5a. Funding

What to write

Sources of funding and other support (eg, supply of drugs), and role of funders in the design, conduct, analysis, and reporting of the trial

Examples

“Grant support was received for the intervention from Plan International and for the research from the Wellcome Trust and Joint United Nations Programme on HIV/AIDS (UNAIDS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”1

“Funding: Merck Sharp and Dohme . . . The study funder had a role in the study design, data collection, data analysis, data interpretation, and writing of the report.”2

The article also states that “Merck employees LY, SB, and PB were involved in the conceptualisation of the study, formal analysis, the investigation process, development of the methodology, project administration, drafting the manuscript, and had critically reviewed and edited the manuscript.”2

Explanation

Reporting the funding source(s), and the exact roles of the trial funders, provides important context for readers of a trial report when ascertaining overall methodological rigor (eg, relevance of the type of comparator intervention and eligibility criteria for patients) and risk of bias (eg, selective reporting of favourable results). The trial report should therefore describe details of all funders and the types of funding, as well as the role of the funder in trial design (ie, protocol development), conduct, data analysis, and reporting (ie, interpretation, manuscript writing, and dissemination of results). This should include whether the funder controlled the final decision regarding any of these aspects of the trial, and any mechanisms introduced to minimise funder influence. If the funder had no direct involvement in the trial, that should be stated.

A randomised trial requires considerable funding, typically from pharmaceutical or device companies (industry funding); or from research councils or other scientific or private foundations, or governmental or non-governmental organisations (non-industry funding).3 One study of trials conducted between 2010 and 2015 estimated the median cost per phase 3 drug company trial at $21.4m (£17.21m; €20.7m),4 with substantial variation. The mean cost of clinical trials funded by the NIHR in the UK, reflecting differences in the research and care infrastructure already funded, was lower, but still sizeable—approximately £1.3m—with considerable variation.5 The various types of funders differ in their overall agenda, their reasons for funding a trial, and their propensity to influence the trial.

Funding of a trial typically involves direct monetary support, but financial support may also be provided indirectly in the form of free trial drugs, equipment, or services (eg, statistical analysis or use of medical writers).6 Among the most highly cited clinical trials published in 2019 to 2022, two thirds were funded by industry sponsors, many of whom also provided industry analysts and coauthors.7

Industry funding of trials is associated with conclusions that favour the experimental intervention. A systematic review of 75 methodological studies, comparing industry funded studies with non-industry funded studies (mostly randomised trials), reported that industry funded studies had favourable conclusions more often than non‐industry funded studies (risk ratio 1.34; 95% confidence interval (CI) 1.19 to 1.51).8 Industry funded trials may also report more favourable results (ie, larger estimates of intervention effects) than comparable trials that are funded by non-industry sources. One review of eight published meta-epidemiological studies reported that intervention effects (odds ratios) from industry funded trials were, on average, exaggerated by 5% (95% CI −6% to 15%), although the result was imprecise and consistent with chance findings. However, trials with a high risk of industry funder influence (eg, on trial design, conduct, analysis, and reporting) exaggerated effect estimates by 12% (95% CI 3% to 19%).9 Undue influence on trials from non-industry funders with a strong interest in a specific trial result has been described,10 but has been studied much less.

A review of 200 trials published in 201511 found that 178 (89%) publications included a funding statement. However, in half of the publications, the role of funder was not reported; in the other half, the reporting was often unclear or incomplete; and undisclosed funding from a for-profit organisation was found in 26 of 54 trials reporting only not-for-profit funding. Another study surveyed authors of 200 trials fully funded by industry and found that funders had been involved in the design of 173 trials (87%), in the data analysis of 146 trials (73%), and in the reporting of 173 trials (87%).6 No clear consensus exists on a monetary threshold for when funding from a source with conflict of interest becomes problematic. It is also unclear whether commercial funding is less important than the degree and type of funder influence on trial design, conduct, analysis, and reporting.

Training

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References

1.
Gregson S, Adamson S, Papaya S, et al. Impact and process evaluation of integrated community and clinic-based HIV-1 control: A cluster-randomised trial in eastern zimbabwe. Lange JMA, ed. PLoS Medicine. 2007;4(3):e102. doi:10.1371/journal.pmed.0040102
2.
Rha SY, Oh DY, Yañez P, et al. Pembrolizumab plus chemotherapy versus placebo plus chemotherapy for HER2-negative advanced gastric cancer (KEYNOTE-859): A multicentre, randomised, double-blind, phase 3 trial. The Lancet Oncology. 2023;24(11):1181-1195. doi:10.1016/s1470-2045(23)00515-6
3.
Speich B, Niederhäusern B von, Schur N, et al. Systematic review on costs and resource use of randomized clinical trials shows a lack of transparent and comprehensive data. Journal of Clinical Epidemiology. 2018;96:1-11. doi:10.1016/j.jclinepi.2017.12.018
4.
Martin L, Hutchens M, Hawkins C, Radnov A. How much do clinical trials cost? Nature Reviews Drug Discovery. 2017;16(6):381-382. doi:10.1038/nrd.2017.70
5.
Gupta JK, Daniels JP, Middleton LJ, et al. A randomised controlled trial of the clinical effectiveness and cost-effectiveness of the levonorgestrel-releasing intrauterine system in primary care against standard treatment for menorrhagia: The ECLIPSE trial. Health Technology Assessment. 2015;19(88):1-118. doi:10.3310/hta19880
6.
Rasmussen K, Bero L, Redberg R, Gøtzsche PC, Lundh A. Collaboration between academics and industry in clinical trials: Cross sectional study of publications and survey of lead academic authors. BMJ. Published online October 2018:k3654. doi:10.1136/bmj.k3654
7.
Siena LM, Papamanolis L, Siebert MJ, Bellomo RK, Ioannidis JPA. Industry involvement and transparency in the most cited clinical trials, 2019-2022. JAMA Network Open. 2023;6(11):e2343425. doi:10.1001/jamanetworkopen.2023.43425
8.
Lundh A, Lexchin J, Mintzes B, Schroll JB, Bero L. Industry sponsorship and research outcome. Cochrane Database of Systematic Reviews. 2017;2017(2). doi:10.1002/14651858.mr000033.pub3
9.
Tan AC, Askie LM, Hunter KE, Barba A, Simes RJ, Seidler AL. Data sharing—trialists’ plans at registration, attitudes, barriers and facilitators: A cohort study and cross‐sectional survey. Research Synthesis Methods. 2021;12(5):641-657. doi:10.1002/jrsm.1500
10.
Østengaard L, Lundh A, Tjørnhøj-Thomsen T, et al. Influence and management of conflicts of interest in randomised clinical trials: Qualitative interview study. BMJ. Published online October 2020:m3764. doi:10.1136/bmj.m3764
11.
Hakoum MB, Jouni N, Abou-Jaoude EA, et al. Characteristics of funding of clinical trials: Cross-sectional survey and proposed guidance. BMJ Open. 2017;7(10):e015997. doi:10.1136/bmjopen-2017-015997

Reuse

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Citation

For attribution, please cite this work as:
Hopewell S, Chan AW, Collins GS, et al. CONSORT 2025 statement: updated guideline for reporting randomised trials. BMJ. 2025;389:e081123. doi:10.1136/bmj-2024-081123

Reporting Guidelines are recommendations to help describe your work clearly

Your research will be used by people from different disciplines and backgrounds for decades to come. Reporting guidelines list the information you should describe so that everyone can understand, replicate, and synthesise your work.

Reporting guidelines do not prescribe how research should be designed or conducted. Rather, they help authors transparently describe what they did, why they did it, and what they found.

Reporting guidelines make writing research easier, and transparent research leads to better patient outcomes.

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Following guidance makes writing easier and quicker.

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You work will be read by different people, for different reasons, around the world, and for decades to come. Reporting guidelines help you consider all of your potential audiences. For example, your research may be read by researchers from different fields, by clinicians, patients, evidence synthesisers, peer reviewers, or editors. Your readers will need information to understand, to replicate, apply, appraise, synthesise, and use your work.

Cohort studies

A cohort study is an observational study in which a group of people with a particular exposure (e.g. a putative risk factor or protective factor) and a group of people without this exposure are followed over time. The outcomes of the people in the exposed group are compared to the outcomes of the people in the unexposed group to see if the exposure is associated with particular outcomes (e.g. getting cancer or length of life).

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Case-control studies

A case-control study is a research method used in healthcare to investigate potential risk factors for a specific disease. It involves comparing individuals who have been diagnosed with the disease (cases) to those who have not (controls). By analysing the differences between the two groups, researchers can identify factors that may contribute to the development of the disease.

An example would be when researchers conducted a case-control study examining whether exposure to diesel exhaust particles increases the risk of respiratory disease in underground miners. Cases included miners diagnosed with respiratory disease, while controls were miners without respiratory disease. Participants' past occupational exposures to diesel exhaust particles were evaluated to compare exposure rates between cases and controls.

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Cross-sectional studies

A cross-sectional study (also sometimes called a "cross-sectional survey") serves as an observational tool, where researchers capture data from a cohort of participants at a singular point. This approach provides a 'snapshot'— a brief glimpse into the characteristics or outcomes prevalent within a designated population at that precise point in time. The primary aim here is not to track changes or developments over an extended period but to assess and quantify the current situation regarding specific variables or conditions. Such a methodology is instrumental in identifying patterns or correlations among various factors within the population, providing a basis for further, more detailed investigation.

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Systematic reviews

A systematic review is a comprehensive approach designed to identify, evaluate, and synthesise all available evidence relevant to a specific research question. In essence, it collects all possible studies related to a given topic and design, and reviews and analyses their results.

The process involves a highly sensitive search strategy to ensure that as much pertinent information as possible is gathered. Once collected, this evidence is often critically appraised to assess its quality and relevance, ensuring that conclusions drawn are based on robust data. Systematic reviews often involve defining inclusion and exclusion criteria, which help to focus the analysis on the most relevant studies, ultimately synthesising the findings into a coherent narrative or statistical synthesis. Some systematic reviews will include a [meta-analysis]{.defined data-bs-toggle="offcanvas" href="#glossaryItemmeta_analyses" aria-controls="offcanvasExample" role="button"}.

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Systematic review protocols

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Meta analyses of Observational Studies

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Randomised Trials

A randomised controlled trial (RCT) is a trial in which participants are randomly assigned to one of two or more groups: the experimental group or groups receive the intervention or interventions being tested; the comparison group (control group) receive usual care or no treatment or a placebo. The groups are then followed up to see if there are any differences between the results. This helps in assessing the effectiveness of the intervention.

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Randomised Trial Protocols

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Qualitative research

Research that aims to gather and analyse non-numerical (descriptive) data in order to gain an understanding of individuals' social reality, including understanding their attitudes, beliefs, and motivation. This type of research typically involves in-depth interviews, focus groups, or field observations in order to collect data that is rich in detail and context. Qualitative research is often used to explore complex phenomena or to gain insight into people's experiences and perspectives on a particular topic. It is particularly useful when researchers want to understand the meaning that people attach to their experiences or when they want to uncover the underlying reasons for people's behaviour. Qualitative methods include ethnography, grounded theory, discourse analysis, and interpretative phenomenological analysis.

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Case Reports

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Diagnostic Test Accuracy Studies

Diagnostic accuracy studies focus on estimating the ability of the test(s) to correctly identify people with a predefined target condition, or the condition of interest (sensitivity) as well as to clearly identify those without the condition (specificity).

Prediction Models

Prediction model research is used to test the accurarcy of a model or test in estimating an outcome value or risk. Most models estimate the probability of the presence of a particular health condition (diagnostic) or whether a particular outcome will occur in the future (prognostic). Prediction models are used to support clinical decision making, such as whether to refer patients for further testing, monitor disease deterioration or treatment effects, or initiate treatment or lifestyle changes. Examples of well known prediction models include EuroSCORE II for cardiac surgery, the Gail model for breast cancer, the Framingham risk score for cardiovascular disease, IMPACT for traumatic brain injury, and FRAX for osteoporotic and hip fractures.

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Animal Research

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Quality Improvement in Healthcare

Quality improvement research is about finding out how to improve and make changes in the most effective way. It is about systematically and rigourously exploring "what works" to improve quality in healthcare and the best ways to measure and disseminate this to ensure positive change. Most quality improvement effectiveness research is conducted in hospital settings, is focused on multiple quality improvement interventions, and uses process measures as outcomes. There is a great deal of variation in the research designs used to examine quality improvement effectiveness.

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Economic Evaluations in Healthcare

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Meta Analyses

A meta-analysis is a statistical technique that amalgamates data from multiple studies to yield a single estimate of the effect size. This approach enhances precision and offers a more comprehensive understanding by integrating quantitative findings. Central to a meta-analysis is the evaluation of heterogeneity, which examines variations in study outcomes to ensure that differences in populations, interventions, or methodologies do not skew results. Techniques such as meta-regression or subgroup analysis are frequently employed to explore how various factors might influence the outcomes. This method is particularly effective when aiming to quantify the effect size, odds ratio, or risk ratio, providing a clearer numerical estimate that can significantly inform clinical or policy decisions.

How Meta-analyses and Systematic Reviews Work Together

Systematic reviews and meta-analyses function together, each complementing the other to provide a more robust understanding of research evidence. A systematic review meticulously gathers and evaluates all pertinent studies, establishing a solid foundation of qualitative and quantitative data. Within this framework, if the collected data exhibit sufficient homogeneity, a meta-analysis can be performed. This statistical synthesis allows for the integration of quantitative results from individual studies, producing a unified estimate of effect size. Techniques such as meta-regression or subgroup analysis may further refine these findings, elucidating how different variables impact the overall outcome. By combining these methodologies, researchers can achieve both a comprehensive narrative synthesis and a precise quantitative measure, enhancing the reliability and applicability of their conclusions. This integrated approach ensures that the findings are not only well-rounded but also statistically robust, providing greater confidence in the evidence base.

Why Don't All Systematic Reviews Use a Meta-Analysis?

Systematic reviews do not always have meta-analyses, due to variations in the data. For a meta-analysis to be viable, the data from different studies must be sufficiently similar, or homogeneous, in terms of design, population, and interventions. When the data shows significant heterogeneity, meaning there are considerable differences among the studies, combining them could lead to skewed or misleading conclusions. Furthermore, the quality of the included studies is critical; if the studies are of low methodological quality, merging their results could obscure true effects rather than explain them.

Protocol

A plan or set of steps that defines how something will be done. Before carrying out a research study, for example, the research protocol sets out what question is to be answered and how information will be collected and analysed.

Source

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