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Randomization to standard regimen or regimen with new drug
Endpoint is time to progression regardless of whether it is an accepted phase III endpoint
One-sided significance level can exceed .05 for analysis and sample size planning
Simon R et al. Clinical trial designs for the early clinical development of therapeutic cancer vaccines. Journal of Clinical Oncology 19:1848-54, 2001
Korn EL et al. Clinical trial designs for cytostatic agents: Are new approaches needed? Journal of Clinical Oncology 19:265-272, 2001
Rubinstein LV, Korn EL, Freidlin B, Hunsberger S, Ivy SP, Smith MA. Design issues of randomized phase 2 trials and a proposal for phase 2 screening trials. Journal of Clinical Oncology 2005;23:7199-7206.
Patients will be accrued until time t1. At t1 accrual will be suspended and patients will be followed for a minimum time f1.
After t1+f1 a comparison of the treated versus control groups based on progression-free survival (PFS) will be performed. If the p-value for PFS in this interim analysis is not less than a specified threshold α1, accrual will terminate and no claims for the new treatment will be made.
Otherwise, accrual will resume until a total of M patients are accrued. After accruing M patients, follow-up will continue for an additional minimum time fo. At the end of the study OS will be evaluated on all M patients. The total sample size M is that of the phase III study.
For the integrated phase II/III and for the phase III with a futility analysis we determined t1 and 1 so that the overall study power (probability of concluding a benefit on OS when starting from phase II) will be maintained at 81%.
This 81% is the power for the strategy of a randomized phase II study with 90% power for PFS followed by a randomized phase III study with 90% power for OS.
For the integrated phase II/III and the futility design we evaluate E[N] and E[T] for different 1 values but always adjusted t1 to maintain 81% power.
For the single arm phase II study, miss-specifying the control median PFS time is a serious problem
When there is no treatment benefit, Table 1a shows the increase in the probability of proceeding to phase III if the patients selected for the phase II trial are slightly more favorable than expected; e.g.l median control PFS is under specified by 2 weeks and 1 month.
.72 4 .4 3.5 .1 3 * Probability of continuing to the phase III study True median PFS rate for the population included in the study (months)
Table 1b shows that specifying the control median too high cuts into the probability of concluding a benefit on OS when a benefit exists. The overall probability is expected to be .81 but it is reduced to .51 or .09 for a 2 week or 1 month over specification.
.09 .1 2 .53 .59 2.5 .81 .9 3 * Probability of concluding an overall survival benefit Probability of continuing to the phase III study True median PFS rate for the population included in the study (months)
Although the single arm phase II study may appear to speed up drug development, even minimal prognostic bias in comparison to historical controls can have major impact on producing misleading results which either lead to futile phase III trials or result in missing active agents.
Dixon, DO, and Simon, R. Sample size considerations for studies comparing survival curves using historical controls. J. Clin. Epidemiology 41: 1209-1214, 1988.
Thall, PF, and Simon, R. Incorporating historical control data in planning phase II clinical trials. Stat. in Med. 9:215-228, 1990.
Thall, P F and Simon R. A Bayesian approach to establishing sample size and monitoring criteria for phase II clinical trials. Controlled Clinical Trials 15:463-481, 1994.
Thall, PF, Simon R. and Estey E. Bayesian designs for Clinical trials with multiple outcomes.Statistics in Medicine 14:357-379, 1995
Thall PF, Simon R, Estey E: A new statistical strategy for monitoring safety and efficacy in single-arm clinical trials. Journal of Clinical Oncology 14:296-303, 1996.
Number of Patients on Experimental Treatment to have 80% Power for Detecting 15% Absolute Increase ( =.05) in PFS vs Historical Controls 65 42 200 83 50 100 101 58 75 167 80 50 285 108 40 >1000 223 30 >1000 >1000 20 80% Control Progression at landmark t 90% Control Progression at landmark t Number of Historical Controls
The interim analysis of PFS may support a claim of accelerated approval if a significance level no greater than .05 is used.
This design would ensure that a randomized phase III trial based on OS was in place at the time that accelerated approval was obtained and would provide a well powered, well designed randomized phase II study with PFS as the basis for the provisional claim.
Develop a completely specified genomic classifier of the patients likely to benefit from a new drug
Establish analytical validity of the classifier
Use the completely specified classifier to design and analyze a new clinical trial to evaluate effectiveness of the new treatment with a pre-defined analysis plan that preserves the overall type-I error of the study.
Using only the first half of patients accrued during the trial, develop a binary classifier that predicts the subset of patients most likely to benefit from the new treatment T compared to control C
Compare T to C for patients accrued in second stage who are predicted responsive to T based on classifier
Perform test at significance level 0.01
If H 0 is rejected, claim effectiveness of T for subset defined by classifier
Treatment effect restricted to subset. 10% of patients sensitive, 10 sensitivity genes, 10,000 genes, 400 patients. 85.3 Overall adaptive signature design 42.2 Sensitive subset .01 level test (performed only when overall .04 level test is negative) 43.1 Overall .04 level test 46.7 Overall .05 level test Power Test
Generalization of Biomarker Adaptive Signature Design
Have identified K candidate predictive biomarker classifiers B 1 , …, B K thought to be predictive of patients likely to benefit from T relative to C
Eligibility not restricted by candidate classifiers
Using a proportion of patients accrued during the trial, evaluate the candidate classifiers
Select a single candidate classifier B* to use as part of the primary analysis plan in the final analysis. In the final analysis of the subset of B* positive patients, omit those used for the evaluation of the candidate biomarkers
New biotechnology and knowledge of tumor biology provide important opportunities to improve the development and utilization of cancer drugs
Treatment of broad populations with regimens that do not benefit most patients is increasingly no longer necessary nor economically sustainable
The established molecular heterogeneity of human diseases increases the complexity of drug development and requires the use of dramatically new approaches to the development and evaluation of therapeutics