30. Limitations

What to write

Trial limitations, addressing sources of potential bias, imprecision, generalisability, and, if relevant, multiplicity of analyses

Examples

“The preponderance of male patients (85%) is a limitation of our study . . . We used bare-metal stents, since drug-eluting stents were not available until late during accrual. Although the latter factor may be perceived as a limitation, published data indicate no benefit (either short-term or long-term) with respect to death and myocardial infarction in patients with stable coronary artery disease who receive drug-eluting stents, as compared with those who receive bare-metal stents.”1

“Our study had several limitations. The early changes to the protocol to accommodate patients with a shorter injury history (but still not acute) to improve recruitment altered the characteristics of the study population. Overall, patients had less long-standing injury than was originally planned. Moreover, the study addressed a deliberately specific population of patients who continued to have ACL injury-related symptoms of instability and had not undergone any previous formal treatment. Another potential limitation is the proportion of patients who did not undergo surgical reconstruction, despite allocation to that group. The true benefit of surgical reconstruction could be somewhat greater than the ITT analysis suggests. The 18-month follow-up period ideally could have been longer but was constrained by various factors including funding. Notwithstanding, most patients had established their level of instability at this timepoint since being included in the trial. The trial design and analysis accounted for delayed surgery in both groups.”2

Explanation

An essential part of a good discussion section is summarising the limitations of the trial. Limitations are frequently omitted from research reports3; identification and discussion of the weaknesses of a study have particular importance.

Some journals have attempted to remedy this problem by encouraging more structure to authors’ discussion of their results.4,5 For example, The BMJ recommends that authors structure the discussion section by presenting (1) a statement of the principal findings; (2) the strengths and weaknesses of the study; (3) the strengths and weaknesses in relation to other studies, discussing important differences in results; (4) the meaning of the study, its possible explanations and implications for clinicians and policymakers; and (5) any unanswered questions and future research.6 We recommend that authors follow these sensible suggestions, perhaps also using suitable subheadings in the discussion section.

Authors should also discuss any imprecision of the results. Imprecision may arise in connection with several aspects of a study, including measurement of a primary outcome (item 14) or diagnosis (item 12a). Perhaps the scale used was validated on an adult population but used in a paediatric one, or the assessor was not trained in how to administer the instrument.

The difference between statistical significance and clinical importance should always be borne in mind. Authors should particularly avoid the common error of interpreting a non-significant result as indicating equivalence of interventions. The CI (item 26) provides valuable insight into whether the trial result is compatible with a clinically important effect, regardless of the P value.7

Authors should exercise special care when evaluating the results of trials with multiple comparisons. Such multiplicity arises from several interventions, outcome measures, time points, subgroup analyses, and other factors. In such circumstances, some statistically significant findings are likely to result from chance alone.

Authors should also consider the extent to which the results of a study can be generalised to other circumstances; also known as external validity. For example, can the results be generalised to an individual participant or groups that differ from those enrolled in the trial with regard to age, sex, severity of disease, and comorbid conditions? Are the results applicable to other drugs within a class of similar drugs, to a different dose, timing, and route of administration? Can similar results be expected in different healthcare settings? What about the effect on related outcomes that were not assessed in the trial, and the importance of length of follow-up and duration of treatment, especially with respect to harms?8 Internal validity, the extent to which the design and conduct of the trial eliminates the possibility of bias, is a prerequisite for external validity: the results of a flawed trial are invalid and the question of its external validity becomes irrelevant. External validity is a matter of judgement and depends on the characteristics of the participants included in the trial, the trial setting, the treatment regimens tested, and the outcomes assessed.

Training

The UK EQUATOR Centre runs training on how to write using reporting guidelines.

Discuss this item

Visit this items’ discussion page to ask questions and give feedback.

References

1.
Boden WE, O’Rourke RA, Teo KK, et al. Optimal medical therapy with or without PCI for stable coronary disease. New England Journal of Medicine. 2007;356(15):1503-1516. doi:10.1056/nejmoa070829
2.
Beard DJ, Davies L, Cook JA, et al. Rehabilitation versus surgical reconstruction for non-acute anterior cruciate ligament injury (ACL SNNAP): A pragmatic randomised controlled trial. The Lancet. 2022;400(10352):605-615. doi:10.1016/s0140-6736(22)01424-6
3.
Purcell GP, Donovan SL, Davidoff F. Changes to manuscripts during the editorial process: Characterizing the evolution of a clinical paper. JAMA. 1998;280(3):227. doi:10.1001/jama.280.3.227
4.
Annals of internal medicine. Information for authors 2008 https://www.annals.org/ [accessed 15 january 2008].
5.
Docherty M, Smith R. The case for structuring the discussion of scientific papers. BMJ. 1999;318(7193):1224-1225. doi:10.1136/bmj.318.7193.1224
6.
The BMJ. Article types and preparation. Https://www.bmj.com/about-bmj/resources-authors/article-types [accessed 18 january 2024] 2024.
7.
Altman DG, Bland JM. Statistics notes: Absence of evidence is not evidence of absence. BMJ. 1995;311(7003):485-485. doi:10.1136/bmj.311.7003.485
8.
Rothwell PM. Factors that can affect the external validity of randomised controlled trials. PLoS Clinical Trials. 2006;1(1):e9. doi:10.1371/journal.pctr.0010009

Reuse

Most of the reporting guidelines and checklists on this website were originally published under permissive licenses that allowed their reuse. Some were published with propriety licenses, where copyright is held by the publisher and/or original authors. The original content of the reporting checklists and explanation pages on this website were drawn from these publications with knowledge and permission from the reporting guideline authors, and subsequently revised in response to feedback and evidence from research as part of an ongoing scholarly dialogue about how best to disseminate reporting guidance. The UK EQUATOR Centre makes no copyright claims over reporting guideline content. Our use of copyrighted content on this website falls under fair use guidelines.

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.

Easier writing

Following guidance makes writing easier and quicker.

Smoother publishing

Many journals require completed reporting checklists at submission.

Maximum impact

From nobel prizes to null results, articles have more impact when everyone can use them.

Who reads research?

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).

Source.

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.

Source.

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.

Source

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"}.

Source

Systematic review protocols

TODO

Meta analyses of Observational Studies

TODO

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.

Source

Randomised Trial Protocols

TODO

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.

Source

Case Reports

TODO

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.

Source

Animal Research

TODO

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.

Source

Economic Evaluations in Healthcare

TODO

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

Asdfghj

sdfghjk