Sequential Clinical Trials Research Articles

Two-stage group-sequential designs with delayed responses – what is the point of applying corresponding methods?

BackgroundIn group-sequential designs, it is typically assumed that there is no time gap between patient enrollment and outcome measurement in clinical trials. However, in practice, there is usually a lag between the two time points. This can affect the statistical analysis of the data, especially in trials with interim analyses. One approach to address delayed responses has been introduced by Hampson and Jennison (J R Stat Soc Ser B Stat Methodol 75:3-54, 2013), who proposed the use of error-spending stopping boundaries for patient enrollment, followed by critical values to reject the null hypothesis if the stopping boundaries are crossed beforehand. Regarding the choice of a trial design, it is important to consider the efficiency of trial designs, e.g. in terms of the probability of trial success (power) and required resources (sample size and time).MethodsThis article aims to shed more light on the performance comparison of group sequential clinical trial designs that account for delayed responses and designs that do not. Suitable performance measures are described and designs are evaluated using the R package rpact. By doing so, we provide insight into global performance measures, discuss the applicability of conditional performance characteristics, and finally whether performance gain justifies the use of complex trial designs that incorporate delayed responses.ResultsWe investigated how the delayed response group sequential test (DR-GSD) design proposed by Hampson and Jennison (J R Stat Soc Ser B Stat Methodol 75:3-54, 2013) can be extended to include nonbinding lower recruitment stopping boundaries, illustrating that their original design framework can accommodate both binding and nonbinding rules when additional constraints are imposed. Our findings indicate that the performance enhancements from methods incorporating delayed responses heavily rely on the sample size at interim and the volume of data in the pipeline, with overall performance gains being limited.ConclusionThis research extends existing literature on group-sequential designs by offering insights into differences in performance. We conclude that, given the overall marginal differences, discussions regarding appropriate trial designs can pivot towards practical considerations of operational feasibility.

Optimum designs for clinical trials in personalized medicine when response variance depends on treatment

ABSTRACT We study optimal designs for clinical trials when the value of the response and its variance depend on treatment and covariates are included in the response model. Such designs are generalizations of Neyman allocation, commonly used in personalized medicine when external factors may have differing effects on the response depending on subgroups of patients. We develop theoretical results for D-, A-, E- and D A -optimal designs and construct semidefinite programming (SDP) formulations that support their numerical computation. D-, A-, and E-optimal designs are appropriate for efficient estimation of distinct properties of the parameters of the response models. Our formulation allows finding optimal allocation schemes for a general number of treatments and of covariates. Finally, we study frequentist sequential clinical trial allocation within contexts where response parameters and their respective variances remain unknown. We illustrate, with a simulated example and with a redesigned clinical trial on the treatment of neuro-degenerative disease, that both theoretical and SDP results, derived under the assumption of known variances, converge asymptotically to allocations obtained through the sequential scheme. Procedures to use static and sequential allocation are proposed.

The performance of a Bayesian value-based sequential clinical trial design in the presence of an equivocal cost-effectiveness signal: evidence from the HERO trial

BackgroundThere is increasing interest in the capacity of adaptive designs to improve the efficiency of clinical trials. However, relatively little work has investigated how economic considerations – including the costs of the trial – might inform the design and conduct of adaptive clinical trials.MethodsWe apply a recently published Bayesian model of a value-based sequential clinical trial to data from the ‘Hydroxychloroquine Effectiveness in Reducing symptoms of hand Osteoarthritis’ (HERO) trial. Using parameters estimated from the trial data, including the cost of running the trial, and using multiple imputation to estimate the accumulating cost-effectiveness signal in the presence of missing data, we assess when the trial would have stopped had the value-based model been used. We used re-sampling methods to compare the design’s operating characteristics with those of a conventional fixed length design.ResultsIn contrast to the findings of the only other published retrospective application of this model, the equivocal nature of the cost-effectiveness signal from the HERO trial means that the design would have stopped the trial close to, or at, its maximum planned sample size, with limited additional value delivered via savings in research expenditure.ConclusionEvidence from the two retrospective applications of this design suggests that, when the cost-effectiveness signal in a clinical trial is unambiguous, the Bayesian value-adaptive design can stop the trial before it reaches its maximum sample size, potentially saving research costs when compared with the alternative fixed sample size design. However, when the cost-effectiveness signal is equivocal, the design is expected to run to, or close to, the maximum sample size and deliver limited savings in research costs.

Return of participant-level clinical trial results to participants: pilot of a simplified centralised approach

ObjectivesPublic access databases such as clinicaltrials.gov achieve dissemination of clinical trial design and aggregated study results. However, return of participant-level data is rarely done. A key barrier includes the proprietary...

Cost-effectiveness analysis of bimekizumab for the treatment of active psoriatic arthritis in Sweden

AimsTo evaluate the cost-effectiveness of bimekizumab, an inhibitor of IL-17F and IL-17A, against biologic and targeted synthetic disease-modifying antirheumatic drugs (DMARD) for psoriatic arthritis (PsA) from the Swedish healthcare system perspective.Materials and methodsA Markov model was developed to simulate the clinical pathway of biologic [b] DMARD-naïve or tumor necrosis factor inhibitor experienced [TNFi-exp] PsA patients over a lifetime horizon. Treatment response was incorporated as achievement of the American College of Rheumatology 50% (ACR50) and Psoriasis Area and Severity Index 75% (PASI75) response, and changes in the Health Assessment Questionnaire-Disability Index (HAQ-DI) score. The efficacy of bimekizumab was obtained from the BE OPTIMAL (bDMARD-naïve) and BE COMPLETE (TNFi-experienced) trials while a network meta-analysis (NMA) informed the efficacy of the comparators. Resource use and drug costs were obtained from published studies and databases of drug retail prices in Sweden. A willingness-to-pay threshold of €50,000 per quality-adjusted life year (QALY) was applied.ResultsIn bDMARD-naïve patients, bimekizumab achieved greater QALYs (14.08) than with all comparators except infliximab (14.22), dominated guselkumab every 4 and 8 weeks, ixekizumab, secukinumab 300 mg, ustekinumab 45 mg and 90 mg, and was cost-effective against risankizumab, tofacitinib, upadacitinib and TNFis, except adalimumab biosimilar. In TNFi-experienced patients, bimekizumab led to greater QALYs (13.56) than all comparators except certolizumab pegol (13.84), and dominated ixekizumab and secukinumab 300 mg while being cost-effective against all other IL-17A-, IL-23- and JAK inhibitors.LimitationsAn NMA informed the comparative effectiveness estimates. Given gaps in evidence of disease management and indirect costs specific to HAQ-DI scores, and sequential clinical trial evidence in PsA, non-PsA cost data from similar joint conditions were used, and one line of active treatment followed by best supportive care was assumed.ConclusionsBimekizumab was cost-effective against most available treatments for PsA in Sweden, irrespective of prior TNFi exposure

Wilcoxon rank-sum tests to detect one-sided mixture alternatives in group sequential clinical trials.

Traditional methods based on the assumption that the treatment distribution is a pure shift of the control distribution may not always hold. The possibility that an individual from the treatment group may not respond to the treatment motivates the use of a mixture distribution for the treatment group. This paper considers two test procedures based on the Wilcoxon rank-sum statistic for a group sequential design to detect the one-sided mixture alternative. Error spending functions are used for the allocation of error rates at each stage. The two tests are evaluated individually in determination of critical values and arm sizes and asymptotic multivariate normality is shown to hold for both. Upon comparison, the tests are presented to be asymptotically equivalent. Both test statistics maintain the Type I error rate even if is misspecified in the design alternative. A more general definition of the treatment effect is used with the mixture distribution. Method of moments estimators and constrained -means estimators for the treatment effect are evaluated.

On Bayesian Sequential Clinical Trial Designs

Clinical trials usually involve sequential patient entry. When designing a clinical trial, it is often desirable to include a provision for interim analyses of accumulating data with the potential for stopping the trial early. We review Bayesian sequential clinical trial designs based on posterior probabilities, posterior predictive probabilities, and decision-theoretic frameworks. A pertinent question is whether Bayesian sequential designs need to be adjusted for the planning of interim analyses. We answer this question from three perspectives: a frequentist-oriented perspective, a calibrated Bayesian perspective, and a subjective Bayesian perspective. We also provide new insights into the likelihood principle, which is commonly tied to statistical inference and decision making in sequential clinical trials. Some theoretical results are derived, and numerical studies are conducted to illustrate and assess these designs.

Role of Cervical Spinal Magnetic Stimulation in Improving Posture and Functional Ambulation of Patients with Relapsing Remitting Multiple Sclerosis.

Balance impairment is one of the hallmarks of early MS. Proprioceptive deficit was found to be one of the main causes of this imbalance. The cervical enlargement has a strong proprioceptive system, with its projections to the reticular formation and the central pattern generators, helping in rhythmic pattern generation and alternate leg movements. Repetitive trans-spinal magnetic stimulation (rTSMS) is a noninvasive technique, which can trigger massive proprioceptive afferents. Therefore, it has the potential of improving proprioceptive deficits and motor control. Objective. To determine the effectiveness of repetitive cervical magnetic stimulation in improving functional ambulation of patients with relapsing remitting multiple sclerosis (RRMS). Design. Prospective sequential clinical trial. Setting. University and academic hospital. Participants. A total of 32 participants (N = 32) with RRMS. Interventions. Outpatient rehabilitation. The 32 patients received 10 sessions over two weeks of 20 Hz cervical spinal magnetic stimulation (SMS). Both groups were assessed at baseline, after 2 weeks, then one month later. Patients were enrolled as a control group at first and received Sham SMS, and then a wash out period of one month was done for all the patients, followed by a baseline assessment. Second, the same 32 patients rejoined as the active group, which received real magnetic stimulation. Both groups performed an intensive physical therapy program with the spinal magnetic stimulation. Main Outcome Measures. Extended Disability status score (EDSS), Timed up and Go test (TUG), Mini-Best test, dynamic posturography sensory organization composite score, and motor composite score. Results. Thirty-two RRMS patients with EDSS range from 1.5 to 6. They showed statistically significant difference between active and control groups in Mini-Best test score. We divided our patients according to EDSS into 3 subgroups: (a) mild: ≤2.5, (b) moderate: 3-5.5, and (c) severe: ≥6. Mild cases showed significant differences in EDSS score, TUG test, Mini-Best test, and dynamic posturography sensory composite scale. The effect size between the different patient subgroups was also measured and showed highly significant improvements in all measured parameters among our mild patients, indicating that this subgroup could be the best responders to cervical repetitive high-frequency magnetic stimulation. Moderate cases showed highly significant improvement in TUG score and Mini-Best test and significant change in EDSS score and the dynamic posturography sensory composite score. Severe cases showed only significant improvements in TUG, Mini-Best test, and sensory composite score. Conclusion. Cervical repetitive magnetic stimulation can help improve balance and functional ambulation and decreases the risk of falls in RRMS patients, especially in the mild, low disability cases.

Novel Clinical Trial Designs in Neuro-Oncology.

Scientific and technologic advances have led to a boon of candidate therapeutics for patients with malignancies of the central nervous system. The path from drug development to clinical use has generally followed a regimented order of sequential clinical trial phases. The recent increase in novel therapies, however, has strained the regulatory process and unearthed limitations of the current system, including significant cost, prolonged development time, and difficulties in testing therapies for rarer tumors. Novel clinical trial designs have emerged to increase efficiencies in clinical trial conduct to better evaluate and bring impactful drugs to patients in a timely manner. In order to better capture meaningful benefits for brain tumor patients, new endpoints to complement or replace traditional endpoints are also an increasingly important consideration. This review will explore the current challenges in the current clinical trial landscape and discuss novel clinical trial concepts, including consideration of limitations and risks of novel trial designs, within the context of neuro-oncology.

Power Calculations for Replication Studies

The reproducibility crisis has led to an increasing number of replication studies being conducted. Sample sizes for replication studies are often calculated using conditional power based on the effect estimate from the original study. However, this approach is not well suited as it ignores the uncertainty of the original result. Bayesian methods are used in clinical trials to incorporate prior information into power calculations. We propose to adapt this methodology to the replication framework and promote the use of predictive instead of conditional power in the design of replication studies. Moreover, we describe how extensions of the methodology to sequential clinical trials can be tailored to replication studies. Conditional and predictive power calculated at an interim analysis are compared and we argue that predictive power is a useful tool to decide whether to stop a replication study prematurely. A recent project on the replicability of social sciences is used to illustrate the properties of the different methods.

Abstract CT167: Neoadjuvant ipilimumab/nivolumab in locally advanced or oligometastatic melanoma: An open label, single arm, multi-institutional clinical study with molecular and immunological biomarker’s analysis

Abstract Efficacy, safety, together with molecular and immunological biomarkers were studied in a sequential clinical trial of neoadjuvant immunotherapy, surgery and adjuvant immunotherapy in locally advanced or oligometastatic melanoma patients (pts), within an open label, single arm and two sites study. Treatment schedule consisted in four primary cycles of inverted dose ipilimumab 1 mg/kg and nivolumab 3 mg/kg every 3 weeks, followed by radical surgery and adjuvant nivolumab 480 mg every 4 weeks for 6 cycles. Primary objective was pathological complete remission (pCR) rate, according to International Neoadjuvant Melanoma Consortium (INMC) criteria, while secondary objectives were: safety, feasibility and efficacy; QoL; identification of biomarkers of response and resistance; degree of immune activation; longitudinal evaluation of the gut microbiome. From March 2019 to April 2021, 43 pts were enrolled in the trial and, with an intent to treat of 35 pts, 34 completed the primary phase, 31 received surgery and 28 completed the adjuvant phase. Four pts were withdrawn during primary phase for progression (2), toxicity (1) and consent withdrawal (1). Study primary endpoint has been met since 20/31 pts undergoing surgery reached a pCR/near pCR (65%), 4/31 (13%) a pathological partial remission (pPR) and 7/31 (22%) pts a pathological no response. With a median follow-up of 17 months, 33/35 pts are alive. Treatment failure occurred in 9 pts: 2 pts progressed during primary phase and did not undergo surgery; 7 pts progressed during adjuvant (3 pts) or follow-up phase (4 pts). Six out of these 7 pts were classified as pNR at surgery, while the other, classified as pCR, did not receive adjuvant therapy. Both pts in stage IV relapsed. Unfortunately, one pt died for ischemic stroke after 5 months from adjuvant therapy while on CR. Treatment related toxicities were mainly G1-2 and only 6 pts (17%) developed G3-4 adverse events (AE): 3 transaminitis, 1 pneumonitis, 1 myocarditis, 1 CPK increase and 1 dermatomyositis. Translational studies on samples collected before, during therapy and at progression have been performed: whole exome sequencing and gut microbiota dynamics on longitudinal samples showed some relationships with responses and developing resistances. These data, never presented elsewhere previously, are in part new and in part confirmatory of immunological or molecular signatures described by other groups. In conclusion, primary immunotherapy with Ipilimumab/Nivolumab in pts affected by locally advanced/oligometastatic melanoma is able to achieve an elevated pCR/near pCR rate which appears to be predictive of long term relapse free survival. Translational data analyzed longitudinally on each patient can allow for a better selection of pts, giving new insight on the mechanisms of melanoma progression and resistance. Citation Format: Pier Francesco Ferrucci, Bruno Achutti Duso, Luigi Nezi, Luca Mazzarella, Fiorenza Lotti, Sara Gandini, Gianmarco Orsolini, Elisabetta Pennacchioli, Patrizia Gnagnarella, Teresa Manzo, Simone Ribero, Maria Teresa Fierro, Rebecca Senetta, Concetta Riviello, Virginia Caliendo, Pietro Quaglino, Massino Barberis, Giuseppina Bonizzi, Emilia Cocorocchio. Neoadjuvant ipilimumab/nivolumab in locally advanced or oligometastatic melanoma: An open label, single arm, multi-institutional clinical study with molecular and immunological biomarker’s analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT167.

Reproducibility of outcomes in sequential trials using CMV-targeted dendritic cell vaccination for glioblastoma.

2005 Background: Vaccination with dendritic cells (DCs) fares poorly in primary and recurrent glioblastoma (GBM). Moreover, GBM vaccine trials are often underpowered due to limited sample size. Methods: To address these limitations, we conducted three sequential clinical trials utilizing Cytomegalovirus (CMV)-specific DC vaccines in patients with newly diagnosed GBM eligible to receive standard of care resection and adjuvant radiation therapy and temozolomide chemotherapy. Autologous DCs were generated and electroporated with mRNA encoding for the CMV protein pp65. Serial vaccination was given throughout adjuvant temozolomide cycles, and 111Indium radiolabeling was implemented to assess migration efficiency of DC vaccines. Patients were followed for median overall survival (mOS) and OS. Results: Our initial study was the phase II ATTAC study (NCT00639639; total n = 12) with 6 patients randomized to vaccine site preconditioning with tetanus-diphtheria (Td) toxoid. This led to an expanded cohort trial (ATTAC-GM; NCT00639639) of 11 patients receiving CMV DC vaccines containing granulocyte-macrophage colony-stimulating factor (GM-CSF). Follow-up data from ATTAC and ATTAC-GM revealed 5-year OS rates of 33.3% (mOS 38.3 months; CI95 17.5-undefined) and 36.4% (mOS 37.7 months; CI95 18.2-109.1), respectively. ATTAC additionally revealed a significant increase in DC migration to draining lymph nodes following Td preconditioning ( P = 0.049). Increased DC migration was associated with OS (Cox proportional hazards model, HR = 0.820, P = 0.023). Td-mediated increased migration has been recapitulated in our larger confirmatory trial ELEVATE (NCT02366728) of 43 patients randomized to preconditioning (Wilcoxon rank sum, Td n = 24, unpulsed DC n = 19; 24h, P = 0.031 and 48h, P = 0.0195). In ELEVATE, median follow-up of 42.2 months revealed significantly longer OS in patients randomized to Td ( P = 0.026). The 3-year OS for Td-treated patients in ELEVATE was 34% (CI95 19-63%) compared to 6% given unpulsed DCs (CI95 1-42%). Conclusions: We report reproducibility of our findings across three sequential clinical trials using CMV pp65 DCs. Despite their small numbers, these successive trials demonstrate consistent survival outcomes, thus supporting the efficacy of CMV DC vaccine therapy in GBM. Clinical trial information: NCT00639639, NCT02366728.

An alternative metric for evaluating the potential patient benefit of response-adaptive randomization procedures.

When planning a two-arm group sequential clinical trial with a binary primary outcome that has severe implications for quality of life (e.g., mortality), investigators may strive to find the design that maximizes in-trial patient benefit. In such cases, Bayesian response-adaptive randomization (BRAR) is often considered because it can alter the allocation ratio throughout the trial in favor of the treatment that is currently performing better. Although previous studies have recommended using fixed randomization over BRAR based on patient benefit metrics calculated from the realized trial sample size, these previous comparisons have been limited by failures to hold type I and II error rates constant across designs or consider the impacts on all individuals directly affected by the design choice. In this paper, we propose a metric for comparing designs with the same type I and II error rates that reflects expected outcomes among individuals who would participate in the trial if enrollment is open when they become eligible. We demonstrate how to use the proposed metric to guide the choice of design in the context of two recent trials in persons suffering out of hospital cardiac arrest. Using computer simulation, we demonstrate that various implementations of group sequential BRAR offer modest improvements with respect to the proposed metric relative to conventional group sequential monitoringalone.

Designing Multi-arm Multistage Adaptive Trials for Neuroprotection in Progressive Multiple Sclerosis.

There are few treatments shown to slow disability progression in progressive multiple sclerosis (PMS). One challenge has been efficiently testing the pipeline of candidate therapies from preclinical studies in clinical trials. Multi-arm multistage (MAMS) platform trials may accelerate evaluation of new therapies compared to traditional sequential clinical trials. We describe a MAMS design in PMS focusing on selection of interim and final outcome measures, sample size, and statistical considerations. The UK MS Society Expert Consortium for Progression in MS Clinical Trials reviewed recent phase II and III PMS trials to inform interim and final outcome selection and design measures. Simulations were performed to evaluate trial operating characteristics under different treatment effect, recruitment rate, and sample size assumptions. People with MS formed a patient and public involvement group and contributed to the trial design, ensuring it would meet the needs of the MS community. The proposed design evaluates 3 experimental arms compared to a common standard of care arm in 2 stages. Stage 1 (interim) outcome will be whole brain atrophy on MRI at 18 months, assessed for 123 participants per arm. Treatments with sufficient evidence for slowing brain atrophy will continue to the second stage. The stage 2 (final) outcome will be time to 6-month confirmed disability progression, based on a composite clinical score comprising the Expanded Disability Status Scale, Timed 25-Foot Walk test, and 9-Hole Peg Test. To detect a hazard ratio of 0.75 for this primary final outcome with 90% power, 600 participants per arm are required. Assuming one treatment progresses to stage 2, the trial will recruit ≈1,900 participants and last ≈6 years. This is approximately two-thirds the size and half the time of separate 2-arm phase II and III trials. The proposed MAMS trial design will substantially reduce duration and sample size compared to traditional clinical trials, accelerating discovery of effective treatments for PMS. The design was well-received by people with multiple sclerosis. The practical and statistical principles of MAMS trial design may be applicable to other neurodegenerative conditions to facilitate efficient testing of new therapies.

Personalized Risk-Based Screening Design for Comparative Two-Arm Group Sequential Clinical Trials.

Personalized medicine has been emerging to take into account individual variability in genes and environment. In the era of personalized medicine, it is critical to incorporate the patients’ characteristics and improve the clinical benefit for patients. The patients’ characteristics are incorporated in adaptive randomization to identify patients who are expected to get more benefit from the treatment and optimize the treatment allocation. However, it is challenging to control potential selection bias from using observed efficacy data and the effect of prognostic covariates in adaptive randomization. This paper proposes a personalized risk-based screening design using Bayesian covariate-adjusted response-adaptive randomization that compares the experimental screening method to a standard screening method based on indicators of having a disease. Personalized risk-based allocation probability is built for adaptive randomization, and Bayesian adaptive decision rules are calibrated to preserve error rates. A simulation study shows that the proposed design controls error rates and yields a much smaller number of failures and a larger number of patients allocated to a better intervention compared to existing randomized controlled trial designs. Therefore, the proposed design performs well for randomized controlled clinical trials under personalized medicine.

Optimal adaptive promising zone designs.

We develop optimal decision rules for sample size re-estimation in two-stage adaptive group sequential clinical trials. It is usual for the initial sample size specification of such trials to be adequate to detect a realistic treatment effect with good power, but not sufficient to detect the smallest clinically meaningful treatment effect . Moreover it is difficult for the sponsors of such trials to make the up-front commitment needed to adequately power a study to detect . It is easier to justify increasing the sample size if the interim data enter a so-called "promising zone" that ensures with high probability that the trial will succeed. We have considered promising zone designs that optimize unconditional power and promising zone designs that optimize conditional power and have discussed the tension that exists between these two objectives. Where there is reluctance to base the sample size re-estimation rule on the parameter we propose a Bayesian option whereby a prior distribution is assigned to the unknown treatment effect , which is then integrated out of the objective function with respect to its posterior distribution at the interim analysis.

A simulation-based comparison of estimation methods for adaptive and classical group sequential clinical trials.

Statistical methods for controlling the type-I error of hypothesis tests in adaptive group sequential clinical trials are well established and well understood. However, methods for obtaining statistically valid point estimates and confidence intervals for adaptive designs are not as well established or as well understood. At the end of an adaptive trial, one may calculate the repeated confidence interval (RCI), which provides conservative coverage of , or the backward image confidence interval (BWCI), which provides exact coverage of and is an extension of the stagewise adjusted confidence interval (SWCI, used in classical group sequential designs). The BWCI can also provide a median unbiased estimate (MUE) of . There is a need to better understand the coverage and possible biases associated with these methods. We conducted a simulation study exploring parameter estimation following sample size reestimation based on testing methods with strong control of type-I error. Generally, the BWCI provided exact coverage, the naïve CI provided inconsistent coverage, and the RCI provided conservative coverage. Additionally, we note considerable asymmetry in the coverage from above/from below for the RCI, although we did not see any instance where the 95% RCI excluded the true parameter more than 2.5% on either side. At the end of an adaptive group sequential trial, we strongly recommend the use of the BWCI (and associated MUE), with the RCI computed during interim looks; the naïve CI should be avoided. These results and conclusions also hold true for classical group sequential designs.

Expected Value of Sample Information to Guide the Design of Group Sequential Clinical Trials.

IntroductionAdaptive designs allow changes to an ongoing trial based on prespecified early examinations of accrued data. Opportunities are potentially being missed to incorporate health economic considerations into the design of these studies.MethodsWe describe how to estimate the expected value of sample information for group sequential design adaptive trials. We operationalize this approach in a hypothetical case study using data from a pilot trial. We report the expected value of sample information and expected net benefit of sampling results for 5 design options for the future full-scale trial including the fixed-sample-size design and the group sequential design using either the Pocock stopping rule or the O’Brien-Fleming stopping rule with 2 or 5 analyses. We considered 2 scenarios relating to 1) using the cost-effectiveness model with a traditional approach to the health economic analysis and 2) adjusting the cost-effectiveness analysis to incorporate the bias-adjusted maximum likelihood estimates of trial outcomes to account for the bias that can be generated in adaptive trials.ResultsThe case study demonstrated that the methods developed could be successfully applied in practice. The results showed that the O’Brien-Fleming stopping rule with 2 analyses was the most efficient design with the highest expected net benefit of sampling in the case study.ConclusionsCost-effectiveness considerations are unavoidable in budget-constrained, publicly funded health care systems, and adaptive designs can provide an alternative to costly fixed-sample-size designs. We recommend that when planning a clinical trial, expected value of sample information methods be used to compare possible adaptive and nonadaptive trial designs, with appropriate adjustment, to help justify the choice of design characteristics and ensure the cost-effective use of research funding.HighlightsOpportunities are potentially being missed to incorporate health economic considerations into the design of adaptive clinical trials.Existing expected value of sample information analysis methods can be extended to compare possible group sequential and nonadaptive trial designs when planning a clinical trial.We recommend that adjusted analyses be presented to control for the potential impact of the adaptive designs and to maintain the accuracy of the calculations.This approach can help to justify the choice of design characteristics and ensure the cost-effective use of limited research funding.

Impact of minimal sufficient balance, minimization, and stratified permuted blocks on bias and power in the estimation of treatment effect in sequential clinical trials with a binary endpoint.

Minimization is among the most common methods for controlling baseline covariate imbalance at the randomization phase of clinical trials. Previous studies have found that minimization does not preserve allocation randomness as well as other methods, such as minimal sufficient balance, making it more vulnerable to allocation predictability and selection bias. Additionally, minimization has been shown in simulation studies to inadequately control serious covariate imbalances when modest biased coin probabilities (≤0.65) are used. This current study extends the investigation of randomization methods to the analysis phase, comparing the impact of treatment allocation methods on power and bias in estimating treatment effects on a binary outcome using logistic regression. Power and bias in the estimation of treatment effect was found to be comparable across complete randomization, minimization, and minimal sufficient balance in unadjusted analyses. Further, minimal sufficient balance was found to have the most modest impact on power and the least bias in covariate-adjusted analyses. The minimal sufficient balance method is recommended for use in clinical trials as an alternative to minimization when covariate-adaptive subject randomization takes place.

CTIM-10. REPRODUCIBILITY OF CLINICAL TRIALS USING CMV-TARGETED DENDRITIC CELL VACCINES IN PATIENTS WITH GLIOBLASTOMA

Abstract INTRODUCTION Vaccination with dendritic cells (DCs) fares poorly in primary and recurrent glioblastoma (GBM). Moreover, GBM vaccine trials are often underpowered due to limited sample size. METHODS To address these limitations, we conducted three sequential clinical trials utilizing Cytomegalovirus (CMV)-specific DC vaccines in patients with primary GBM. Autologous DCs were generated and electroporated with mRNA encoding for the CMV protein pp65. Serial vaccination was given throughout adjuvant temozolomide cycles, and 111Indium radiolabeling was implemented to assess migration efficiency of DC vaccines. Patients were followed for median overall survival (mOS) and OS. RESULTS Our initial study was the phase II ATTAC study (NCT00639639; total n=12) with 6 patients randomized to vaccine site preconditioning with tetanus-diphtheria (Td) toxoid. This led to an expanded cohort trial (ATTAC-GM; NCT00639639) of 11 patients receiving CMV DC vaccines containing granulocyte-macrophage colony-stimulating factor (GM-CSF). Follow-up data from ATTAC and ATTAC-GM revealed 5-year OS rates of 33.3% (mOS 38.3 months; CI95 17.5-undefined) and 36.4% (mOS 37.7 months; CI95 18.2-109.1), respectively. ATTAC additionally revealed a significant increase in DC migration to draining lymph nodes following Td preconditioning (P=0.049). Increased DC migration was associated with OS (Cox proportional hazards model, HR=0.820, P=0.023). Td-mediated increased migration has been recapitulated in our larger confirmatory trial ELEVATE (NCT02366728) of 43 patients randomized to preconditioning (Wilcoxon rank sum, Td n=24, unpulsed DC n=19; 24h, P=0.031 and 48h, P=0.0195). In ELEVATE, median follow-up of 42.2 months revealed significantly longer OS in patients randomized to Td (P=0.026). The 3-year OS for Td-treated patients in ELEVATE was 34% (CI95 19-63%) compared to 6% given unpulsed DCs (CI95 1-42%). CONCLUSION We report reproducibility of our findings across three sequential clinical trials using CMV pp65 DCs. Despite their small numbers, these successive trials demonstrate consistent survival outcomes, thus supporting the efficacy of CMV DC vaccine therapy in GBM.