The motivations, barriers, and sociodemographic characteristics of healthy Chinese volunteers in phase I research

Evaluation of factors associated with recruitment rates in early phase clinical trials based on the European Clinical Trials Register data

Effective participant recruitment is a critical challenge in clinical trials. Inadequate enrollment of participants can precipitate delays, escalated costs, and compromise scientific integrity. Despite its relevance, particularly during the early phases, it persists as an obstacle in the field of clinical research. The primary aim of this study was to analyze the recruitment rates of early-phase clinical trials and evaluate their potential associations with key trial characteristics. Using a descriptive and statistical analysis, a research study was conducted based on the early-phase trials registered at the European Clinical Trials Register (EU-CTR), spanning the timeframe from January 2017 to December 2021. Among the 194 trials examined, we found median recruitment rates of 68%. A more detailed exploration revealed a greater level of success in terms of recruitment achievement in pediatric trials when compared to trials involving adults, non-oncologic trials, or those also developed in non-European countries. It is important to underscore that only 69 trials out of the total managed to conclude recruitment, with the most prevalent reason for premature cessation being the presence of efficacy and safety issues or sponsor's strategy. This number can be greatly improved. Despite certain disparities observed in the information within EU-CTR, we have successfully determined the recruitment rates of the studies and established associations with some of the clinical trial characteristics analyzed. Owing to the inherent constraints of this study, further research is warranted to gain a comprehensive understanding of the intricate interplay between trial characteristics and their impact on recruitment rates in early-phase studies.

Factors that impact on recruitment to vaccine trials in the context of a pandemic or epidemic: a qualitative evidence synthesis

BACKGROUND

The World Health Organization declared the COVID-19 pandemic on 11 March 2020. Vaccine development and deployment were swiftly prioritised as a method to manage and control disease spread. The development of an effective vaccine relies on people's participation in randomised trials. Recruitment to vaccine trials is particularly challenging as it involves healthy volunteers who may have concerns around the potential risks and benefits associated with rapidly developed vaccines.

OBJECTIVES

To explore the factors that influence a person's decision to participate in a vaccine trial in the context of a pandemic or epidemic.

SEARCH METHODS

We used standard, extensive Cochrane search methods. The latest search date was June 2021.

SELECTION CRITERIA

We included qualitative studies and mixed-methods studies with an identifiable qualitative component. We included studies that explored the perspectives of adults aged 18 years or older who were invited to take part in vaccine trials in the context of a pandemic or epidemic.

DATA COLLECTION AND ANALYSIS

We assessed the title, abstracts and full texts identified by the search. We used a sampling frame to identify data-rich studies that represented a range of diseases and geographical spread. We used QSR NVivo to manage extracted data. We assessed methodological limitations using an adapted version of the Critical Skills Appraisal Programme (CASP) tool for qualitative studies. We used the 'best-fit framework approach' to analyse and synthesise the evidence from our included studies. We then used the Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual) assessment to assess our confidence in each finding and develop implications for practice.

MAIN RESULTS

We included 34 studies in our review. Most studies related to HIV vaccine trials. The other studies related to Ebola virus, tuberculosis, Zika virus and COVID-19. We developed 20 key findings, under three broad themes (with seven subthemes), that described the factors that people consider when deciding whether to take part in a vaccine trial for a pandemic or epidemic disease. Our GRADE-CERQual confidence was high in nine of the key findings, moderate in 10 key findings and low in one key finding. The main reason for downgrading review findings were concerns regarding the relevance and adequacy of the underlying data. As a result of the over-representation of HIV studies, our GRADE-CERQual assessment of some findings was downgraded in terms of relevance because the views described may not reflect those of people regarding vaccine trials for other pandemic or epidemic diseases. Adequacy relates to the degree of richness and quantity of data supporting a review finding. Moderate concerns about adequacy resulted in a downgrading of some review findings. Some factors were considered to be under the control of the trial team. These included how trial information was communicated and the inclusion of people in the community to help with trial information dissemination. Aspects of trial design were also considered under control of the trial team and included convenience of participation, provision of financial incentives and access to additional support services for those taking part in the trial. Other factors influencing people's decision to take part could be personal, from family, friends or wider society. From a personal perceptive, people had concerns about vaccine side effects, vaccine efficacy and possible impact on their daily lives (carer responsibilities, work, etc.). People were also influenced by their families, and the impact participation may have on relationships. The fear of stigma from society influenced the decision to take part. Also, from a societal perspective, the level of trust in governments' involvement in research and trial may influence a person's decision. Finally, the perceived rewards, both personal and societal, were influencing factors on the decision to participate. Personal rewards included access to a vaccine, improved health and improved disease knowledge, and a return to normality in the context of a pandemic or epidemic. Potential societal rewards included helping the community and contributing to science, often motivated by the memories of family and friends who had died from the disease.

AUTHORS' CONCLUSIONS

This review identifies many of the factors that influence a person's decision to take part in a vaccine trial, and these reflect findings from reviews that examine trials more broadly. However, we also recognise some factors that become more important in connection with a vaccine trial in the context of a pandemic or epidemic. These factors include the potential stigma of taking part, the possible adverse effects of a vaccine, the added motivation for helping society, the role of community leaders in trial dissemination, and the level of trust placed in governments and companies developing vaccines. These specific influences need to be considered by trial teams when designing, and communicating about, vaccine trials in the context of a pandemic or epidemic.

Why not? Motivations for entering a volunteer register for clinical trials during the COVID-19 pandemic

Backgrounds

Healthy volunteers play a key role in clinical trials and it is crucial to develop recruitment strategies that capitalise on their motivations and maximise their participation. The COVID-19 pandemic has shown the importance of finding motivated healthy volunteers for the development of new vaccines. Public registers represent a promising way to promote the participation of healthy volunteers in the research field, but their adoption is still limited. The current study aimed to explore the motivations of healthy volunteers to enrol in an Italian public register for clinical trials during the COVID-19 pandemic and their attitude toward participating in a phase 1 COVID-19 vaccine clinical trial. The impacts of different enrolling interview modalities (in person, by phone, by mail) on motivation, understanding of information and trust in researchers were also investigated.

Methods

An online survey investigating experience with COVID-19, motivations to enrol, trust in researchers, political and healthcare authorities and pharmacological companies was presented to people applying as healthy volunteers in the public register for clinical trials at Phase 1 Unit Research Centre of ASST Monza, Italy, and considering to participate in a COVID-19 vaccine clinical trial. Data were collected in June 2021.

Results

Altruistic motivations were the main driver for enrolling in the public register, while self-interested motivations were secondary. No gender differences were found. As for enrolling modalities, no differences emerged between in-person and interviews for motivation to enrol, understanding of information and trust in researchers. Email modality led to significantly lower volunteers’ satisfaction and understanding of information but similar trust in research.

Conclusions

This study supports the validity of different interview modalities (in person and by phone) for the enrolment of healthy volunteers for clinical trials and highlights the positive role of public registers for the recruitment procedures.

External evaluation of published population pharmacokinetic models of polymyxin B

OBJECTIVES

Several population pharmacokinetics (popPK) models for polymyxin B have been constructed to optimize therapeutic regimens. However, their predictive performance remains unclear when extrapolated to different clinical centers. Therefore, this study aimed to evaluate the predictive ability of polymyxin B popPK models.

METHODS

A literature search was conducted, and the predictive performance was determined for each selected model using an independent dataset of 20 patients (92 concentrations) from the Third Xiangya Hospital. Prediction- and simulation-based diagnostics were used to evaluate model predictability. The influence of prior information was assessed using Bayesian forecasting.

RESULTS

Eight published studies were evaluated. In prediction-based diagnostics, the prediction error within ± 30% was over 50% in two models. In simulation-based diagnostics, the prediction- and variability-corrected visual predictive check (pvcVPC) showed satisfactory predictivity in three models, while the normalized prediction distribution error (NPDE) tests indicated model misspecification in all models. Bayesian forecasting demonstrated a substantially improvement in the model predictability even with one prior observation.

CONCLUSION

Not all published models were satisfactory in prediction- and simulation-based diagnostics; however, Bayesian forecasting improved the predictability considerably with priors, which can be applied to guide polymyxin B dosing recommendations and adjustments for clinicians.

Model-Informed Therapeutic Drug Monitoring of Meropenem in Critically Ill Patients: Improvement of the Predictive Ability of Literature Models with the PRIOR Approach

BACKGROUND AND OBJECTIVE

To improve the predictive ability of literature models for model-informed therapeutic drug monitoring (TDM) of meropenem in intensive care units, we propose to tweak the literature models with the "prior approach" using a subset of the data. This study compares the predictive ability of both literature and tweaked models on TDM concentrations of meropenem in critically ill patients.

METHODS

Blood samples were collected from patients of an intensive care unit treated with intravenous meropenem. Data were split six times into an "estimation" and a "prediction" datasets. Population pharmacokinetic (popPK) models of meropenem were selected from literature. These models were run on the "estimation" dataset with the $PRIOR subroutine in NONMEM to obtain tweaked models. The literature and tweaked models were used a priori (with covariate only) and with Bayesian fitting to predict each individual concentration from the previous concentration(s). Their respective predictive abilities were compared using median relative prediction error (MDPE%) and median absolute relative prediction error (MDAPE%).

RESULTS

The total dataset was composed of 115 concentrations from 58 patients. For each of the six splits, the "estimation" and the "prediction" datasets were respectively composed of 44 and 14 patients or 45 and 13 patients. Six popPK models were selected in the literature. MDPE% and MDAPE% were globally lower for the tweaked than for the literature models, especially for a priori predictions.

CONCLUSION

The "prior approach" could be a valuable tool to improve the predictive ability of literature models, especially for a priori predictions, which are important to optimize dosing in emergency situations.