Skip to main content
SpringerLink
Log in

Dose-Finding and Dose-Ranging Studies

  • Living reference work entry
  • First Online:
Principles and Practice of Clinical Trials

  • 228 Accesses

Abstract

There is a growing recognition of the importance of well-designed dose-finding studies in the overall development process. This chapter is an overview of designs for studies that are meant to identifying one or more doses of an agent to be tested in subsequent stages of the drug development process. The chapter also provides a summary of dose-finding designs that have been developed to meet the challenges of contemporary dose-finding trials, including the use of combinations of agents, more complex outcome measures, and heterogeneous groups of participants.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Similar content being viewed by others

References

  • Ananthakrishnan R, Green S, Chang M, Doros G, Massaro J, LaValleya M (2017) Systematic comparison of the statistical operating characteristics of various phase I oncology designs. Contemp Clin Trials Commun 5:34–48

    Article  Google Scholar 

  • Babb J, Rogatko A (2001) Patient specific dosing in a cancer phase I clinical trial. Stat Med 20:2079–2090

    Article  Google Scholar 

  • Babb J, Rogatko A, Zacks S (1998) Cancer phase I clinical trials: efficient dose escalation with overdose control. Stat Med 17:1103–1120

    Article  MATH  Google Scholar 

  • Cheung YK (2005) Coherence principles in dose-finding studies. Biometrika 92:203–215

    Article  MathSciNet  MATH  Google Scholar 

  • Cheung YK (2011) Dose finding by the continual reassessment method. Chapman and Hall/CRC Biostatistics Series, New York

    Book  Google Scholar 

  • Cheung YK, Chappell R (2010) Sequential designs for phase I clinical trials with late-onset toxicities. Biometrics 56:1177–1182

    Article  MathSciNet  MATH  Google Scholar 

  • Chu PL, Lin Y, Shih WJ (2009) Unifying CRM and EWOC designs for phase I cancer clinical trials. J Stat Plann Inference 139:1146–1163

    Article  MathSciNet  MATH  Google Scholar 

  • Clertant M, O’Quigley J (2017) Semiparametric dose finding methods. J R Stat Soc Ser B 79(5):1487–1508

    Article  MathSciNet  MATH  Google Scholar 

  • Clertant M, O’Quigley J (2019) Semiparametric dose finding methods: special cases. Appl Stat 68(2):271–288

    MathSciNet  MATH  Google Scholar 

  • Conaway M (2017a) A design for phase I trials in completely or partially ordered groups. Stat Med 36(15):2323–2332

    Article  MathSciNet  Google Scholar 

  • Conaway M (2017b) Isotonic designs for phase I trials in partially ordered groups. Clin Trials 14(5):491–498

    Article  Google Scholar 

  • Conaway M, Petroni G (2019a) The impact of early stage design on the drug development process. Clin Cancer Res 25(2):819–827

    Article  Google Scholar 

  • Conaway M, Petroni G (2019b) The role of early-phase design-response. Clin Cancer Res 25(10):3191

    Article  Google Scholar 

  • Conaway M, Dunbar S, Peddada S (2004) Designs for single- or multiple-agent phase I trials. Biometrics 60:661–669

    Article  MathSciNet  MATH  Google Scholar 

  • Durham S, Flournoy N (1994) Random walks for quantile estimation. In: Gupta S, Berger J (eds) Statistical decision theory and related topics V. Springer, New York, pp 467–476

    Chapter  Google Scholar 

  • Durham S, Flournoy N (1995) Up-and-down designs I: stationary treatment distributions. In: Flournoy N, Rosenberger W (eds) Adaptive designs. Institute of Mathematical Statistics, Hayward, pp 139–157

    Chapter  MATH  Google Scholar 

  • Durham S, Flournoy N, Rosenberger W (1997) A random walk rule for phase 1 clinical trials. Biometrics 53(2):745–760

    Article  MATH  Google Scholar 

  • Eussen S, de Groot L, Clarke R, Schneede J, Ueland P, Hoefnagels W, van Staveren W (2005) Oral cyanocobalamin supplementation in older people with vitamin B12 deficiency: a dose-finding trial. Arch Intern Med 165:1167–1172

    Article  Google Scholar 

  • Ezard N, Dunlop A, Clifford B, Bruno R, Carr A, Bissaker A, Lintzeris N (2016) Study protocol: a dose-escalating, phase-2 study of oral lisdexamfetamine in adults with methamphetamine dependence. BMC Psychiatry 16:428

    Article  Google Scholar 

  • Guo W, Wang S-J, Yang S, Lynna H, Ji Y (2017) A Bayesian interval dose-finding design addressing Ockham’s razor: mTPI-2. Contemp Clin Trials 58:23–33

    Article  Google Scholar 

  • Horton B, Wages N, Conaway M (2017) Performance of toxicity probability interval based designs in contrast to the continual reassessment method. Stat Med 36:291–300

    Article  MathSciNet  Google Scholar 

  • Horton BJ, Wages NA, Conaway MR (2019a) Shift models for dose-finding in partially ordered groups. Clin Trials 16(1):32–40

    Article  Google Scholar 

  • Horton BJ, O’Quigley J, Conaway M (2019b) Consequences of performing parallel dose finding trials in heterogeneous groups of patients. JNCI Cancer Spectrum. https://doi.org/10.1093/jncics/pkz013. Online ahead of print

  • Hwang J, Peddada S (1994) Confidence interval estimation subject to order restrictions. Ann Stat 22:67–93

    Article  MathSciNet  MATH  Google Scholar 

  • Iasonos A, Wilton AS, Riedel ER, Seshan VE, Spriggs DR (2008) A comprehensive comparison of the continual reassessment method to the standard 3+3 dose escalation scheme in phase I dose-finding studies. Clin Trials 5(5):465–477

    Article  Google Scholar 

  • Ivanova A, Flournoy N, Chung Y (2007) Cumulative cohort design for dose-finding. J Stat Plann Inference 137:2316–2327

    Article  MathSciNet  MATH  Google Scholar 

  • Ji Y, Li Y, Bekele B (2007) Dose-finding in phase I clinical trials based on toxicity probability intervals. Clin Trials 4:235–244

    Article  Google Scholar 

  • Kim K, Kim H, Sym S, Bae K, Hong Y, Chang H, Lee J, Kang Y, Lee J, Shin J, Kim T (2013) A UGT1A1*28 and *6 genotype-directed phase I dose-escalation trial of irinotecan with fixed-dose capecitabine in Korean patients with metastatic colorectal cancer. Cancer Chemother Pharmacol 71:1609–1617

    Article  Google Scholar 

  • Korn E, Simon R (1993) Using tolerable-dose diagrams in the design of phase I combination chemotherapy trials. J Clin Oncol 11:794–801

    Article  Google Scholar 

  • Kramar A, Lebecq A, Candalh E (1999) Continual reassessment methods in phase I trials of the combination of two agents in oncology. Stat Med 18:849–864

    Article  Google Scholar 

  • Le Tourneau C, Lee J, Siu L (2009) Dose escalation methods in phase I clinical trials. J Natl Cancer Inst 101:708–720

    Article  Google Scholar 

  • Lee S, Cheung YK (2009) Model calibration in the continual reassessment method. Clin Trials 6:227–238

    Article  Google Scholar 

  • Leung D, Wang Y-G (2001) Isotonic designs for phase I trials. Clin Trials 22:126–138

    Article  Google Scholar 

  • Lin R (2018) R codes for interval designs. https://github.com/ruitaolin/IntervalDesign

  • Lin Y, Shih W (2001) Statistical properties of traditional algorithm-based designs for phase I cancer clinical trials. Biostatistics 2(2):203–215

    Article  MATH  Google Scholar 

  • Lin R, Yin G (2017) Bayesian optimal interval design for dose finding in drug-combination trials. Stat Methods Med Res 26(5):2155–2167

    Article  MathSciNet  Google Scholar 

  • Liu S, Yuan Y (2015) Bayesian optimal interval designs for phase I clinical trials. J R Stat Soc Ser C Appl Stat 32:2505–2511

    MathSciNet  Google Scholar 

  • LoRusso P, Venkatakrishnan K, Ramanathan R, Sarantopoulos J, Mulkerin D, Shibata S, Hamilton A, Dowlati A, Mani S, Rudek M, Takimoto C, Neuwirth R, Esseltine D, Ivy P (2012) Pharmacokinetics and safety of Bortezomib in patients with advanced malignancies and varying degrees of liver dysfunction: phase I NCI Organ Dysfunction Working Group Study NCI-6432. Clin Cancer Res 18(10):1–10

    Article  Google Scholar 

  • Mauguen A, Le Deleya M, Zohar S (2011) Dose-finding approach for dose escalation with overdose control considering incomplete observations. Stat Med 30:1584–1594

    Article  MathSciNet  Google Scholar 

  • Normolle D, Lawrence T (2006) Designing dose-escalation trials with late-onset toxicities using the time-to-event continual reassessment method. J Clin Oncol 24:4426–4433

    Article  Google Scholar 

  • O’Quigley J (2006) Phase I and phase I/II dose finding algorithms using continual reassessment method. In: Crowley J, Ankherst D (eds) Handbook of statistics in clinical oncology, 2nd edn. Chapman and Hall/CRC Biostatistics Series, New York

    Google Scholar 

  • O’Quigley J, Iasonos A (2012) Dose-finding designs based on the continual reassessment method. In: Crowley J, Hoering (eds) Handbook of statistics in clinical oncology, 3rd edn. Chapman and Hall/CRC Biostatistics Series, New York

    Google Scholar 

  • O’Quigley J, Iasonos A (2014) Bridging solutions in dose-finding problems. J Biopharm Stat 6(2):185–197

    Article  Google Scholar 

  • O’Quigley J, Paoletti X (2003) Continual reassessment method for ordered groups. Biometrics 59:430–440

    Article  MathSciNet  MATH  Google Scholar 

  • O’Quigley J, Pepe M, Fisher L (1990) Continual reassessment method: a practical design for phase I clinical trials in cancer. Biometrics 46(1):33–48

    Article  MathSciNet  MATH  Google Scholar 

  • O’Quigley J, Shen L, Gamst A (1999) Two sample continual reassessment method. J Biopharm Stat 9:17–44

    Article  MATH  Google Scholar 

  • O’Quigley J, Paoletti X, Maccario J (2002) Nonparametric optimal design in dose finding studies. Biostatistics 3(1):51–56

    Article  MATH  Google Scholar 

  • Paoletti X, O’Quigley J, Maccario J (2004) Design efficiency in dose finding studies. Comput Stat Data Anal 45:197–214

    Article  MathSciNet  MATH  Google Scholar 

  • Partinen M, Hirvonen K, Jama L, Alakuijala A, Hublin C, Tamminen I, Koester J, Reess J (2006) Efficacy and safety of pramipexole in idiopathic restless legs syndrome: a polysomnographic dose-finding study – the PRELUDE study. Sleep Med 7:407–417

    Article  Google Scholar 

  • Piantadosi S (2017) Clinical trials: a methodologic perspective, 3rd edn. Wiley, Hoboken

    MATH  Google Scholar 

  • Polley M (2011) Practical modifications to the time-to-event continual reassessment method for phase I cancer trials with fast patient accrual and late-onset toxicities. Stat Med 30:2130–2143

    Article  MathSciNet  Google Scholar 

  • Ramanathan R, Egorin M, Takimoto C, Remick S, Doroshow J, LoRusso P, Mulkerin D, Grem J, Hamilton A, Murgo A, Potter D, Belani C, Hayes M, Peng B, Ivy P (2008) Phase I and pharmacokinetic study of Imatinib Mesylate in patients with advanced malignancies and varying degrees of liver dysfunction: a study by the National Cancer Institute Organ Dysfunction Working Group. J Clin Oncol 26:563–569

    Article  Google Scholar 

  • Raphael M, le Deley M, Vassal G, Paoletti X (2010) Operating characteristics of two independent sample design in phase I trials in paediatric oncology. Eur J Cancer 46:1392–1398

    Article  Google Scholar 

  • Reiner E, Paoletti X, O’Quigley J (1999) Operating characteristics of the standard phase I clinical trial design. Comput Stat Data Anal 30(3):303–315

    Article  MATH  Google Scholar 

  • Robertson T, Wright FT, Dykstra R (1988) Order restricted statistical inference. Wiley, New York

    MATH  Google Scholar 

  • Rogatko A, Schoeneck D, Jonas W, Tighiouart M, Khuri F, Porter A (2007) Translation of innovative designs into phase I trials. J Clin Oncol 25(31):4982–4986

    Article  Google Scholar 

  • Sauter A, Ullensvang K, Niemi G, Lorentzen H, Bendtsen T, Børglum J, Pripp A, Romundstad L (2015) The shamrock lumbar plexus block: a dose-finding study. Eur J Anaesthesiol 32:764–770

    Article  Google Scholar 

  • Schaller S, Fink H, Ulm K, Blobner M (2010) Sugammadex and neostigmine dose-finding study for reversal of shallow residual neuromuscular block. Anesthesiology 113:1054–1060

    Article  Google Scholar 

  • Senderowicz A (2010) Information needed to conduct first-in-human oncology trials in the United States: a view from a former FDA medical reviewer. Clin Cancer Res 16(6):1719–1725

    Article  Google Scholar 

  • Shen L, O’Quigley J (1996) Continual reassessment method: a likelihood approach. Biometrics 52:673–684

    Article  MATH  Google Scholar 

  • Shi Y, Yin G (2013) Escalation with overdose control for phase I drug combination trials. Stat Med 32:4400–4412

    Article  MathSciNet  Google Scholar 

  • Skolnik JM, Barrett JS, Jayaraman B, Patel D, Adamson PC (2008) Shortening the timeline of pediatric phase I trials: the rolling six design. J Clin Oncol 26(2):190–195

    Article  Google Scholar 

  • Storer B (1989) Design and analysis of phase I clinical trials. Biometrics 45(3):925–937

    Article  MathSciNet  MATH  Google Scholar 

  • Stylianou M, Flournoy N (2002) Dose finding using the biased coin up-and-down design and isotonic regression. Biometrics 58(1):171–177

    Article  MathSciNet  MATH  Google Scholar 

  • Thall P, Millikan R, Mueller P, Lee S-J (2003) Dose-finding with two agents in phase I oncology trials. Biometrics 59:487–496

    Article  MathSciNet  MATH  Google Scholar 

  • Tighiouart M, Rogatko (2014) A dose finding with escalation with overdose control (EWOC) in cancer clinical trials. Stat Sci 25(2):217–226

    MathSciNet  MATH  Google Scholar 

  • Tighiouart M, Cook-Wiens G, Rogatko A (2012) Incorporating a patient dichotomous characteristic in cancer phase I clinical trials using escalation with overdose control. J Probab Stat 10:Article ID: 567819

    Google Scholar 

  • Tighiouart M, Liu Y, Rogatko A (2014a) Escalation with overdose control using time to toxicity for cancer phase I clinical trials. PLoS One 9(3):e93070

    Article  Google Scholar 

  • Tighiouart M, Piantadosi S, Rogatko A (2014b) Dose finding with drug combinations in cancer phase I clinical trials using conditional escalation with overdose control. Stat Med 33(22):3815–3829

    Article  MathSciNet  Google Scholar 

  • Vidoni ED, Johnson DK, Morris JK, Van Sciver A, Greer CS, Billinger SA et al (2015) Dose-response of aerobic exercise on cognition: a community-based, pilot randomized controlled trial. PLoS One 10(7):e0131647

    Article  Google Scholar 

  • Wages NA, Conaway MR (2013) Specifications of a continual reassessment method design for phase I trials of combined drugs. Pharm Stat 12(4):217–224

    Article  Google Scholar 

  • Wages N, Conaway M (2018) Revisiting isotonic phase I design in the era of model-assisted dose-finding. Clin Trials 15(5):524–529

    Article  Google Scholar 

  • Wages N, Conaway M, O’Quigley J (2011a) Dose-finding design for multi-drug combinations. Clin Trials 8:380–389

    Article  Google Scholar 

  • Wages N, Conaway M, O’Quigley J (2011b) Continual reassessment method for partial ordering. Biometrics 67:1555–1563

    Article  MathSciNet  MATH  Google Scholar 

  • Wages N, Conaway M, O’Quigley J (2013) Performance of two-stage continual reassessment method relative to an optimal benchmark. Clin Trials 10:862–875

    Article  Google Scholar 

  • Wages NA, Iasonos A, O’Quigley J, Conaway MR (2019) Coherence principles in interval-based dose-finding. Submitted

    Google Scholar 

  • Wang K, Ivanova A (2005) Two-dimensional dose finding in discrete dose space. Biometrics 61:217–222

    Article  MathSciNet  MATH  Google Scholar 

  • Wheeler G, Sweeting M, Mander A (2016) AplusB: a web application for investigating A+B designs for phase I cancer clinical trials. PLOS. https://doi.org/10.1371/journal.pone.0159026. Published: July 12, 2016

  • Yan F, Mandrekar S, Ying Y (2017) Keyboard: a novel Bayesian toxicity probability interval design for phase I clinical trials. Clin Cancer Res 23(15):3994–4003

    Article  Google Scholar 

  • Yin G, Yuan Y (2009) Bayesian dose finding in oncology for drug combinations by copula regression. Appl Stat 58(2):211–224

    MathSciNet  Google Scholar 

  • Yuan Z, Chapell R (2004) Isotonic designs for phase I cancer clinical trials with multiple risk groups. Clin Trials 1(6):499–508

    Article  Google Scholar 

  • Zhao L, Lee J, Mody R, Braun T (2011) The superiority of the time-to-event continual reassessment method to the rolling six design in pediatric oncology phase I trials. Clin Trials 8(4):361–369

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Virginia Health System, Charlottesville, VA, USA

    Mark R. Conaway

  2. Translational Research and Applied Statistics, Public Health Sciences, University of Virginia Health System, Charlottesville, VA, USA

    Gina R. Petroni

Authors
  1. Mark R. Conaway
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gina R. Petroni
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mark R. Conaway .

Editor information

Editors and Affiliations

  1. Samuel Oschin Comprehensive Cancer Insti, WEST HOLLYWOOD, CA, USA

    Steven Piantadosi

  2. Bloomberg School of Public Health, Johns Hopkins Center for Clinical Trials Bloomberg School of Public Health, Baltimore, MD, USA

    Curtis L. Meinert

Section Editor information

  1. University of Iowa, Iowa, IA, USA

    Christopher S Coffey

  2. The Johns Hopkins Center for Clinical Trials and Evidence Synthesis, Johns Hopkins University, Baltimore, MD, USA

    Curtis L. Meinert

  3. Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Steven Piantadosi

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Conaway, M.R., Petroni, G.R. (2021). Dose-Finding and Dose-Ranging Studies. In: Piantadosi, S., Meinert, C.L. (eds) Principles and Practice of Clinical Trials. Springer, Cham. https://doi.org/10.1007/978-3-319-52677-5_77-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-52677-5_77-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52677-5

  • Online ISBN: 978-3-319-52677-5

  • eBook Packages: Springer Reference MathematicsReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Search

Navigation