).

    Article  CAS  Google Scholar 

  18. G. E. P. Box and G. C. Tiao.Bayesian Inference in Statistical Analysis (Wiley classics library edition), Wiley, New York, 1992.

    Book  Google Scholar 

  19. B. D. Ripley.Stochastic Simulation, Wiley, New York, 1987, Section 4.7.

    Book  Google Scholar 

  20. A. E. Gelfand and A. F. M. Smith. Sampling-based approaches to calculating marginal densities.J. Am. Stat. Assoc. 85:398–409 (1990).

    Article  Google Scholar 

  21. A. F. M. Smith and G. O. Roberts. Bayesian computation via the Gibbs sampler and related Markov chain Monte Carlo methods.J. R. Stat. Soc. B 55:3–23 (1993).

    Google Scholar 

  22. L. Tierney. Markov chains for exploring posterior distributions (with discussion).Ann. Statist. 22:1701–1762 (1994).

    Article  Google Scholar 

  23. G. Casella and E. I. George. Explaining the Gibbs sampler.Am. Statist. 46:167–174 (1992).

    Google Scholar 

  24. W. K. Hastings. Monte Carlo sampling methods using Markov chains and their applications.Biometrika 57:97–109 (1970).

    Article  Google Scholar 

  25. A. Gelman and D. Rubin. Inference from iterative simulation using multiple sequences.Statist. Sci. 7:457–473 (1992).

    Article  Google Scholar 

  26. J. Geweke. Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments. In J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith (eds),Bayesian Statistics 4, Oxford University Press, Oxford, UK, 1992, pp. 169–194.

    Google Scholar 

  27. A. E. Gelfand, D. K. Dey, and H. Chang. Model determination using predictive distributions with implementations via sampling-based methods. In J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith (eds.),Bayesian Statistics 4, Oxford University Press, Oxford, UK, 1992, pp. 147–167.

    Google Scholar 

  28. P. McCullagh and J. A. Nelder.Generalized Linear Models, 2nd ed. Chapman and Hall, London, UK, 1989.

    Book  Google Scholar 

  29. S. L. Zeger and M. R. Karim. Generalized linear models with random effects; A Gibbs sampling approach.J. Am. Statist. Soc. 86:79–86 (1991).

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

Supported, in part, by grants from the American Cancer Society (ACS-IRG 158H) and the NCI through the Cancer and Leukemia Group B.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rosner, G.L., Müller, P. Pharmacodynamic analysis of hematologic profiles. Journal of Pharmacokinetics and Biopharmaceutics 22, 499–524 (1994). https://doi.org/10.1007/BF02353792

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02353792

Key Words

Navigation