Adaptive design clinical trials: a review of the literature and ClinicalTrials.gov

Characterization of medical device randomized controlled trials with adaptive designs

Aim: Adaptive designs are frequently used in drug randomized controlled trials (RCTs). However, their use in medical device RCTs remains unclear. We aimed to characterize medical device RCTs with adaptive designs. Materials & methods: We searched for adaptive RCTs in the following databases: ClinicalTrials.gov, International Clinical Trials Registry Platform and the International Standard Randomised Controlled Trial Number registry. Adaptive design keywords and medical device corporation names were used as terms to search the trial records registered between 1 January 2000 and 18 October 2024 in the databases. The annual number and proportions of adaptive trials were analyzed, and characteristics such as design type, sponsor, therapeutic area, trial stage and regulatory status were summarized. Results: Overall, 105 adaptive RCTs were identified from ClinicalTrials.gov, accounting for 2.112 per 1000 trials in 49,721 medical device clinical trials registered in ClinicalTrials.gov during the period. The average annual number of adaptive RCTs per 1000 clinical trials was the highest (8.55 ± 11.65) during 2005-2010, reduced to 3.33 ± 2.35 during 2011-2016, and significantly decreased to 1.29 ± 0.85 during 2017-2024 (p = 0.011). The most common adaptive designs were group sequential design (GSD, 50.5%), sample size reassessment (SSR, 17.1%) and investigating both superiority and non-inferiority (10.5%). Most RCTs were sponsored by the private sector (62.9%), conducted in Europe/North America (95.2%), in the field of heart disease (46.7%) and post-market trials (76.2%). Compared with pre-market RCTs, post-market RCTs showed more diverse adaptive designs such as response-adaptive randomization and adaptive enrichment. Conclusion: The average annual proportions of adaptive medical device RCTs in ClinicalTrials.gov has reduced in the last 10 years. The most-used adaptive designs in medical device RCTs are GSD, SSR and investigating both superiority and non-inferiority.

Seamless trials in oncology: A cross-sectional analysis of characteristics and reporting

OBJECTIVES

Seamless clinical trials have received much attention as a possible way to expedite drug development. The growing importance of seamless design can be seen in oncology research, especially in the early stages of drug development. Our objective is to examine the basic characteristics of seamless early-phase oncology trials registered on the ClinicalTrials.gov database and to determine their results reporting rates. We also aim to identify factors associated with results reporting.

METHODS

Cross-sectional study. We defined seamless early-phase trials as either those registered as Phase 1/2 or Phase 1 with planned expansion cohort(s). Using the ClinicalTrials.gov registry, we searched for interventional cancer clinical trials with primary completion date (PCD) between 2016 and 2020. After trial selection, we performed manual data extraction based on the trial record description and the results posted in the trial registry. We used logistic regression to search for predictors of results reporting. Protocol: https://osf.io/m346x/.

RESULTS

We included 1051 seamless early-phase oncology trials reported as completed (PCD) between 2016 and 2020. We provided descriptive statistics including the number of patients enrolled, study start date, primary completion date, funding, type of intervention, cancer type, design details, type of endpoints, recruitment regions, and number of trial sites. Overall, only 34.7% trials reported results on ClinicalTrials.gov. The results reporting rates for 24 months was 24.0%. The overall reporting rate for Phase 1/2 studies was over three times higher than for seamless Phase 1.

CONCLUSIONS

Our study provides cross-sectional data on seamless early-phase oncology trials registered on ClinicalTrials.gov. We highlight the challenges of the evolving clinical trial design landscape and the problem of missing results in the seamless design context, which raises serious ethical concerns. Efforts should be made to adapt the functionality of the ClinicalTrials.gov database to emerging clinical trial models.

A review of the potential use of melatonin in cancer treatment: Data analysis from Clinicaltrials.gov

BACKGROUND

Melatonin's antioxidative and immune effects suggest potential in cancer therapy. This review assesses related clinical trials on ClinicalTrials.gov.

METHODS

All ClinicalTrials.gov trials registered up to January 17, 2024 were examined, focusing on trials that involved use of melatonin in cancer treatment. A 46 trials were summarized by their study status, study phase, study type, funder type and study results in the use of melatonin in cancer treatment.

RESULTS

The examination of the research data revealed a collective count of 46 clinical trials enlisted on ClinicalTrials.gov, all focus around the utilization of melatonin in cancer treatment. Among these, 24 trials had reached completion, constituting 91.3% of the entire trials, while 5 trials were presently in the recruitment phase, making up 10.8% of the total. None of these trials had received approval for marketing yet. The majority focus of the analysis encompassed interventional studies, around 42 trials and representing 91.3% of the overall trials, thereby incorporating most enrolled patients. In contrast, observational studies are a smaller fraction, comprising 4 trials (8.6% of the total), with a correspondingly lower number of involved patients. Regarding funding sources, most registered studies secured funding from diverse entities such as individuals, universities, and organizations, constituting 95.6% of all trials. In comparison, a minority of studies received funding from the National Institutes of Health, comprising 5 trials and accounting for 10.8% of the total trials.

CONCLUSION

The analysis of 46 clinical trials on melatonin's use in cancer treatment reveals a significant importance on interventional studies. Overall, these findings contribute to the evolving understanding of melatonin's role in cancer treatment.

The Great Controversy of Obstructive Sleep Apnea Treatment for Cardiovascular Risk Benefit: Advancing the Science Through Expert Consensus. An Official American Thoracic Society Workshop Report

The prevalence of obstructive sleep apnea (OSA) is on the rise, driven by various factors including more sensitive diagnostic criteria, increased awareness, enhanced technology through at-home testing enabling easy and cost-effective diagnosis, and a growing incidence of comorbid conditions such as obesity. Treating symptomatic patients with OSA syndrome to enhance quality of life remains a cornerstone approach. However, there is a lack of consensus regarding treatment to improve cardiovascular disease (CVD) outcomes, particularly in light of overall negative results from several randomized controlled trials (RCT) indicating no benefit of positive airway pressure (PAP) therapy on primary and secondary CVD events. These RCTs were limited by suboptimal PAP adherence, use of composite CVD outcomes, and limited diversity and generalizability to Sleep Clinic patients. As such, this workshop assembled clinical experts, as well as researchers in basic and translational science, epidemiology, clinical trials, and population health to discuss the current state, and future research directions to guide personalized therapeutic strategies and future research directions in OSA. There was overall consensus among workshop participants that OSA represents a heterogeneous disease with variable endotypes and phenotypes, and heterogeneous responses to treatment. Future research should prioritize employing multi-modal therapeutic approaches within innovative and adaptive trial designs, focusing on specific subgroups of OSA patients hypothesized to benefit from a CVD perspective. Future work should also be inclusive of diverse populations and consider the life-course of OSA to better comprehend treatment strategies that can address the disproportionate impact of OSA on racially minoritized groups. Further, a more holistic approach to sleep must be adopted to include broader assessments of symptoms, sleep duration, and comorbid sleep and circadian disorders. Finally, it is imperative to establish a sleep research consortium dedicated to collecting raw data and biospecimens categorized by OSA subtypes. This will facilitate mechanistic determinations, foster collaborative research, and help bolster the pipeline of early-career researchers.

Adaptive Trials in Stroke: Current Use and Future Directions

Inclusion of adaptive design features in a clinical trial provides preplanned flexibility to dynamically modify a trial during its conduct while preserving validity and integrity. Adaptive trials are needed to accelerate the conduct of more efficient, informative, and ethical clinical research in the field of neurology. Stroke is a natural candidate for adoption of these innovative approaches to trial design. This Research Methods in Neurology article is informed by a scoping review that identified 45 completed or ongoing adaptive clinical trials in stroke that were appraised: 15 trials had published results with or without a published protocol and 30 ongoing trials (14 trials had a published protocol, and 16 trials were registered only). Interventions spanned acute (n = 28), rehabilitation (n = 8), prevention (n = 8), and rehabilitation and prevention (n = 1). A subsample of these trials was selected to illustrate the utility of adaptive design features and discuss why each adaptive feature was incorporated in the design to best achieve the aim; whether each individual feature was used and whether it resulted in expected efficiencies; and any learnings during preparation, conduct, or reporting. We then discuss the operational, ethical, and regulatory considerations that warrant careful consideration during adaptive trial planning and reflect on the workforce readiness to deliver adaptive trials in practice. We conclude that adaptive trials can be designed, funded, conducted, and published for a wide range of research questions and offer future directions to support adoption of adaptive trial designs in stroke and neurologic research more broadly.

Preclinical and clinical studies in the drug development process of European Medicines Agency-approved non-HIV antiviral agents: a narrative review

BACKGROUND

Viral diseases represent a substantial global health challenge, necessitating the urgent development of effective antiviral medications.

OBJECTIVES

This review aims to present a thorough examination of systemic antiviral drugs approved by the European Medicines Agency (EMA) since its founding, excluding those targeting HIV, with a focus on preclinical and clinical studies in the drug development process.

SOURCES

Data was extracted from the European Public Assessment Reports and Summary of Product Characteristics issued by the EMA.

CONTENT

In total, 21 currently approved agents were analysed with a focus on preclinical and clinical studies. The majority of substances have been approved for hepatitis C (38%) and B (19%) followed by influenza and SARS-CoV-2 (14% and 10%, respectively). A smaller subset obtained approval for the indications of hepatitis D, cytomegalovirus, and pox viruses. As for preclinical studies, heterogeneity in the methods used for efficacy studies was observed, which is at least partly explained by the diverse nature of viruses and their hosts and the lack of general guidelines for antiviral pharmacokinetics and pharmacodynamics studies by the EMA. Clinical studies varied in sample sizes, ranging from a few hundred to several thousand patients. Many antiviral agents have a high potential for cytochrome P450 (CYP) and other enzyme interactions, resulting in the need for a high number of drug-drug interaction studies. Special market authorizations are available, including conditional approval for urgently required drugs such as nirmatrelvir/ritonavir for the treatment of COVID-19, and authorization under exceptional circumstances when comprehensive data cannot be provided, as seen with tecovirimat for pox viruses.

IMPLICATIONS

Streamlining the drug development process of antiviral substances and providing more guidelines would be crucial given the ongoing demand for effective treatment options for existing and new viral diseases.

Adaptive designs in dermatology clinical trials: Current status and future perspectives

Current drug development strategies present many challenges that can impede drug approval by regulatory agencies. Alternative study models, such as adaptive trial designs, have recently sparked interest, as they provide a flexible and more efficient approach in conducting clinical trials. Adaptive trial designs offer several potential benefits over traditional randomized controlled trials, which include decrease in costs, reduced clinical development time and limiting exposure of patients to potentially ineffective treatments allowing completion of studies with fewer patients. This article explores the current use of adaptive trial designs in non-oncologic skin diseases and highlights the most common types of adaptive designs used in the field. We also review the operational challenges and statistical considerations associated with such designs and propose clinical development strategies to successfully implement adaptive designs. The article also proposes instances where adaptive trial designs are particularly beneficial, and other situations where they may not be very useful.

A landscape of methodology and implementation of adaptive designs in cancer clinical trials

BACKGROUND

The use of adaptive designs in cancer trials has considerably increased worldwide in recent years, along with the release of various guidelines for their application. This systematic review aims to comprehensively summarize the key methodological and executive features of adaptive designs in cancer clinical trials.

METHODS

A comprehensive search from PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials was conducted to screen eligible clinical trials that employed adaptive designs and were conducted in cancer patients. The methodological and executive characteristics of adaptive designs were the main measurements extracted. Descriptive analyses, primarily consisting of frequency and percentage, were employed to analyzed and reported the data.

RESULTS

A total of 180 cancer clinical trials with adaptive designs were identified. The first three most common type of adaptive design was the group sequential design (n=114, 63.3 %), adaptive dose-finding design (n=22, 12.2 %), and adaptive platform design (n=16, 8.9 %). The results showed that 4.4 % (n=8) of trials conducted post hoc modifications, and around 29.4 % (n=53) did not provide the methods for controlling type I errors. Among phase II or above trials, 79.9 % (112/140) applied the surrogate endpoint as the primary outcome in these trials. Importantly, 27.2 % (49/180) of trials did not report clear information on the independent data monitoring committee (iDMC), and 13.3 % (n=24) without clear information on interim analyses. Interim analyses suggested 34.4 % (62/180) of trials being stopped for futility, 10.6 % (n=19) for efficacy, and 2.2 % (n=4) for safety concerns in the early stage.

CONCLUSIONS

This study emphasizes adaptive designs in cancer trials face significant challenges in their design or strict implementation according to protocol, which might significantly compromise the validity and integrity of trials. It is thus important for researchers, sponsors, and policymakers to actively oversee and guide their application.

Adaptive designs were primarily used but inadequately reported in early phase drug trials

BACKGROUND

Faced with the high cost and limited efficiency of classical randomized controlled trials, researchers are increasingly applying adaptive designs to speed up the development of new drugs. However, the application of adaptive design to drug randomized controlled trials (RCTs) and whether the reporting is adequate are unclear. Thus, this study aimed to summarize the epidemiological characteristics of the relevant trials and assess their reporting quality by the Adaptive designs CONSORT Extension (ACE) checklist.

METHODS

We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL) and ClinicalTrials.gov from inception to January 2020. We included drug RCTs that explicitly claimed to be adaptive trials or used any type of adaptative design. We extracted the epidemiological characteristics of included studies to summarize their adaptive design application. We assessed the reporting quality of the trials by Adaptive designs CONSORT Extension (ACE) checklist. Univariable and multivariable linear regression models were used to the association of four prespecified factors with the quality of reporting.

RESULTS

Our survey included 108 adaptive trials. We found that adaptive design has been increasingly applied over the years, and was commonly used in phase II trials (n = 45, 41.7%). The primary reasons for using adaptive design were to speed the trial and facilitate decision-making (n = 24, 22.2%), maximize the benefit of participants (n = 21, 19.4%), and reduce the total sample size (n = 15, 13.9%). Group sequential design (n = 63, 58.3%) was the most frequently applied method, followed by adaptive randomization design (n = 26, 24.1%), and adaptive dose-finding design (n = 24, 22.2%). The proportion of adherence to the ACE checklist of 26 topics ranged from 7.4 to 99.1%, with eight topics being adequately reported (i.e., level of adherence ≥ 80%), and eight others being poorly reported (i.e., level of adherence ≤ 30%). In addition, among the seven items specific for adaptive trials, three were poorly reported: accessibility to statistical analysis plan (n = 8, 7.4%), measures for confidentiality (n = 14, 13.0%), and assessments of similarity between interim stages (n = 25, 23.1%). The mean score of the ACE checklist was 13.9 (standard deviation [SD], 3.5) out of 26. According to our multivariable regression analysis, later published trials (estimated β = 0.14, p < 0.01) and the multicenter trials (estimated β = 2.22, p < 0.01) were associated with better reporting.

CONCLUSION

Adaptive design has shown an increasing use over the years, and was primarily applied to early phase drug trials. However, the reporting quality of adaptive trials is suboptimal, and substantial efforts are needed to improve the reporting.

Adaptive design trials in eating disorder research: A scoping review

OBJECTIVE

This scoping review sought to map the breadth of literature on the use of adaptive design trials in eating disorder research.

METHOD

A systematic literature search was conducted in Medline, Scopus, PsycInfo, Emcare, Econlit, CINAHL and ProQuest Dissertations and Theses. Articles were included if they reported on an intervention targeting any type of eating disorder (including anorexia nervosa, bulimia nervosa, binge-eating disorder, and other specified feeding or eating disorders), and employed the use of an adaptive design trial to evaluate the intervention. Two independent reviewers screened citations for inclusion, and data abstraction was performed by one reviewer and verified by a second.

RESULTS

We identified five adaptive design trials targeting anorexia nervosa, bulimia nervosa and binge-eating disorder conducted in the USA and Australia. All employed adaptive treatment arm switching based on early response to treatment and identified a priori stopping rules. None of the studies included value of information analysis to guide adaptive design decisions and none included lived experience perspectives.

DISCUSSION

The limited use of adaptive designs in eating disorder trials represents a missed opportunity to improve enrolment targets, attrition rates, treatment outcomes and trial efficiency. We outline the range of adaptive methodologies, how they could be applied to eating disorder research, and the specific operational and statistical considerations relevant to adaptive design trials.

PUBLIC SIGNIFICANCE

Adaptive design trials are increasingly employed as flexible, efficient alternatives to fixed trial designs, but they are not often used in eating disorder research. This first scoping review identified five adaptive design trials targeting anorexia nervosa, bulimia nervosa and binge-eating disorder that employed treatment arm switching adaptive methodology. We make recommendations on the use of adaptive design trials for future eating disorder trials.

The Next Horizon of Drug Development: External Control Arms and Innovative Tools to Enrich Clinical Trial Data

Conducting clinical trials (CTs) has become increasingly costly and complex in terms of designing and operationalizing. These challenges exist in running CTs on novel therapies, particularly in oncology and rare diseases, where CTs increasingly target narrower patient groups. In this study, we describe external control arms (ECA) and other relevant tools, such as virtualization and decentralized clinical trials (DCTs), and the ability to follow the clinical trial subjects in the real world using tokenization. ECAs are typically constructed by identifying appropriate external sources of data, then by cleaning and standardizing it to create an analysis-ready data file, and finally, by matching subjects in the external data with the subjects in the CT of interest. In addition, ECA tools also include subject-level meta-analysis and simulated subjects' data for analyses. By implementing the recent advances in digital health technologies and devices, virtualization, and DCTs, realigning of CTs from site-centric designs to virtual, decentralized, and patient-centric designs can be done, which reduces the patient burden to participate in the CTs and encourages diversity. Tokenization technology allows linking the CT data with real-world data (RWD), creating more comprehensive and longitudinal outcome measures. These tools provide robust ways to enrich the CT data for informed decision-making, reduce the burden on subjects and costs of trial operations, and augment the insights gained for the CT data.

A systematic survey of adaptive trials shows substantial improvement in methods is needed

OBJECTIVES

To investigate the design, conduct, and analysis of adaptive trials through a systematic survey and provide recommendations for future adaptive trials.

STUDY DESIGN AND SETTING

We systematically searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases up to January 2020. We included trials that were self-described as adaptive trials or applied adaptive designs. We identified three frequently used adaptive designs and summarized their methodological details in terms of design, conduct, and analysis. Lastly, we provided recommendations for future adaptive trials.

RESULTS

We included a total of 128 trials in this study. The primary motivations for using adaptive design were to speed up the trials and facilitate decision-making (n = 29, 31.5%). The three most frequently used methods were group sequential design (GSD) (n = 71, 55.5%), adaptive dose-finding design (ADFD) (n = 35, 27.3%), and adaptive randomization design (ARD) (n = 26, 20.3%). The timing and frequency of interim analysis were detailed in three-fourths of the GSD trials (n = 55, 77.5%) and in half of the ADFD trials (n = 19, 54.3%); however, more than half of the ARD trials (n = 15, 57.7%) did not provide this information. Some trials selected a different outcome than the primary outcome for interim analysis (GSD: n = 7, 12.7%; ADFD: n = 8, 27.6%; ARD: n = 7, 50.0%), but the majority of these trials did not provide explicit reasons for this choice (GSD: n = 7, 100.0%; ADFD: n = 7, 87.5%; ARD: n = 5, 71.4%). More than half (n = 76, 59.4%) of trials did not mention the accessibility of supporting documents, and two-thirds (n = 86, 67.2%) did not state the establishment of independent data monitoring committees (IDMCs). Moreover, unplanned adjustments were observed during the conduct of one-sixth adaptive trials (n = 22, 17.2%). Based on our findings, we provide 14 recommendations for improving adaptive trials in the future.

CONCLUSION

Substantial improvements were needed in methods of adaptive trials, particularly in the areas of interim analysis, the establishment of independent data monitoring committees, and unplanned adjustments. In this study, we offer recommendations from both general and specific aspects for researchers to carefully design, conduct, and analyze adaptive trials.

The Story of ECMO

Extracorporeal Circulation in Neonatal Respiratory Failure: A Prospective Randomized Study. By RH Bartlett, DW Roloff, RG Cornell, AF Andrews, PW Dillon, JB Zwischenberger. Pediatrics 1985; 76:479-87. Extracorporeal membrane oxygenation (ECMO) is the use of mechanical devices to replace cardiac and pulmonary function in critical care. In the 1960s, laboratory research showed that extracorporeal circulation could be maintained for days using a membrane oxygenator. In the 1970s, the first clinical trials showed that ECMO could sustain life in severe cardiac and pulmonary failure for days or weeks, leading to organ recovery. From 1980 to 2000, ECMO became standard practice for neonatal and pediatric respiratory and cardiac failure. The critical clinical trial was a prospective randomized trial of ECMO in newborn respiratory failure, published in 1985. This is the classic article reviewed in this publication. This was the first use of a randomized, adaptive design trial to minimize the potential ethical dilemma inherent to clinical trials in which the endpoint is death. Other randomized trials followed, and ECMO is now standard practice for severe respiratory and cardiac failure in all age groups.

A diagnostic phase III/IV seamless design to investigate the diagnostic accuracy and clinical effectiveness using the example of HEDOS and HEDOS II

The development process of medical devices can be streamlined by combining different study phases. Here, for a diagnostic medical device, we present the combination of confirmation of diagnostic accuracy (phase III) and evaluation of clinical effectiveness regarding patient-relevant endpoints (phase IV) using a seamless design. This approach is used in the Thyroid HEmorrhage DetectOr Study (HEDOS & HEDOS II) investigating a post-operative hemorrhage detector named ISAR-M THYRO® in patients after thyroid surgery. Data from the phase III trial are reused as external controls in the control group of the phase IV trial. An unblinded interim analysis is planned between the two study stages which includes a recalculation of the sample size for the phase IV part after completion of the first stage of the seamless design. The study concept presented here is the first seamless design proposed in the field of diagnostic studies. Hence, the aim of this work is to emphasize the statistical methodology as well as feasibility of the proposed design in relation to the planning and implementation of the seamless design. Seamless designs can accelerate the overall trial duration and increase its efficiency in terms of sample size and recruitment. However, careful planning addressing numerous methodological and procedural challenges is necessary for successful implementation as well as agreement with regulatory bodies.

Uncontrolled pain: a call for better study design

Studies assessing animal pain in veterinary research are often performed primarily for the benefit of animals. Frequently, the goal of these studies is to determine whether the analgesic effect of a novel treatment is clinically meaningful, and therefore has the capacity to improve the welfare of treated animals. To determine the treatment effect of a potential analgesic, control groups are necessary to allow comparison. There are negative control groups (where pain is unattenuated) and positive control groups (where pain is attenuated). Arising out of animal welfare concerns, there is growing reluctance to use negative control groups in pain studies. But for studies where pain is experimentally induced, the absence of a negative control group removes the opportunity to demonstrate that the study methods could differentiate a positive control intervention from doing nothing at all. For studies that are controlled by a single comparison group, the capacity to distinguish treatment effects from experimental noise is more difficult; especially considering that pain studies often involve small sample sizes, small and variable treatment effects, systematic error and use pain assessment measures that are unreliable. Due to these limitations, and with a focus on farm animals, we argue that many pain studies would be enhanced by the simultaneous inclusion of positive and negative control groups. This would help provide study-specific definitions of pain and pain attenuation, thereby permitting more reliable estimates of treatment effects. Adoption of our suggested refinements could improve animal welfare outcomes for millions of animals globally.

Seamless phase 2/3 design for trials with multiple co-primary endpoints using Bayesian predictive power

Seamless phase 2/3 design has become increasingly popular in clinical trials with a single endpoint. Trials that define success based on the achievement of all co-primary endpoints (CPEs) encounter the challenge of inflated type 2 error rates, often leading to an overly large sample size. To tackle this challenge, we introduced a seamless phase 2/3 design strategy that employs Bayesian predictive power (BPP) for futility monitoring and sample size re-estimation at interim analysis. The correlations among multiple CPEs are incorporated using a Dirichlet-multinomial distribution. An alternative approach based on conditional power (CP) was also discussed for comparison. A seamless phase 2/3 vaccine trial employing four binary endpoints under the non-inferior hypothesis serves as an example. Our results spotlight that, in scenarios with relatively small phase 2 sample sizes (e.g., 50 or 100 subjects), the BPP approach either outperforms or matches the CP approach in terms of overall power. Particularly, with n1 = 50 and ρ = 0, BPP showcases an overall power advantage over CP by as much as 8.54%. Furthermore, when the phase 2 stage enrolled more subjects (e.g., 150 or 200), especially with a phase 2 sample size of 200 and ρ = 0, the BPP approach evidences a peak difference of 5.76% in early stop probability over the CP approach, emphasizing its better efficiency in terminating futile trials. It's noteworthy that both BPP and CP methodologies maintained type 1 error rates under 2.5%. In conclusion, the integration of the Dirichlet-Multinominal model with the BPP approach offers improvement in certain scenarios over the CP approach for seamless phase 2/3 trials with multiple CPEs.

Towards achieving transnational research partnership equity: lessons from implementing adaptive platform trials in low- and middle-income countries

Background

Use of adaptive clinical trials, particularly adaptive platform trials, has grown exponentially in response to the coronavirus disease (COVID-19) pandemic. Implementation of these trials in low- and middle-income countries (LMICs) has been fostered through the formation or modification of transnational research partnerships, typically between research groups from LMICs and high-income countries (HICs). While these partnerships are important to promote collaboration and overcome the structural and economic disadvantages faced by LMIC health researchers, it is critical to focus attention on the multiple dimensions of partnership equity.

Methods

Based on informal literature reviews and a meeting with leaders of one of the multinational COVID-19 adaptive platform trials, we describe some important considerations about research partnership equity in this context.

Results

We organize these considerations into eight thematic categories: 1) epistemic structures, 2) funding, 3) ethics oversight, 4) regulatory oversight, 5) leadership, 6) post-trial access to interventions, data, and specimens, 7) knowledge translation and dissemination, and 8) research capacity strengthening and maintenance. Within each category we review normative claims that support its relevance to research partnership equity followed by discussion of how adaptive platform trials highlight new dimensions, considerations, or challenges.

Conclusion

In aggregate, these observations provide insight into procedural and substantive equity-building measures within transnational global health research partnerships more broadly.

Application of sample size re-estimation in clinical trials: A systematic review

Background

Sample size re-estimation (SSR) is a method used to recalculate sample size during clinical trial conduct to address a lack of adequate information and can have a significant impact on study size, duration, resources, and cost. Few studies to date have summarized the conditions and circumstances under which SSR is applied. We therefore performed a systematic review of the literature related to SSR to better understand its application in clinical trial settings.

Methods

PubMed was used as the primary search source, supplemented with information from ClinicalTrials.gov where necessary details were lacking from PubMed. A systematic review was performed according to a pre-specified search strategy to identify clinical trials using SSR. Features of SSR, such as study phase and study start year, were summarized.

Results

In total, 253 publications met the pre-specified search criteria and 27 clinical trials were subsequently determined as relevant in SSR usage. Among trials where the study phase was provided, 2 (7.4%) trials were Phase I, 5 (18.5%) trials were Phase II, 11 (40.7%) trials were Phase III, and 2 (7.4%) trials were Phase IV.

Conclusion

Our results showed that SSR is also used in Phase I and II, which involve earlier decision making. We expect that SSR will continue to be used in early-phase trials where sufficient prior information may not be available. Furthermore, no major trends were observed in relation to therapy area or type of SSR, meaning that SSR may become a feasible and widely applied method in the future.

Adaptive design clinical trials: current status by disease and trial phase in various perspectives

An adaptive design is a clinical trial design that allows for modification of a structured plan in a clinical trial based on data accumulated during pre-planned interim analyses. This flexible approach to clinical trial design improves the success rate of clinical trials while reducing time, cost, and sample size compared to conventional methods. The purpose of this study is to identify the current status of adaptive design and present key considerations for planning an appropriate adaptive design based on specific circumstances. We searched for clinical trials conducted between January 2006 to July 2021 in the Clinical Trials Registry (ClinicalTrials.gov) using keywords specified in the Food and Drug Administration Adaptive Design Clinical Trial Guidelines. In order to analyze the adaptive designs used in selected cases, we classified the results according to the phase of the clinical trial, type of indication, and the specific adaptation method employed. A total of 267 clinical trials were identified on ClinicalTrials.gov. Among them, 236 clinical trials actually applied adaptive designs and were classified according to phase, indication types, and adaptation methods. Adaptive designs were most frequently used in phase 2 clinical trials and oncology research. The most commonly used adaptation method was the adaptive treatment selection design. In the case of coronavirus disease 2019, the most frequently used designs were adaptive platform design and seamless design. Through this study, we expect to provide valuable insights and considerations for the implementation of adaptive design clinical trials in different diseases and stages.

Adaptive designs in critical care trials: a simulation study

BACKGROUND

Adaptive clinical trials are growing in popularity as they are more flexible, efficient and ethical than traditional fixed designs. However, notwithstanding their increased use in assessing treatments for COVID-19, their use in critical care trials remains limited. A better understanding of the relative benefits of various adaptive designs may increase their use and interpretation.

METHODS

Using two large critical care trials (ADRENAL.

CLINICALTRIALS

gov number, NCT01448109. Updated 12-12-2017; NICE-SUGAR.

CLINICALTRIALS

gov number, NCT00220987. Updated 01-29-2009), we assessed the performance of three frequentist and two bayesian adaptive approaches. We retrospectively re-analysed the trials with one, two, four, and nine equally spaced interims. Using the original hypotheses, we conducted 10,000 simulations to derive error rates, probabilities of making an early correct and incorrect decision, expected sample size and treatment effect estimates under the null scenario (no treatment effect) and alternative scenario (a positive treatment effect). We used a logistic regression model with 90-day mortality as the outcome and the treatment arm as the covariate. The null hypothesis was tested using a two-sided significance level (α) at 0.05.

RESULTS

Across all approaches, increasing the number of interims led to a decreased expected sample size. Under the null scenario, group sequential approaches provided good control of the type-I error rate; however, the type I error rate inflation was an issue for the Bayesian approaches. The Bayesian Predictive Probability and O'Brien-Fleming approaches showed the highest probability of correctly stopping the trials (around 95%). Under the alternative scenario, the Bayesian approaches showed the highest overall probability of correctly stopping the ADRENAL trial for efficacy (around 91%), whereas the Haybittle-Peto approach achieved the greatest power for the NICE-SUGAR trial. Treatment effect estimates became increasingly underestimated as the number of interims increased.

CONCLUSIONS

This study confirms the right adaptive design can reach the same conclusion as a fixed design with a much-reduced sample size. The efficiency gain associated with an increased number of interims is highly relevant to late-phase critical care trials with large sample sizes and short follow-up times. Systematically exploring adaptive methods at the trial design stage will aid the choice of the most appropriate method.

A systematic review of randomised controlled trials with adaptive and traditional group sequential designs - applications in cardiovascular clinical trials

BACKGROUND

Trial design plays a key role in clinical trials. Traditional group sequential design has been used in cardiovascular clinical trials over decades as the trials can potentially be stopped early, therefore, it can reduce pre-planned sample size and trial resources. In contrast, trials with adoptive designs provide greater flexibility and are more efficient due to the ability to modify trial design according to the interim analysis results. In this systematic review, we aim to explore characteristics of adaptive and traditional group sequential trials in practice and to gain an understanding how these trial designs are currently being reported in cardiology.

METHODS

PubMed, Embase and Cochrane Central Register of Controlled Trials database were searched from January 1980 to June 2022. Randomised controlled phase 2/3 trials with either adaptive or traditional group sequential design in patients with cardiovascular disease were included. Descriptive statistics were used to present the collected data.

RESULTS

Of 456 articles found in the initial search, 56 were identified including 43 (76.8%) trials with traditional group sequential design and 13 (23.2%) with adaptive. Most trials were large, multicentre, led by the USA (50%) and Europe (28.6%), and were funded by companies (78.6%). For trials with group sequential design, frequency of interim analyses was determined mainly by the number of events (47%). 67% of the trials stopped early, in which 14 (32.6%) were due to efficacy, and 5 (11.6%) for futility. The commonly used stopping rule to terminate trials was O'Brien- Fleming-type alpha spending function (10 (23.3%)). For trials with adaptive designs, 54% of the trials stopped early, in which 4 (30.8%) were due to futility, and 2 (15.4%) for efficacy. Sample size re-estimation was commonly used (8 (61.5%)). In 69% of the trials, simulation including Bayesian approach was used to define the statistical stopping rules. The adaptive designs have been increasingly used (from 0 to 1999 to 38.6% after 2015 amongst adaptive trials). 25% of the trials reported "adaptive" in abstract or title of the studies.

CONCLUSIONS

The application of adaptive trials is increasingly popular in cardiovascular clinical trials. The reporting of adaptive design needs improving.

Mesenchymal STRO-1/STRO-3+ precursor cells for the treatment of chronic heart failure with reduced ejection fraction

The heart is susceptible to proinflammatory and profibrotic responses after myocardial injury, leading to further worsening of cardiac dysfunction. Important developments in the management of heart failure with reduced ejection fraction have reduced morbidity and mortality; however, these therapies focus on optimizing cardiac function through hemodynamic and neurohormonal pathways and not by repairing the underlying cardiac injury. The potential of cell-based therapy to reverse cardiac injury has received substantial attention. Herein are examined the phase II and III studies of bone marrow-derived mesenchymal STRO-1+ or STRO-1/STRO-3+ precursor cells in patients with ischemic and nonischemic heart failure with reduced ejection fraction, addressing the safety and efficacy of cell-based therapy throughout multiple clinical trials, the optimal dose and the steps toward revolutionizing the treatment of heart failure.

Ethics of Adaptive Designs for Randomized Controlled Trials

Over recent decades, adaptive trial designs have been used more and more often for clinical trials, including randomized controlled trials (RCTs). This rise in the use of adaptive RCTs has been accompanied by debates about whether such trials offer ethical and methodological advantages over traditional, fixed RCTs. This study examined how experts on clinical trial methods and ethics believe that adaptive RCTs, compared to fixed ones, affect the ethical character of clinical research. We conducted in-depth interviews with 17 researchers from bioethics, epidemiology, biostatistics, and/or medical backgrounds. While about half believed that adaptive trials are more complex and may thus threaten autonomy, these respondents also expressed that this challenge is not insurmountable. Most respondents expressed that efficiency and potential for participant benefit were the main justifications for adaptive trials. There was tension about whether adaptive randomization in response to increasing information disrupts clinical equipoise, with some respondents insisting that uncertainty still exists and therefore clinical equipoise is not disrupted. These findings suggest that further discussion is needed to increase the awareness and utility of these study designs.

Pulmonary Hypertension: A Contemporary Review

Major advances in pulmonary arterial hypertension, pulmonary hypertension (PH) associated with lung disease, and chronic thromboembolic PH cast new light on the pathogenetic mechanisms, epidemiology, diagnostic approach, and therapeutic armamentarium for pulmonary vascular disease. Here, we summarize key basic, translational, and clinical PH reports, emphasizing findings that build on current state-of-the-art research. This review includes cutting-edge progress in translational pulmonary vascular biology, with a guide to the diagnosis of patients in clinical practice, incorporating recent PH definition revisions that continue emphasis on early detection of disease. PH management is reviewed including an overview of the evolving considerations for the approach to treatment of PH in patients with cardiopulmonary comorbidities, as well as a discussion of the groundbreaking sotatercept data for the treatment of pulmonary arterial hypertension.

Adaptive Clinical Trials in Pediatric Critical Care: A Systematic Review

OBJECTIVES

This systematic review investigates the use of adaptive designs in randomized controlled trials (RCTs) in pediatric critical care.

DATA SOURCES

PICU RCTs, published between 1986 and 2020, stored in the www.PICUtrials.net database and MEDLINE, EMBASE, CENTRAL, and LILACS databases were searched (March 9, 2022) to identify RCTs published in 2021. PICU RCTs using adaptive designs were identified through an automated full-text screening algorithm.

STUDY SELECTION

All RCTs involving children (< 18 yr old) cared for in a PICU were included. There were no restrictions to disease cohort, intervention, or outcome. Interim monitoring by a Data and Safety Monitoring Board that was not prespecified to change the trial design or implementation of the study was not considered adaptive.

DATA EXTRACTION

We extracted the type of adaptive design, the justification for the design, and the stopping rule used. Characteristics of the trial were also extracted, and the results summarized through narrative synthesis. Risk of bias was assessed using the Cochrane Risk of Bias Tool 2.

DATA SYNTHESIS

Sixteen of 528 PICU RCTs (3%) used adaptive designs with two types of adaptations used; group sequential design and sample size reestimation. Of the 11 trials that used a group sequential adaptive design, seven stopped early due to futility and one stopped early due to efficacy. Of the seven trials that performed a sample size reestimation, the estimated sample size decreased in three trials and increased in one trial.

CONCLUSIONS

Little evidence of the use of adaptive designs was found, with only 3% of PICU RCTs incorporating an adaptive design and only two types of adaptations used. Identifying the barriers to adoption of more complex adaptive trial designs is needed.

Reducing Health Inequalities in Individuals with Severe Mental Disorders: Harnessing Real-World Data and Patient-Reported Measures

Mental disorders are the leading cause of diminished lifespans worldwide and make up 5 of the top 10 most significant causes of disability [...].

Treating intrusive memories after trauma in healthcare workers: a Bayesian adaptive randomised trial developing an imagery-competing task intervention

Intensive care unit (ICU) staff continue to face recurrent work-related traumatic events throughout the COVID-19 pandemic. Intrusive memories (IMs) of such traumatic events comprise sensory image-based memories. Harnessing research on preventing IMs with a novel behavioural intervention on the day of trauma, here we take critical next steps in developing this approach as a treatment for ICU staff who are already experiencing IMs days, weeks, or months post-trauma. To address the urgent need to develop novel mental health interventions, we used Bayesian statistical approaches to optimise a brief imagery-competing task intervention to reduce the number of IMs. We evaluated a digitised version of the intervention for remote, scalable delivery. We conducted a two-arm, parallel-group, randomised, adaptive Bayesian optimisation trial. Eligible participants worked clinically in a UK NHS ICU during the pandemic, experienced at least one work-related traumatic event, and at least three IMs in the week prior to recruitment. Participants were randomised to receive immediate or delayed (after 4 weeks) access to the intervention. Primary outcome was the number of IMs of trauma during week 4, controlling for baseline week. Analyses were conducted on an intention-to-treat basis as a between-group comparison. Prior to final analysis, sequential Bayesian analyses were conducted (n = 20, 23, 29, 37, 41, 45) to inform early stopping of the trial prior to the planned maximum recruitment (n = 150). Final analysis (n = 75) showed strong evidence for a positive treatment effect (Bayes factor, BF = 1.25 × 106): the immediate arm reported fewer IMs (median = 1, IQR = 0-3) than the delayed arm (median = 10, IQR = 6-16.5). With further digital enhancements, the intervention (n = 28) also showed a positive treatment effect (BF = 7.31). Sequential Bayesian analyses provided evidence for reducing IMs of work-related trauma for healthcare workers. This methodology also allowed us to rule out negative effects early, reduced the planned maximum sample size, and allowed evaluation of enhancements. Trial Registration NCT04992390 ( www.clinicaltrials.gov ).

Point estimation for adaptive trial designs II: Practical considerations and guidance

In adaptive clinical trials, the conventional end-of-trial point estimate of a treatment effect is prone to bias, that is, a systematic tendency to deviate from its true value. As stated in recent FDA guidance on adaptive designs, it is desirable to report estimates of treatment effects that reduce or remove this bias. However, it may be unclear which of the available estimators are preferable, and their use remains rare in practice. This article is the second in a two-part series that studies the issue of bias in point estimation for adaptive trials. Part I provided a methodological review of approaches to remove or reduce the potential bias in point estimation for adaptive designs. In part II, we discuss how bias can affect standard estimators and assess the negative impact this can have. We review current practice for reporting point estimates and illustrate the computation of different estimators using a real adaptive trial example (including code), which we use as a basis for a simulation study. We show that while on average the values of these estimators can be similar, for a particular trial realization they can give noticeably different values for the estimated treatment effect. Finally, we propose guidelines for researchers around the choice of estimators and the reporting of estimates following an adaptive design. The issue of bias should be considered throughout the whole lifecycle of an adaptive design, with the estimation strategy prespecified in the statistical analysis plan. When available, unbiased or bias-reduced estimates are to be preferred.

Alleviation of Pain, PAIN Interference, and Oxidative Stress by a Novel Combination of Hemp Oil, Calamari Oil, and Broccoli: A Randomized, Double-Blind, Placebo-Controlled Trial

Chronic pain is a critical health issue in the US that is routinely managed pharmacologically with diminishing results. The widespread misuse and abuse of prescription opioid pain medications have caused both healthcare providers and patients to seek alternative therapeutic options. Several dietary ingredients have been traditionally used for pain relief and are known to have potential analgesic properties. This double-blind, placebo-controlled randomized clinical trial aimed to test whether a novel combination of full spectrum hemp oil (phytocannabinoids), calamari oil (omega-3 fatty acids), and broccoli (glucosinolates) could reduce chronic pain and attenuate damage from oxidative stress in adults seeking chiropractic care. Participants (average age = 54.8 ± 13.6 years old) were randomly assigned to consume a whole-food, multi-ingredient supplement (n = 12, intervention and standard chiropractic care) or placebo (n = 13, mineral oil and standard chiropractic care) daily for 12 weeks. The subjects' self-reported perceived pain, pain interference, and reactive oxygen species (ROS) status in the peripheral blood mononuclear cells (PBMC) were quantified at baseline, mid-checkpoint, and postintervention. The intervention was positively associated with a 52% decrease in pain intensity and several parameters of pain interference, including quality of sleep. Decreases in the markers of oxidative stress were also observed in the participants from the intervention group (29.4% decrease in PMBC ROS). Our findings indicated that supplementation with a novel combination of hemp oil, calamari oil, and broccoli has the potential to manage chronic pain when combined with standard chiropractic care, as suggested by its effects on pain intensity and oxidative stress.

Recent innovations in adaptive trial designs: A review of design opportunities in translational research

Clinical trials are constantly evolving in the context of increasingly complex research questions and potentially limited resources. In this review article, we discuss the emergence of "adaptive" clinical trials that allow for the preplanned modification of an ongoing clinical trial based on the accumulating evidence with application across translational research. These modifications may include terminating a trial before completion due to futility or efficacy, re-estimating the needed sample size to ensure adequate power, enriching the target population enrolled in the study, selecting across multiple treatment arms, revising allocation ratios used for randomization, or selecting the most appropriate endpoint. Emerging topics related to borrowing information from historic or supplemental data sources, sequential multiple assignment randomized trials (SMART), master protocol and seamless designs, and phase I dose-finding studies are also presented. Each design element includes a brief overview with an accompanying case study to illustrate the design method in practice. We close with brief discussions relating to the statistical considerations for these contemporary designs.

Adapting adaptive design methods to accelerate adoption of a digital asthma management intervention

Investigators conducting translational research in real-world settings may experience changes that create challenges to the successful completion of the trial as well as post-trial adoption and implementation. Adaptive designs support translational research by systematically adapting content and methods to meet the needs of target populations, settings and contexts. This manuscript describes an adaptive implementation research model that provides strategies for changing content, delivery processes, and research methods to correct course when anticipated and unanticipated circumstances occur during a pragmatic trial. The Breathewell Program included two large pragmatic trials of the effectiveness of a digital communication technology intervention to improve symptom management and medication adherence in asthma care. The first trial targeted parents of children with asthma; the second targeted adults with asthma. Adaptations were made iteratively to adjust to dynamic conditions within the healthcare setting, informed by prospectively collected stakeholder input, and were categorized retrospectively by the authors as proactive or reactive. Study outcomes demonstrated improved treatment adherence and clinical efficiency. Kaiser Permanente Colorado, the setting for both studies, adopted the speech recognition intervention into routine care, however, both interventions required numerous adaptations, including changes to target population, intervention content, and internal workflows. Proactive and reactive adaptations assured that both trials were successfully completed. Adaptive research designs will continue to provide an important pathway to move healthcare delivery research into practice while conducting ongoing effectiveness evaluation.

Towards achieving transnational research partnership equity: lessons from implementing adaptive platform trials in low- and middle-income countries

Background: Use of adaptive clinical trials, particularly adaptive platform trials, has grown exponentially in response to the coronavirus disease (COVID-19) pandemic. Implementation of these trials in low- and middle-income countries (LMICs) has been fostered through the formation or modification of transnational research partnerships, typically between research groups from LMICs and high-income countries (HICs). While these partnerships are important to promote collaboration and overcome the structural and economic disadvantages faced by LMIC health researchers, it is critical to focus attention on the multiple dimensions of partnership equity. Methods: Based on informal literature reviews and meetings with leaders of one of the multinational COVID-19 adaptive platform trials, we describe what can be learned about research partnership equity from these experiences. Results: We organize these considerations into eight thematic categories: 1) epistemic structures, 2) funding, 3) ethics oversight, 4) regulatory oversight, 5) leadership, 6) post-trial access to interventions, data, and specimens, 7) knowledge translation, and 8) research capacity strengthening and maintenance. Within each category we review the normative claims that support its relevance to research partnership equity followed by discussion of how adaptive platform trials highlight new dimensions, considerations, or challenges. Conclusion: These observations provide insight into procedural and substantive equity-building measures within transnational global health research partnerships more broadly.

Evaluation of clinical trial designs for novel anticancer drugs in China: a cohort study of drugs approved between 2015 and 2021

China has greatly facilitated the approval of many novel anticancer drugs since the drug regulatory reform in 2015. Here, we review the clinical trial designs used in pivotal clinical trials for approved anticancer agents in China from 2015 to 2021. Overall, 79 new molecular entities (NMEs) with 140 anticancer indications were identified. Of these, adaptive randomized controlled trial (RCT) designs were used most frequently in pivotal clinical trials (n=83, 49%), followed by single-arm design trials (n=52, 30%) and traditional RCT design trials (n=36, 21%). The single-arm trials and adaptive RCTs can significantly shorten clinical trial duration compared with traditional RCT designs. Our findings show that novel clinical trial designs were widely used in China to accelerate the launch of anticancer drugs. Teaser: To address unmet clinical needs, more flexible clinical trial designs were encouraged for novel anticancer drugs in China, including single-arm trials and adaptive designs, as compared with traditional randomized controlled trials.

Reporting quality was suboptimal in a systematic review of randomized controlled trials with adaptive designs

OBJECTIVE

The study was conducted to evaluate the reporting quality of randomized controlled trials (RCTs) that use an adaptive design (AD) based on the 2020 AD Consolidated Standards for Reporting Trials 2010 extension (ACE) guidelines and identify factors associated with better reporting quality.

STUDY DESIGN AND SETTING

PubMed, Embase, Cochrane, Web of Science, and Google Scholar were searched until November 1, 2022. Multivariable linear regression analysis was performed to investigate potential predictors.

RESULTS

In total, 109 RCTs were included in our study. The mean compliance rate for the ACE checklist items was 69.75% ± 16.02. Key methodological items including allocation concealment and its implementations were poorly reported. There was also suboptimal reporting of checklist items related to the conduct of interim analyzes. Multivariable regression analysis showed better reporting quality with trial registration, nonindustry affiliation (first author), a sample size of >100, general medical journal type, publication date (≥2020), funding, and disclosure of the number of interim analyzes.

CONCLUSION

Our study showed that RCTs with AD had suboptimal reporting of 2020 ACE checklist items, particularly AD-specific items. Following the development of ACE guidelines, stricter adherence to the ACE guideline is necessary to improve their reporting quality. Pre-ACE and post-ACE adherence comparisons can be conducted in the future.

Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials

BACKGROUND

A single generalizable metric that accurately predicts early dropout from digital health interventions has the potential to readily inform intervention targets and treatment augmentations that could boost retention and intervention outcomes. We recently identified a type of early dropout from digital health interventions for smoking cessation, specifically, users who logged in during the first week of the intervention and had little to no activity thereafter. These users also had a substantially lower smoking cessation rate with our iCanQuit smoking cessation app compared with users who used the app for longer periods.

OBJECTIVE

This study aimed to explore whether log-in count data, using standard statistical methods, can precisely predict whether an individual will become an iCanQuit early dropout while validating the approach using other statistical methods and randomized trial data from 3 other digital interventions for smoking cessation (combined randomized N=4529).

METHODS

Standard logistic regression models were used to predict early dropouts for individuals receiving the iCanQuit smoking cessation intervention app, the National Cancer Institute QuitGuide smoking cessation intervention app, the WebQuit.org smoking cessation intervention website, and the Smokefree.gov smoking cessation intervention website. The main predictors were the number of times a participant logged in per day during the first 7 days following randomization. The area under the curve (AUC) assessed the performance of the logistic regression models, which were compared with decision trees, support vector machine, and neural network models. We also examined whether 13 baseline variables that included a variety of demographics (eg, race and ethnicity, gender, and age) and smoking characteristics (eg, use of e-cigarettes and confidence in being smoke free) might improve this prediction.

RESULTS

The AUC for each logistic regression model using only the first 7 days of log-in count variables was 0.94 (95% CI 0.90-0.97) for iCanQuit, 0.88 (95% CI 0.83-0.93) for QuitGuide, 0.85 (95% CI 0.80-0.88) for WebQuit.org, and 0.60 (95% CI 0.54-0.66) for Smokefree.gov. Replacing logistic regression models with more complex decision trees, support vector machines, or neural network models did not significantly increase the AUC, nor did including additional baseline variables as predictors. The sensitivity and specificity were generally good, and they were excellent for iCanQuit (ie, 0.91 and 0.85, respectively, at the 0.5 classification threshold).

CONCLUSIONS

Logistic regression models using only the first 7 days of log-in count data were generally good at predicting early dropouts. These models performed well when using simple, automated, and readily available log-in count data, whereas including self-reported baseline variables did not improve the prediction. The results will inform the early identification of people at risk of early dropout from digital health interventions with the goal of intervening further by providing them with augmented treatments to increase their retention and, ultimately, their intervention outcomes.

Using the AR-V7 biomarker to determine treatment in metastatic castrate resistant prostate cancer, a feasibility randomised control trial, conclusions from the VARIANT trial

Background

Prostate cancer is the most commonly diagnosed malignancy in the UK. Castrate resistant prostate cancer (CRPC) can be difficult to manage with response to next generation hormonal treatment variable. AR-V7 is a protein biomarker that can be used to predict response to treatment and potentially better inform management in these patients. Our aim was to establish the feasibility of conducting a definitive randomised controlled trial comparing the clinical utility of AR-V7 biomarker assay in personalising treatments for patients with metastatic CRPC within the United Kingdom (UK) National Health Service (NHS). Due to a number of issues the trial was not completed successfully, we aim to discuss and share lessons learned herein.

Methods

We conducted a randomised, open, feasibility trial, which aimed to recruit 70 adult men with metastatic CRPC within three secondary care NHS trusts in the UK to be run over an 18-month period. Participants were randomised to personalised treatment based on AR-V7 status (intervention) or standard care (control). The primary outcome was feasibility, which included: recruitment rate, retention and compliance. Additionally, a baseline prevalence of AR-V7 expression was to be estimated.

Results

Fourteen participants were screened and 12 randomised with six into each arm over a nine-month period. Reliability issues with the AR-V7 assay meant prevalence was not estimated. Due to limited recruitment the study did not complete to target.

Conclusions

Whilst the trial did not complete to target, we have ascertained that men with advanced cancer are willing to take part in trials utilising biomarker guided treatment. A number of issues were identified that serve as important learning points in future clinical trials.

Clinical Trial Design Innovations for Precision Medicine in Asthma

Severe asthma is a spectrum disorder with numerous subsets, many of which are defined by clinical history and a general predisposition for T2 inflammation. Most of the approved therapies for severe asthma have required clinical trial designs with population enrichment for exacerbation frequency and/or elevation of blood eosinophils. Moving beyond this framework will require trial designs that increase efficiency for studying nondominant subsets and continue to improve upon biomarker signatures. In addition to reviewing the current literature on biomarker-informed trials for severe asthma, this chapter will also review the advantages of master protocols and adaptive design methods for establishing the efficacy of new interventions in prospectively defined subsets of patients. The incorporation of methods that allow for data collection outside of traditional study visits at academic centers, called remote decentralized trial design, is a growing trend that may increase diversity in study participation and allow for enhanced resiliency during the COVID-19 pandemic. Finally, reaching the goals of precision medicine in asthma will require increased emphasis on effectiveness studies. Recent advances in real-world data utilization from electronic health records are also discussed with a view toward pragmatic trial designs that could also incorporate the evaluation of biomarker signatures.

Landscape of Phase II Trials in Alzheimer's Disease

BACKGROUND

Drug development in Alzheimer's disease (AD) over the past two decades has had high rates of failure. Novel trial designs, such as adaptive designs, have the potential to improve the efficiency of drug development in AD.

OBJECTIVE

To evaluate the design characteristics, temporal trends, and differences in design between sponsor types in phase II trials of investigational agents in AD.

METHODS

Phase I/II, II, and II/III trials for AD with drug or other biological interventions registered from December 1996 to December 2021 in ClinicalTrials.gov were included. Descriptive statistics were used to summarize trial characteristics. Linear, logistic, and multinomial regression models assessed temporal trends and differences between sponsor types in design characteristics.

RESULTS

Of N = 474 trials identified, randomized parallel group design was the most common design (72%). Only 12 trials (2.5%) used an adaptive design; adaptive features included early stopping rules, model-based dose-finding, adaptive treatment arm selection, and response adaptive randomization. The use of non-randomized parallel-group and open-label single arm designs increased over time. No temporal trend in the use of adaptive design was identified. Trials sponsored by industry only were more likely to use a randomized parallel-group design and have a larger estimated sample size than trials with other sponsor types.

CONCLUSION

Our systematic review showed that very few phase II trials in AD used an adaptive trial design. Innovation and implementation of novel trial designs in AD trials can accelerate the drug development process.

The evolving landscape of pulmonary arterial hypertension clinical trials

Although it is a rare disease, the number of available therapeutic options for treating pulmonary arterial hypertension has increased since the late 1990s, with multiple drugs developed that are shown to be effective in phase 3 randomised controlled trials. Despite considerable advancements in pulmonary arterial hypertension treatment, prognosis remains poor. Existing therapies target pulmonary endothelial dysfunction with vasodilation and anti-proliferative effects. Novel therapies that target proliferative vascular remodelling and affect important outcomes are urgently needed. There is need for additional innovations in clinical trial design so that all emerging candidate therapies can be rigorously studied. Pulmonary arterial hypertension trial design has shifted from short-term submaximal exercise capacity as a primary endpoint, to larger clinical event-driven trial outcomes. Event-driven pulmonary arterial hypertension trials could face feasibility and efficiency issues in the future because increasing sample sizes and longer follow-up durations are needed, which would be problematic in such a rare disease. Enrichment strategies, innovative and alternative trial designs, and novel trial endpoints are potential solutions that could improve the efficiency of future pulmonary arterial hypertension trials while maintaining robustness and clinically meaningful evidence.

Baseline data of a sequential multiple assignment randomized trial (STEP study)

AIM

Research has shown that preventative intervention in individuals at ultra-high risk of psychosis (UHR) improves symptomatic and functional outcomes. The staged treatment in early psychosis (STEP) trial aims to determine the most effective type, timing and sequence of interventions in the UHR population by sequentially studying the effectiveness of (1) support and problem solving, (2) cognitive-behavioural case management and (3) antidepressant medication with an embedded fast-fail option of (4) omega-3 fatty acids or low-dose antipsychotic medication. This paper presents the recruitment flow and baseline clinical characteristics of the sample.

METHODS

STEP is a sequential multiple assignment randomized trial. We present the baseline demographics, clinical characteristics and acceptability and feasibility of this treatment approach as indicated by the flow of participants from first contact up until enrolment into the trial. Recruitment took place between April 2016 and January 2019.

RESULTS

Of 1343, help-seeking young people who were considered for participation, 402 participants were not eligible and 599 declined/disengaged, resulting in a total of 342 participants enrolled in the study. The most common reason for exclusion was an active prescription of antidepressant medication. Eighty-five percent of the enrolled sample had a non-psychotic DSM-5 diagnosis and symptomatic/functional measures showed a moderate level of clinical severity and functional impairment.

DISCUSSION

The present study demonstrates the acceptability and participant's general positive appraisal of sequential treatment. It also shows, in line with other trials in UHR individuals, a significant level of psychiatric morbidity and impairment, demonstrating the clear need for care in this group and that treatment is appropriate.

Adaptive interventions to optimise the mobile phone-based smoking cessation support: study protocol for a sequential, multiple assignment, randomised trial (SMART)

BACKGROUND

Mobile health (mHealth) is promising in developing personalised smoking cessation interventions. By using an adaptive trial design, we aim to evaluate the effectiveness of personalised mHealth intervention in increasing smoking cessation.

METHODS

This study is a two-arm, parallel, accessor-blinded Sequential Multiple-Assignment Randomised Trial (SMART) that randomises 1200 daily cigarette smokers from 70 community sites at two timepoints. In the first phase, participants receive brief cessation advice plus referral assistance to smoking cessation services and are randomly allocated to receive personalised instant messaging (PIM) or regular instant messaging (RIM). In the second phase, PIM participants who are non-responders (i.e. still smoking at 1 month) are randomised to receive either optional combined interventions (multi-media messages, nicotine replacement therapy sampling, financial incentive for active referral, phone counselling, and family/peer support group chat) or continued-PIM. Non-responders in the RIM group are randomised to receive PIM or continued-RIM. Participants who self-report quitting smoking for 7 days or longer at 1 month (responders) in both groups continue to receive the intervention assigned in phase 1. The primary outcomes are biochemical abstinence validated by exhaled carbon monoxide (< 4 ppm) and salivary cotinine (< 10 ng/ml) at 3 and 6 months from treatment initiation. Intention-to-treat analysis will be adopted.

DISCUSSION

This is the first study using a SMART design to evaluate the effect of adaptive mHealth intervention on abstinence in community-recruited daily smokers. If found effective, the proposed intervention will inform the development of adaptive smoking cessation treatment and benefits smokers non-responding to low-intensity mHealth support.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03992742 . Registered on 20 June 2019.

Design and implementation of an adaptive confirmatory trial in Japanese patients with palmoplantar pustulosis

Background/Aims

Methods

Results

Conclusion

Adaptive Designs: Benefits and Cautions for Neurosurgery Trials

BACKGROUND

It is well accepted that randomized controlled trials provide the greatest quality of evidence about effectiveness and safety of new interventions. In neurosurgery, randomized controlled trials face challenges, with their use remaining relatively low compared with other clinical areas. Adaptive designs have emerged as a method for improving the efficiency and patient benefit of trials. They allow modifications to the trial design to be made as patient outcome data are collected. The benefit they provide is highly variable, predominantly governed by the time taken to observe the primary endpoint compared with the planned recruitment rate. They also face challenges in design, conduct, and reporting.

METHODS

We provide an overview of the benefits and challenges of adaptive designs, with a focus on neurosurgery applications. To investigate how often an adaptive design may be advantageous in neurosurgery, we extracted data on recruitment rates and endpoint lengths for ongoing neurosurgery trials registered in ClinicalTrials.gov.

RESULTS

We found that a majority of neurosurgery trials had a relatively short endpoint length compared with the planned recruitment period and therefore may benefit from an adaptive trial. However, we did not identify any ongoing ClinicalTrials.gov registered neurosurgery trials that mentioned using an adaptive design.

CONCLUSIONS

Adaptive designs may provide benefits to neurosurgery trials and should be considered for use more widely. Use of some types of adaptive design, such as multiarm multistage, may further increase the number of interventions that can be tested with limited patient and financial resources.

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

INTRODUCTION

Adaptive 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.

METHODS

We 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.

RESULTS

The 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.

CONCLUSIONS

Cost-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.

HIGHLIGHTS

Opportunities 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.

Uptake of the multi-arm multi-stage (MAMS) adaptive platform approach: a trial-registry review of late-phase randomised clinical trials

BACKGROUND

For medical conditions with numerous interventions worthy of investigation, there are many advantages of a multi-arm multi-stage (MAMS) platform trial approach. However, there is currently limited knowledge on uptake of the MAMS design, especially in the late-phase setting. We sought to examine uptake and characteristics of late-phase MAMS platform trials, to enable better planning for teams considering future use of this approach.

DESIGN

We examined uptake of registered, late-phase MAMS platforms in the EU clinical trials register, Australian New Zealand Clinical Trials Registry, International Standard Randomised Controlled Trial Number registry, Pan African Clinical Trials Registry, WHO International Clinical Trial Registry Platform and databases: PubMed, Medline, Cochrane Library, Global Health Library and EMBASE. Searching was performed and review data frozen on 1 April 2021. MAMS platforms were defined as requiring two or more comparison arms, with two or more trial stages, with an interim analysis allowing for stopping of recruitment to arms and typically the ability to add new intervention arms.

RESULTS

62 late-phase clinical trials using an MAMS approach were included. Overall, the number of late-phase trials using the MAMS design has been increasing since 2001 and been accelerated by COVID-19. The majority of current MAMS platforms were either targeting infectious diseases (52%) or cancers (29%) and all identified trials were for treatment interventions. 89% (55/62) of MAMS platforms were evaluating medications, with 45% (28/62) of the MAMS platforms having at least one or more repurposed medication as a comparison arm.

CONCLUSIONS

Historically, late-phase trials have adhered to long-established standard (two-arm) designs. However, the number of late-phase MAMS platform trials is increasing, across a range of different disease areas. This study highlights the potential scope of MAMS platform trials and may assist research teams considering use of this approach in the late-phase randomised clinical trial setting.

PROSPERO REGISTRATION NUMBER

CRD42019153910.

Designing and conducting adaptive trials to evaluate interventions in health services and implementation research: practical considerations

Randomized controlled clinical trials are widely considered the gold standard for evaluating the efficacy or effectiveness of interventions in health care. Adaptive trials incorporate changes as the study proceeds, such as modifying allocation probabilities or eliminating treatment arms that are likely to be ineffective. These designs have been widely used in drug discovery studies but can also be useful in health services and implementation research and have been minimally used. As motivating examples, we use an ongoing adaptive trial and two completed parallel group studies and highlight potential advantages, disadvantages, and important considerations when using adaptive trial designs in health services and implementation research. In addition, we investigate the impact on power and the study duration if the two completed parallel-group trials had instead been conducted using adaptive principles. Compared with traditional trial designs, adaptive designs can often allow one to evaluate more interventions, adjust participant allocation probabilities (e.g., to achieve covariate balance), and identify participants who are likely to agree to enroll. These features could reduce resources needed to conduct a trial. However, adaptive trials have potential disadvantages and practical aspects that need to be considered, most notably outcomes that can be rapidly measured and extracted (e.g., long-term outcomes that take significant time to measure from data sources can be challenging), minimal missing data, and time trends. In conclusion, adaptive designs are a promising approach to help identify how best to implement evidence-based interventions into real-world practice in health services and implementation research.

Trends in Adaptive Design Methods in Dialysis Clinical Trials: A Systematic Review

Rationale & Objective

Adaptive design methods are intended to improve the efficiency of clinical trials and are relevant to evaluating interventions in dialysis populations. We sought to determine the use of adaptive designs in dialysis clinical trials and quantify trends in their use over time.

Study Design

We completed a novel full-text systematic review that used a machine learning classifier (RobotSearch) for filtering randomized controlled trials and adhered to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines.

Setting & Study Populations

We searched MEDLINE (PubMed) and ClinicalTrials.gov using sensitive dialysis search terms.

Selection Criteria for Studies

We included all randomized clinical trials with patients receiving dialysis or clinical trials with dialysis as a primary or secondary outcome. There was no restriction of disease type or intervention type.

Data Extraction & Analytical Approach

We performed a detailed data extraction of trial characteristics and a completed a narrative synthesis of the data.

Results

57 studies, available as 68 articles and 7 ClinicalTrials.gov summaries, were included after full-text review (initial search, 209,033 PubMed abstracts and 6,002 ClinicalTrials.gov summaries). 31 studies were conducted in a dialysis population and 26 studies included dialysis as a primary or secondary outcome. Although the absolute number of adaptive design methods is increasing over time, the relative use of adaptive design methods in dialysis trials is decreasing over time (6.12% in 2009 to 0.43% in 2019, with a mean of 1.82%). Group sequential designs were the most common type of adaptive design method used. Adaptive design methods affected the conduct of 50.9% of trials, most commonly resulting in stopping early for futility (41.2%) and early stopping for safety (23.5%). Acute kidney injury was studied in 32 trials (56.1%), kidney failure requiring dialysis was studied in 24 trials (42.1%), and chronic kidney disease was studied in 1 trial (1.75%). 27 studies (47.4%) were supported by public funding. 44 studies (77.2%) did not report their adaptive design method in the title or abstract and would not be detected by a standard systematic review.

Limitations

We limited our search to 2 databases (PubMed and ClinicalTrials.gov) due to the scale of studies sourced (209,033 and 6,002 results, respectively).

Conclusions

Adaptive design methods are used in dialysis trials but there has been a decline in their relative use over time.