Unsuccessful trial accrual and human subjects protections: an empirical analysis of recently closed trials

The Social Value Misconception in Clinical Research

Clinical researchers should help respect the autonomy and promote the well-being of prospective study participants by helping them make voluntary, informed decisions about enrollment. However, participants often exhibit poor understanding of important information about clinical research. Bioethicists have given special attention to "misconceptions" about clinical research that can compromise participants' decision-making, most notably the "therapeutic misconception." These misconceptions typically involve false beliefs about a study's purpose, or risks or potential benefits for participants. In this article, we describe a misconception involving false beliefs about a study's potential benefits for non-participants, or its expected social value. This social value misconception can compromise altruistically motivated participants' decision-making, potentially threatening their autonomy and well-being. We show how the social value misconception raises ethical concerns for inherently low-value research, hyped research, and even ordinary research, and advocate for empirical and normative work to help understand and counteract this misconception's potential negative impacts on participants.

Matching Patients to Clinical Trials using LLaMA 2 Embeddings and Siamese Neural Network

Patient recruitment is a key desideratum for the success of a clinical trial that entails identifying eligible patients that match the selection criteria for the trial. However, the complexity of criteria information and heterogeneity of patient data render manual analysis a burdensome and time-consuming task. In an attempt to automate patient recruitment, this work proposes a Siamese Neural Network-based model, namely Siamese-PTM. Siamese-PTM employs the pretrained LLaMA 2 model to derive contextual representations of the EHR and criteria inputs and jointly encodes them using two weight-sharing identical subnetworks. We evaluate Siamese-PTM on structured and unstructured EHR to analyze their predictive informativeness as standalone and collective feature sets. We explore a variety of deep models for Siamese-PTM's encoders and compare their performance against the Single-encoder counterparts. We develop a baseline rule-based classifier, compared to which Siamese-PTM improved performance by 40%. Furthermore, visualization of Siamese-PTM's learned embedding space reinforces its predictive robustness.

Virtual Clinical Trials - Implications of Computer Simulations and Artificial Intelligence for Musculoskeletal Research

ABSTRACT

In silico clinical trials, particularly when augmented with artificial intelligence methods, represent an innovative approach with much to offer, particularly in the musculoskeletal field. They are a cost-effective, efficient, and ethical means of evaluating treatments and interventions by supplementing and/or augmenting traditional randomized controlled trials (RCTs). While they are not a panacea and should not replace traditional RCTs, their integration into the research process promises to accelerate medical advancements and improve patient outcomes. To accomplish this, a multidisciplinary approach is needed, and collaboration is instrumental. With advances in computing and analytical prowess, and by adhering to the tenets of team science, realization of such a novel integrative approach toward clinical trials may not be far from providing far-reaching contributions to medical research. As such, by harnessing the power of in silico clinical trials, investigators can potentially unlock new possibilities in treatment and intervention for ultimately improving patient care and outcomes.

Social media recruitment of participants in a female stress urinary incontinence trial: A feasibility study

OBJECTIVE

This study explores the opportunities of social media advertisements as a recruitment strategy in women with stress urinary incontinence (SUI).

STUDY DESIGN

This feasibility study was part of a larger clinical trial on the effects of a patient decision aid for SUI treatment. We started a 61-day social media advertisement campaign to recruit women for the trial. The primary outcome of our study was enrolment pace. Secondary outcomes involved cost per participant, baseline demographic comparison and ad campaign performance metrics. Additionally, we interviewed recruited participants to identify the facilitators and barriers of our approach.

RESULTS

Ten participants were recruited, of whom 8 completed the full study protocol (2 questionnaires 6 months apart). The enrolment pace, 4.0 study participants per month, was faster compared to the average of 2.7 participants per month through conventional methods. The campaign reached 87 clicks on the advertisement per day and 1 % of these women showed interest in our study by contacting us. The overall conversion rate from click to full participation was 0.2 %. The costs per participant were €112. Besides higher age, the demographics of the social media recruited participants were comparable to the conventional inclusions. Qualitative analysis identified more user-oriented enrolment procedures and potential participant benefit as facilitators of social media recruitment.

CONCLUSION

This study shows that social media recruitment can be feasible in trials for women with SUI. It can accelerate recruitment of eligible participants. Optimising the enrolment procedure to better meet participants' needs and recruitment benefits may improve participation and cost-effectiveness. Trial registration ID 2017-3540.

Phase II study of vemurafenib in children and young adults with tumors harboring BRAF V600 mutations: NCI-COG pediatric MATCH trial (APEC1621) Arm G

BACKGROUND

This is a phase II subprotocol of the NCI-COG Pediatric MATCH study evaluating vemurafenib, a selective oral inhibitor of BRAF V600 mutated kinase, in patients with relapsed or refractory solid tumors harboring BRAF V600 mutations.

METHODS

Patients received vemurafenib at 550 mg/m2 (maximum 960 mg/dose) orally twice daily for 28-day cycles until progression or intolerable toxicity. The primary aim was to determine the objective response rate and secondary objectives included estimating progression-free survival and assessing the tolerability of vemurafenib.

RESULTS

Twenty-two patients matched to the subprotocol and 4 patients (18%) enrolled. Primary reasons for non-enrollment were ineligibility due to exclusions of low-grade glioma (nâ=â7) and prior BRAF inhibitor therapy (nâ=â7). Enrolled diagnoses were one each of histiocytosis, ameloblastoma, Ewing sarcoma, and high-grade glioma, all with BRAF V600E mutations. Treatment was overall tolerable with mostly expected grade 1/2 adverse events (AE). Grade 3 or 4 AE on treatment were acute kidney injury, hyperglycemia, and maculopapular rash. One patient came off therapy due to AE. One patient (glioma) had an objective partial response and remained on protocol therapy for 15 cycles.

CONCLUSION

There was a low accrual rate on this MATCH subprotocol, with only 18% of those who matched with BRAFV600 mutations enrolling, resulting in early termination, and limiting study results (ClinicalTrials.gov Identifier: NCT03220035).

Publication Bias in Upper Gastrointestinal Oncology Clinical Trials

PURPOSE

Evidence-based medicine requires evaluation of the medical literature to guide clinical reasoning and treatment recommendations. The presence of publication bias towards exclusion of non-statistically significant clinical trials may be leading to an incomplete evaluation of the literature and cause potentially incomplete guidance for patients. We aimed to compare publication rates and impact of publications of positive and negative outcome clinical trials.

METHODS

We queried the US National Library of Medicine Clinical Trials database identifying clinical trials with reported results on the topics of pancreatic, liver, and gastric cancer. A "positive" trial was defined as having a statistically significant difference between the treatment arms, while a "negative" did not. Data collected included termination cause, intervention, funding type, publication rates, and journal characteristics.

RESULTS

In total, 535 clinical trials were examined, across all pathologies clinical trials with significant findings for the primary outcome were published at a higher rate (99%) compared to those with non-significant findings (77%) (p < 0.01). Significantly, more studies with significant findings reached at least 80% of their estimated enrollment goal versus non-significant studies, 72% and 53% respectively (p < 0.01). Three of four metrics for impact of publication showed no difference between significant and non-significant studies once they reached publication.

CONCLUSION

These findings suggest that clinical trials of three of the most common upper gastrointestinal malignancies have a publication bias towards studies with significant primary outcome findings. This study has implications to the way evidence-based medicine is practiced as the medical literature appears to be failing to capture important data for consideration of clinical decision making.

[Development of an artificial intelligence system to improve cancer clinical trial eligibility screening]

INTRODUCTION

The recruitment step of all clinical trials is time consuming, harsh and generate extra costs. Artificial intelligence tools could improve recruitment in order to shorten inclusion phase. The objective was to assess the performance of an artificial intelligence driven tool (text mining, machine learning, classification…) for the screening and detection of patients, potentially eligible for recruitment in one of the clinical trials open at the "Institut de Cancérologie de Lorraine".

METHODS

Computerized clinical data during the first medical consultation among patients managed in an anticancer center over the 2019-2023 period were used to study the performances of an artificial intelligence tool (SAS® Viya). Recall, precision and F1-score were used to determine the artificial intelligence algorithm effectiveness. Time saved on screening was determined by the difference between the time taken using the artificial intelligence-assisted method and that taken using the standard method in clinical trial participant screening.

RESULTS

Out of 9876 patients included in the study, the artificial intelligence algorithm obtained the following scores: precision of 96 %, recall of 94 % and a 0.95 F1-score to detect patients with breast cancer (n=2039) and potentially eligible for inclusion in a clinical trial. The screening of 258 potentially eligible patient's files took 20s per file vs. 5min and 6s with standard method.

DISCUSSION

This study suggests that artificial intelligence could yield sizable improvements over standard practices in several aspects of the patient screening process, as well as in approaches to feasibility, site selection, and trial selection.

A maturity model for the scientific review of clinical trial designs and their informativeness

BACKGROUND

Informativeness, in the context of clinical trials, defines whether a study's results definitively answer its research questions with meaningful next steps. Many clinical trials end uninformatively. Clinical trial protocols are required to go through reviews in regulatory and ethical domains: areas that focus on specifics outside of trial design, biostatistics, and research methods. Private foundations and government funders rarely require focused scientific design reviews for these areas. There are no documented standards and processes, or even best practices, toward a capability for funders to perform scientific design reviews after their peer review process prior to a funding commitment.

MAIN BODY

Considering the investment in and standardization of ethical and regulatory reviews, and the prevalence of studies never finishing or failing to provide definitive results, it may be that scientific reviews of trial designs with a focus on informativeness offer the best chance for improved outcomes and return-on-investment in clinical trials. A maturity model is a helpful tool for knowledge transfer to help grow capabilities in a new area or for those looking to perform a self-assessment in an existing area. Such a model is offered for scientific design reviews of clinical trial protocols. This maturity model includes 11 process areas and 5 maturity levels. Each of the 55 process area levels is populated with descriptions on a continuum toward an optimal state to improve trial protocols in the areas of risk of failure or uninformativeness.

CONCLUSION

This tool allows for prescriptive guidance on next investments to improve attributes of post-funding reviews of trials, with a focus on informativeness. Traditional pre-funding peer review has limited capacity for trial design review, especially for detailed biostatistical and methodological review. Select non-industry funders have begun to explore or invest in post-funding review programs of grantee protocols, based on exemplars of such programs. Funders with a desire to meet fiduciary responsibilities and mission goals can use the described model to enhance efforts supporting trial participant commitment and faster cures.

Sociotechnical feasibility of natural language processing-driven tools in clinical trial eligibility prescreening for Alzheimer's disease and related dementias

BACKGROUND

Alzheimer's disease and related dementias (ADRD) affect over 55 million globally. Current clinical trials suffer from low recruitment rates, a challenge potentially addressable via natural language processing (NLP) technologies for researchers to effectively identify eligible clinical trial participants.

OBJECTIVE

This study investigates the sociotechnical feasibility of NLP-driven tools for ADRD research prescreening and analyzes the tools' cognitive complexity's effect on usability to identify cognitive support strategies.

METHODS

A randomized experiment was conducted with 60 clinical research staff using three prescreening tools (Criteria2Query, Informatics for Integrating Biology and the Bedside [i2b2], and Leaf). Cognitive task analysis was employed to analyze the usability of each tool using the Health Information Technology Usability Evaluation Scale. Data analysis involved calculating descriptive statistics, interrater agreement via intraclass correlation coefficient, cognitive complexity, and Generalized Estimating Equations models.

RESULTS

Leaf scored highest for usability followed by Criteria2Query and i2b2. Cognitive complexity was found to be affected by age, computer literacy, and number of criteria, but was not significantly associated with usability.

DISCUSSION

Adopting NLP for ADRD prescreening demands careful task delegation, comprehensive training, precise translation of eligibility criteria, and increased research accessibility. The study highlights the relevance of these factors in enhancing NLP-driven tools' usability and efficacy in clinical research prescreening.

CONCLUSION

User-modifiable NLP-driven prescreening tools were favorably received, with system type, evaluation sequence, and user's computer literacy influencing usability more than cognitive complexity. The study emphasizes NLP's potential in improving recruitment for clinical trials, endorsing a mixed-methods approach for future system evaluation and enhancements.

Using Bayesian hierarchical modeling for performance evaluation of clinical trial accrual for a cancer center

Introduction

Slow patient accrual in cancer clinical trials is always a concern. In 2021, the University of Kansas Comprehensive Cancer Center (KUCC), an NCI-designated comprehensive cancer center, implemented the Curated Cancer Clinical Outcomes Database (C3OD) to perform trial feasibility analyses using real-time electronic medical record data. In this study, we proposed a Bayesian hierarchical model to evaluate annual cancer clinical trial accrual performance.

Methods

The Bayesian hierarchical model uses Poisson models to describe the accrual performance of individual cancer clinical trials and a hierarchical component to describe the variation in performance across studies. Additionally, this model evaluates the impacts of the C3OD and the COVID-19 pandemic using posterior probabilities across evaluation years. The performance metric is the ratio of the observed accrual rate to the target accrual rate.

Results

Posterior medians of the annual accrual performance at the KUCC from 2018 to 2023 are 0.233, 0.246, 0.197, 0.150, 0.254, and 0.340. The COVID-19 pandemic partly explains the drop in performance in 2020 and 2021. The posterior probability that annual accrual performance is better with C3OD in 2023 than pre-pandemic (2019) is 0.935.

Conclusions

This study comprehensively evaluates the annual performance of clinical trial accrual at the KUCC, revealing a negative impact of COVID-19 and an ongoing positive impact of C3OD implementation. Two sensitivity analyses further validate the robustness of our model. Evaluating annual accrual performance across clinical trials is essential for a cancer center. The performance evaluation tools described in this paper are highly recommended for monitoring clinical trial accrual.

Algorithmic benchmark modulation: A novel method to develop success rates for clinical studies

BACKGROUND

High-quality decision-making in the pharmaceutical industry requires accurate assessments of the Probability of Technical Success of clinical trials. Failure to do so will lead to lost opportunities for both patients and investors. Pharmaceutical companies employ different methodologies to determine Probability of Technical Success values. Some companies use power and assurance calculations; others prefer to use industry benchmarks with or without the overlay of subjective modulations. At AstraZeneca, both assurance calculations and industry benchmarks are used, and both methods are combined with modulations.

METHODS

AstraZeneca has recently implemented a simple algorithm that allows for modulation of a Probability of Technical Success value. The algorithm is based on a set of multiple-choice questions. These questions cover a comprehensive set of issues that have historically been considered by AstraZeneca when subjective modulations to Probability of Technical Success values were made but do so in a much more structured way.

RESULTS

A set of 57 phase 3 Probability of Technical Success assessments suggests that AstraZeneca's historical estimation of Probability of Technical Success has been reasonably accurate. A good correlation between the subjective modulation and the modulation algorithm was found. This latter observation, combined with the finding that historically AstraZeneca has been reasonably accurate in its estimation of Probability of Technical Success, gives confidence in the validity of the novel method.

DISCUSSION

Although it is too early to demonstrate whether the method has improved the accuracy of company's Probability of Technical Success assessments, we present our data and analysis here in the hope that it may assist the pharmaceutical industry in addressing this key challenge. This new methodology, developed for pivotal studies, enables AstraZeneca to develop more consistent Probability of Technical Success assessments with less effort and can be used to adjust benchmarks as well as assurance calculations.

CONCLUSION

The Probability of Technical Success modulation algorithm addresses several concerns generally associated with assurance calculations or benchmark without modulation: selection biases, situations where little relevant prior data are available and the difficulty to model many factors affecting study outcomes. As opposed to using industry benchmarks, the Probability of Technical Success modulation algorithm allows to accommodate project-specific considerations.

Decision-making and autonomy among participants in early-phase cancer immunotherapy trials: a qualitative study

BACKGROUND

Participants considering early-phase cancer clinical trials (CTs) need to understand the unique risks and benefits prior to providing informed consent. This qualitative study explored the factors that influence patients' decisions about participating in early-phase cancer immunotherapy CTs through the ethical lens of relational autonomy.

METHODS

Using an interpretive descriptive design, interviews were conducted with 21 adult patients with advanced cancer who had enrolled in an early-phase CT. Data was analyzed using relational autonomy ethical theory and constant comparative analysis.

RESULTS

The extent to which participants perceived themselves as having a choice to participate in early-phase cancer immunotherapy CTs was a central construct. Perceptions of choice varied according to whether participants characterized their experience as an act of desperation or as an opportunity to receive a novel treatment. Intersecting psychosocial and structural factors influenced participants' decision making about participating in early-phase cancer immunotherapy trials. These relational factors included: (1) being provided with hope; (2) having trust; (3) having the ability to withdraw; and (4) timing constraints.

CONCLUSIONS

Findings highlight the continuum of perceived choice that exists among patients with cancer when considering participation in early-phase cancer immunotherapy CTs. All participants were interpreted as exhibiting some degree of relational autonomy within the psychosocial and structural context of early-phase CT decision making. This study offers insights into the intersection of cancer care delivery, personal beliefs and values, and established CT processes and structures that can inform future practices and policies associated with early-phase cancer immunotherapy CTs to better support patients in making informed decisions.

Experience with a hybrid recruitment approach of patient-facing web portal screening and subsequent phone and medical record review for a neurosurgical intervention trial for chronic ischemic stroke disability (PISCES III)

BACKGROUND

Recruitment of participants is the greatest risk to completion of most clinical trials, with 20-40% of trials failing to reach the targeted enrollment. This is particularly true of trials of central nervous system (CNS) therapies such as intervention for chronic stroke. The PISCES III trial was an invasive trial of stereotactically guided intracerebral injection of CTX0E03, a fetal derived neural stem cell line, in patients with chronic disability due to ischemic stroke. We report on the experience using a novel hybrid recruitment approach of a patient-facing portal to self-identify and perform an initial screen for general trial eligibility (tier 1), followed by phone screening and medical records review (tier 2) prior to a final in-person visit to confirm eligibility and consent.

METHODS

Two tiers of screening were established: an initial screen of general eligibility using a patient-facing web portal (tier 1), followed by a more detailed screen that included phone survey and medical record review (tier 2). If potential participants passed the tier 2 screen, they were referred directly to visit 1 at a study site, where final in-person screening and consent were performed. Rates of screening were tracked during the period of trial recruitment and sources of referrals were noted.

RESULTS

The approach to screening and recruitment resulted in 6125 tier 1 screens, leading to 1121 referrals to tier 2. The tier 2 screening resulted in 224 medical record requests and identification of 86 qualifying participants for referral to sites. The study attained a viable recruitment rate of 6 enrolled per month prior to being disrupted by COVID 19.

CONCLUSIONS

A tiered approach to eligibility screening using a hybrid of web-based portals to self-identify and screen for general eligibility followed by a more detailed phone and medical record review allowed the study to use fewer sites and reduce cost. Despite the difficult and narrow population of patients suffering moderate chronic disability from stroke, this strategy produced a viable recruitment rate for this invasive study of intracranially injected neural stem cells.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03629275.

Evaluation of an artificial intelligence-based clinical trial matching system in Chinese patients with hepatocellular carcinoma: a retrospective study

BACKGROUND

Artificial intelligence (AI)-assisted clinical trial screening is a promising prospect, although previous matching systems were developed in English, and relevant studies have only been conducted in Western countries. Therefore, we evaluated an AI-based clinical trial matching system (CTMS) that extracts medical data from the electronic health record system and matches them to clinical trials automatically.

METHODS

This study included 1,053 consecutive inpatients primarily diagnosed with hepatocellular carcinoma who were referred to the liver tumor center of an academic medical center in China between January and December 2019. The eligibility criteria extracted from two clinical trials, patient attributes, and gold standard were decided manually. We evaluated the performance of the CTMS against the established gold standard by measuring the accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and run time required.

RESULTS

The manual reviewers demonstrated acceptable interrater reliability (Cohen's kappa 0.65-0.88). The performance results for the CTMS were as follows: accuracy, 92.9-98.0%; sensitivity, 51.9-83.5%; specificity, 99.0-99.1%; PPV, 75.7-85.1%; and NPV, 97.4-98.9%. The time required for eligibility determination by the CTMS and manual reviewers was 2 and 150 h, respectively.

CONCLUSIONS

We found that the CTMS is particularly reliable in excluding ineligible patients in a significantly reduced amount of time. The CTMS excluded ineligible patients for clinical trials with good performance, reducing 98.7% of the work time. Thus, such AI-based systems with natural language processing and machine learning have potential utility in Chinese clinical trials.

Effectiveness of IT-supported patient recruitment: study protocol for an interrupted time series study at ten German university hospitals

BACKGROUND

As part of the German Medical Informatics Initiative, the MIRACUM project establishes data integration centers across ten German university hospitals. The embedded MIRACUM Use Case "Alerting in Care - IT Support for Patient Recruitment", aims to support the recruitment into clinical trials by automatically querying the repositories for patients satisfying eligibility criteria and presenting them as screening candidates. The objective of this study is to investigate whether the developed recruitment tool has a positive effect on study recruitment within a multi-center environment by increasing the number of participants. Its secondary objective is the measurement of organizational burden and user satisfaction of the provided IT solution.

METHODS

The study uses an Interrupted Time Series Design with a duration of 15 months. All trials start in the control phase of randomized length with regular recruitment and change to the intervention phase with additional IT support. The intervention consists of the application of a recruitment-support system which uses patient data collected in general care for screening according to specific criteria. The inclusion and exclusion criteria of all selected trials are translated into a machine-readable format using the OHDSI ATLAS tool. All patient data from the data integration centers is regularly checked against these criteria. The primary outcome is the number of participants recruited per trial and week standardized by the targeted number of participants per week and the expected recruitment duration of the specific trial. Secondary outcomes are usability, usefulness, and efficacy of the recruitment support. Sample size calculation based on simple parallel group assumption can demonstrate an effect size of d=0.57 on a significance level of 5% and a power of 80% with a total number of 100 trials (10 per site). Data describing the included trials and the recruitment process is collected at each site. The primary analysis will be conducted using linear mixed models with the actual recruitment number per week and trial standardized by the expected recruitment number per week and trial as the dependent variable.

DISCUSSION

The application of an IT-supported recruitment solution developed in the MIRACUM consortium leads to an increased number of recruited participants in studies at German university hospitals. It supports employees engaged in the recruitment of trial participants and is easy to integrate in their daily work.

Choosing Wisely: Applying Value-Based Economic Principles to Population Science Research Investment

Scientific research requires a substantial investment of time, effort, and money by researchers and funders. The funding that would be needed for all meritorious proposals far exceeds available resources. Major funding organizations use a multistep process for allocating research dollars that follows and extends beyond scientific peer review with considerations including mission priority, budget, and potential duplication of past or ongoing research activities. At the level of programmatic review, the process tends to be less proscribed than scientific review, but considerations relate to and are akin to basic value-driven economic principles. We propose a framework that encompasses the elements of programmatic review and provide examples of how the economic principles of opportunity costs, diminishing marginal productivity, sunk costs, economic optimization, return on investment, and option value apply to both research planning and funding decisions. Examples use cancer control population science research, as the nature of observational and interventional research involves large population studies (large sample size, recruitment, and often long-duration follow-up costs) which demand a high level of resource utilization; the same principles can be applied throughout medical and population health research. Awareness of the aspects of programmatic review and context to focus discussion regarding funding decisions may help guide research planning, decision-making, and increase transparency of the overall review process.

Smart Start - Designing Powerful Clinical Trials Using Pilot Study Data

BACKGROUND: Digital health interventions may be optimized before evaluation in a randomized clinical trial. Although many digital health interventions are deployed in pilot studies, the data collected are rarely used to refine the intervention and the subsequent clinical trials. METHODS: We leverage natural variation in patients eligible for a digital health intervention in a remote patient-monitoring pilot study to design and compare interventions for a subsequent randomized clinical trial. RESULTS: Our approach leverages patient heterogeneity to identify an intervention with twice the estimated effect size of an unoptimized intervention. CONCLUSIONS: Optimizing an intervention and clinical trial based on pilot data may improve efficacy and increase the probability of success. (Funded by the National Institutes of Health and others; ClinicalTrials.gov number, NCT04336969.)

Evaluation of Eligibility Criteria Relevance for the Purpose of IT-Supported Trial Recruitment: Descriptive Quantitative Analysis

BACKGROUND

Clinical trials (CTs) are crucial for medical research; however, they frequently fall short of the requisite number of participants who meet all eligibility criteria (EC). A clinical trial recruitment support system (CTRSS) is developed to help identify potential participants by performing a search on a specific data pool. The accuracy of the search results is directly related to the quality of the data used for comparison. Data accessibility can present challenges, making it crucial to identify the necessary data for a CTRSS to query. Prior research has examined the data elements frequently used in CT EC but has not evaluated which criteria are actually used to search for participants. Although all EC must be met to enroll a person in a CT, not all criteria have the same importance when searching for potential participants in an existing data pool, such as an electronic health record, because some of the criteria are only relevant at the time of enrollment.

OBJECTIVE

In this study, we investigated which groups of data elements are relevant in practice for finding suitable participants and whether there are typical elements that are not relevant and can therefore be omitted.

METHODS

We asked trial experts and CTRSS developers to first categorize the EC of their CTs according to data element groups and then to classify them into 1 of 3 categories: necessary, complementary, and irrelevant. In addition, the experts assessed whether a criterion was documented (on paper or digitally) or whether it was information known only to the treating physicians or patients.

RESULTS

We reviewed 82 CTs with 1132 unique EC. Of these 1132 EC, 350 (30.9%) were considered necessary, 224 (19.8%) complementary, and 341 (30.1%) total irrelevant. To identify the most relevant data elements, we introduced the data element relevance index (DERI). This describes the percentage of studies in which the corresponding data element occurs and is also classified as necessary or supplementary. We found that the query of "diagnosis" was relevant for finding participants in 79 (96.3%) of the CTs. This group was followed by "date of birth/age" with a DERI of 85.4% (n=70) and "procedure" with a DERI of 35.4% (n=29).

CONCLUSIONS

The distribution of data element groups in CTs has been heterogeneously described in previous works. Therefore, we recommend identifying the percentage of CTs in which data element groups can be found as a more reliable way to determine the relevance of EC. Only necessary and complementary criteria should be included in this DERI.

Real-World Experience on Why Research Flatlines: A Review of Trials From the Coordinator's Perspective

INTRODUCTION

Investigator-initiated research trial failure is a national concern that hinders the dissemination of information while wasting resources, time, and funding. The goal of this analysis was to provide an objective review of points to consider increasing an investigator's chances of success.

METHODS

The included trials were divided into two groups based on whether they were successful or unsuccessful in meeting enrollment goals. Common issues were noted for each trial to identify prevalent issues and compare their quantity within each group.

RESULTS

Unsuccessful trials averaged twice as many issues as trials in the successful group. The most common problems identified in unsuccessful studies involved study planning, whereas the most common problems identified in successful studies revolved around study staff.

CONCLUSIONS

There is no single definitive indicator for trial failure; however, awareness of these issues in a trial's planning phase can help prevent their occurrence and aid in overall completion and publication.

Implementation of inclusion and exclusion criteria in clinical studies in OHDSI ATLAS software

Clinical trials are essential parts of a medical study process, but studies are often cancelled due to a lack of participants. Clinical Trial Recruitment Support Systems are systems that help to increase the number of participants by seeking more suitable subjects. The software ATLAS (developed by Observational Health Data Sciences and Informatics) can support the launch of a clinical trial by building cohorts of patients who fulfill certain criteria. The correct use of medical classification systems aiming at clearly defined inclusion and exclusion criteria in the studies is an important pillar of this software. The aim of this investigation was to determine whether ATLAS can be used in a Clinical Trial Recruitment Support System to portray the eligibility criteria of clinical studies. Our analysis considered the number of criteria feasible for integration with ATLAS and identified its strengths and weaknesses. Additionally, we investigated whether nonrepresentable criteria were associated with the utilized terminology systems. We analyzed ATLAS using 223 objective eligibility criteria from 30 randomly selected trials conducted in the last 10 years. In the next step, we selected appropriate ICD, OPS, LOINC, or ATC codes to feed the software. We classified each criterion and study based on its implementation capability in the software, ensuring a clear and logical progression of information. Based on our observations, 51% of the analyzed inclusion criteria were fully implemented in ATLAS. Within our selected example set, 10% of the studies were classified as fully portrayable, and 73% were portrayed to some extent. Additionally, we conducted an evaluation of the software regarding its technical limitations and interaction with medical classification systems. To improve and expand the scope of criteria within a cohort definition in a practical setting, it is recommended to work closely with personnel involved in the study to define the criteria precisely and to carefully select terminology systems. The chosen criteria should be combined according to the specific setting. Additional work is needed to specify the significance and amount of the extracted criteria.

The future of clinical trials-is it virtual?

INTRODUCTION

Participant recruitment to clinical trials is often sub-optimal. Decentralized clinical trials have the potential to address challenges in traditional site-based clinical trial recruitment.

SOURCES OF DATA

This review is based on recently published literature and the experience of running a large industry-sponsored interventional trial using both traditional and decentralized methods.

AREAS OF AGREEMENT

Efficient delivery of clinical trials is essential to continue to provide therapeutic improvements in a timely and cost-efficient way. Clinical trial designs are constantly evolving to achieve effective trial delivery, manage the complexity of new therapeutic algorithms and conform to cultural developments.

AREAS OF CONTROVERSY

Digitally innovative decentralized clinical trials may be a solution to improve recruitment and retention. Although many trials incorporate digital innovations to reduce patient burden, decentralized clinical trials allow remote access to clinical research, potentially enhancing geographical diversity as well as reducing participant burden.

GROWING POINTS

Areas for development currently being discussed are developing a 'recruitment platform' that exploits the reach of digital connectivity, automated identification of eligible participants from volunteers, employing technology for remote interaction and exploring the logistic process of delivering the interventions.

AREAS TIMELY FOR RELEVANT RESEARCH

The focus of development must ensure that the overall impact will widen participation and reduce inequalities in healthcare.

Health care professional recruitment of patients and family carers to palliative care randomised controlled trials: A qualitative multiple case study

BACKGROUND

Trial participant recruitment is an interactional process between health care professionals, patients and carers. Little is known about how clinicians carry out this role in palliative care trials and the reasons why they do or do not recruit participants.

AIMS

To explore how clinicians recruit to palliative care trials, why they choose to implement particular recruitment strategies, and the factors that influence their choices.

DESIGN

A qualitative multiple case study of three UK palliative care trials. Data collection included interviews and study documentation. Analysis involved developing and refining theoretical propositions, guided by the '6Ps' of the 'Social Marketing Mix Framework' as an a priori framework (identifying participants, product, price, place, promotion and working with partners). Framework Analysis guided within and then cross-case analysis.

SETTINGS/PARTICIPANTS

Study investigators and research staff (n = 3, 9, 7) from trial coordinating centres and recruitment sites (hospice and hospital).

RESULTS

Cross-case analysis suggests the 'Social Marketing Mix Framework' is useful for understanding recruitment processes but wider contextual issues need to be incorporated. These include the 'emotional labour' of diagnosing dying and communicating palliative and end-of-life care to potential participants and how the recruitment process is influenced by the power relationships and hierarchies that exist among professional groups. These factors can lead to and support paternalistic practices.

CONCLUSIONS

Those planning trials need to ensure that trial recruiters, depending on their experience and trial characteristics, have access to training and support to address the 'emotional labour' of recruitment. The type of training required requires further research.

Leveraging the Expertise of the CTSA Program to Increase the Impact and Efficiency of Clinical Trials

Importance

Multicenter clinical trials play a critical role in the translational processes that enable new treatments to reach all people and improve public health. However, conducting multicenter randomized clinical trials (mRCT) presents challenges. The Trial Innovation Network (TIN), established in 2016 to partner with the Clinical and Translational Science Award (CTSA) Consortium of academic medical institutions in the implementation of mRCTs, consists of 3 Trial Innovation Centers (TICs) and 1 Recruitment Innovation Center (RIC). This unique partnership has aimed to address critical roadblocks that impede the design and conduct of mRCTs, in expectation of accelerating the translation of novel interventions to clinical practice. The TIN's challenges and achievements are described in this article, along with examples of innovative resources and processes that may serve as useful models for other clinical trial networks providing operational and recruitment support.

Observations

The TIN has successfully integrated more than 60 CTSA institution program hubs into a functional network for mRCT implementation and optimization. A unique support system for investigators has been created that includes the development and deployment of novel tools, operational and recruitment services, consultation models, and rapid communication pathways designed to reduce delays in trial start-up, enhance recruitment, improve engagement of diverse research participants and communities, and streamline processes that improve the quality, efficiency, and conduct of mRCTs. These resources and processes span the clinical trial spectrum and enable the TICs and RIC to serve as coordinating centers, data centers, and recruitment specialists to assist trials across the National Institutes of Health and other agencies. The TIN's impact has been demonstrated through its response to both historical operational challenges and emerging public health emergencies, including the national opioid public health crisis and the COVID-19 pandemic.

Conclusions and Relevance

The TIN has worked to reduce barriers to implementing mRCTs and to improve mRCT processes and operations by providing needed clinical trial infrastructure and resources to CTSA investigators. These resources have been instrumental in more quickly and efficiently translating research discoveries into beneficial patient treatments.

Count Me In: an inclusive approach towards patient recruitment for clinical research studies in the NHS

BACKGROUND

Participation in clinical research is associated with better patient outcomes and higher staff retention and satisfaction rates. Nevertheless, patient recruitment to mental health studies is challenging due to a reliance on clinician or patient referrals (standard approach). To empower patients and make healthcare research more equitable, we explored a novel researcher-led approach, called 'Count Me In' (CMI).

OBJECTIVE

To evaluate a 12-month implementation of CMI in a routine clinical setting.

METHODS

CMI was launched in August 2021 in a mental health National Health Service (NHS) Trust in England. Patients (aged 18+) learnt about CMI at their initial clinical appointment. Unless they opted out, they became contactable for research (via research informatics searches).

FINDINGS

After 12 months, 368 patients opted out and 22 741 became contactable through CMI, including 2716 through the standard approach and 20 025 through electronic searches (637% increase). Of those identified via electronic searches, 738 were contacted about specific studies and 270 consented to participate. Five themes were identified based on patient and staff experiences of CMI: 'level of awareness and accessibility of CMI', 'perceptions of research and perceived engagement with CMI', 'inclusive research practice', 'engagement and incentives for research participation', and 'relationships between clinical and research settings'.

CONCLUSIONS

CMI (vs standard) led to a larger and diverse patient cohort and was favoured by patients and staff. Yet a shift in the NHS research culture is needed to ensure that this diversity translates to actual research participation.

CLINICAL IMPLICATIONS

Through collaboration with other NHS Trusts and services, key funders (National Institute for Health and Care Research) and new national initiatives (Office for Life Sciences Mental Health Mission), CMI has the potential to address recruitment challenges through rapid patient recruitment into time-sensitive country-wide studies.

Uncovering key clinical trial features influencing recruitment

Background

Randomized clinical trials (RCT) are the foundation for medical advances, but participant recruitment remains a persistent barrier to their success. This retrospective data analysis aims to (1) identify clinical trial features associated with successful participant recruitment measured by accrual percentage and (2) compare the characteristics of the RCTs by assessing the most and least successful recruitment, which are indicated by varying thresholds of accrual percentage such as ≥ 90% vs ≤ 10%, ≥ 80% vs ≤ 20%, and ≥ 70% vs ≤ 30%.

Methods

Data from the internal research registry at Columbia University Irving Medical Center and Aggregated Analysis of ClinicalTrials.gov were collected for 393 randomized interventional treatment studies closed to further enrollment. We compared two regularized linear regression and six tree-based machine learning models for accrual percentage (i.e., reported accrual to date divided by the target accrual) prediction. The outperforming model and Tree SHapley Additive exPlanations were used for feature importance analysis for participant recruitment. The identified features were compared between the two subgroups.

Results

CatBoost regressor outperformed the others. Key features positively associated with recruitment success, as measured by accrual percentage, include government funding and compensation. Meanwhile, cancer research and non-conventional recruitment methods (e.g., websites) are negatively associated with recruitment success. Statistically significant subgroup differences (corrected p-value < .05) were found in 15 of the top 30 most important features.

Conclusion

This multi-source retrospective study highlighted key features influencing RCT participant recruitment, offering actionable steps for improvement, including flexible recruitment infrastructure and appropriate participant compensation.

Analysis of Terminated Hand and Wrist-Related Clinical Trials

Purpose

While clinical trials provide high-quality evidence guiding medical decision-making, early trial termination can result in both lost time and resources. Our purpose was to investigate the rate of and reasons for clinical trial termination for hand and wrist-related conditions and identify study characteristics associated with early trial termination.

Methods

The ClinicalTrials.gov database was queried for all hand and wrist-related clinical trials. All terminated and completed trials were reviewed, with characteristics and reasons for termination recorded. Study characteristics included type, purpose, intervention assessed, enrollment, group allocation, blinding, trial phase, sponsor type, and geographic region. Chi-square test was used to identify associations between trial characteristics and terminated versus completed status.

Results

A total of 793 hand and wrist-related clinical trials were identified, with 77 trials (10%) terminated prior to completion. The most common reason for termination was "recruitment/retention difficulty," reported in 37 (48%) terminated trials. In comparing competed versus terminated trials, primary purpose (nonobservational studies), enrollment (<50 patients), and geographic region (North America) were all significantly more likely to be terminated. Terminated trials were more likely to have an intervention type investigating a specific device or drug.

Conclusions

Early trial termination for hand and wrist-related conditions is common (10%), with patient recruitment and retention identified as the leading cause of termination. Trials involving potential commercial incentives (those investigating a device or drug) were associated with an increased rate of trial termination.

Clinical relevance

An emphasis on patient enrollment during study design may aid in mitigating the most common cause of early clinical trial termination.

Design issues in crossover trials involving patients with Parkinson's disease

Background and objectives

Crossover designs are frequently used to assess treatments for patients with Parkinson's disease. Typically, two-period two-treatment trials include a washout period between the 2 periods and assume that the washout period is sufficiently long to eliminate carryover effects. A complementary strategy might be to jointly model carryover and treatment effects, though this has rarely been done in Parkinson's disease crossover studies. The primary objective of this research is to demonstrate a modeling approach that assesses treatment and carryover effects in one unified mixed model analysis and to examine how it performs in a simulation study and a real data analysis example, as compared to other data analytic approaches used in Parkinson's disease crossover studies.

Methods

We examined how three different methods of analysis (standard crossover t-test, mixed model with a carryover term included in model statement, and mixed model with no carryover term) performed in a simulation study and illustrated the methods in a real data example in Parkinson's disease.

Results

The simulation study based on the presence of a carryover effect indicated that mixed models with a carryover term and an unstructured correlation matrix provided unbiased estimates of treatment effect and appropriate type I error. The methods are illustrated in a real data example involving Parkinson's disease. Our literature review revealed that a majority of crossover studies included a washout period but did not assess whether the washout was sufficiently long to eliminate the possibility of carryover.

Discussion

We recommend using a mixed model with a carryover term and an unstructured correlation matrix to obtain unbiased estimates of treatment effect.

The RIC Recruitment & Retention Materials Toolkit - a resource for developing community-informed study materials

Clinical trials face many challenges with meeting projected enrollment and retention goals. A study's recruitment materials and messaging convey necessary key information and therefore serve as a critical first impression with potential participants. Yet study teams often lack the resources and skills needed to develop engaging, culturally tailored, and professional-looking recruitment materials. To address this gap, the Recruitment Innovation Center recently developed a Recruitment & Retention Materials Content and Design Toolkit, which offers research teams guidance, actionable tips, resources, and customizable templates for creating trial-specific study materials. This paper seeks to describe the creation and contents of this new toolkit.

Factors Affecting Success of New Drug Clinical Trials

Clinical trials are an essential process in the development of new drugs. In spite of time-consuming processes and high costs, the overall success rate of clinical trials is only 7.9%, which is a high risk for biopharmaceutical companies. However, despite these huge risks, research on finding factors affecting clinical trials to overcome and manage to risks has been insufficient. Considering these characteristics of the pharmaceutical industry, this study investigated the factors affecting the success of sponsor-initiated clinical trials. The success factors investigated were categorized into four factors: quality of clinical trials, speed of clinical trials, relationship type, and communication. Logistic regression was performed to measure each factor by analyzing 24,295 cases of Phase 1 to 4 trials from ClinicalTrials.gov. Because of the analysis, the factors affecting the success of the clinical trials were varied according to each clinical phase and the drug types: New Molecular Entity (NME)/Biologics, and the success ratio in the quality variable affected the overall clinical trial phases. Additionally, the experience, speed, relationship type, and communication variables were also found to be statistically significant for the success of each phase and drug type.

Principal Investigators' Perceptions on Factors Associated with Successful Recruitment in Clinical Trials

Participant recruitment continues to be a challenge to the success of randomized controlled trials, resulting in increased costs, extended trial timelines and delayed treatment availability. Literature provides evidence that study design features (e.g., trial phase, study site involvement) and trial sponsor are significantly associated with recruitment success. Principal investigators oversee the conduct of clinical trials, including recruitment. Through a cross-sectional survey and a thematic analysis of free-text responses, we assessed the perceptions of sixteen principal investigators regarding success factors for participant recruitment. Study site involvement and funding source do not necessarily make recruitment easier or more challenging from the perspective of the principal investigators. The most commonly used recruitment strategies are also the most effort inefficient (e.g., in-person recruitment, reviewing the electronic medical records for prescreening). Finally, we recommended actionable steps, such as improving staff support and leveraging informatics-driven approaches, to allow clinical researchers to enhance participant recruitment.

Status of pediatric echocardiography clinical trials: a cross-sectional study of registered trials in ClinicalTrials.gov

Background

The objective of this study is to analyze the characteristics of pediatric echocardiography clinical trials registered in ClinicalTrials.gov.

Methods

A data set including pediatric echocardiography clinical trials was downloaded from ClinicalTrials.gov until May 13, 2022. We searched the PubMed, Medline, Google Scholar, and Embase databases to extract publication data. Pediatric echocardiography trial characteristics, application areas, and publication status were described. The secondary objectives were to evaluate factors associated with trial publication.

Results

We identified 410 pediatric echocardiography reporting definite age, of which 246 were interventional and 146 were observational. Drug interventions were the most commonly studied (32.9%). The most applied area of pediatric echocardiography was congenital heart disease, followed by hemodynamics of preterm or neonatal infants, cardiomyopathy, inflammatory heart disease, pulmonary hypertension, and cardio-oncology. According to the primary completion data, 54.9% of the trials were completed before August 2020. 34.2% of the trials had been published within 24 months. Union countries and quadruple masking were more likely to be published.

Conclusion

Echocardiography is rapidly evolving in pediatric clinical applications, including anatomic imaging and functional imaging. Novel speckle tracking techniques have also been pivotal in the assessment of cancer therapeutics-related cardiac dysfunction. A small number of clinical trials in pediatric echocardiography are published in a timely fashion. Concerted efforts are needed to promote trial transparency.

Understanding potential participation barriers to improve trial design and outcomes: clinical trial simulation in palmoplantar pustulosis as a case study

OBJECTIVES

Evaluate the experiences and perceptions of patients participating in a simulated clinical trial and identify ways to enhance future patient-centric trial designs.

DESIGN

International, multicentre, non-interventional, virtual clinical trial visits with patient debriefs and advisory boards.

SETTING

Virtual clinic visits and accompanying advisory boards.

PARTICIPANTS

Nine patients with palmoplantar pustulosis for simulated trial visits; 14 patients and patient representatives for advisory boards.

MAIN OUTCOME MEASURES

Qualitative responses to trial documentation, visit schedule and logistics, and trial design were collected during patient debriefs. Results were discussed at two virtual advisory board meetings.

RESULTS

Patients identified key barriers to participation and potential difficulties encountered when attending trial visits and completing assessments. They also proposed recommendations to overcome these challenges. Patients recognised the need for comprehensive informed consent forms, but recommended use of non-technical language, brevity and additional support to aid understanding. Other trial documentations should be relevant to the disease and include known efficacy and safety of the study drug. Patients were concerned about receiving placebo, stopping existing medications and being unable to receive the study drug after trial completion; therefore, patients and physicians recommended an open-label extension following trial completion. Trial visits were too numerous (n=20) and too long (3-4 hours each); patients recommended improvements to the design to make best use of their time and reduce unnecessary waiting. They also requested financial and logistical support. Patients expressed a desire for study outcomes that matter to them, related to their ability to undertake normal daily activities and not be a burden to others.

CONCLUSIONS

Simulated trials are an innovative method for assessing trial design and acceptance from a patient-centric perspective, enabling specific improvements to be made prior to trial initiation. Incorporation of recommendations from simulated trials could enhance trial recruitment and retention, and optimise trial outcomes and data quality.

Building an infrastructure to support the development, conduct, and reporting of informative clinical studies: The Rockefeller University experience

Introduction

Clinical trials are a vital component of translational science, providing crucial information on the efficacy and safety of new interventions and forming the basis for regulatory approval and/or clinical adoption. At the same time, they are complex to design, conduct, monitor, and report successfully. Concerns over the last two decades about the quality of the design and the lack of completion and reporting of clinical trials, characterized as a lack of "informativeness," highlighted by the experience during the COVID-19 pandemic, have led to several initiatives to address the serious shortcomings of the United States clinical research enterprise.

Methods and Results

Against this background, we detail the policies, procedures, and programs that we have developed in The Rockefeller University Center for Clinical and Translational Science (CCTS), supported by a Clinical and Translational Science Award (CTSA) program grant since 2006, to support the development, conduct, and reporting of informative clinical studies.

Conclusions

We have focused on building a data-driven infrastructure to both assist individual investigators and bring translational science to each element of the clinical investigation process, with the goal of both generating new knowledge and accelerating the uptake of that knowledge into practice.

Recruitment rates and strategies in exercise trials in cancer survivorship: a systematic review

PURPOSE

Despite clear evidence-based supporting a benefit to exercise on physical and psychological metrics in patients with cancer, recruitment to exercise trials amongst cancer survivors is suboptimal. We explore current recruitment rates, strategies, and common barriers to participation in exercise oncology trials in cancer survivorship.

METHODS

A systematic review was conducted using a pre-defined search strategy in EMBASE, CINAHL, Medline, Cochrane Library, and Web of Science. The search was performed up to 28/02/2022. Screening of titles and abstracts, full-text review, and data extraction was completed in duplicate.

RESULTS

Of the 3204 identified studies, 87 papers corresponding to 86 trials were included. Recruitment rates were highly variable with a median rate of 38% (range 0.52-100%). Trials recruiting prostate cancer patients only had the highest median recruitment rate (45.9%) vs trials recruiting colorectal cancer patients only which had the lowest (31.25%). Active recruitment strategies such as direct recruitment via a healthcare professional were associated with higher recruitment rates (rho = 0.201, p = 0.064). Common reasons for non-participation included lack of interest (46.51%, n (number of studies) = 40); distance and transport (45.3%, n = 39); and failure to contact (44.2%, n = 38).

CONCLUSIONS

Recruitment of cancer survivors to exercise interventions is suboptimal with barriers being predominantly patient-oriented. This paper provides the benchmark for current recruitment rates to exercise oncology trials, providing data for trialists planning future trial design and implementation, optimise future recruitment strategies, and evaluate their own recruitment success against current practice.

IMPLICATIONS FOR CANCER SURVIVORS

Enhanced recruitment to cancer survivorship exercise trials is necessary in facilitating the publication of definitive exercise guidelines, generalisable to varying cancer cohorts.

PROSPERO REGISTRATION NUMBER

CRD42020185968.

Monitoring and modifying recruitment and retention strategies for an ongoing randomised clinical trial with venous leg ulcer patients: Overcoming barriers to participation

Venous leg ulcers (VLUs) are open skin lesions of the lower legs arising in areas affected by venous hypertension that are associated with substantial morbidity. Clinical trials testing innovative approaches to improve healing outcomes are critically needed because standard therapies are often ineffective. However, patients with VLUs frequently have multiple physical, emotional and socioeconomic challenges that can negatively impact their decision to enrol in a clinical trial. To benefit clinical researchers and ultimately the community of patients with chronic wounds, this paper describes the monitoring and modification of recruitment strategies in an ongoing clinical trial testing effects of omega-3 fatty acid oral supplementation on VLU healing in ageing adults (n = 208). Multiple modifications over time in this study have targeted participation barriers identified through data monitoring and include expanding inclusion criteria, adding recruitment sites, enhancing communication methods, and meeting patients' transportation needs. Recruitment activities from January 2019 to June 2022 have resulted in 57 participants (mean age: 63.7 years). Overall, the recruitment rate is 42.5% of patients contacted during face-to-face visits. Overcoming barriers to participation is key to helping patients with VLUs interested in research enrol in clinical trials aiming to improve healing outcomes in this vulnerable population.

Rates of discontinuation and non-publication of upper and lower extremity fracture clinical trials

PURPOSE

To our knowledge, no study has quantified the rate of discontinuation and nonpublication of randomized controlled trials (RCTs) regarding upper and lower extremity fractures.

METHODS

We searched ClinicalTrials.gov on September 9th, 2020, for phase 3 and 4 RCTs pertaining to upper and lower extremity fractures. Trial completion status was determined using records available on ClinicalTrials.gov. Publication status was determined using records on ClinicalTrials.gov and by searching PubMed (MEDLINE), Embase, and Google Scholar. We queried corresponding authors on trial status if a peer-reviewed publication was not identified.

RESULTS

Our final analysis included 142 RCTs, of which 57 (40.1%) were discontinued and 71 (50%) were unpublished. Thirty-six (of 57, 63.2%) discontinued trials failed to provide a reason for discontinuation, the most commonly identified reason for discontinuation was due to inadequate recruitment (13/21, 61.9%). Completed trials were more likely to reach publication (59/85; 69.4%; X² = 32.92; P ≤ 0.001) than discontinued trials. Trials with more than 80 participants were less likely not to reach publication (AOR: 0.12; 95% CI 0.15-0.66).

CONCLUSION

Our analysis of 142 upper and lower extremity fracture RCTs demonstrated one-half failed to reach publication and two-fifths were discontinued prior to trial completion. These findings indicate the need for increased guidance in developing, completing, and publishing RCTs in upper and lower extremity fractures. Discontinuation and nonpublication of orthopaedic RCTs hinder the public's access to collected data and negate the valued contribution from study participants. Discontinuation and non-publication of clinical trials may subject participants to potentially harmful interventions, limit the advancement of clinical research, and contribute to research waste.

LEVEL OF EVIDENCE

III.

Participant Recruitment Issues in Child and Adolescent Psychiatry Clinical Trials with a Focus on Prevention Programs: A Meta-Analytic Review of the Literature

Introduction: There is a strong need to conduct rigorous and robust trials for children and adolescents in mental health settings. One of the main barriers to meeting this requirement is the poor recruitment rate. Effective recruitment strategies are crucial for the success of a clinical trial, and therefore, we reviewed recruitment strategies in clinical trials on children and adolescents in mental health with a focus on prevention programs. Methods: We reviewed the literature by searching PubMed/Medline, the Cochrane Library database, and Web of Science through December 2022 as well as the reference lists of relevant articles. We included only studies describing recruitment strategies for pediatric clinical trials in mental health settings and extracted data on recruitment and completion rates. Results: The search yielded 13 studies that enrolled a total of 14,452 participants. Overall, studies mainly used social networks or clinical settings to recruit participants. Half of the studies used only one recruitment method. Using multiple recruitment methods (56.6%, 95%CI: 24.5–86.0) resulted in higher recruitment. The use of monetary incentives (47.0%, 95%CI: 24.6–70.0) enhanced the recruitment rate but not significantly (32.6%, 95%CI: 15.7–52.1). All types of recruitment methods showed high completion rates (82.9%, 95%CI: 61.7–97.5) even though prevention programs showed the smallest recruitment rate (76.1%, 95%CI: 50.9–94.4). Conclusions: Pediatric mental health clinical trials face many difficulties in recruitment. We found that these trials could benefit from faster and more efficient recruitment of participants when more than one method is implemented. Social networks can be helpful where ethically possible. We hope the description of these strategies will help foster innovation in recruitment for pediatric studies in mental health.

The need for a new keyword - "Trial registry-metaresearch" - to track certain uses of clinical trial registry records

Public clinical trial registries contain a large amount of information about a large number of trials. Academic researchers have conducted various analyses using such data. However, some of these studies do not concern the medical condition or intervention that is the focus of each trial. We list examples of publications that have performed such analyses. Currently, there is no keyword to track relevant publications. Here, we propose a novel keyword, "Trial registry-metaresearch", that could be used in such publications. This would be a great help to researchers who wish to more systematically search the literature for such metaresearch.

Direct-to-Consumer Recruitment Methods via Traditional and Social Media to Aid in Research Accrual for Clinical Trials for Rare Diseases: Comparative Analysis Study

BACKGROUND

Recruitment into clinical trials is a challenging process, with as many as 40% of studies failing to meet their target sample sizes. The principles of direct-to-consumer (DTC) advertising rely upon novel marketing strategies. The ability to reach expansive audiences in the web-based realm presents a unique opportunity for researchers to overcome various barriers to enrollment in clinical trials. Research has investigated the use of individual web-based platforms to aid in recruitment and accrual into trials; however, a gap in the literature exists, whereby multiple mass communication platforms have yet to be investigated across a range of clinical trials.

OBJECTIVE

There is a need to better understand how individual factors combine to collectively influence trial recruitment. We aimed to test whether DTC recruitment of potentially eligible study participants via social media platforms (eg, Facebook [Meta Platforms Inc] and Twitter [Twitter Inc]) was an effective strategy or whether this acted as an enhancement to traditional (eg, email via contact registries) recruitment strategies through established clinical research sites.

METHODS

This study tested multiple DTC web-based recruitment efforts (Facebook, Twitter, email, and patient advocacy group [PAG] involvement) across 6 national and international research studies from 5 rare disease consortia. Targeted social media messaging, social media management software, and individual study websites with prescreening questions were used in the Protocol for Increasing Accrual Using Social Media (PRISM).

RESULTS

In total, 1465 PRISM website referrals occurred across all 6 studies. Organic (unpaid) Facebook posts (676/1465, 46.14%) and Rare Diseases Clinical Research Network patient contact registry emails (461/1465, 31.47%) represented the most successful forms of engagement. PRISM was successful in accumulating a 40.1% (136/339) lead generation (those who screened positive and consented to share their contact information to be contacted by a clinical site coordinator). Despite the large number of leads generated from PRISM recruitment efforts, the number of patients who were subsequently enrolled in studies was low. Across 6 studies, 3 participants were ultimately enrolled, meaning that 97.8% (133/136) of leads dropped off.

CONCLUSIONS

The results indicate that although accrual results were low, this is consistent with previously documented challenges of studying populations with rare diseases. Targeted messaging integrated throughout the recruitment process (eg, referral, lead, and accrual) remains an area for further research. Key elements to consider include structuring the communicative workflow in such a way that PAG involvement is central to the process, with clinical site coordinators actively involved after an individual consents to share their contact information. Customized approaches are needed for each population and research study, with observational studies best suited for social media recruitment. As evidenced by lead generation, results suggest that web-based recruitment efforts, coupled with targeted messaging and PAG partnerships, have the potential to supplement clinical trial accrual.

Can learnings from the COVID-19 pandemic improve trial conduct post-pandemic? A case study of strategies used by the DISC trial

Background

RCTs often face issues such as slow recruitment, poor intervention adherence and high attrition, however the 2020/2021 COVID-19 pandemic intensified these challenges. Strategies employed by the DISC trial to overcome pandemic-related barriers to recruitment, treatment delivery and retention may be useful to help overcome routine problems.

Methods

A structured survey and teleconference with sites was undertaken. Key performance indicators in relation to recruitment, treatment delivery and retention were compared descriptively before and after the pandemic started. This was situated also in relation to qualitative opinions of research staff.

Results

Prior to the pandemic, retention was 93.6%. Increased support from the central trial management team and remote data collection methods kept retention rates high at 81.2% in the first 6 months of the pandemic, rising to 89.8% in the subsequent 6 months. Advertising the study to patients resulted in 12.8 patients/month enquiring about participation, however only six were referred to recruiting sites. Sites reported increased support from junior doctors resolved research nurse capacity issues. One site avoided long delays by using theatre space in a private hospital.

Conclusions

Recruitment post-pandemic could be improved by identification of barriers, increased support from junior doctors through the NIHR associate PI scheme and advertising. Remote back-up options for data collection can keep retention high while reducing patient and site burden. To future proof studies against similar disruptions and provide more flexibility for participants, we recommend that RCTs have a back-up option of remote recruitment, a back-up location for surgeries and flexible approaches to collecting data.

Pediatric subspecialty health care providers' views of recruitment during a randomized controlled trial of a mobile health intervention

Background

Randomized clinical trials (RCTs) enrolling pediatric populations often struggle with recruitment. Engaging healthcare providers in the recruitment process may increase patients' and caregivers' willingness to participate in research. The purpose of this study was to understand the perspectives of pediatric subspecialty healthcare providers considering recruiting patients to participate in an mobile health (mHealth) RCT.

Methods

We conducted 9 semi-structured interviews and 1 focus group with a total of N = 11 providers from various disciplines before the initiation of an mHealth RCT addressing medication nonadherence. Then, we conducted 5 follow-up interviews and 1 follow-up focus group with a total of 8 of these providers several months later. We used thematic analysis to generate themes describing providers' views of the RCT and patient recruitment.

Results

Providers indicated that they were willing to recruit for this study because they believed that the intervention sought to address a significant problem. They also thought it made sense to intervene using technology for this age group. However, many providers thought that certain patients (e.g., those with mild, shorter-lasting adherence difficulties) were the most appropriate to recruit. They described how keeping the trial front of mind facilitated recruitment, and they advised researchers to use strategies to promote their ongoing awareness of the study if conducting similar research in the future.

Conclusion

Pediatric healthcare providers are important stakeholders in mHealth intervention research. Engaging them in participant recruitment is a complex endeavor that might promote patient enrollment, but their views of research and demanding clinical roles are important to understand when designing study procedures.

Decentralised clinical trials in multiple sclerosis research

Randomised controlled trials (RCTs) play an important role in multiple sclerosis (MS) research, ensuring that new interventions are safe and efficacious before their introduction into clinical practice. Trials have been evolving to improve the robustness of their designs and the efficiency of their conduct. Advances in digital and mobile technologies in recent years have facilitated this process and the first RCTs with decentralised elements became possible. Decentralised clinical trials (DCTs) are conducted remotely, enabling participation of a more heterogeneous population who can participate in research activities from different locations and at their convenience. DCTs also rely on digital and mobile technologies which allows for more flexible and frequent assessments. While hospitals quickly adapted to e-health and telehealth assessments during the COVID-19 pandemic, the conduct of conventional RCTs was profoundly disrupted. In this paper, we review the existing evidence and gaps in knowledge in the design and conduct of DCTs in MS.

Remote and in-person research education for people with Parkinson's disease and their care partners

OBJECTIVE

TeleDREAMS, a distance learning version of the Developing a Research Participation Enhancement and Advocacy Training Program for Diverse Seniors (DREAMS) program, provides remote clinical research process and advocacy education to older adults with Parkinson's disease (PD) and their care partners.

METHOD

Participants engaged in remote learning, reading eight weekly clinical research process and advocacy education modules. They also had weekly half hour phone discussions with staff about each module. Participants (PD: n = 28, care partner: n = 15) were tested on health literacy, quality of life, depression, research involvement, and advocacy measures.

RESULTS

People with PD improved on health literacy postintervention. PD participants who participated with care partners improved more on health literacy than those without care partners. PD participants' attrition rates were lower for PD participants in TeleDREAMS than those of the similar, in-person program DREAMS program studied before TeleDREAMS. Most participants reported research involvement and patient advocacy for older adults with PD 6 to 9 months postprogram.

CONCLUSIONS

TeleDREAMS may improve health literacy in participants with Parkinson's and their care partners. If increased advocacy and health and research literacy translates to increased research involvement, then TeleDREAMS could be an important strategy for researchers interested in increasing participation. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Feasibility of recruiting in prisons during a randomized controlled trial with people with serious mental illness

BACKGROUND

Successful participant recruitment is vital to the feasibly of intervention research. In the behavioral and social sciences, intervention researchers face a myriad of recruitment barriers, many of which stem from working in real-world settings and among hard-to-access populations. Optimizing recruitment efforts requires being intentional about study planning and resource allocation, carefully documenting the outcomes of recruitment efforts, and developing and implementing procedures and strategies to overcome anticipated recruitment barriers.

METHODS

The current article presents recruitment flowcharts to illustrate (a) the multistep recruitment process and (b) the points of potential participant attrition during recruitment from a two-phase group-based intervention study conducted among individuals with serious mental illness incarcerated in a state prison system in the U.S. In addition, qualitative methods are used to examine strategies employed during the study to support recruitment efforts.

RESULTS

Despite challenges, this study was able to achieve recruitment goals. Analyses found the majority of potential participant attrition occurred prior to informed consent, highlighting the need for studies to track recruitment efforts in more detail than is currently recommended by commonly used guidelines. Strategies to optimize recruitment efforts included maximizing recruiter availability, developing a responsive communication approach, demonstrating respect for facility procedures and operations, and ensuring peak preparedness.

CONCLUSION

Careful documentation of recruitment efforts and the early deployment of recruitment strategies is vital to the feasibility of intervention studies conducted in real-world settings with hard-to-access populations. The publication of recruitment procedures and outcomes can help future researchers anticipate recruitment challenges and inform recruitment goals, timelines, and strategies.

Efficacy and toxicity of primary re-irradiation for malignant spinal cord compression based on radiobiological modelling: a phase II clinical trial

BACKGROUND

The efficacy and safety of primary re-irradiation for MSCC are not known. Our aim was to establish the efficacy and safety of biologically effective dose-based re-irradiation.

METHODS

Patients presenting with MSCC at a previously irradiated spine segment, and not proceeding with surgical decompression, were eligible. A 3 Gray per fraction experimental schedule (minimum 18 Gy/6 fractions, maximum 30 Gy/10 fractions) was used, delivering a maximum cumulative spinal dose of 100 Gy2 if the interval since the last radiotherapy was within 6 months, or 130 Gy2 if longer. The primary outcome was a change in mobility from week 1 to week 5 post-treatment, as assessed by the Tomita score. The RTOG SOMA score was used to screen for spinal toxicity, and an MRI performed to assess for radiation-induced myelopathy (RIM).

RESULTS

Twenty-two patients were enroled, of whom eleven were evaluable for the primary outcome. Nine of eleven (81.8%) had stable or improved Tomita scores at 5 weeks. One of eight (12.5%) evaluable for late toxicity developed RIM.

CONCLUSIONS

Re-irradiation is an efficacious treatment for MSCC. There is a risk of RIM with a cumulative dose of 120 Gy2.

CLINICAL TRIAL REGISTRATION

Cancer Trials Ireland (ICORG 07-11); NCT00974168.

Ensuring the Scientific Value and Feasibility of Clinical Trials: A Qualitative Interview Study

BACKGROUND

Ethical and scientific principles require that clinical trials address an important question and have the resources needed to complete the study. However, there are no clear standards for review that would ensure that these principles are upheld.

METHODS

We conducted semi-structured interviews with a convenience sample of nineteen experts in clinical trial design, conduct, and/or oversight to elucidate current practice and identify areas of need with respect to ensuring the scientific value and feasibility of clinical trials prior to initiation and while ongoing. We used a priori and grounded theory to analyze the data and constant comparative method to induce higher order themes.

RESULTS

Interviewees perceived determination of scientific value as the responsibility of the investigator and, secondarily, other parties who review or oversee research. Interviewees reported that ongoing trials are rarely reevaluated due to emerging evidence from external sources, evaluation is complex, and there would be value in the development of standards for monitoring and evaluating evidence systematically. Investigators, IRBs, and/or data monitoring committees (DMCs) could undertake these responsibilities. Feasibility assessments are performed but are typically inadequate; potential solutions are unclear.

CONCLUSIONS

There are three domains where current approaches are suboptimal and in which further guidance is needed. First, who has the responsibility for conducting scientific review, whether it be the investigator, IRB, and/or DMC is often unclear. Second, the standards for scientific review (e.g., appropriate search terms, data sources, and analytic plan) should be defined. Third, guidance is needed on the evaluation of ongoing studies in light of potentially new and evolving evidence, with particular reference to evidence from outside the trial itself.

Utilization of a Best Practice Alert (BPA) at Point-of-Care for Recruitment into a US-Based Autism Research Study

Provider referral is one of the most influential factors in research recruitment. To ease referral burden on providers, we adapted the Best Practice Alert (BPA) in the EPIC Electronic Health Record and assessed its utility in recruiting pediatric patients with autism spectrum disorder for the national SPARK study. During a year-long surveillance, 1203 (64.0%) patients were Interested in SPARK and 223 enrolled. Another 754 participants not recruited via the BPA also enrolled; 35.5% of these participants completed their participation compared to 58.3% of BPA-referred participants. Results suggest that (a) a BPA can successfully engage providers in the study-referral process and (b) families who learn about research through their providers may be more engaged and effectively retained.

Can we predict trial failure among older adult-specific clinical trials using trial-level factors?

INTRODUCTION

Conducting older adult-specific clinical trials can help overcome the lack of clinical evidence for older adults due to their underrepresentation in clinical trials. Understanding factors contributing to the successful completion of such trials can help trial sponsors and researchers prioritize studies and optimize study design. We aimed to develop a model that predicts trial failure among older adult-specific cancer clinical trials using trial-level factors.

MATERIALS AND METHODS

We identified phase 2-4 interventional cancer clinical trials that ended between 2008 and 2019 and had the minimum age limit of 60 years old or older using Aggregate Analysis of ClinicalTrials.gov data. We defined trial failure as closed early for reasons other than interim results or toxicity or completed with a sample of <85% of the targeted size. Candidate trial-level predictors were identified from a literature review. We evaluated eight types of machine learning algorithms to find the best model. Model fitting and testing were performed using 5-fold nested cross-validation. We evaluated the model performance using the area under receiver operating characteristic curve (AUROC).

RESULTS

Of 209 older adult-specific clinical trials, 87 were failed trials per the definition of trial failure. The model with the highest AUROC in the validation set was the least absolute shrinkage and selection operator (AUROC in the test set = 0.70; 95% confidence interval [CI]: 0.53, 0.86). Trial-level factors included in the best model were the study sponsor, the number of participating centers, the number of modalities, the level of restriction on performance score, study location, the number of arms, life expectancy restriction, and the number of target size. Among these factors, the number of centers (odds ratio [OR] = 0.83, 95% CI: 0.71, 0.94), study being in non-US only vs. US only (OR = 0.32, 95% CI: 0.12, 0.82), and life expectancy restriction (OR = 2.17, 95% CI: 1.04, 4.73) were significantly associated with the trial failure.

DISCUSSION

We identified trial-level factors predictive of trial failure among older adult-specific clinical trials and developed a prediction model that can help estimate the risk of failure before a study is conducted. The study findings could aid in the design and prioritization of future older adult-specific clinical trials.

How do study design features and participant characteristics influence willingness to participate in clinical trials? Results from a choice experiment

BACKGROUND

Research about the decision to participate in a clinical study has tended to be limited to single indications and has focused on narrow sets of study and participant characteristics. This study applied stated preference methods to understand the clinical trial design attributes that most influence willingness to participate and how this varied with participant characteristics.

METHODS

Adults residing in the US, China, or Poland with a self-reported diagnosis of cancer, heart disease, migraine, rheumatoid arthritis, or multiple sclerosis completed an online survey. Participants were asked whether they would participate in clinical studies defined by seventeen attributes within five categories (payment/support, administration/procedures, treatment-related, study location/time commitment, and data collection/feedback). Participants saw six different hypothetical clinical study profiles. Depending on their participation decision to an initial clinical study profile, the subsequent five questions had one design attribute (randomly selected per question) consecutively improved or deteriorated to elicit preferences. A logistic regression was used to determine which participant characteristics influenced participation decisions. A latent class logit model was used to identify how the influence of study design features varied between participants and whether groups of participants with similar preferences could be identified.

RESULTS

The survey was completed by 487 participants (32% China, 35% Poland, 33% US; 8%-19% per indication). Willingness to participate was found to be a function of participant age, certain elements of quality of life, and previous treatment experience, in particular number of lines of treatment received and experience of adverse events. Willingness to participate was influenced by study design features such as payment, study duration, and time commitment - both the overall time and whether the time was at home or away from home, with the latter being particularly relevant to participants experiencing fatigue due to their disease.

CONCLUSIONS

This study quantifies how study designs influence willingness to participate and how this varies with participant types. These findings suggest that it is how an indication influences quality of life and treatment experience, rather than the indication alone, that impacts participation rates, opening the way for insights that are transferrable across indications, which may be particularly useful when considering rare diseases.