Randomised controlled trials (RCTs) have long been considered the backbone of clinical research. RCTs involve large groups of participants randomly assigned to either a treatment or control group. The goal of using an RCT is to identify whether a treatment or intervention is effective on average. Randomisation (and blinding, where possible) is used to reduce biases that can interfere with the interpretation of the data, ensuring results are generalisable to a wider population. In contrast, N of 1 trials focus on individual patients, offering a highly personalised approach. Data from multiple N of 1 trials can be aggregated to draw conclusions about a larger group, while retaining individual-patient insights. Both RCTs and N of 1 trials play an important role in clinical research, but the decision to use an RCT or N of 1 trial depends on a number of considerations such as the nature of the condition being studied and the goals of conducting the trial. Here’s a closer look at how they compare, paying particular attention to efficiency, cost, flexibility, and adaptability.
Efficiency and Cost
Aggregating data from N of 1 trials that have been conducted with individual patients can yield meaningful insights for evaluating treatments. This approach is known as a pooled (or aggregated) N of 1 trial. This particular methodology has proven especially useful in situations where participant recruitment is challenging, for instance in pediatric and palliative care. Research shows that aggregated N of 1 trials require fewer participants to produce the same statistical power as traditional RCTs, leading to faster results and lower costs (Blackston et al., 2019). In fields like complementary medicine, rare diseases, and medical devices where large participant pools are often unavailable. In such scenarios, using a much smaller sample size can provide valuable insights and significantly impact research outcomes.
For instance, the effectiveness of mexiletine for muscle stiffness in patients with nondystrophic myotonia was evaluated using a pooled N of 1 trial. This study found that sufficient data from just 11 individual N of 1 trials was enough to draw conclusions about the average treatment effect of mexiletine. In contrast, a previous RCT required 60 participants to achieve similar outcomes - a process that typically demands more time, effort, and resources.
To put these numbers into perspective, the average cost of a standard Phase 3 or 4 RCT can reach $USD20 million, with a per-patient cost of around $USD41,000 in pivotal trials (Moore et al., 2020). On the other hand, a typical pooled N of 1 trial, having a sample size of up to 40 participants, would cost $USD1.64 million using the same per-patient figures. This substantial reduction in costs makes N of 1 trials more affordable for people conducting clinical research.
Flexible and Adaptable Design
Pooled N of 1 trials offer a distinct advantage over traditional RCTs by allowing a flexible, adaptable trial design that can better suit individual patient needs. Unlike in standard RCTs where treatment parameters are usually fixed, N of 1 trials allow researchers to modify the protocol to suit the type of intervention and the clinical context. For instance, new medications can be added as required, which is particularly useful for conditions that may evolve or change over time. Washout periods between treatment phases can be customised to ensure the elimination of residual effects from the previous treatment, creating a fresh baseline and ensuring that any observed treatment benefits or side effects can be more accurately attributed to the specific intervention being tested (Vohra et al., 2009). Additionally, the dose of a treatment can be tailored and adjusted to determine the most effective amount for each patient, fine-tuning as needed to maximise the therapeutic benefit while minimising side effects. This adaptability makes pooled N of 1 trials a powerful tool for exploring individualised treatment responses offering a level of customisation and precision that standard RCTs cannot achieve..
Retention and Adherence
N of 1 trials generally demonstrate high retention rates , largely due to their personalised approach and their focus on individual patient. In one study, found that N of 1 trials may enhance participant retention in research studies, as the individualised treatment approach can adapt to each participant’s specific responses over time (Kravitz and Duan, 2022). Additionally, the provision of personalised feedback on progress to the participant helps maintain engagement and adherence to the study protocol.. This customisation creates a more interactive and responsive trial experience, which helps to keep participants engaged and motivated to continue. Patients often feel more involved in their care, which strengthens their commitment to the trial. Unlike RCTs, which maintain fixed treatment protocols, N of 1 trials offer a flexibility that allows individuals to feel the trial is genuinely suited to their needs, making it easier for them to stay on board. This adaptable design supports better engagement and sustained participation, highlighting N of 1 trials as an effective option for clinical research where ongoing patient involvement is essential.
Real World Application
Additionally, there's a growing understanding that while the gold standard for establishing broad efficacy of a treatment can be derived from RCTs, their results may not always apply to real-world patients. In fact, several systematic reviews have highlighted that participants in RCTs are often so carefully selected that the generalisability of their findings is extremely limited. Consequently, the effects of interventions may vary in populations that are often excluded from trials. These include older adults, children, and individuals with psychiatric conditions or multiple comorbidities, as such groups are commonly excluded by the eligibility criteria of RCTs. One study identified 37 (71.2%) of 52 published RCTs even explicitly noted that their samples were not broadly representative of people seen in routine clinical practice.
Pooled N of 1 trials, when designed well, can generate evidence that can be generalised like in RCTs, as well as offering personalised per-patient insights. The generalisability of findings from pooled N of 1 trials depends on similar considerations like participant representativeness, eligibility criteria, and robust statistical analysis. Bayesian models are particularly well-suited for analysing data from pooled N-of-1 trials, as they can provide estimates that are generalisable to broader populations. N-of-1 trials can complement RCTs by providing evidence about interventions tested in individuals and groups of people who are more representative of patients seen in everyday clinical practice.
N of 1 trials can also complement observational data by providing a structured, experimental approach to understanding individual treatment responses in real-world settings. Research shows how N of 1 trials can integrate with larger observational studies, creating a robust framework for personalised care while still contributing to population-level insights (Gabler et al., 2011). This dual benefit makes N of 1 trials particularly useful for chronic or complex conditions, where traditional RCTs may struggle to capture the nuances of individual patient responses.
RCTs are often seen as the gold standard in clinical research, but their translation into clinical practice can be slow. On average, it can take up to 14 years for the results of an RCT to make a meaningful impact on patient care. This delay is due to the complex processes of conducting large-scale trials, regulatory approvals, and disseminating findings across healthcare systems. By the time results are implemented, the needs of individual patients may have shifted or evolved. N of 1 trials facilitate an evaluation of treatment effects for an individual patient that is closer to real time, enabling quicker decision-making and adaptation to evolving patient needs. This individualised approach bridges the gap between research and clinical care, avoiding the delays inherent in translating large-scale trial findings into practice.
Broader Implications for Clinical Research
Companies conducting clinical trials of therapeutic products such as drugs, medical devices, and emerging therapies like medicinal cannabis, will find that N of 1 trials are an appealing option that can address areas where traditional RCT trials can fall short. Whether it’s due to the complexity of testing products in a rare disease where the sample size is small, or there is difficulty in gathering a large sample of participants for other reasons, the efficiency and flexibility of N of 1 trials can provide timely, actionable data without the need to recruit large numbers. Furthermore, by aggregating results across multiple individual N of 1 trials, companies can build a strong body of evidence without the major costs associated with RCTs. With their significant cost-saving implications, N of 1 trials are proving to be a more efficient way of conducting research that delivers high-quality patient-centred outcomes.
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