Trial Design: Should Randomized Phase III Trials in Gynecological Cancers Be Abandoned?

  • Mark F. Brady
  • Val Gebski


For the past 60 years, the gold standard for assessing a new treatment’s efficacy is the randomized phase III trial. When properly designed, conducted, and reported, these studies can provide level-1 evidence that a new treatment is, on average, more effective than standard treatment in a patient population. This trial design does have some limitations, however, and nonrandomized treatment comparisons can be used to provide level-2 evidence concerning treatment effects or even extend the interpretation of a randomized trial. Propensity score analysis is one analytic approach for comparing nonrandomized treatments. Alternative analytic approaches to comparing nonrandomized treatments are an active area of statistical research.

Due to the increasing complexity and cost of conducting randomized phase III trials, there has been a growing reliance on early phase trials to provide preliminary evidence of the new treatment’s activity or to refine the hypotheses for the phase III trial. Growing interest in targeted therapies has contributed to a shift away from single-arm trials toward randomized phase II trials. In an effort to shorten the time for drug development and reduce resource requirements, clinical trialists are reassessing the phase II/III trial design. Adaptive trial designs attempt to provide a more seamless approach to speeding up and increasing the efficiency of drug development.


Overall Survival Epidermal Growth Factor Receptor Propensity Score Balance Function Propensity Score Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    DiMasi JA, Hansen RW, Grabowski HG. The price of innovation: new estimates of drug development costs. J Health Econ. 2003;22(2):151–85.PubMedCrossRefGoogle Scholar
  2. 2.
    Grove A. Rethinking clinical trials. Science. 2011;333:1679.PubMedCrossRefGoogle Scholar
  3. 3.
    Feinstein A, editor. Clinical biostatistics. St. Louis: C.V. Mosby Company; 1977.Google Scholar
  4. 4.
    George SL. Reducing patient eligibility criteria in cancer clinical trials. J Clin Oncol. 1996;14(4):1364–70.PubMedGoogle Scholar
  5. 5.
    Nguyen TT, Somkin CP, Ma Y, Fung LC, Nguyen T. Participation of Asian-American women in cancer treatment research: a pilot study. J Natl Cancer Inst Monogr. 2005;35:102–5.PubMedCrossRefGoogle Scholar
  6. 6.
    Phend C. Kidney ca drugs worked better inside trials. Medpage Today; 2012 [cited 2012 Feb 20]; Primary source: genitourinary cancers symposium: Heng DYC, et al. A multicentered population-based analysis of outcomes of patients with metastatic renal cell carcinoma (mRCC) who do not meet eligibility criteria for clinical trials. GUCS. 2012; Abstract 353. Available from:
  7. 7.
    Rosenbaum P, Rubin D. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70(1):41–55.CrossRefGoogle Scholar
  8. 8.
    Rubin DB. The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials. Stat Med. 2007;26(1):20–36.PubMedCrossRefGoogle Scholar
  9. 9.
    D’Agostino Jr RB. Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Stat Med. 1998;17(19):2265–81.PubMedCrossRefGoogle Scholar
  10. 10.
    D’Agostino Jr RB, D’Agostino Sr RB. Estimating treatment effects using observational data. JAMA. 2007;297(3):314–6.PubMedCrossRefGoogle Scholar
  11. 11.
    Wilkinson PM, Antonopoulos M, Lahousen M, Lind M, Kosmidis P. Epoetin alfa in platinum-treated ovarian cancer patients: results of a multinational, multicentre, randomised trial. Br J Cancer. 2006;94(7):947–54.PubMedCentralPubMedCrossRefGoogle Scholar
  12. 12.
    Rocconi R, Long B, Sullivan P, Blaize M, Brown J, Arbuckle J, et al., editors. Treatment of chemotherapy-induced anemia in patients with ovarian cancer: does the use of erythropoiesis-stimulating agents worsen survival? Orlando: Society of Gynecologic Oncology; 2011.Google Scholar
  13. 13.
    Burger RA, Brady MF, Bookman MA, Fleming GF, Monk BJ, Huang H, et al. Incorporation of bevacizumab in the primary treatment of ovarian cancer. N Engl J Med. 2011;365(26):2473–83.PubMedCrossRefGoogle Scholar
  14. 14.
    Stehman FB, Brady MF, Thigpen JT, Rossi EC, Burger RA. Cytokine use and survival in the first-line treatment of ovarian cancer: a Gynecologic Oncology Group Study. Gynecol Oncol. 2012;127(3):495–501.PubMedCentralPubMedCrossRefGoogle Scholar
  15. 15.
    Shah B, Laupacis A, Hux JE, Austin PC. Propensity score methods gave similar results to traditional regression modeling in observational studies: a systematic review. J Clin Epidemiol. 2005;58(6):550–9.PubMedCrossRefGoogle Scholar
  16. 16.
    Sturmer T, Joshi M, Glynn RJ, Avorn J, Tothman KJ, Schneeweiss S. A review of the application of propensity score methods yielded increase use, advantages in specific settings, but not substantially difference estimates compared with conventional multivariable methods. J Clin Epidemiol. 2006;59(5):437–47.PubMedCentralPubMedGoogle Scholar
  17. 17.
    Senn S, Graf E, Caputo A. Stratification for the propensity score compared with linear regression techniques to assess the effect of treatment or exposure. Stat Med. 2007;26(30):5529–44.PubMedCrossRefGoogle Scholar
  18. 18.
    Funk MJ, Westreich D, Wiesen C, Sturmer T, Brookhart MA, Davidian M. Doubly robust estimation of causal effects. Am J Epidemiol. 2011;173(7):761–7.PubMedCentralPubMedCrossRefGoogle Scholar
  19. 19.
    Robins JM, Finkelstein DM. Correcting for noncompliance and dependent censoring in an AIDS clinical trial with inverse probability of censoring weighted (IPCW) log-rank tests. Biometrics. 2000;56(3):779–88.PubMedCrossRefGoogle Scholar
  20. 20.
    Thurlimann B, Keshaviah A, Coates AS, Mouridsen H, Mauriac L, Forbes JF, et al. A comparison of letrozole and tamoxifen in postmenopausal women with early breast cancer. N Engl J Med. 2005;353(26):2747–57.PubMedCrossRefGoogle Scholar
  21. 21.
    Meyerhardt JA, Li L, Sanoff HK, Carpenter W, Schrag D. Effectiveness of bevacizumab with first-line combination chemotherapy for Medicare patients with stage IV colorectal cancer. J Clin Oncol. 2012;30(6):608–15.PubMedCentralPubMedCrossRefGoogle Scholar
  22. 22.
    Lau J, Schmid C, Chambers T. Cumulative meta-analysis of clinical trials builds evidence for exemplary medical care. J Clin Epidemiol. 1995;48(1):45–57.PubMedCrossRefGoogle Scholar
  23. 23.
    The ICON and AGO Collaborators. Paclitaxel plus platinum-based chemotherapy versus conventional platinum-based chemotherapy in women with relapsed ovarian cancer: the ICON4/AGO-OVAR-2.2 trial. Lancet. 2003;361:2099–106.CrossRefGoogle Scholar
  24. 24.
    Pujade-Lauraine E, Wagner U, Aavall-Lundqvist E, Gebski V, Heywood M, Vasey P, et al. Pegylated liposomal doxorubicin and carboplatin compared with paclitaxel and carboplatin for patients with platinum-sensitive ovarian cancer in late relapse. J Clin Oncol. 2010;28(20):323–3329.Google Scholar
  25. 25.
    Piccart-Gebhart M, Procter M, Leyland-Jones B, Goldhirsch A, Untch M, Smith I, et al. Trastuzumab after adjuvant chemotherapy in HER2-positive breast cancer. N Engl J Med. 2005;353(16):1659–72.PubMedCrossRefGoogle Scholar
  26. 26.
    Karapetis C, Khambata-Ford S, Jonker D, O’Callaghan C, Tu D, Tebbutt N, et al. K-ras mutations and benefit from cetuximab in advanced colorectal cancer. N Engl J Med. 2008;359(17):1757–65.PubMedCrossRefGoogle Scholar
  27. 27.
    Romond E, Jeong J, Sledge G, Geyer C, Martino S, Rastogi P, et al. Trastuzumab plus adjuvant chemotherapy for HER2-positive breast cancer: final planned joint analysis of overall survival (OS) from NSABP B-31 and NCCTG N9831. In: San Antonio breast cancer symposium abstract S5-5 7 Dec 2012. San Antonio 2012.Google Scholar
  28. 28.
    Bang Y, Van Cutsem E, Feyereislova A, Chung H, Shen L, Sawaki A, et al. Trastuzumab in combination with chemotherapy versus chemotherapy alone for treatment of HER2-positive advanced gastric or gastro-oesophageal junction cancer (ToGA): a phase 3, open-label, randomised controlled trial. Lancet. 2010;376:687–97.PubMedCrossRefGoogle Scholar
  29. 29.
    Allegra C, Yothers G, O’Connell M, Sharif S, Petrelli N, Colangelo L, et al. Phase III trial assessing bevacizumab in stages II and III carcinoma of the colon: results of NSABP protocol C-08. J Clin Oncol. 2010;29:11–6.PubMedCentralPubMedCrossRefGoogle Scholar
  30. 30.
    Perren T, Swart A, Pfisterer J, Ledermann J, Pujade-Lauraine E, Kristensen G, et al. A phase 3 trial of bevacizumab in ovarian cancer. N Engl J Med. 2011;365:2484–96.PubMedCrossRefGoogle Scholar
  31. 31.
    Burger R, Brady M, Bookman M, Fleming G, Monk B, Huang H, et al. Incorporation of bevacizumab in the primary treatment of ovarian cancer. N Engl J Med. 2011;365:2473–83.PubMedCrossRefGoogle Scholar
  32. 32.
    Mehta C, Cain K. Charts for the early stopping of pilot studies. J Clin Oncol. 1984;2(6):676–82.PubMedGoogle Scholar
  33. 33.
    Simon R, Willes R, Ellenberg S. Randomized phase II clinical trials. Cancer Treat Rep. 1985;69:1375–81.PubMedGoogle Scholar
  34. 34.
    Simon R. Optimal two-stage designs for phase II clinical trials. Control Clin Trials. 1989;10:1–10.PubMedCrossRefGoogle Scholar
  35. 35.
    Warr D, McKinney S, Tannock I. Influence of measurement error on assessment of response to anticancer chemotherapy: proposal for new criteria of tumor response. J Clin Oncol. 1984;2(9):1040–6.PubMedGoogle Scholar
  36. 36.
    Kramar A, Potvin D, Hill C. Multistage designs for phase II clinical trials: statistical issues in cancer research. Br J Cancer. 1996;74:1317–20.PubMedCentralPubMedCrossRefGoogle Scholar
  37. 37.
    Wieand S. Randomized phase II trials: what does randomization gain? J Clin Oncol. 2005;23(9):1794–5.PubMedCrossRefGoogle Scholar
  38. 38.
    Gan H, Grothey A, Pond G, Moore M, Siu L, Sargent D. Randomized phase II trials: inevitable or inadvisable? J Clin Oncol. 2010;28(15):3641–7.Google Scholar
  39. 39.
    Rubinstein L, Crowley J, Ivy P, LeBlanc M, Sargent D. Randomized phase II designs. Clin Cancer Res. 2009;15(6):1883–90.PubMedCentralPubMedCrossRefGoogle Scholar
  40. 40.
    Mandrekar S, Sargent D. Randomized phase II trials time for a new era in clinical trial design. J Thorac Oncol. 2010;5(7):932–4.PubMedCentralPubMedCrossRefGoogle Scholar
  41. 41.
    Freidlin B, Korn E, Hunsberger S, Gray R, Saxman S, Zujewski J. Proposal for the use of progression-free survival in unblinded randomized trials. J Clin Oncol. 2007;25(15):2122–6.PubMedCrossRefGoogle Scholar
  42. 42.
    Moher D, Schulz K, Altman D. The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomized trials. Ann Intern Med. 2001;134:657–62.PubMedCrossRefGoogle Scholar
  43. 43.
    Keech A, Gebski V, Pike R, editors. Interpreting and reporting clinical trials. A guide to the consort statement and the principles of randomised controlled trials. Sydney: Australasian Medical Publishing; 2007.Google Scholar
  44. 44.
    Eisenhauer E, ten Bokkel Huinink W, Swenerton K, Gianni L, Myles J, van der Burg M, et al. European–Canadian randomized trial of paclitaxel in relapsed ovarian cancer: high-dose versus low-dose and long versus short infusion. J Clin Oncol. 1994;12:2654–66.PubMedGoogle Scholar
  45. 45.
    Bookman M, Brady M, McGuire W, Harper P, Alberts D, Friedlander M, et al. Evaluation of new platinum-based treatment regimens in advanced-stage ovarian cancer: a Phase III Trial of the Gynecologic Cancer Inter Group. J Clin Oncol. 2009;27:1419–25.PubMedCentralPubMedCrossRefGoogle Scholar
  46. 46.
    Sydes M, Parmar M, James N, Clarke N, Dearnaley D, Mason M, et al. Issues in applying multi-arm multi-stage methodology to a clinical trial in prostate cancer: the MRC STAMPEDE trial. Trials. 2009;10:39.PubMedCentralPubMedCrossRefGoogle Scholar
  47. 47.
    Hudmon K, Chamberlain R, Frankowski R. Outcomes of a placebo run-in period in a head and neck cancer chemoprevention trial. Control Clin Trials. 1997;18:228–40.PubMedCrossRefGoogle Scholar
  48. 48.
    Goss G, Arnold A, Shepherd F, Dediu M, Ciuleanu T, Fenton D, et al. Randomized, double-blind trial of carboplatin and paclitaxel with either daily oral cediranib or placebo in advanced non–small-cell lung cancer: NCIC clinical trials group BR24 study. J Clin Oncol. 2010;28(1):49–55.PubMedCrossRefGoogle Scholar
  49. 49.
    Gynecologic Oncology Group. Cisplatin and radiation therapy with or without carboplatin and paclitaxel in patients with locally advanced cervical cancer. NCT01414608. 2012;
  50. 50.
    Mackay H, Provencheur D, Heywood M, Eisenhauer E, Oza A, Meyer R. Phase II/III study of intraperitoneal chemotherapy after neoadjuvant chemotherapy for ovarian cancer: NCIC CTG OV21. Curr Oncol. 2011;18(2):84–90.PubMedCentralPubMedGoogle Scholar
  51. 51.
    Berry D. Adaptive clinical trials in oncology. Nat Rev Clin Oncol. 2012;9:199–207.CrossRefGoogle Scholar
  52. 52.
    Lee C, Lord S, Coates A, Simes R. Molecular biomarkers to individualise treatment: assessing the evidence. Med J Aust. 2009;190(11):631–6.PubMedGoogle Scholar
  53. 53.
    Clark G. Prognostic factors versus predictive factors: examples from a clinical trial of erlotinib. Mol Oncol. 2008;1(4):406–12.PubMedCrossRefGoogle Scholar
  54. 54.
    Henderson C, Patek A. The relationship between prognostic and predictive factors in the management of breast cancer. Breast Cancer Res Treat. 1998;52:261–88.PubMedCrossRefGoogle Scholar
  55. 55.
    Hayes D, Track B, Harris A. Assessing the clinical impact of prognostic factors: when is “statistically significant” clinically useful? Breast Cancer Res Treat. 1998;52:305–19.PubMedCrossRefGoogle Scholar
  56. 56.
    Romond E, Perez E, Bryant J, Suman V, Geyer C, Davidson N, et al. Trastuzumab plus adjuvant chemotherapy for operable HER2-positive breast cancer. N Engl J Med. 2005;353(16):1673–84.PubMedCrossRefGoogle Scholar
  57. 57.
    Paik S, Kim C, Jeong J, Geyer C, Romond E, Mejia-Mejia O, et al. Benefit from adjuvant trastuzumab may not be confined to patients with IHC 3+ and/or FISH-positive tumors: central testing results from NSABP B-31. ASCO annual meeting proceedings part I; Chicago, Illinois. J Clin Oncol. 2007;25:511.Google Scholar
  58. 58.
    Paik S, Kim C, Wolmark N. HER2 status and benefit from adjuvant trastuzumab in breast cancer (letter). N Engl J Med. 2008;358(13):1409–11.PubMedCrossRefGoogle Scholar
  59. 59.
    Cappuzzo F, Ciuleanu T, Stelmakh L, Cicenas S, Szczésna A, Juhász E, et al. Erlotinib as maintenance treatment in advanced non-small-cell lung cancer: a multicentre, randomised, placebo-controlled phase 3 study. Lancet Oncol. 2010;11:521–9.PubMedCrossRefGoogle Scholar
  60. 60.
    Sargent D, Conley B, Allegra C, Collette L. Clinical trial designs for predictive marker validation in cancer treatment trials. J Clin Oncol. 2005;23:2020–7.PubMedCrossRefGoogle Scholar
  61. 61.
    Lee C, Simes RJ, Brown C, Lord S, Wagner U, Plante M, et al. Prognostic nomogram to predict progression-free survival in patients with platinum-sensitive recurrent ovarian cancer. Br J Cancer. 2011;105:1144–50.PubMedCentralPubMedCrossRefGoogle Scholar
  62. 62.
    Mandrekar S, Sargent D. Clinical trial designs for predictive biomarker validation: theoretical considerations and practical challenges. J Clin Oncol. 2009;27(24):4027–34.PubMedCentralPubMedCrossRefGoogle Scholar
  63. 63.
    Bogaerts J, Cardoso F, Buyse M, Braga S, Loi S, Harrison J, et al. Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial. Nat Clin Pract Oncol. 2006;3(10):540–51.PubMedCrossRefGoogle Scholar
  64. 64.
    Rubin E, Anderson K, Gause C. The BATTLE trial: a bold step toward improving the efficiency of biomarker-based drug development. Cancer Discov. 2011;1:17–20.PubMedCrossRefGoogle Scholar
  65. 65.
    Zhou X, Liu S, Kim E, Herbst R, Lee J. Bayesian adaptive design for targeted therapy development in lung cancer – a step toward personalized medicine. Clin Trials. 2008;5(3):181–93.PubMedCrossRefGoogle Scholar
  66. 66.
    Kim E, Herbst R, Wistuba I, Lee J, Blumenschein G, Tsao A, et al. The BATTLE trial: personalizing therapy for lung cancer. Cancer Discov. 2011;1:44–51.PubMedCrossRefGoogle Scholar
  67. 67.
    Barker A, Sigman C, Kelloff G, Hylton N, Berry D, Esserman L. I-SPY 2: an adaptive breast cancer trial design in the setting of neoadjuvant chemotherapy. Clin Pharmacol Ther. 2009;86(1):97–100.PubMedCrossRefGoogle Scholar
  68. 68.
    Flaherty K, Puzanov I, Kim K, Ribas A, McArthur G, Sosman J, et al. Inhibition of mutated, activated BRAF in metastatic melanoma. N Engl J Med. 2010;363(9):809–19.PubMedCentralPubMedCrossRefGoogle Scholar
  69. 69.
    Kopetz S, Desai J, Chan E, Hecht J, O’Dwyer P, Lee R, et al. PLX4032 in metastatic colorectal cancer patients with mutant BRAF tumors. J Clin Oncol. 2010;28(15 Suppl):3534.Google Scholar
  70. 70.
    Prentice R. Surrogate endpoints in clinical trials: definitions and operational criteria. Stat Med. 1989;8:431–40.PubMedCrossRefGoogle Scholar
  71. 71.
    Lee C, Marschner I, Simes R, Voysey M, Egleston B, Hudes G, et al. Increase in cholesterol predicts survival advantage in renal cell carcinoma patients treated with temsirolimus. Clin Cancer Res. 2012;18:3188–96.PubMedCrossRefGoogle Scholar
  72. 72.
    Yusuf S, Collins R, Peto R. Why do we need some large, simple randomized trials? Stat Med. 1984;3:409–20.PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  1. 1.Gynecology Oncology Group Statistical and Data CenterRoswell Park Cancer InstituteBuffaloUSA
  2. 2.NHMRC Clinical Trials CentreThe University of SydneyCamperdownAustralia

Personalised recommendations