Jay J H Park, Robin Mogg, Gerald E Smith, Etheldreda Nakimuli-Mpungu
Summary
COVID-19 has had negative repercussions on the entire global population. Despite there being a common goal that should have unified resources and efforts, there have been an overwhelmingly large number of clinical trials that have been registered that are of questionable methodological quality. As the final paper of this Series, we discuss how the medical research community has responded to COVID-19. We recognise the incredible pressure that this pandemic has put on researchers, regulators, and policy makers, all of whom were doing their best to move quickly but safely in a time of tremendous uncertainty. However, the research community's response to the COVID-19 pandemic has prominently highlighted many fundamental issues that exist in clinical trial research under the current system and its incentive structures. The COVID-19 pandemic has not only re-emphasised the importance of well designed randomised clinical trials but also highlighted the need for large-scale clinical trials structured according to a master protocol in a coordinated and collaborative manner. There is also a need for structures and incentives to enable faster data sharing of anonymised datasets, and a need to provide similar opportunities to those in high-income countries for clinical trial research in low-resource regions where clinical trial research receives considerably less research funding.
This is the fourth in a Series of four papers about clinical trials in global health
Introduction
Since the beginning of this Series on clinical trials in global health, the global pandemic of COVID-19 has occurred. This major global health threat has highlighted the importance of global health by reminding us how diseases arising from a single country can affect all other countries, and how health risks and inequities transcend national borders. The pandemic has had negative ramifications on the entire global population. We recognise the incredible pressure this pandemic has put on researchers, regulators, and policy makers, all of whom are doing their best to move quickly but safely in a time of tremendous uncertainty, but the readiness of the research community to bring about rapidly informed decisions on the basis of research evidence has been inadequate. The challenges faced in the global response to initiate and coordinate COVID-19 clinical trials are not new, but the problems and limitations that have existed for clinical trial research have arguably become much more visible.
Despite there being a common goal that should unify resources and efforts, clinical research efforts around the world might easily be described as chaotic and exclusive of many low-income and middle-income countries (LMICs). The global collective clinical trial response to COVID-19 has occurred with inadequate collaboration between researchers. Inconclusive research findings from many clinical trials have re-emphasised the importance of high-quality clinical trial research.
As the final paper of this Series on global health trial research, we discuss the need to embrace coordination and collaboration instead of competition in medical and public health research. We specifically draw on the COVID-19 pandemic to describe how the research community has responded to the outbreak.
How the medical research community has responded to COVID-19
The new norm of publishing: quantity over quality
The COVID-19 pandemic's threat to global security and the economy has captured the entire world's attention. The number of COVID-19 cases continues to rise globally with little sign of slowing down.
The COVID-19 pandemic has mobilised researchers worldwide on a scale and timeframe that have never been seen before for one specific disease. In hopes of rapid discovery of therapeutics, vaccines, and diagnostics for COVID-19, a substantial amount of money is being invested towards clinical research. Despite the sheer volume of research and discussion on the research related to COVID-19, we will illustrate in this Series paper that we are not fighting this common fight very efficiently.
In response to COVID-19, the research community has rapidly adopted a new way of research dissemination but, unfortunately, how that research is being done has not changed. There has been a surge of COVID-19-related preprints and peer-reviewed publications on a scale that has never been seen in other areas of health-care research.
As of Sept 30, 2020, there were 9214 COVID-19-related preprints on major preprint servers such as medRxiv and bioRxiv.
The number of COVID-19 manuscripts being submitted for peer review has also greatly increased. For instance, The Journal of the American Medical Association has indicated that more than 11 000 manuscripts were submitted between Jan 1 and June 1, 2020, whereas around 4000 manuscripts were submitted during the same period in 2019.
Scientific journals have accelerated their peer review process to expedite the publications of studies for COVID-19·
One analysis shows that the time between submission and publication of articles on COVID-19 has decreased on average by around 50%, from 117 days down to 60.
This analysis also showed that the time to publication for research not related to COVID-19 has remained unaffected, but it is probable that the number of research articles unrelated to COVID-19 has dropped considerably, with COVID-19 predominating in receipt of funding and attention from the research community.
There are clear merits of preprint servers and having a faster peer review process, as results can be disseminated quicker and potentially be used to inform policies and speed up the research and development (R&D) process for COVID-19 therapeutics and vaccines. Unfortunately, COVID-19 research has largely not been of high quality so far and many preprints, which are not peer-reviewed, were rushed to dissemination without sufficient oversight. The differentiation between preprints and peer-reviewed publications with appropriate oversight became blurred. The floods of preprints and publications from COVID-19 research have created confusion, not only among the scientific community, but also among the public, who are eagerly waiting for the scientific community to make the next breakthrough for COVID-19. The aim is to strike a balance between quickly disseminating data via preprint servers while ensuring that the work is scientifically credible.
The clinical trial landscape for COVID-19
During the COVID-19 pandemic, the importance of well designed randomised clinical trials has been re-emphasised, owing to studies being published with questionable findings , and due to an overwhelming number of COVID-19 clinical trials that are being done without methodological rigour and adequate planning. Close to 2516 clinical trials were registered globally as of Nov 27, 2020 with 1278 actively recruiting participants. These trials are looking at patients in contexts ranging from pre-exposure prophylaxis through to severely ill hospitalised patients. The experimental interventions that are being evaluated vary greatly, ranging from herbal preparations through to invasive medical procedures, vaccines, and experimental stem-cell therapy. The majority of trials have involved patients who have been admitted to hospital, and few clinical trials have investigated earlier stages of the disease process such as pre-exposure, or post-exposure and outpatient treatment. With regard to treatments, although there are more than 100 unique therapeutic agents being investigated, there is also substantial overlap and duplicated trial efforts as the majority of these trials are evaluating drugs that are already approved for other indications, such as hydroxychloroquine and lopinavir–ritonavir, but that are being repurposed for COVID-19.
These trials have, on average, planned sample sizes of fewer than 100 participants, and are typically evaluating only one experimental intervention. It is also striking that study dose regimen comparisons have largely been absent in the current trial landscape of COVID-19· It is generally well accepted that confirming dose–response in a clinical environment is the foundation to defining an optimal dose regimen, the core clinical pharmacology principle that researchers are overlooking due to the urgency to find COVID-19 treatments. Failing to explore an adequate dose range or not including dosing that accounts for pharmacokinetic and pharmacodynamic variability in different patient populations can lead to an effective treatment being determined as falsely ineffective.
In addition to the requirements of determining a safe and effective dose, the shortage of clinical pharmacology in these clinical trials will potentially be problematic for manufacturing and scale-up efforts. As a result, clinical pharmacology professional societies have issued global calls to action to accelerate the development of COVID-19 therapeutics, as the ignorance relating to the science of dosing has added to the inefficiencies of the global clinical trial landscape.
The current trial landscape of COVID-19 highlights important issues that illustrate the inefficiencies of clinical trial research. Most COVID-19 trials are small, so they will not provide sufficient statistical power to detect a meaningful treatment effect. Most will never achieve their target recruitment numbers. Many are investigating identical or similar treatments with dose regimen selection being made without adequate clinical pharmacology. The preponderance of two-arm trials also leads to other important issues. Instead of doing multi-arm or platform trials with a common control group, the prevalence of two-arm trials has resulted in multiple redundant control groups, which is an another example of inefficient clinical trial practices. Different trials being run in the same region or institution will ultimately compete for participants and delay recruitment into well designed trials that can provide reliable scientific evidence.
Given that many COVID-19 trials have been done across different geographical settings without standardised operating procedures and have been powered according to different endpoints, it has been difficult to make sense of the data from these trials.
Problems with published peer-reviewed trials
68 published peer-reviewed articles of randomised clinical trials on COVID-19 were available as of Dec 4, 2020 (appendix pp 2–4). Given the location of where the COVID-19 pandemic originated, a large proportion of this trial evidence (21 [31%] of the 68 clinical trials) comes from China. Most of these clinical trials have been done in the hospital setting (61 [90%] of 68). Hydroxychloroquine was the most commonly investigated intervention (14 [21%])
The other trials that reported the sample size calculation had a median recruitment target of 186 (IQR 81·5–393) participants, highlighting that most of the trials were not large enough to provide convincing answers unless the treatment effect was overwhelmingly large. It is important to note that most of these COVID-19 trials were published without meeting their recruitment target due to the waning of the virus epidemiology in the studied regions. The median number of participants recruited into these published COVID-19 trials (87 [IQR 52–199]) was smaller than the median planned recruitment target. Of the 54 trials that reported information on planned sample size, 25 (46%) did not meet their recruitment target; in fact, on average they only recruited about half of their planned sample (median 52·3% [IQR 31·7–80·6%]).
Despite registered trials from 40 different countries worldwide, the epidemiology will vary across regions due to differences in physical distancing and other public health measures. We predict that a large number of COVID-19 trials will stop early, not for statistical reasons but because of insufficient recruiment.
13 For instance, despite the public health measures in China that reduced the number of active COVID-19 cases considerably, the number of clinical trials being registered in China, like many other countries around the world, has continued to rise.
13 Given that the recruitment target greatly exceeds the number of daily active cases in China, the fierce competition for patients has led to early termination of many of these trials in China. While the number of COVID-19 cases continues to rise globally, there is likely to be similar competition for patients between different trials being done in other regions of the world.
Trials stopped early for feasibility are always going to be underpowered and thereby prone to produce inconclusive findings. Most of the COVID-19 trials will be underpowered, either by design or because they are terminated before reaching their recruitment target. During non-pandemic settings, the standard solution to the challenge of underpowered studies is to pool the reported aggregated results using pairwise or network meta-analyses.
For COVID-19, there will be many challenges of doing meta-analyses with aggregated reported data. First, even within trials studying the same intervention, there is substantial heterogeneity in dose, duration, endpoints, and data collected between different trials. Second, there is, in general, a shortage of data sharing and no coordinated global approach to aggregate data. Lastly, trials that fail to reach their recruitment target are less likely to be published and thus not available for typical meta-analyses.
Integration of different trial datasets for individual participant-level data (IPD) meta-analyses might be the only solution in determining what works and is safe for COVID-19·
However, the inadequate number of data sharing mechanisms that exists for COVID-19 is a major obstacle. For instance, except for the the USA and Canada randomised clinical trial on post-exposure hydroxychloroquine, the authors of other publications have either declined to share IPD or have indicated that the corresponding author can be contacted for data access (appendix pp 5–6). The process of obtaining de-identified IPD from corresponding authors is very inefficient and time consuming, and often does not result in data sharing.
Researchers who have attempted to acquire IPD from other published trials know too well that a statement indicating that data can be accessed on request by contacting the corresponding authors is often just a requirement of the publishing process that is not subsequently honoured.
The need for coordination and collaboration
The research community's fulfilment to study participants
When individuals participate in clinical trials, they often hope to gain some benefits from new treatment interventions, but they can end up exposing themselves to risks.
Given the experimental nature of clinical research, risks to participants could be unavoidable. Although the value of clinical trials for society is different from the benefits that clinical trial interventions have on individual participants, study participants expect and want their data to be used responsibly to advance science.
The advancement of science and improved public health outcomes require collaboration, which includes publishing of all data, regardless of the results, and releasing them to the research community.
A single data repository
Sharing of IPD has historically proven to be challenging.
Rather than data sharing being optional, for investigators of COVID-19 there is a need to mandate data sharing, expedite systems to apportion credit for data sharing, and preserve commercial interests. In the current COVID-19 pandemic, the need to share and collaborate openly supersedes personal careers or organisational goals. Funders could facilitate data sharing by having a mandate of sharing anonymised data as a requirement for funding. Funders should also ensure that any publications resulting from secondary data analysis credit the data generators.
As the processes for dealing with personal privacy, data security, and data standardisation have become sufficiently more sophisticated over the past 10 years, there is no real barrier to centralising and sharing IPD from different clinical trials under one repository.
Investigators that have started clinical trials can utilise existing global clinical research data-sharing platforms, such as Vivli and Health Data Research UK, in which data can be collectively and securely curated and analysed. The data from different trials can be pooled to answer meaningful public health questions, rather than staying inconclusive in isolation.
The need for rapid and robust clinical research for discovery of effective and safe therapeutics and vaccines has never been higher. Strengthening the public health response to COVID-19 will require larger collated IPD sets to facilitate the scientific precision required for accurate assessment of COVID-19 medical interventions. As COVID-19 has forced reconsideration of policies, processes, and interests, now is the time to advance scientific cooperation and shift the clinical research enterprise toward a data-sharing norm that can maximise the response to the COVID-19 pandemic in the service of public health. Given their small-scale design and inability to reach their recruitment target, most clinical trials done so far will not provide conclusive answers that can be used to inform new practices for COVID-19. If investigators of clinical trials all over the world share their data in a single data repository that is accessible to the research community, these data can be used collectively to make sense of which therapies work and are safe for patients with COVID-19. Key principles of data sharing are provided in panel 1.
Smarter investments for clinical trial research
The aim of clinical trial research is to generate high-quality evidence to inform new clinical practices and public health policies. Given the scarcity of funding, funding clinical trial research can mean that there is less funding available to implement public health initiatives (and vice versa). Recognising this trade-off between clinical trial research and clinical practice and public health, investments should be made that enable coordination and collaboration in clinical trial research. Smarter investments for clinical trial research—whereby funds are allocated to clinical trials that are asking important research questions and that are well designed—should be made so that the funded trials have a high probability of generating conclusive evidence that can inform clinical practice and public health policies. As currently experienced in the era of COVID-19, uncoordinated funding schemes will probably continue funding multiple independent trials that are too small to provide conclusive evidence.
The COVID-19 pandemic has catalysed the acceptance of master protocols by the research community as there is a clear need for more structured and sustainable approaches to clinical trial evaluation (a detailed discussion of master protocol framework can be found in the second paper of this Series. For instance, on Feb 18, 2020, WHO's R&D Blueprint—a global strategy and preparedness plan to increase the R&D processes of diagnostics, therapeutics, and vaccines during epidemics—released a core master protocol for COVID-19.
This core protocol outlined plans for clinical trial evaluation in hospitalised patients, including an ordinal clinical progression scale that was formulated by a special WHO committee.
WHO's core master protocol has been widely shared as a template for potential COVID-19 treatments across multiple sponsors and investigational teams and has helped to standardise clinical outcomes across different trials.
Recognising the critical importance of discovering effective and safe interventions for COVID-19, WHO has also leveraged its international influence and is doing an adaptive platform trial called the Solidarity trial (panel 2). WHO's Solidarity I trial (ISRCTN83971151) has now been expanded to more than 100 countries worldwide since being announced on March 18, 2020, and is recruiting patients hospitalised with COVID-19.
In parallel with this trial, WHO will begin Solidarity II, a global serological study to better understand immunology and other biological profiles of COVID-19.
WHO is also planning a prophylaxis study (Solidarity III) to evaluate possible therapeutic options that can prevent health-care workers and other high-risk populations from contracting SARS-CoV-2.
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