Skip to main content

Avoiding biostatistical pitfalls in the design and analysis of head and neck cancer clinical trials

  • Chapter
Cancers of the Head and Neck

Part of the book series: Cancer Treatment and Research ((CTAR,volume 32))

  • 79 Accesses

Abstract

The ultimate objective of any clinical trial is to obtain the correct answer to an important medical question. The science of biostatistics plays an important role in helping to meet this fundamental objective. By properly applying sound statistical principles to clinical research in oncology, one can insure that results of completed studies are valid and convincing to others in the scientific community. To this end, the biomedical literature contains several excellent and thorough discussions regarding the design, execution, and analysis of cancer clinical trials and methods of data acquisition [1–3]. These references draw attention to certain basic components of a successful clinical trial, including: (1) a clear, unambiguous protocol which addresses a significant medical question, (2) well-defined conditions for entry of patients on-study, (3) sample sizes sufficiently large and duration of follow-up adequate to detect treatment effects if they are present, (4) a clear description of treatment regimens and experimental design, (5) explicit definition of endpoints used for efficacy and safety evaluation, (6) patient record forms and data management procedures which enhance data quality, (7) appropriate methodology for data monitoring and statistical analysis to account for incomplete data, and (8) appropriate consideration of ethical issues. While there may be a variety of equally plausible ways to satisfy each of these criteria, their precise specification will depend on the goals of the particular trial, its administrative structure, and the nature of the treatment and disease under study.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Buyse, M.E., Staquet, M.J., Sylvester, R.J. 1984. Cancer Clinical Trials: Methods and Practice. Oxford University Press, Oxford.

    Google Scholar 

  2. Mike, V., Stanley, K.E. 1982. Statistics in Medical Research: Methods and Issues, with Applications in Cancer Research. John Wiley and Sons, Inc., New York.

    Google Scholar 

  3. Symposium on Methodology and Quality Assurance in Cancer Clinical Trials. 1985. Cancer Treat. Rep. 69: 1039–1233.

    Google Scholar 

  4. Gehan, E.A., Freireich, E.J. 1974. Non-randomized controls in cancer clinical trials. N. Engl. J. Med. 290: 198–203.

    Article  PubMed  CAS  Google Scholar 

  5. Byar, D.P., Simon, R.M., Friedewald, W.T. et al. 1976. Randomized clinical trials. N. Engl. J. Med. 295: 74–80.

    Article  PubMed  CAS  Google Scholar 

  6. Farewell, V.T., D’Angio, G.J. 1981. A simulated study of historical controls using real data. Biometrics 37: 169–176.

    Article  PubMed  CAS  Google Scholar 

  7. Pocock, S.J. 1977. Randomized clinical trials (letter). Br. Med. J. 1 (6077): 1661.

    Article  PubMed  CAS  Google Scholar 

  8. Byar, D.P. 1979. Necessity and justification of randomized clinical studies. In: Controversies in Cancer Treatment (H.J. Tagnon, M.J. Staquet, eds.). Mason Publishing, New York, pp. 75–82.

    Google Scholar 

  9. Zelen, M. 1979. A new design for randomized clinical trials. N. Engl. J. Med. 300: 1273–1275. 10.

    Google Scholar 

  10. Schoenfeld, D., Gelber, R. 1979. Designing and analyzing clinical trials which allow institutions to randomize patients to a subset of the treatments under study. Biometrics 35: 825–829.

    Article  PubMed  CAS  Google Scholar 

  11. Makuch, R.W., Simon, R.M. 1978. A note on the design of multi-institution three-treatment studies. Cancer Clin. Trials 1: 301–303.

    CAS  Google Scholar 

  12. Peto, R. 1978. Clinical trial methodology. Biomedicine 28: 24–36.

    PubMed  Google Scholar 

  13. Byar, D.P., Piantadosi, S. 1985. Factorial designs for randomized clinical trials. Cancer Treat. Rep. 69: 1055–1062.

    CAS  Google Scholar 

  14. Freiman, J.A., Chalmers, T.C., Smith, H., Jr., et al 1978. The importance of beta, the type II error and sample size in the design and interpretation of the randomized control trial: Survey of 71 ’negative’ trials. N. Engl. J. Med. 299: 690–694.

    Article  PubMed  CAS  Google Scholar 

  15. Lachin, J.M. 1981. Introduction to sample size determination and power analysis for clinical trials. Controlled Clin. Trials 2: 93–113.

    CAS  Google Scholar 

  16. Casagrande, J.T., Pike, M.C., Smith, P.G. 1978. An improved formula for calculating sample size for comparing two binomial distributions. Biometrics 34: 483–486.

    Article  PubMed  CAS  Google Scholar 

  17. Makuch, R.W., Simon, R.M. 1978. Sample size requirements for evaluating a conservative therapy. Cancer Treat. Rep. 62: 1037–1040.

    CAS  Google Scholar 

  18. Detsky, A.S., Sackett, D.L. 1985. When was a ’negative’ clinical trial big enough? How many patients you needed depends on what you found. Arch. Intern. Med. 145: 709–712.

    CAS  Google Scholar 

  19. Makuch, R.W., Johnson, M.F. 1986. Some issues in the design and interpretation of ’negative’ clinical studies. Arch. Intern. Med. 146: 986–989.

    CAS  Google Scholar 

  20. George, S.L., Desu, M.M. 1974. Planning the size and duration of a clinical trial studying the time to some critical event. J. Chronic. Dis. 27: 15–24.

    Article  PubMed  CAS  Google Scholar 

  21. Makuch, R.W., Simon, R.M. 1982. Sample size requirements for comparing time-to-failure among k treatment groups. J. Chron. Dis. 35: 861–867.

    Article  PubMed  CAS  Google Scholar 

  22. Schoenfeld, D. 1981. The asymptotic properties of nonparametric tests for comparing survival distributions. Biometrika 68: 316–319.

    Article  Google Scholar 

  23. Rubinstein, L.V., Gail, M.H., Santner, T.J. 1981. Planning the duration of a comparative clinical trial with loss to follow-up and a period of continued observation. J. Chronic. Dis. 34: 469–479.

    Article  PubMed  CAS  Google Scholar 

  24. Palta, M., McHugh, R. 1980. Planning the size of a cohort study in the presence of both losses to follow-up and non-compliance. J. Chron. Dis. 33: 501–512.

    Article  PubMed  CAS  Google Scholar 

  25. Bernstein, D., Lagakos, S.W. 1978. Sample size and power determination for stratified clinical trials. J. Stat. Comput. Simu. 8: 65–73.

    Article  Google Scholar 

  26. Peto, R., Pike, M.C., Armitage, P. et al 1976. Design and analysis of randomized clinical trials, requiring prolonged observation of each treatment. I. Introduction and design. B. J. Cancer 34: 585–612.

    CAS  Google Scholar 

  27. Grizzle, J.E. 1982. A note on stratifying versus complete random assignment in clinical trials. Controlled Clin. Trials 3: 365–368.

    CAS  Google Scholar 

  28. Brown, B.W., Jr. 1980. Statistical controversies in the design of clinical trials - some personal views. Controlled Clin. Trials 1: 13–27.

    Google Scholar 

  29. Pocock, S.J., Simon, R. 1975. Sequential treatment assignment with balancing for prognostic factors in the controlled clinical trial. Biometrics 31: 103–115.

    Article  PubMed  CAS  Google Scholar 

  30. Wei, L.J. 1978. An application of an urn model to the design of sequential controlled clinical trials. J. Am. Stat. Assn. 73: 559–563.

    Article  Google Scholar 

  31. Kaplan, E.L., Meier, P. 1958. Nonparametric estimation from incomplete observations. J. Am. Stat. Assn. 53: 458–481.

    Google Scholar 

  32. Glatstein, E., Makuch, R.W. 1984. Illusion and reality: Practical pitfalls in interpreting clinical trials. J. Clin. Oncol. 5: 488–497.

    Google Scholar 

  33. Brookmeyer, R., Crowley, J. 1982. A confidence interval for the median survival time. Biometrics 38: 29–41.

    Article  Google Scholar 

  34. Gehan, E.A. 1965. A generalized Wilcoxon test for comparing arbitrarily singly censored samples. Biometrika 52: 203–224.

    PubMed  CAS  Google Scholar 

  35. Mantel, N. 1966. Evaluation of survival data and two new rank order statistics arising in its consideration. Cancer Chemother. Rep. 50: 163–170.

    CAS  Google Scholar 

  36. Schwartz, D., Lellouch, J. 1967. Explanatory and pragmatic attitudes in therapeutic trials. J. Chronic. Dis. 20: 637–648.

    Article  PubMed  CAS  Google Scholar 

  37. Peto, R. 1982. Statistical aspects of cancer trials. In: Treatments of Cancer (K.E. Hainan, ed.). Chapman and Hall, London, pp. 867–871.

    Google Scholar 

  38. Tukey, J.W. 1977. Some thoughts on clinical trials, especially problems of multiplicity. Science 198: 679–684.

    Article  PubMed  CAS  Google Scholar 

  39. Gail, M., Simon, R. 1985. Testing for qualitative interactions between treatment effects and patient subsets. Biometrics 41: 361–371.

    Article  PubMed  CAS  Google Scholar 

  40. Shuster, J., van Eys, J. 1983. Interaction between prognostic factors and treatment. Controlled Clin. Trials 4: 209–214.

    CAS  Google Scholar 

  41. Byar, D.P. 1985. Assessing apparent treatment-covariate interactions in randomized clinical trials. Stat. Med. 4: 255–263.

    CAS  Google Scholar 

  42. Ingelfinger, J.A., Mosteller, F., Thibodeau, L.A., Ware, J.H. 1983. Biostatistics in Clinical Medicine. Maillan, New York, pp. 253–260.

    Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1987 Martinus Nijhoff Publishers, Boston

About this chapter

Cite this chapter

Makuch, R., Johnson, M. (1987). Avoiding biostatistical pitfalls in the design and analysis of head and neck cancer clinical trials. In: Jacobs, C. (eds) Cancers of the Head and Neck. Cancer Treatment and Research, vol 32. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-2029-6_13

Download citation

  • DOI: https://doi.org/10.1007/978-1-4613-2029-6_13

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4612-9208-1

  • Online ISBN: 978-1-4613-2029-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics