A simulation study for comparing testing statistics in response-adaptive randomization
TL;DR: The Cook's correction to chi-square test and Williams' correction to log-likelihood-ratio test are generally recommended for hypothesis test in response-adaptive randomization, especially when sample sizes are small.
Abstract: Background
Response-adaptive randomizations are able to assign more patients in a comparative clinical trial to the tentatively better treatment. However, due to the adaptation in patient allocation, the samples to be compared are no longer independent. At large sample sizes, many asymptotic properties of test statistics derived for independent sample comparison are still applicable in adaptive randomization provided that the patient allocation ratio converges to an appropriate target asymptotically. However, the small sample properties of commonly used test statistics in response-adaptive randomization are not fully studied.
Citations
More filters
TL;DR: This work focuses on the design principles and research issues that lead to particular designs being appealing or unappealing in particular applications, and describes a number of current barriers and suggestions for overcoming them in order to promote wider use of appropriate adaptive designs.
Abstract: Adaptive designs allow planned modifications based on data accumulating within a study. The promise of greater flexibility and efficiency stimulates increasing interest in adaptive designs from clinical, academic, and regulatory parties. When adaptive designs are used properly, efficiencies can include a smaller sample size, a more efficient treatment development process, and an increased chance of correctly answering the clinical question of interest. However, improper adaptations can lead to biased studies. A broad definition of adaptive designs allows for countless variations, which creates confusion as to the statistical validity and practical feasibility of many designs. Determining properties of a particular adaptive design requires careful consideration of the scientific context and statistical assumptions. We first review several adaptive designs that garner the most current interest. We focus on the design principles and research issues that lead to particular designs being appealing or unappealing in particular applications. We separately discuss exploratory and confirmatory stage designs in order to account for the differences in regulatory concerns. We include adaptive seamless designs, which combine stages in a unified approach. We also highlight a number of applied areas, such as comparative effectiveness research, that would benefit from the use of adaptive designs. Finally, we describe a number of current barriers and provide initial suggestions for overcoming them in order to promote wider use of appropriate adaptive designs. Given the breadth of the coverage all mathematical and most implementation details are omitted for the sake of brevity. However, the interested reader will find that we provide current references to focused reviews and original theoretical sources which lead to details of the current state of the art in theory and practice.
208 citations
TL;DR: Subgroup-based adaptive (SUBA), designs that simultaneously search for prognostic subgroups and allocate patients adaptively to the best subgroup-specific treatments throughout the course of the trial, are proposed and found that SUBA compares favorably against the alternatives.
Abstract: Targeted therapies based on biomarker profiling are becoming a mainstream direction of cancer research and treatment. Depending on the expression of specific prognostic biomarkers, targeted therapies assign different cancer drugs to subgroups of patients even if they are diagnosed with the same type of cancer by traditional means, such as tumor location. For example, Herceptin is only indicated for the subgroup of patients with HER2+ breast cancer, but not other types of breast cancer. However, subgroups like HER2+ breast cancer with effective targeted therapies are rare, and most cancer drugs are still being applied to large patient populations that include many patients who might not respond or benefit. Also, the response to targeted agents in humans is usually unpredictable. To address these issues, we propose subgroup-based adaptive (SUBA), designs that simultaneously search for prognostic subgroups and allocate patients adaptively to the best subgroup-specific treatments throughout the course of the trial. The main features of SUBA include the continuous reclassification of patient subgroups based on a random partition model and the adaptive allocation of patients to the best treatment arm based on posterior predictive probabilities. We compare the SUBA design with three alternative designs including equal randomization, outcome-adaptive randomization, and a design based on a probit regression. In simulation studies, we find that SUBA compares favorably against the alternatives.
38 citations
Cites background from "A simulation study for comparing te..."
...There is a need for adaptive designs to accommodate the situations above to improve trial efficiency and maintain trial ethics [19, 20, 21]....
[...]
...There is a need for adaptive designs to accommodate the situations above to improve trial efficiency and maintain trial ethic (Yin et al., 2012; Gu and Lee, 2010; Zhu et al., 2013)....
[...]
TL;DR: A new clinical trial design is developed to address the difficulties and issues in the development and validation of biomarker-based personalized therapies and shows the advantages of using likelihood inference and interim analysis to meet the challenges in the sample size needed and in the constantly evolving biomarker landscape and genomic and proteomic technologies.
Abstract: Background Advances in molecular therapeutics in the past decade have opened up new possibilities for treating cancer patients with personalized therapies, using biomarkers to determine which treatments are most likely to benefit them, but there are difficulties and unresolved issues in the development and validation of biomarker-based personalized therapies. We develop a new clinical trial design to address some of these issues. The goal is to capture the strengths of the frequentist and Bayesian approaches to address this problem in the recent literature and to circumvent their limitations.Methods We use generalized likelihood ratio tests of the intersection null and enriched strategy null hypotheses to derive a novel clinical trial design for the problem of advancing promising biomarker-guided strategies toward eventual validation. We also investigate the usefulness of adaptive randomization (AR) and futility stopping proposed in the recent literature.Results Simulation studies demonstrate the advantag...
37 citations
Cites background from "A simulation study for comparing te..."
...Although such adjustments are available for ER, their counterparts for AR are not yet developed because of the analytic difficulties caused by data-dependent randomization; the inadequacy of χ(2)-approximations under AR is also noted in [35] for comparing two proportions at small samples sizes....
[...]
TL;DR: Most pregnant women access antenatal care late at Abakaliki because of misconception and poverty, and health education and subsidization of cost of medical services will help in reversing the trend of late antenatal booking.
Abstract: Background: Antenatal care is one of the pillars of SAFE Motherhood Initiative aimed at preventing adverse pregnancy outcome. Early antenatal booking is recommended for this benefit. Aim: The objective of this study was to determine the antenatal booking pattern of pregnant women and its determinants. Subjects and Methods: A crossâÂÂÂÂsectional survey of pregnant women attending the antenatal booking clinic at Federal Medical Centre Abakaliki Ebonyi State between April 6, 2011 to August 5, 2011 was undertaken. Epi info 2008 version was used for analysis. Results: The mean age of the respondents was 27.46 (5.81) years and the mean gestational age at booking was 24.33 (5.52) weeks. A total of 83.1% (286/344) of the pregnant women booked after the first trimester while the remaining 16.9% (56/344) booked early. SocioâÂÂÂÂbiological variables and past obstetrics history did not contribute significantly to the gestational age at booking while sickness in index pregnancy, personal wishes, and financial constraint were statistically significant reasons given for seeking antenatal care. Majority of the pregnant women 37.2% (128/344) suggested that the second trimester was the ideal gestational age for booking while 18.3% (63/344) did not know the ideal gestational age for booking. Most pregnant women 81.1% ( 279/344) knew the benefits of early antenatal care even though they booked late 83.1% (286/344). Conclusion: Most pregnant women access antenatal care late at Abakaliki because of misconception and poverty. Health education and subsidization of cost of medical services will help in reversing the trend of late antenatal booking.
33 citations
TL;DR: Male and female schistosomal parasites differ in gene expression patterns, many metabolic and biological pathways have been identified in this study and genes differentially expressed in gender specific manner were presented.
Abstract: Background
Schistosoma japonicum is one of the remarkable Platyhelminths that are endemic in China and Southeast Asian countries. The parasite is dioecious and can reside inside the host for many years. Rapid reproduction by producing large number of eggs and count-react host anti-parasite responses are the strategies that benefit long term survival of the parasite. Praziquantel is currently the only drug that is effective against the worms. Development of novel antiparasite reagents and immune-prevention measures rely on the deciphering of parasite biology. The decoding of the genomic sequence of the parasite has made it possible to dissect the functions of genes that govern the development of the parasite. In this study, the polyadenylated transcripts from male and female S. japonicum were isolated for deep sequencing and the sequences were systematically analysed.
Results
First, the number of genes actively expressed in the two sexes of S. japonicum was similar, but around 50% of genes were biased to either male or female in expression. Secondly, it was, at the first time, found that more than 50% of the coding region of the genome was transcribed from both strands. Among them, 65% of the genes had sense and their cognate antisense transcripts co-expressed, whereas 35% had inverse relationship between sense and antisense transcript abundance. Further, based on gene ontological analysis, more than 2,000 genes were functionally categorized and biological pathways that are differentially functional in male or female parasites were elucidated.
Conclusions
Male and female schistosomal parasites differ in gene expression patterns, many metabolic and biological pathways have been identified in this study and genes differentially expressed in gender specific manner were presented. Importantly, more than 50% of the coding regions of the S. japonicum genome transcribed from both strands, antisense RNA-mediated gene regulation might play a critical role in the parasite biology.
31 citations
Cites methods from "A simulation study for comparing te..."
...The general Chi test was employed which has been proved to be one of the most efficient tests [32]....
[...]
References
More filters
2,793 citations
"A simulation study for comparing te..." refers methods in this paper
...More detailed exposition of Bayesian methods for response adaptive randomization is beyond the scope of this paper and interested readers should consult the original work on this topic [37-40]....
[...]
Book•
15 Sep 1999TL;DR: A short history of sequential and group sequential methods can be found in this paper, where the authors present a road map for the application of two-sided tests for comparing two treatments with normal response of known variance.
Abstract: INTRODUCTION About This Book Why Sequential Methods A Short History of Sequential and Group Sequential Methods Chapter Organization: A Roadmap Bibliography and Notes TWO-SIDED TESTS: INTRODUCTION Two-Sided Tests for Comparing Two Treatments with Normal Response of Known Variance A Fixed Sample Test Group Sequential Tests Pocock's Test O'Brien and Fleming's Test Properties of Pocock and O'Brien and Fleming Tests Other Tests Conclusions TWO-SIDED TESTS: GENERAL APPLICATIONS A Unified Formulation Applying the Tests with Equal Group Sizes Applying the Tests with Unequal Increments in Information Normal Linear Models Other Parametric Models Binary Data: Group Sequential Tests for Proportions The Group Sequential Log-Rank Test for Survival Data Group Sequential t-Tests ONE-SIDED TESTS Introduction The Power Family of One-Sided Group Sequential Tests Adapting Power Family Tests to Unequal Increments in Information Group Sequential One-Sided t-Tests Whitehead's Triangular Test TWO-SIDED TESTS WITH EARLY STOPPING UNDER THE NULL HYPOTHESIS Introduction The Power Family of Two-Sided, Inner Wedge Tests Whitehead's Double Triangular Test EQUIVALENCE TESTS Introduction One-Sided Tests of Equivalence Two-Sided Tests of Equivalence: Application to Comparative Bioavailability Studies Individual Bioequivalence: A One-Sided Test for Proportions Bibliography and Notes FLEXIBLE MONITORING: THE ERROR SPENDING APPROACH Unpredictable Information Sequences Two-Sided Tests One-Sided Tests Data Dependent Timing of Analyses Computations for Error Spending Tests ANALYSIS FOLLOWING A SEQUENTIAL TEST Introduction Distribution Theory Point Estimation P-Values Confidence intervals REPEATED CONFIDENCE INTERVALS Introduction Example: Difference of Normal Means Derived Tests: Use of RCIs to Aid Early Stopping Decisions Repeated P-Values Discussion STOCHASTIC CURTAILMENT Introduction Conditional Power Approach Predictive Power Approach A Parameter-Free Approach A Case Study with Survival Data Bibliography and Notes GENERAL GROUP SEQUENTIAL DISTRIBUTION THEORY Introduction A Standard Joint Distribution for Successive Estimates of a Parameter Vector Normal Linear Models Normal Linear Models with Unknown Variance: Group Sequential t-Tests Example: An Exact One-Sample Group Sequential t-Test General Parametric Models: Generalized Linear Models Connection with Survival Analysis BINARY DATA A Single Bernoulli Probability Two Bernoulli Probabilities The Odds Ratio and Multiple 2 x 2 Tables Case-Control and Matched Pair Analysis Logistic Regression: Adjusting for Covariates Bibliography and Notes SURVIVAL DATA Introduction The Log Rank Test The Stratified Log-Rank Test Group Sequential Methods for Survival Data with Covariates Repeated Confidence Intervals for a Hazard Ratio Example: A Clinical Trial for Carcinoma of the Oropharynx Survival Probabilities and Quantiles Bibliography and Notes INTERNAL PILOT STUDIES: SAMPLE SIZE RE-ESTIMATION The Role of an Internal Pilot Phase Sample Size Re-estimation for a Fixed Sample Test Sample Size Re-estimation in Group Sequential Tests MULTIPLE ENDPOINTS Introduction The Bonferroni Procedure A Group Sequential Hotelling Test A Group Sequential Version of O'Brien's Test Tests Based on other Global Statistics Tests Based on Marginal Criteria Bibliography and Notes MULTI-ARMED TRIALS Introduction Global Tests Monitoring Pairwise Comparisons Bibliography and Notes ADAPTIVE TREATMENT ASSIGNMENT A Multi-Stage Adaptive Design A Multi-Stage Adaptive Design with Time Trends Validity of Adaptive Multi-Stage Procedures Bibliography and Notes BAYESIAN APPROACHES The Bayesian Paradigm Stopping Rules Choice of Prior Distribution Discussion NUMERICAL COMPUTATIONS FOR GROUP SEQUENTIAL TESTS Introduction The Basic Calculation Error Probabilities and Sample Size Distributions Tests Defined by Error Spending Functions Analysis Following a Group Sequential Test Further Applications of Numerical Computation Computer Software
1,138 citations
"A simulation study for comparing te..." refers background in this paper
...The derivation of TRisk, TOdds, TWald, TChisq, and TLLR can be found in [33,34], which is equivalent to minimizing the variance of corresponding test statistic at a fixed total sample size, and consequently the power of that test statistic is maximized....
[...]
TL;DR: In this article, a simple randomized treatment assignment rule is proposed and analyzed in a sequential medical trial, and on the average this rule assigns more patients to the better treatment, and it is applicable to the case where patients have delayed responses to treatments.
Abstract: In a sequential medical trial, a simple randomized treatment assignment rule is proposed and analyzed. On the average this rule assigns more patients to the better treatment, and it is applicable to the case where patients have delayed responses to treatments. This new assignment rule is studied for both a fixed sample size and an inverse stopping rule.
441 citations
"A simulation study for comparing te..." refers background or methods in this paper
...Many RAR designs have been proposed over the years [1-13]....
[...]
...Among the three allocation targets that assign more patients to the better treatment (RRSIHR, RRisk and RRPW), RRSIHR has a stable and often the lowest variation in patient allocation....
[...]
...For SEU method [13], if the limiting allocation of RPW urn is the target in a two-arm trial, then q i q i q ii ∧ ∧ ∧( ) ( ) + ( )⎡ ⎣⎢ ⎤ ⎦⎥ / 1 2 balls of type 2 and q i q i q i ∧ ∧ ∧( ) ( ) + ( )⎡ ⎣⎢ ⎤ ⎦⎥2 1 2 / balls of type 1 are added to the urn following the allocation of the ith patient....
[...]
...When RRPW (the same as RDL) is the allocation target, DL urn method has the lowest variation in patient allocation, which is consistent with the fact that the lower bound of the estimate of Var(RRPW) is attained by DL urn [4]....
[...]
...The simulation comparison of statistical power for different RAR methods also indicates that DL urn has the best statistical properties at RRPW, mainly due to its low variation in patient allocation....
[...]
TL;DR: Investigation of the conduct of a clinical trial where the “Play the Winner Rule” (PWR) is used to assign patients to the different therapies shows that over a wide range of situations this rule leads to near optimum results when used in a two-stage manner.
Abstract: Consider a clinical trial to compare two treatments where response is dichotomous and patients enter the trial sequentially. This paper investigates the conduct of such a trial where the “Play the Winner Rule” (PWR) is used to assign patients to the different therapies. The implementation of the PWR in a clinical trial tends to place more patients on the better treatment. Both theoretical and numerical investigations show that over a wide range of situations this rule leads to near optimum results when used in a two-stage manner. Furthermore, these results are insensitive to optimum sample size requirements.
436 citations
"A simulation study for comparing te..." refers background or methods in this paper
...Many RAR designs have been proposed over the years [1-13]....
[...]
...Among the three allocation targets that assign more patients to the better treatment (RRSIHR, RRisk and RRPW), RRSIHR has a stable and often the lowest variation in patient allocation....
[...]
...For SEU method [13], if the limiting allocation of RPW urn is the target in a two-arm trial, then q i q i q ii ∧ ∧ ∧( ) ( ) + ( )⎡ ⎣⎢ ⎤ ⎦⎥ / 1 2 balls of type 2 and q i q i q i ∧ ∧ ∧( ) ( ) + ( )⎡ ⎣⎢ ⎤ ⎦⎥2 1 2 / balls of type 1 are added to the urn following the allocation of the ith patient....
[...]
...When RRPW (the same as RDL) is the allocation target, DL urn method has the lowest variation in patient allocation, which is consistent with the fact that the lower bound of the estimate of Var(RRPW) is attained by DL urn [4]....
[...]
...The simulation comparison of statistical power for different RAR methods also indicates that DL urn has the best statistical properties at RRPW, mainly due to its low variation in patient allocation....
[...]
01 Jan 2000
TL;DR: In this article, simple adjustments of these confidence intervals based on adding four pseudo observations, half of each type, perform surprisingly well even for small samples, and one can bypass awkward sample size guidelines and use the same formulas with small and large samples.
Abstract: Abstract The standard confidence intervals for proportions and their differences used in introductory statistics courses have poor performance, the actual coverage probability often being much lower than intended. However, simple adjustments of these intervals based on adding four pseudo observations, half of each type, perform surprisingly well even for small samples. To illustrate, for a broad variety of parameter settings with 10 observations in each sample, a nominal 95% interval for the difference of proportions has actual coverage probability below .93 in 88% of the cases with the standard interval but in only 1% with the adjusted interval; the mean distance between the nominal and actual coverage probabilities is .06 for the standard interval, but .01 for the adjusted one. In teaching with these adjusted intervals, one can bypass awkward sample size guidelines and use the same formulas with small and large samples.
412 citations
"A simulation study for comparing te..." refers background in this paper
...Similarly, Agresti and Caffo proposed a modification to TWald by adding 1 to each cell of a contingency table [30], which results in the test statistic TMW in Table 2....
[...]