What inference for two-stage phase II trials?

Porcher, Raphaël; Desseaux, Kristell

doi:10.1186/1471-2288-12-117

Cited by 19 publications

(33 citation statements)

References 35 publications

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“…However, this maximum likelihood estimate (MLE) is biased. 2,3 Later, Jung and Kim 2 derived the uniformly minimum variance unbiased estimator (UMVUE) for the response rate by using the Rao–Blackwell theorem. They showed that the unbiased estimate has comparable efficiency when compared to the biased MLE.…”

Section: Introductionmentioning

confidence: 99%

Exact confidence limits for the response rate in two-stage designs with over- or under-enrollment in the second stage

Shan

2016

Stat Methods Med Res

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Simon’s two-stage design has been widely used in early phase clinical trials to assess the activity of a new investigated treatment. In practice, the actual sample sizes do not always follow the study design precisely, especially in the second stage. When over- or under-enrollment occurs in a study, the original critical values for the study design are no longer valid for making proper statistical inference in a clinical trial. The hypothesis for such studies is always one-sided, and the null hypothesis is rejected when only a few responses are observed. Therefore, a one-sided lower interval is suitable to test the hypothesis. The commonly used approaches for confidence interval construction are based on asymptotic approaches. These approaches generally do not guarantee the coverage probability. For this reason, Clopper-Pearson approach can be used to compute exact confidence intervals. This approach has to be used in conjunction with a method to order the sample space. The frequently used method is based on point estimates for the response rate, but this ordering has too many ties which lead to conservativeness of the exact intervals. We propose developing exact one-sided intervals based on the p-value to order the sample space. The proposed approach outperforms the existing asymptotic and exact approaches. Therefore, it is recommended for use in practice.

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Section: Introductionmentioning

confidence: 99%

Exact confidence limits for the response rate in two-stage designs with over- or under-enrollment in the second stage

Shan

2016

Stat Methods Med Res

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“…10 The use of the UMVUE to estimate RR is recommended as it addresses situations when the actual number of patients recruited is equal to or different from preplanned values. 3 The calculation of RR, p-values and CIs has been incorporated in open-access statistical libraries (packages "clinfun" and "OneArmPhaseTwoStudy", R statistical software) based on previously published methods 9,12 . We observed some differences between calculated (p-value) and simulated values (type I error). However, they were not relevant to the most common design constraints used in phase II single-arm trials (0.01 to 0.1 type I errors and 0.1 to 0.2 type II errors).…”

Section: Discussionmentioning

confidence: 99%

“…Two-stage designs are becoming increasingly more common, allowing for early trial termination in cases with low response rates (RRs) towards avoiding wasting time resources on ineffective treatments. 3 These trials aim to determine whether the new regimen is superior to a pre-speci ed RR (often 5%) 4 or experience with the standard of care, whereas the alternative hypothesis is that RR is somewhat higher, say 20%. 4 Nevertheless, the non-inferiority (NI) question might also be relevant in the phase II setting.…”

Section: Introductionmentioning

confidence: 99%

Inclusion of non-inferiority analysis in superiority-based clinical trials with single-arm, two-stage Simon’s design

Sampayo-Cordero

Miguel-Huguet

Peréz-García³

et al. 2019

Preprint

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Background The non-inferiority (NI) hypothesis is not usually considered in the early phases of clinical development. A proof-of-concept phase II study that allows for the analysis of NI, if superiority criteria cannot be met, may balance between multiple endpoints and additional parameters, which will result in more informed decisions in regard to the therapeutics’ potential value. Methods A total of 12,768 two-stage Simon’s design trials were constructed based on different assumptions of rejection response probability, minimum desired response probability, type I and II errors, and NI margins. P-value and type II error were calculated with stochastic ordering using Uniformly Minimum Variance Unbiased Estimator. Type I and II errors were simulated using the Monte Carlo method. Agreement between calculated and simulated values was analyzed with Bland-Altman plots. Results The level of agreement was equivalent between calculated and simulated values in two-stage superiority designs and ones in which switching to NI was allowed. Conclusion Switching to NI analysis, when superiority criteria are not achieved, may be useful for weighing additional factors such as clinical benefit duration, safety, cost, or biomarker strategy while assessing activity and early efficacy rate. Implementation of this strategy can be achieved through simple adaptations to existing designs for one-arm phase II clinical trials.

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“…Porcher and Desseaux [ 3 ] considered different approaches for point and confidence intervals estimation, as well as computation of p-values for the same setting as KC. In their methods, the rankings used for computing p-values were based on estimators instead of likelihood.…”

Section: Introductionmentioning

confidence: 99%

“…They recommended the uniformly minimum variance unbiased estimator (UMVUE) as it exhibited good properties. In particular, when the second stage sample size is unaltered, they pointed out that the method based on UMVUE is equivalent to KC [ 3 ]. For this reason, our method should also improve on their methods.…”

Section: Introductionmentioning

confidence: 99%

Statistical inference for extended or shortened phase II studies based on Simon’s two-stage designs

Zhao

Xiong

2015

BMC Med Res Methodol

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BackgroundSimon’s two-stage designs are popular choices for conducting phase II clinical trials, especially in the oncology trials to reduce the number of patients placed on ineffective experimental therapies. Recently Koyama and Chen (2008) discussed how to conduct proper inference for such studies because they found that inference procedures used with Simon’s designs almost always ignore the actual sampling plan used. In particular, they proposed an inference method for studies when the actual second stage sample sizes differ from planned ones.MethodsWe consider an alternative inference method based on likelihood ratio. In particular, we order permissible sample paths under Simon’s two-stage designs using their corresponding conditional likelihood. In this way, we can calculate p-values using the common definition: the probability of obtaining a test statistic value at least as extreme as that observed under the null hypothesis.ResultsIn addition to providing inference for a couple of scenarios where Koyama and Chen’s method can be difficult to apply, the resulting estimate based on our method appears to have certain advantage in terms of inference properties in many numerical simulations. It generally led to smaller biases and narrower confidence intervals while maintaining similar coverages. We also illustrated the two methods in a real data setting.ConclusionsInference procedures used with Simon’s designs almost always ignore the actual sampling plan. Reported P-values, point estimates and confidence intervals for the response rate are not usually adjusted for the design’s adaptiveness. Proper statistical inference procedures should be used.

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What inference for two-stage phase II trials?

Cited by 19 publications

References 35 publications

Exact confidence limits for the response rate in two-stage designs with over- or under-enrollment in the second stage

Exact confidence limits for the response rate in two-stage designs with over- or under-enrollment in the second stage

Inclusion of non-inferiority analysis in superiority-based clinical trials with single-arm, two-stage Simon’s design

Statistical inference for extended or shortened phase II studies based on Simon’s two-stage designs

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