Skip to main content Accessibility help
×
Hostname: page-component-7479d7b7d-k7p5g Total loading time: 0 Render date: 2024-07-14T02:00:00.548Z Has data issue: false hasContentIssue false

Part I - Introduction and History of Clinical Trial Research

Published online by Cambridge University Press:  20 March 2023

Jay J. H. Park
Affiliation:
McMaster University, Ontario
Edward J. Mills
Affiliation:
McMaster University, Ontario
J. Kyle Wathen
Affiliation:
Cytel, Cambridge, Massachusetts
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2023

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

References

Friedman, LM, Furberg, C, DeMets, DL, Reboussin, D, Granger, CB. Fundamentals of Clinical Trials: Springer; 2015.Google Scholar
Yuan, J, Pang, H, Tong, T, et al. Seamless phase IIa/IIb and enhanced dose-finding adaptive design. J Biopharm Stat. 2016;26(5):912–23.Google Scholar
Malay, S, Chung, KC. The choice of controls for providing validity and evidence in clinical research. Plast Reconstr Surg. 2012;130(4):959–65.Google Scholar
Viele, K, Berry, S, Neuenschwander, B, et al. Use of historical control data for assessing treatment effects in clinical trials. Pharm Stat. 2014;13(1):4154.Google Scholar
Lachin, JM. Statistical properties of randomization in clinical trials. Control Clin Trials. 1988;9(4):289311.CrossRefGoogle ScholarPubMed
Lachin, JM, Matts, JP, Wei, LJ. Randomization in clinical trials: conclusions and recommendations. Control Clin Trials. 1988;9(4):365–74.Google Scholar
Cartwright, N. What are randomised controlled trials good for? Philos Stud. 2010;147(1):59.Google Scholar
Senn, S. Seven myths of randomisation in clinical trials. Stat Med. 2013;32(9):1439–50.CrossRefGoogle ScholarPubMed
Deaton, A, Cartwright, N. Understanding and misunderstanding randomized controlled trials. Soc Sci Med. 2018;210:221.Google Scholar
Roberts, C, Torgerson, DJ. Understanding controlled trials: baseline imbalance in randomised controlled trials. BMJ. 1999;319(7203):185.CrossRefGoogle ScholarPubMed
Broglio, K. Randomization in clinical trials: permuted blocks and stratification. JAMA. 2018;319(21):2223–4.CrossRefGoogle ScholarPubMed
McPherson, GC, Campbell, MK, Elbourne, DR. Use of randomisation in clinical trials: a survey of UK practice. Trials. 2012;13(1):17.Google Scholar
Matts, JP, Lachin, JM. Properties of permuted-block randomization in clinical trials. Control Clin Trials. 1988;9(4):327–44.Google Scholar
Kang, M, Ragan, BG, Park, JH. Issues in outcomes research: an overview of randomization techniques for clinical trials. J Athl Train. 2008;43(2):215–21.Google Scholar
Therneau, TM. How many stratification factors are ‘too many’ to use in a randomization plan? Control Clin trials. 1993;14(2):98108.Google Scholar
Kahan, BC, Morris, TP. Improper analysis of trials randomised using stratified blocks or minimisation. Stat Med. 2012;31(4):328340.Google Scholar
Freedman, B. Equipoise and the ethics of clinical research. N Engl J Med. 1987;317(3):141–5.Google Scholar
Cook, C, Sheets, C. Clinical equipoise and personal equipoise: two necessary ingredients for reducing bias in manual therapy trials. J Man Manip Ther. 2011;19(1):55–7.Google Scholar
Jepson, M, Elliott, D, Conefrey, C, et al. An observational study showed that explaining randomization using gambling-related metaphors and computer-agency descriptions impeded randomized clinical trial recruitment. J Clin Epidemiol. 2018;99:7583.CrossRefGoogle ScholarPubMed
Angus, DC. Optimizing the trade-off between learning and doing in a pandemic. JAMA. 2020;323(19):1895–6.Google Scholar
London, AJ. Equipoise in research: integrating ethics and science in human research. JAMA. 2017;317(5):525–6.Google Scholar
Parmar, MK, Carpenter, J, Sydes, MR. More multiarm randomised trials of superiority are needed. Lancet. 2014;384(9940):283–4.Google Scholar
Box, GE, Hunter, J, Hunter, W. Statistics for Experimenters. Design, Innovation and Discovery, 2nd ed. John Wiley; 2005.Google Scholar
Montgomery, AA, Peters, TJ, Little, P. Design, analysis and presentation of factorial randomised controlled trials. BMC Med Res Methodol. 2003;3:26.Google Scholar
Ondra, T, Dmitrienko, A, Friede, T, et al. Methods for identification and confirmation of targeted subgroups in clinical trials: a systematic review. J Biopharm Stat. 2016;26(1):99119.Google Scholar
Thorlund, K, Haggstrom, J, Park, JJ, Mills, EJ. Key design considerations for adaptive clinical trials: a primer for clinicians. BMJ. 2018;360:k698.Google Scholar
Park, JJ, Thorlund, K, Mills, EJ. Critical concepts in adaptive clinical trials. Clin Epidemiol. 2018;10:343–51.Google Scholar
Dimairo, M, Pallmann, P, Wason, J et al. The Adaptive designs CONSORT Extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design. BMJ. 2020;369:m115.Google Scholar
Dimairo, M, Pallmann, P, Wason, J, et al. The Adaptive designs CONSORT extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design. Trials. 2020;21(1):528.Google Scholar
Adaptive Platform Trials Coalition. Adaptive platform trials: definition, design, conduct and reporting considerations. Nat Rev Drug Discov 2019;18(10):797807.Google Scholar
Woodcock, J, LaVange, LM. Master protocols to study multiple therapies, multiple diseases, or both. N Engl J Med. 2017;377(1):6270.Google Scholar
Chan, AW, Tetzlaff, JM, Gotzsche, PC, et al. SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials. BMJ. 2013;346:e7586.Google Scholar
International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. Addendum on Estimands and Sensitivity Analysis in Clinical Trials to the Guideline on Statistical Principles for Clinical Trials E9(R1); 2019. https://database.ich.org/sites/default/files/E9-R1_Step4_Guideline_2019_1203.pdfGoogle Scholar
Bell, J, Hamilton, A, Sailer, O, Voss, F. The detailed clinical objectives approach to designing clinical trials and choosing estimands. Pharm Stat. 2021;20(6):1112–24.Google Scholar
Ratitch, B, Goel, N, Mallinckrodt, C, et al. Defining efficacy estimands in clinical trials: examples illustrating ICH E9(R1) guidelines. Ther Innov Regul Sci. 2020;54(2):370–84.Google Scholar
Smith, VA, Coffman, CJ, Hudgens, MG. Interpreting the results of intention-to-treat, per-protocol, and as-treated analyses of clinical trials. JAMA. 2021;326(5):433–4.Google Scholar
Sussman, JB, Hayward, RA. An IV for the RCT: using instrumental variables to adjust for treatment contamination in randomised controlled trials. BMJ (Clinical Res Ed). 2010;340:c2073.Google Scholar
Parra, CO, Daniel, RM, Bartlett, JW. Hypothetical estimands in clinical trials: a unification of causal inference and missing data methods. arXiv preprint arXiv:210704392. 2021.Google Scholar
Bornkamp, B, Rufibach, K, Lin, J, et al. Principal stratum strategy: potential role in drug development. Pharm Stat. 2021;20(4):737–51.Google Scholar
Burton, A, Altman, DG, Royston, P, Holder, RL. The design of simulation studies in medical statistics. Stat Med. 2006;25(24):4279–92.Google Scholar
Holford, N, Ma, SC, Ploeger, BA. Clinical trial simulation: a review. Clin Pharm Therap. 2010;88(2):166–82.Google Scholar
U.S. Food and Drug Administration. Adaptive Designs for Medical Device Clinical Studies Guidance for Industry and Food and Drug Administration Staff. United States Department of Health and Human Services; 2016.Google Scholar
Hummel, J, Wang, S, Kirkpatrick, J. Using simulation to optimize adaptive trial designs: applications in learning and confirmatory phase trials. Clin Investig. 2015;5(4):401–13.Google Scholar
Bland, JM, Altman, DG. Bayesians and frequentists. BMJ. 1998;317(7166):1151–60.Google Scholar
Berry, DA. Bayesian clinical trials. Nat Rev Drug Discov. 2006;5(1):2736.Google Scholar
Wasserstein, RL, Lazar, NA. The ASA Statement on p-Values: Context, Process, and Purpose. Taylor & Francis; 2016. pp. 129–33.Google Scholar
Greenland, S, Senn, SJ, Rothman, KJ, et al. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 2016;31(4):337–50.CrossRefGoogle Scholar
Gill, CJ, Sabin, L, Schmid, CH. Why clinicians are natural Bayesians. BMJ. 2005;330(7499):1080–3.Google Scholar

References

Bothwell, LE, Podolsky, SH. The emergence of the randomized, controlled trial. N Engl J Med. 2016;375(6):501–4.Google Scholar
Jones, DS, Podolsky, SH. The history and fate of the gold standard. Lancet. 2015;385(9977):1502–3.Google Scholar
Hill, AB. Suspended judgment. Memories of the British Streptomycin Trial in Tuberculosis. The first randomized clinical trial. Control Clin Trials. 1990;11(2):77–9.Google Scholar
Hill, AB. Principles of Medical Statistics. 1st ed. Lancet. 1937.Google Scholar
Hill, AB. I. – The aim of the statistical method. Lancet. 1937;229(5914):41–3.Google Scholar
Crofton, J. The MRC randomized trial of streptomycin and its legacy: a view from the clinical front line. J R Soc Med. 2006;99(10):531–4.Google Scholar
Schatz, A, Waksman, SA. Effect of streptomycin and other antibiotic substances upon Mycobacterium tuberculosis and related organisms. Proc Soc Exp Biol Med. 1944;57(2):244–8.Google Scholar
Bartlett, RH, Roloff, DW, Cornell, RG, et al. Extracorporeal circulation in neonatal respiratory failure: a prospective randomized study. Pediatrics. 1985;76(4):479–87.Google Scholar
Angus, DC. Optimizing the trade-off between learning and doing in a pandemic. JAMA. 2020;323(19):1895–6.Google Scholar
Zelen, M. Play the winner rule and the controlled clinical trial. J Am Stat Assoc. 1969;64(325):131–46.Google Scholar
Wei, L, Durham, S. The randomized play-the-winner rule in medical trials. J Am Stat Assoc. 1978;73(364):840–3.Google Scholar
O’Rourke, PP, Crone, RK, Vacanti, JP, et al. Extracorporeal membrane oxygenation and conventional medical therapy in neonates with persistent pulmonary hypertension of the newborn: a prospective randomized study. Pediatrics. 1989;84(6):957–63.Google Scholar
UK Collaborative ECMO Trial Group. UK Collaborative Randomised Trial of Neonatal Extracorporeal Membrane Oxygenation. Lancet. 1996;348(9020):7582.Google Scholar
Kumar-Sinha, C, Chinnaiyan, AM. Precision oncology in the age of integrative genomics. Nat Biotechnol. 2018;36(1):4660.Google Scholar
Ke, X, Shen, L. Molecular targeted therapy of cancer: the progress and future prospect. Front Lab Med. 2017;1(2):6975.Google Scholar
Redman, MW, Allegra, CJ. The master protocol concept. Semin Oncol. 2015;42(5):724–30.Google Scholar
Hirakawa, A, Asano, J, Sato, H, Teramukai, S. Master protocol trials in oncology: review and new trial designs. Contemp Clin Trials Commun. 2018;12:18.Google Scholar
U.S. Department of Health and Human Services, U.S. Food and Drug Administration. Master Protocols: Efficient Clinical Trial Design Strategies to Expedite Development of Oncology Drugs and Biologics Guidance for Industry (Draft Guidance). United States Department of Health and Human Services; 2018. www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM621817.pdfGoogle Scholar
Woodcock, J, LaVange, LM. Master protocols to study multiple therapies, multiple diseases, or both. N Engl J Med. 2017;377(1):6270.Google Scholar
Park, JJH, Siden, E, Zoratti, MJ, et al. Systematic review of basket trials, umbrella trials, and platform trials: a landscape analysis of master protocols. Trials. 2019;20(1):572.Google Scholar
Bogin, V. Master protocols: new directions in drug discovery. Contemp Clin Trials Commun. 2020;18:100568.Google Scholar
Vanderbeek, AM, Bliss, JM, Yin, Z, Yap, C. Implementation of platform trials in the COVID-19 pandemic: a rapid review. Contemp Clin Trials. 2022;112:106625.Google Scholar
Park, JJ, Mogg, R, Smith, GE, et al. How COVID-19 has fundamentally changed clinical research in global health. Lancet Glob Health. 2021;9(5):e711–e20.Google Scholar
Park, JJH, Dron, L, Mills, EJ. Moving forward in clinical research with master protocols. Contemp Clin Trials. 2021;106:106438.Google Scholar
Armitage, P. Sequential medical trials. Biomedicine. 1978;28 Spec No:40–1.Google Scholar
Bauer, P, Bretz, F, Dragalin, V, Konig, F, Wassmer, G. Twenty-five years of confirmatory adaptive designs: opportunities and pitfalls. Stat Med. 2016;35(3):325–47.Google Scholar
Woodcock, J, LaVange, LM. Master protocols to study multiple therapies, multiple diseases, or both. N Engl J Med. 2017; 377(1):6270.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×