Harms In Clinical Trials Research Articles

Public perspective on potential treatment intervention harm in clinical trials—terminology and communication

BackgroundRandomised controlled trials (RCTs) are typically designed to determine beneficial intervention effects. In addition, an important aspect of every trial is to collect data on any potential harmful effects, with the aim of ensuring that the benefit-risk balance is appropriate. The language used by trialists to describe these potential harmful effects is inconsistent. In pharmacological trials, researchers collect adverse events; when a causal relationship is suspected adverse events are further classified as adverse reactions. Academic researchers have moved to collectively refer to these as harm outcomes; the pharmaceutical industry refer to these events as safety outcomes. In trials of complex interventions, phrases such as unintended consequences or effects are used. With the inconsistent use of terminology by researchers and the potential benefits to be gained from harmonising communications, we sought public opinion on terminology used to describe harmful effects and how these outcomes are communicated in the scientific literature, as well as in public facing material on medications.MethodsWe held two in-person public involvement meetings with public partners, in London and Aberdeen in 2023. Both meetings followed a pre-specified format. We provided a background to the topic including the information researchers collect on potential harms in clinical trials and shared examples on how this information gets presented in practice. We then discussed public partners’ perspectives on terminology used and communication of intervention harm in academic journals and in public facing materials. A summary of these discussions and the main topics raised by public partners are presented.ResultsPublic partners endorsed the use of different terms for different situations, preferring the use of ‘side-effect’ across all contexts and reserving the use of ‘harm’ to indicate more severe events. Generally, public partners were happy with the type of information presented in public facing materials but discussions revealed that presentation of information on public NHS websites led to misconceptions about harm.ConclusionThis work provides a starting point on preferred terminology by patients and the public to describe potential harmful intervention effects. Whilst researchers have tried to seek agreement, public partners endorsed use of different terms for different situations. We highlight some key areas for improvement in public facing materials that are necessary to avoid miscommunication and incorrect perception of harm.

Reporting of harms in clinical trials of esketamine in depression: a systematic review.

While previous systematic reviews of trials evaluating conventional antidepressants highlighted inadequacies and inconsistencies in adverse event (AE) reporting, no evaluation is available on esketamine in resistant depression. The objective of this review was to assess quality of reporting AEs in all published clinical trials studying esketamine. It also aimed to compare the proportions of AEs reported in journal articles to those recorded in the ClinicalTrial.gov Registers. Clinical trials evaluating the efficacy and safety of esketamine in depression were searched using Medline and ClinicalTrials.gov. The quality of reporting harms was assessed using a 21-item checklist from the CONSORT Extension of Harms (1 point by item). The total quality score was graded into four categories: high (17-21), moderate (12-16), low (7-11) and very low (0-6). Ten clinical trials were included in the analysis. Nine trials were classified as 'low quality' with regard to safety, one trial was classified as 'moderate quality'. Compared to AEs recorded in ClinicalTrials.gov, we found that 41.5% of serious AEs and 39% of non-serious AEs were not reported in the published articles. Among them, the majority were psychiatric events but also cardiovascular events and 94% concerned patients from esketamine groups. Quality of AEs reporting in published clinical trials of esketamine was poor and harms were reported less frequently in journal publications than in ClinicalTrial.gov Registers. The study suggests that an assessment of the benefits/risks balance of esketamine based on the results reported in trial publications is flawed due to the poor accuracy and completeness of harm data.

A Plea to Improve Reporting of Harms in Clinical Trials—So Patients and Providers Can Make Informed Decisions

A Plea to Improve Reporting of Harms in Clinical Trials—So Patients and Providers Can Make Informed Decisions

Toxicity Reporting Is Inconsistent and Incomplete, and Subjective Minimizing Language Is Common in Acute Leukemia Clinical Trials: A Systematic Review of Randomized Controlled Trials Presented at ASH between 2017-2021

Introduction: Despite calls for greater transparency in reporting harms in cancer clinical trials, data on drug toxicity continues to be obscured by incomplete reporting and use of subjective, minimizing language. Subjective terms such as "acceptable" or "tolerable" toxicity are commonly employed in peer-reviewed publications in oncology (Gyawali et al. BMJ 2018). The use of subjective language that minimizes harms in clinical trials can adversely impact informed consent and shared decision-making by overlooking the fact that only individual patients can determine if a therapy is tolerable. The scope of this problem in clinical trials in hematologic malignancies and at medical conferences, however, remains unknown. To further assess this issue, we conducted a systematic review of abstracts presented at ASH annual meetings from 2017-2021 to characterize toxicity reporting and use of subjective, minimizing language in phase 3 clinical trials in acute leukemia. Methods: Following a pilot phase to identify and define minimization terms, we conducted a systematic search of all ASH abstracts from 2017-2021. Phase 3 randomized controlled trials in acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) were included; subset analyses, long-term follow up studies and supportive care trials were excluded. Subjective, minimizing language was defined a priori as use of "acceptable", "tolerable", "manageable", "favorable", "feasible" "safe", and/or "limited" in reference to treatment-related adverse events (AE), which falsely suggested that patients deemed the therapy as such without evaluating patient experiences. Primary toxicity outcome assessment included fatal AE (FAE), serious AE (SAE), and use of common terminology criteria for AE (CTCAE), as well as absent and incomplete AE reporting, defined in Table 1A. Complete severe AE reporting was defined as reporting of cumulative rates (per 100 patients; %) of CTCAE grade ≥3 toxicities or cumulative SAE. An across-disease assessment was performed including phase 3 clinical trials in multiple myeloma and lymphoma from the same time period. Results: 341 studies in acute leukemia underwent abstract screening, of which 40 met inclusion criteria. Study characteristics are reported in Table 1A. AE reporting was variable across trials. Ten trials (25%) provided no information on AE in their abstract, and 6 (15%) had incomplete AE reporting. Subjective, minimizing language was used to describe AE data in 16 trials (40%), with "tolerable" and "acceptable" being the most frequently used terms, and a total of 26 (65%) studies had either absent AE reporting or used minimizing terms (Table 1A). Minimizing language was seen across a range of different study types, including trials in patients with adult and pediatric leukemia, trials of systemic therapies and stem cell transplantation, and trials in frontline and relapsed/refractory settings. Severe toxicities were reported in 10 of the 16 trials that used minimizing language (62.5%) and FAE in 6 of 16 (37.5%). In experimental arms of trials using minimizing terms, rates of CTCAE grade ≥3 AE or SAE ranged from 17-97.3%, and rates of fatal AE from 0-19.5% (Table 1B). FAE and severe AE rates were similar or numerically higher in abstracts that used minimizing terms compared to those abstracts that did not. A total of 65 abstracts reporting results of randomized clinical trials in multiple myeloma and lymphoma (including Hodgkin and non-Hodgkin lymphoma) were available for across-disease assessment and demonstrated similar high rates of absent and incomplete AE reporting, as well as subjective, minimizing terms, used to describe a wide range of severe AE (Table 1B). Discussion: This systematic review of ASH abstracts highlights inconsistent, incomplete, and often absent toxicity reporting, as well as frequent use of subjective, minimizing language. The findings suggest that formal toxicity minimization and subjective minimizing terms are common. Conference abstracts often form the first impression of a clinical trial and can have a disproportionate influence on physician perspectives, thus impacting clinical practice. These findings will inform a larger systematic review to inform policy to improve reporting transparency at hematology and oncology conferences. #co-senior authors Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Comparing the Value of Data Visualization Methods for Communicating Harms in Clinical Trials.

In clinical trials, harms (i.e., adverse events) are often reported by simply counting the number of people who experienced each event. Reporting only frequencies ignores other dimensions of the data that are important for stakeholders, including severity, seriousness, rate (recurrence), timing, and groups of related harms. Additionally, application of selection criteria to harms prevents most from being reported. Visualization of data could improve communication of multidimensional data. We replicated and compared the characteristics of 6 different approaches for visualizing harms: dot plot, stacked bar chart, volcano plot, heat map, treemap, and tendril plot. We considered binary events using individual participant data from a randomized trial of gabapentin for neuropathic pain. We assessed their value using a heuristic approach and a group of content experts. We produced all figures using R and share the open-source code on GitHub. Most original visualizations propose presenting individual harms (e.g., dizziness, somnolence) alone or alongside higher level (e.g., by body systems) summaries of harms, although they could be applied at either level. Visualizations can present different dimensions of all harms observed in trials. Except for the tendril plot, all other plots do not require individual participant data. The dot plot and volcano plot are favored as visualization approaches to present an overall summary of harms data. Our value assessment found the dot plot and volcano plot were favored by content experts. Using visualizations to report harms could improve communication. Trialists can use our provided code to easily implement these approaches.

“Who Am I to Judge These Things”: Intersectional Dimensions of Self-Silencing of People with a Neuromuscular Disease in a Clinical Trial

Ethical guidelines protecting medical research participants have been criticized for stripping the sociocultural contexts of research. This critique is urgent considering ongoing calls to account for participant diversity in recruitment and inclusion procedures. Our intersectional analysis of illness narratives explores how sociostructural factors might play a role in participants’ exposure to research-related harm in clinical trials. Although widening participation does respond to generalizability concerns, we argue that gendered, classed, and ableist processes of self-silencing could simultaneously enhance risk of harm for participants with multiple oppressed identities. To prevent this, researchers might actively involve participants when designing trials.

Visualising harms in publications of randomised controlled trials: consensus and recommendations.

ObjectiveTo improve communication of harm in publications of randomised controlled trials via the development of recommendations for visually presenting harm outcomes.DesignConsensus study.Setting15 clinical trials units registered with the UK Clinical Research Collaboration, an academic population health department, Roche Products, and The BMJ.ParticipantsExperts in clinical trials: 20 academic statisticians, one industry statistician, one academic health economist, one data graphics designer, and two clinicians.Main outcome measures A methodological review of statistical methods identified visualisations along with those recommended by consensus group members. Consensus on visual recommendations was achieved (at least 60% of the available votes) over a series of three meetings with participants. The participants reviewed and critically appraised candidate visualisations against an agreed framework and voted on whether to endorse each visualisation. Scores marginally below this threshold (50-60%) were revisited for further discussions and votes retaken until consensus was reached.Results28 visualisations were considered, of which 10 are recommended for researchers to consider in publications of main research findings. The choice of visualisations to present will depend on outcome type (eg, binary, count, time-to-event, or continuous), and the scenario (eg, summarising multiple emerging events or one event of interest). A decision tree is presented to assist trialists in deciding which visualisations to use. Examples are provided of each endorsed visualisation, along with an example interpretation, potential limitations, and signposting to code for implementation across a range of standard statistical software. Clinician feedback was incorporated into the explanatory information provided in the recommendations to aid understanding and interpretation.ConclusionsVisualisations provide a powerful tool to communicate harms in clinical trials, offering an alternative perspective to the traditional frequency tables. Increasing the use of visualisations for harm outcomes in clinical trial manuscripts and reports will provide clearer presentation of information and enable more informative interpretations. The limitations of each visualisation are discussed and examples of where their use would be inappropriate are given. Although the decision tree aids the choice of visualisation, the statistician and clinical trial team must ultimately decide the most appropriate visualisations for their data and objectives. Trialists should continue to examine crude numbers alongside visualisations to fully understand harm profiles.

Going digital: a narrative overview of the effects, quality and utility of mobile apps in chronic disease self-management.

Objective Smartphone health applications (apps) are being increasingly used to assist patients in chronic disease self-management. The effects of such apps on patient outcomes are uncertain, as are design features that maximise usability and efficacy, and the best methods for evaluating app quality and utility. Methods In assessing efficacy, PubMed, Cochrane Library and EMBASE were searched for systematic reviews (and single studies if no systematic review was available) published between January 2007 and January 2018 using search terms (and synonyms) of 'smartphone' and 'mobile applications', and terms for each of 11 chronic diseases: asthma, chronic obstructive lung disease (COPD), diabetes, chronic pain, serious mental health disorders, alcohol and substance addiction, heart failure, ischaemic heart disease, cancer, cognitive impairment, chronic kidney disease (CKD). With regard to design features and evaluation methods, additional reviews were sought using search terms 'design', 'quality,' 'usability', 'functionality,' 'adherence', 'evaluation' and related synonyms. Results Of 13 reviews and six single studies assessing efficacy, consistent evidence of benefit was seen only with apps for diabetes, as measured by decreased glycosylated haemoglobin levels (HbA1c). Some, but not all, studies showed benefit in asthma, low back pain, alcohol addiction, heart failure, ischaemic heart disease and cancer. There was no evidence of benefit in COPD, cognitive impairment or CKD. In all studies, benefits were clinically marginal and none related to morbid events or hospitalisation. Twelve design features were identified as enhancing usability. An evaluation framework comprising 32 items was formulated. Conclusion Evidence of clinical benefit of most available apps is very limited. Design features that enhance usability and maximise efficacy were identified. A provisional 'first-pass' evaluation framework is proposed that can help decide which apps should be endorsed by government agencies following more detailed technical assessments and which could then be recommended with confidence by clinicians to their patients. What is known about the topic? Smartphone health apps have attracted considerable interest from patients and health managers as a means of promoting more effective self-management of chronic diseases, which leads to better health outcomes. However, most commercially available apps have never been evaluated for benefits or harms in clinical trials, and there are currently no agreed quality criteria, standards or regulations to ensure health apps are user-friendly, accurate in content, evidence based or efficacious. What does this paper add? This paper presents a comprehensive review of evidence relating to the efficacy, usability and evaluation of apps for 11 common diseases aimed at assisting patients in self-management. Consistent evidence of benefit was only seen for diabetes apps; there was absent or conflicting evidence of benefit for apps for the remaining 10 diseases. Benefits that were detected were of marginal clinical importance, with no reporting of hard clinical end-points, such as mortality or hospitalisations. Only a minority of studies explicitly reported using behaviour change theories to underpin the app intervention. Many apps lacked design features that the literature identified as enhancing usability and potential to confer benefit. Despite a plethora of published evaluation tools, there is no universal framework that covers all relevant clinical and technical attributes. An inclusive list of evaluation criteria is proposed that may overcome this shortcoming. What are the implications for practitioners? The number of smartphone apps will continue to grow, as will the appetite for patients and clinicians to use them in chronic disease self-management. However, the evidence to date of clinical benefit of most apps already available is very limited. Design features that enhance usability and clinical efficacy need to be considered. In making decisions about which apps should be endorsed by government agencies and recommended with confidence by clinicians to their patients, a comprehensive but workable evaluation framework needs to be used by bodies assuming the roles of setting and applying standards.

Bias in the reporting of harms in clinical trials of second-generation antidepressants: The tip of the iceberg?

Serious adverse events are poorly reported in clinical trials of second-generation antidepressants. Moreover some key opinion leaders (eg. in France) deliberately failed to warn against them. The gross distortions of antidepressants’ benefit:harm ratio in adolescents showed evidence that open science (ie access to de-identified individual patient data for re-analyses) is a mandatory prerequisite for a trustworthy science.

Bias in the reporting of harms in clinical trials of second-generation antidepressants for depression and anxiety: A meta-analysis

Previous research has shown that reporting bias has inflated the apparent efficacy of antidepressants. We investigated whether apparent safety was also affected. We included 133 trials, involving 31,296 patients, of second-generation antidepressants for the treatment of major depressive disorder (MDD) or anxiety disorders, obtained from Food and Drug Administration (FDA) reviews. We extracted data on overall discontinuation, discontinuation due to adverse events, and serious adverse events (SAEs). Meta-analysis was used to compare discontinuation rates between FDA reviews and matching journal articles, while SAEs were compared qualitatively. The odds ratio for overall discontinuation, comparing drug to placebo, was 1.0 for both sources, while that for discontinuation due to adverse events was 2.4 for both sources. Seventy-seven of 97 (79%) journal articles provided incomplete information on SAEs; sixty-one (63%) articles made no mention of SAEs at all. Of 21 articles which could be compared to the FDA, only 6 (29%) had full reporting without discrepancies. Nine (43%) articles reported a discrepant number of SAEs. Descriptions were absent or discrepant in 6 (29%) additional articles, even for important SAEs such as suicide attempts. In conclusion, reporting bias has not affected average discontinuation rates over trials. However, SAE reporting is not only very poor, with over half of articles failing to discuss SAEs altogether, but discrepancies between the FDA and articles were common and often led to a more favorable drug-placebo comparison. These findings suggest that journal articles are an unreliable source of data on SAEs in antidepressant trials.

Benefits and harms in clinical trials of duloxetine for treatment of major depressive disorder: comparison of clinical study reports, trial registries, and publications

Objective To determine, using research on duloxetine for major depressive disorder as an example, if there are inconsistencies between protocols, clinical study reports, and main publicly available sources (journal articles...

Clinical trials of antiarrhythmic therapies and optimizing health care resource deployment: the need for a paradigm shift

Randomized clinical trials (RCTs) of antiarrhythmic therapies have proliferated since they replaced observational clinical reports over two decades ago. Challenged initially at almost every step, from ethics to endpoints, RCTs have formed the bedrock of evidence-based medicine and practice guidelines in cardiac arrhythmias. Yet the implementation of evidence-based diagnostic or therapeutic guidelines suitable for clinical practice has not been without difficulty. Some have evoked an uneasy acceptance in many quarters and others even more difficult execution in medical practice. Examples abound. The rate versus rhythm debate in atrial fibrillation (AF) management is a prominent one. Clinical trial outcomes were more readily accepted by generalists than specialists, with the latter perplexed by the unexpected outcome that ran counter to physiologic principles and lacked a robust and complete explanation [1, 2]. Prophylaxis of sudden death events in clinical practice using implantable defibrillator devices in high-risk patients resulted in unused device therapy in a very large proportion of all recipients [3]. These non-uniform outcomes are also seen in cardiac resynchronization therapy and ablation of an increasingly broad spectrum of the AF population [4, 5]. Recently, these foundational clinical trials have been revisited in part or in great measure [6, 7]. These reports have been both enlightening and concerning. They enlighten us by revealing common underlying threads of behavior in arrhythmia disorders. They evoke concern in two areas. Firstly, by revealing serious adverse effects of long established and widely employed therapeutic interventions; and secondly, that our current paradigms of clinical trial design and patient enrollment result in highly variable benefits with a serious proportion of patients receiving little or no longterm benefit from the intervention. Statisticians remind us regularly of the perils and pitfalls of both retrospective visits to clinical trial data and subgroup analyses. To paraphrase a distinguished editor of this Journal, there should be due caution around “relying on subgroup analyses or declaring a difference when there is none and vice versa.” This concern arises mostly due to lack of statistical power in the original trial design for the subgroup analysis, which may actually mask potential benefit or harm. At best, we accept the premise that these subgroup analyses can be construed as hypothesis generating. We do appear to be better at selecting subgroups that achieve significant harm in clinical trials with safety monitoring. However, the implications of looking away from highly visible patterns of behavior in clinical outcomes have enormous implications for both patients subjected to unnecessary care and wasted resources in a resource-limited global health care environment. For example, with direct and indirect cardiac resynchronization defibrillator expenditures exceeding three billion US dollars in this year past, nonresponders to this therapy contributed over one billion dollars in cost. Some of these individuals could be simply identified by baseline characteristics at implant, according to trial subgroup analyses. In this authors’ view, it is time for a paradigm shift in health care resource deployment that does take into account important subgroup data. What are common threads of behavior in arrhythmia outcomes? They appear to lie in three different areas. Firstly, a clear understanding of important baseline variables in recruited populations that will impact outcomes. Managing S. Saksena (*) UMDNJ-Robert Wood Johnson School of Medicine, 161 Washington Valley Road, Suite 201, Warren, NJ 07059, USA e-mail: DRSSEPNJ@aol.com

Investigating harms in clinical trials - no easy task

Investigating harms in clinical trials - no easy task

CONSORT recommendations for reporting harms in clinical trials

CONSORT recommendations for reporting harms in clinical trials

CONSORT recommendations for reporting harms in clinical trials

CONSORT recommendations for reporting harms in clinical trials

Valuing Risk: The Ethical Review of Clinical Trial Safety

Despite its mandate on minimizing harms in clinical trials, the Common Rule provides little guidance as to how IRBs should evaluate risk. The Common Rule and derivative commentaries tend to conceptualize risk review as an expert-based endeavor aimed at an objective and universal evaluation of possible harm; they also have tended to locate risk in the research activity itself rather than in the context of research. These views of risk conflict with scholarship showing that risk evaluations are socially determined even among experts, that the context of harms can influence how persons evaluate risks, and that forums that approach risk assessment as a technical endeavor bracket from discussion the numerous values that ground risk judgments. Possible reforms are proposed for clinical trial risk review that would render it more inclusive of the different types of risk encountered and more attuned to the priorities of trial subjects.