Skip to main content

Advertisement

SpringerLink
Log in

Study Designs in Multi-arm Trials for Breast Cancer: A Systematic Literature Review of Major Journals

  • Original Research
  • Published:
Therapeutic Innovation & Regulatory Science Aims and scope Submit manuscript

Abstract

Background

Several articles showed that statistical efficiency of multi-arm randomized clinical trials (RCTs) is much better than conventional two-arm RCTs. Multi-arm RCTs attract interest mainly when the experimental treatment regimen is not optimized or several pipelines under development exist. Breast cancer is a possible candidate disease. Our aim was to elucidate the current study designs and multiplicity adjustment methods in multi-arm RCTs.

Methods

A search of the PubMed database revealed 468 articles on breast cancer RCTs published from 2010 to 2016. Information on study designs and analysis methods was collected from 4 major journals.

Results

A total of 202 RCTs were selected, 48 were multi-arm and 29 were three-arm RCTs. In two of the target journals, multi-arm RCTs have been increasingly reported since 2013. Compared with two-arm RCTs, three-arm RCTs were frequently conducted in neoadjuvant settings (7.7% vs 33.3%). The number of trials performed in perioperative settings was 46 in two-arm and 15 in three-arm RCTs. Of these, the proportion of industry-sponsored trials in two-arm and three-arm RCTs was 26.1% and 53.3%, respectively. Shared control designs (SCDs) which randomized to a common control arm and multiple experimental arms comprised 54.2% of 48 multi-arm RCTs. For SCDs, detailed information on multiplicity adjustment methods was seldom reported. The Bonferroni adjustment method together with alpha-spending functions was commonly used.

Conclusion

Breast cancer multi-arm RCTs have been increasingly reported. The majority of multi-arm RCTs are industry-sponsored trials using SCDs in neoadjuvant settings. Detailed description about multiplicity adjustment methods is required for multi-arm RCTs.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Figure 1.
Figure 2.

Similar content being viewed by others

References

  1. Parmar MK, Carpenter J, Sydes MR. More multiarm randomised trials of superiority are needed. The Lancet. 2014;384:283–4.

    Article  Google Scholar 

  2. Freidlin B, Korn EL, Gray R, et al. Multi-arm clinical trials of new agents: some design considerations. Clin Cancer Res. 2008;14:4368–71.

    Article  CAS  Google Scholar 

  3. Dmitrienko A, D'Agostino R Sr. Traditional multiplicity adjustment methods in clinical trials. Stat Med. 2013;32:5172–218.

    Article  Google Scholar 

  4. Dmitrienko A, D'Agostino RB Sr, Huque MF. Key multiplicity issues in clinical drug development. Stat Med. 2013;32:1079–111.

    Article  Google Scholar 

  5. Huque MF, Dmitrienko A, D’Agostino R. Multiplicity issues in clinical trials with multiple objectives. Stat in Biopharm Res. 2013;5:321–37.

    Article  Google Scholar 

  6. Dmitrienko A, D’Agostino RB Sr. Multiplicity considerations in clinical trials. N Engl J Med. 2018;378:2115–222.

    Article  Google Scholar 

  7. Parmar MK, Barthel FMS, Sydes M, et al. Speeding up the evaluation of new agents in cancer. J Natl Cancer Inst. 2008;100:1204–14.

    Article  CAS  Google Scholar 

  8. EMA (2002) Points to consider on multiplicity issues in clinical trials. The European Medicine Agency

  9. EMA (2016) Guideline on multiplicity issues in clinical trials (draft version)

  10. US FDA. Multiple endpoints in clinical trials: guidance for industry (draft version). Silver Spring: U.S. Food and Drug Administration; 2017.

    Google Scholar 

  11. Sherman RE, Anderson SA, Dal Pan GJ, et al. Real-world evidence—what is it and what can it tell us. N Engl J Med. 2016;375:2293–7.

    Article  Google Scholar 

  12. Sherman RE, Davies KM, Robb MA, et al. Accelerating development of scientific evidence for medical products within the existing US regulatory framework. Nat Rev Drug Discov. 2017;16:297.

    Article  CAS  Google Scholar 

  13. Woodcock J, LaVange LM. Master protocols to study multiple therapies, multiple diseases, or both. N Engl J Med. 2017;377:62–70.

    Article  CAS  Google Scholar 

  14. US FDA (2017) Work plan and proposed funding allocations of FDA innovation account.

  15. Baron G, Perrodeau E, Boutron I, et al. Reporting of analyses from randomized controlled trials with multiple arms: a systematic review. BMC Med. 2013;11:84.

    Article  Google Scholar 

  16. Wason JM, Stecher L, Mander AP. Correcting for multiple-testing in multi-arm trials: is it necessary and is it done? Trials. 2014;15:364.

    Article  Google Scholar 

  17. WHO primary registries of international clinical trials registry platform (ICTRP). World Health Organization

  18. US FDA. Pathological complete response in neoadjuvant treatment of high-risk early-stage breast cancer: use as an end point to support accelerated approval. Silver Spring: U.S Food and Drug Administration; 2014.

    Google Scholar 

  19. Simon R, Wittes R, Ellenberg S. Randomized phase II clinical trials. Cancer Treat Rep. 1985;69:1375–81.

    CAS  PubMed  Google Scholar 

  20. Stockler MR, Harvey VJ, Francis PA, et al. Capecitabine versus classical cyclophosphamide, methotrexate, and fluorouracil as first-line chemotherapy for advanced breast cancer. J Clin Oncol. 2011;29:4498–504.

    Article  CAS  Google Scholar 

  21. Perez EA, Suman VJ, Davidson NE, et al. Sequential versus concurrent trastuzumab in adjuvant chemotherapy for breast cancer. J Clin Oncol. 2011;29:4491.

    Article  CAS  Google Scholar 

  22. Wason JM, Jaki T, Stallard N. Planning multi-arm screening studies within the context of a drug development program. Stat Med. 2013;32:3424–35.

    Article  Google Scholar 

  23. Juszczak E, Altman DG, Hopewell S, et al. Reporting of multi-arm parallel-group randomized trials: extension of the CONSORT 2010 statement. JAMA. 2019;321:1610–20.

    Article  Google Scholar 

  24. Moher D, Schulz KF, Altman D. The consort statement: revised recommendations for improving the quality of reports of parallel-group randomized trials. JAMA. 2001;285:1987–91.

    Article  CAS  Google Scholar 

  25. Altman DG, Schulz KF, Moher D, et al. The revised CONSORT statement for reporting randomized trials: explanation and elaboration. Ann Intern Med. 2001;134:663–94.

    Article  CAS  Google Scholar 

  26. Moher D, Hopewell S, Schulz KF, et al. CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c869.

    Article  Google Scholar 

  27. Schulz KF, Altman DG, Moher D. CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c332.

    Article  Google Scholar 

  28. Kantarjian HM, Fojo T, Mathisen M, et al. Cancer drugs in the United States: Justum Pretium—the just price. J Clin Oncol. 2013;31:3600–4.

    Article  Google Scholar 

  29. Kocher R, Roberts B. The calculus of cures. N Engl J Med. 2014;370:1473–5.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Biostatistics Division, Center for Research Administration and Support, National Cancer Center, Chiba, Japan

    Shogo Nomura

  2. Department of Management Science, Tokyo University of Science Graduate School of Engineering, Tokyo University of Science, Tokyo, Japan

    Yu Miyauchi & Kento Isogaya

  3. Biostatistics Department, Shionogi & Co., Ltd., Osaka, Japan

    Yoshikazu Ajisawa

  4. Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, Tokyo, Japan

    Takashi Sozu

Authors
  1. Shogo Nomura
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yu Miyauchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yoshikazu Ajisawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kento Isogaya
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Takashi Sozu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shogo Nomura.

Ethics declarations

Conflict of interest

SN reports personal fees from Taiho, AstraZeneca, Chugai, and Pfizer, outside the submitted work. YA is the employee of Shionogi & Co., Ltd.

Additional information

Presented at the 2018 Eastern North American Region Spring Meeting, March 25–28, 2018, Atlanta, United States.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 47 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nomura, S., Miyauchi, Y., Ajisawa, Y. et al. Study Designs in Multi-arm Trials for Breast Cancer: A Systematic Literature Review of Major Journals. Ther Innov Regul Sci 54, 1185–1191 (2020). https://doi.org/10.1007/s43441-020-00141-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s43441-020-00141-3

Keywords

Search

Navigation