Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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A Review of Dose Finding Methods and Theory

  • Cheung, Ying Kuen (Department of Biostatistics, Mailman School of Public Health, Columbia University)
  • Received : 2015.08.26
  • Accepted : 2015.08.31
  • Published : 2015.09.30
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Abstract

In this article, we review the statistical methods and theory for dose finding in early phase clinical trials, where the primary objective is to identify an acceptable dose for further clinical investigation. The dose finding literature is initially motivated by applications in phase I clinical trials, in which dose finding is often formulated as a percentile estimation problem. We will present some important phase I methods and give an update on new theoretical developments since a recent review by Cheung (2010), with an aim to cover a broader class of dose finding problems and to illustrate how the general dose finding theory may be applied to evaluate and improve a method. Specifically, we will illustrate theoretical techniques with some numerical results in the context of a phase I/II study that uses trinary toxicity/efficacy outcomes as basis of dose finding.

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References

  1. Anbar, D. (1984). Stochastic approximation methods and their use in bioassay and phase I clinical trials, Communications in Statistics - Theory and Methods, 13, 2451-2467. https://doi.org/10.1080/03610928408828835
  2. Azriel, D., Mandel, M. and Rinott, Y. (2011). The treatment versus experimentation dilemma in dose finding studies, Journal of Statistical Planning and Inference, 141, 2759-2768. https://doi.org/10.1016/j.jspi.2011.03.001
  3. Bekele, B. N. and Thall, P. F. (2004). Dose-finding based on multiple toxicities in a soft tissue sarcoma trial, Journal of the American Statistical Association, 99, 26-35. https://doi.org/10.1198/016214504000000043
  4. Braun, T. M. (2002). The bivariate continual reassessment method: Extending the CRM to phase I trials of two competing outcomes, Controlled Clinical Trials, 23, 240-256. https://doi.org/10.1016/S0197-2456(01)00205-7
  5. Cheung, Y. K. (2002). On the use of nonparametric curves in phase I trials with low toxicity tolerance, Biometrics, 58, 237-240. https://doi.org/10.1111/j.0006-341X.2002.00237.x
  6. Cheung, Y. K. (2005). Coherence principles in dose-finding studies, Biometrika, 92, 863-873. https://doi.org/10.1093/biomet/92.4.863
  7. Cheung, Y. K. (2007). Sequential implementation of stepwise procedures for identifying the maximum tolerated dose, Journal of the American Statistical Association, 102, 1448-1461. https://doi.org/10.1198/016214507000000699
  8. Cheung, Y. K. (2010). Stochastic approximation and modern model-based designs for dose-finding clinical trials, Statistical Science, 25, 191-201. https://doi.org/10.1214/10-STS334
  9. Cheung, Y. K. (2011). Dose Finding by the Continual Reassessment Method, CRC Press/Taylor & Francis Group, Boca Raton, FL.
  10. Cheung, Y. K. (2013). Sample size formulae for the Bayesian continual reassessment method, Clinical Trials, 10, 852-861. https://doi.org/10.1177/1740774513497294
  11. Cheung, Y. K. (2014). Simple benchmark for complex dose finding studies, Biometrics, 70, 389-397. https://doi.org/10.1111/biom.12158
  12. Cheung, Y. K. (2015). Dose Finding in Tandem to Identify the Maximum Response, Unpublished manuscript.
  13. Cheung, Y. K., Chakraborty, B. and Davidson, K.W. (2015). Sequential multiple assignment randomized trial (SMART) with adaptive randomization for quality improvement in depression treatment program, Biometrics, 71, 450-459. https://doi.org/10.1111/biom.12258
  14. Cheung, Y. K. and Chappell, R. (2000). Sequential designs for phase I clinical trials with late-onset toxicities, Biometrics, 56, 1177-1182. https://doi.org/10.1111/j.0006-341X.2000.01177.x
  15. Cheung, Y. K. and Chappell, R. (2002). A simple technique to evaluate model sensitivity in the continual reassessment method, Biometrics, 58, 671-674. https://doi.org/10.1111/j.0006-341X.2002.00671.x
  16. Cheung, Y. K. and Elkind, M. S. (2010). Stochastic approximation with virtual observations for dose-finding on discrete levels, Biometrika, 97, 109-121. https://doi.org/10.1093/biomet/asp065
  17. Durham, S. D., Flournoy, N. and Rosenberger, W. F. (1997). A random walk rule for phase I clinical trials, Biometrics, 53, 745-760. https://doi.org/10.2307/2533975
  18. Finney, D. J. (1978). Statistical Methods in Biological Assay, Griffin, London.
  19. Gasparini, M. and Eisele, J. (2000). A curve-free method for phase I clinical trials, Biometrics, 56, 609-615. https://doi.org/10.1111/j.0006-341X.2000.00609.x
  20. Haines, L. M., Perevozskaya, I. and Rosenberger, W. F. (2003). Bayesian optimal designs for phase I clinical trials, Biometrics, 59, 591-600. https://doi.org/10.1111/1541-0420.00069
  21. Houede, N., Thall, P. F., Nguyen, H., Paoletti, X. and Kramar, A. (2010). Utility-based optimization of combination therapy using ordinal toxicity and efficacy in phase I/II trials, Biometrics, 66, 532-540. https://doi.org/10.1111/j.1541-0420.2009.01302.x
  22. Jia, X., Lee, S. M. and Cheung, Y. K. (2014). Characterization of the likelihood continual reassessment method, Biometrika, 101, 599-612. https://doi.org/10.1093/biomet/asu012
  23. Lee, S. M., Cheng, B. and Cheung, Y. K. (2011). Continual reassessment method with multiple toxicity constraints, Biostatistics, 12, 386-398. https://doi.org/10.1093/biostatistics/kxq062
  24. Lee, S. M. and Cheung, Y. K. (2009). Model calibration in the continual reassessment method, Clinical Trials, 6, 227-238. https://doi.org/10.1177/1740774509105076
  25. Lee, S. M. and Cheung, Y. K. (2011). Calibration of prior variance in the Bayesian continual reassessment method, Statistics in Medicine, 30, 2081-2089. https://doi.org/10.1002/sim.4139
  26. Lee, S. M., Hershman, D. L., Martin, P., Leonard, J. P. and Cheung, Y. K. (2012). Toxicity burden score: A novel approach to summarize multiple toxic effects, Annals of Oncology, 23, 537-541. https://doi.org/10.1093/annonc/mdr146
  27. Leung, D. H. Y. andWang, Y. G. (2001). Isotonic designs for phase I trials, Controlled Clinical Trials, 22, 126-138. https://doi.org/10.1016/S0197-2456(00)00132-X
  28. Lin, Y. and Shih, W. J. (2001). Statistical properties of the traditional algorithm-based designs for phase I cancer clinical trials, Biostatistics, 2, 203-215. https://doi.org/10.1093/biostatistics/2.2.203
  29. O'Quigley, J. and Chevret, S. (1991). Methods for dose finding studies in cancer clinical trials: A review and results of a Monte Carlo study, Statistics in Medicine, 10, 1647-1664. https://doi.org/10.1002/sim.4780101104
  30. O'Quigley, J., Hughes, M. D. and Fenton, T. (2001). Dose-finding designs for HIV studies, Biometrics, 57, 1018-1029. https://doi.org/10.1111/j.0006-341X.2001.01018.x
  31. O'Quigley, J., Paoletti, X. and Maccario, J. (2002). Non-parametric optimal design in dose finding studies, Biostatistics, 3, 51-56. https://doi.org/10.1093/biostatistics/3.1.51
  32. O'Quigley, J., Pepe, M. and Fisher, L. (1990). Continual reassessment method: A practical design for phase 1 clinical trials in cancer, Biometrics, 46, 33-48. https://doi.org/10.2307/2531628
  33. O'Quigley, J. and Shen, L. Z. (1996). Continual reassessment method: A likelihood approach, Biometrics, 52, 673-684. https://doi.org/10.2307/2532905
  34. Polley, M. Y. C. (2011). Practical modifications to the time-to-event continual reassessment method for phase I cancer trials with fast patient accrual and late-onset toxicities, Statistics in Medicine, 30, 2130-2143. https://doi.org/10.1002/sim.4255
  35. Robbins, H. and Monro, S. (1951). A stochastic approximation method, Annals of Mathematical Statistics, 22, 400-407. https://doi.org/10.1214/aoms/1177729586
  36. Shen, L. Z. and O'Quigley, J. (1996). Consistency of the continual reassessment method under model misspecification, Biometrika, 83, 395-405. https://doi.org/10.1093/biomet/83.2.395
  37. Storer, B. E. (1989). Design and analysis of phase I clinical trials, Biometrics, 45, 925-937. https://doi.org/10.2307/2531693
  38. Storer, B. E. and DeMets, D. (1987). Current phase I/II designs: Are they adequate?, Journal of Clinical Research and Drug Development, 1, 121-130.
  39. Thall, P. F. and Cook, J. D. (2004). Dose-finding based on efficacy-toxicity trade-offs, Biometrics, 60, 684-693. https://doi.org/10.1111/j.0006-341X.2004.00218.x
  40. Wu, C. J. (1985). Efficient sequential designs with binary data, Journal of the American Statistical Association, 80, 974-984. https://doi.org/10.1080/01621459.1985.10478213
  41. Yuan, Z., Chappell, R. and Bailey, H. (2007). The continual reassessment method for multiple toxicity grades: A Bayesian quasi?likelihood approach, Biometrics, 63, 173-179. https://doi.org/10.1111/j.1541-0420.2006.00666.x
  42. Zacks, S., Rogatko, A. and Babb,- J. (1998). Optimal Bayesian-feasible dose escalation for cancer phase I trials, Statistics & Probability Letters, 38, 215-220. https://doi.org/10.1016/S0167-7152(98)00016-9