N of 1 trial

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An N of 1 trial (N=1) is a multiple crossover clinical trial, conducted in a single patient [1] . A trial in which random allocation is used to determine the order in which an experimental and a control intervention are given to a single patient is an N of 1 randomized controlled trial. Some N of 1 trials involve randomized assignment and blinding, but the order of experimental and control interventions can also be fixed by the researcher [2] .

Contents

This type of study has enabled practitioners to achieve experimental progress without the overwhelming work of designing a group comparison study. This design, especially if including blinding and wash-out periods, can be very effective in confirming causality. The N of 1 trials can be designed in many ways. For example, Single-Patient Open Trials (SPOTs) are located somewhere in between the formal (explanatory) N of 1 trials and the trial and error approach used in clinical practice and are characterized by at least one crossover period with washout in between. [3] One of the most common procedures is the ABA withdrawal experimental design, where the patient problem is measured before a treatment is introduced (baseline) and then measured again during the treatment and finally when the treatment has terminated. If the problem vanished during the treatment it can be established that the treatment was effective. But the N=1 study can also be executed in an AB quasi experimental way; such type-2 N of 1 studies can be effective for testing treatments for severe, rare diseases when the expected effect of the intervention exceeds the effect size of confounders [4] . Another variation is non-concurrent experimental design where different points in time are compared with one another. The standard approach to therapy choice, the trial and error method, may also be included in the N of 1 design [5] . This experimental design also has a problem with causality, whereby statistical significance under a frequentist paradigm may be un-interpretable but other methods, such as clinical significance [6] or Bayesian methods should be considered. Many consider this framework to be a proof of concept or hypothesis generating process to inform subsequent, larger clinical trials. However, N-of-1 trials, if used in clinical practice to inform therapeutic decisions concerned with the patient participating in the trial, can be a promising source of evidence about individual treatment responses, fulfilling the promise of personalized medicine [7] [8] .

List of variation in N of 1 trial

DesignCausalityUse
A-BQuasi experimentOften the only possible method
A-A1-AExperimentPlacebo design where A is no drug and A1 is a placebo
A-B-AExperimentWithdrawal design where effects of B phase can be established
A-B-A-BExperimentWithdrawal design where effects of B phase can be established
A-B-A-B-A-BExperimentWithdrawal design where effects of B phase can be established
A-B1-B2-B3-Bn-AExperimentEstablishing the effect of different versions of B phase

Quasi experiment means that causality cannot be definitively demonstrated.
Experiment means that it can be demonstrated.

Plot of a possible dataset from an A-A -A N-of-1 trial: Imagine that during day 1-30, day 61-90, and day 121-150, the participant is taking a drug developed to treat high blood pressure. They are taking a placebo in the remaining time. Normal systolic pressure is slightly below 120 (in mmHg). Single subject blood pressure example.png
Plot of a possible dataset from an A-A -A N-of-1 trial: Imagine that during day 1-30, day 61-90, and day 121-150, the participant is taking a drug developed to treat high blood pressure. They are taking a placebo in the remaining time. Normal systolic pressure is slightly below 120 (in mmHg).

Examples

An N of 1 trial is usually used to assess individual responses to treatments targeting chronic diseases [9] . This design can be successfully implemented to determine optimal treatments for patients with diseases as diverse as osteoarthritis, chronic neuropathic pain and attention deficit hyperactivity disorder. [10]

N-of-1 designs can also be observational and describe natural intra-individual changes in health-related behaviours or symptoms longitudinally. N-of-1 observational designs require complex statistical analysis of N-of-1 data however, a simple 10-step procedure is available. [11] There has also been work to adapt causal inference counterfactual methods for using n-of-1 observational studies to design subsequent n-of-1 trials. [12]

While N-of-1 trials are increasing, results of a recent systematic review found that statistical analyses in these studies would improve with more methodological and statistical rigor across all periods of the studies. [13]

The Quantified Self

Recently, a proliferation of personal experiments akin to N=1 is occurring, along with some detailed reports about them. This trend has been sparked in part by the growing ease of collecting data and analysing it, and also motivated by the ability of individuals to report such data easily. [14]

A famous proponent and active experimenter was Seth Roberts, who reported on his self-experimental findings on his blog, and later published The Shangri-La Diet based on his conclusions from these self-experiments.

Global networks

The International Collaborative Network for N-of-1 Trials and Single-Case Designs (ICN) is a global network for clinicians, researchers and consumers who have an interest in these methods. There are over 400 members of the ICN who are based in over 30 countries across the globe. The ICN was established in 2017 and is co-chaired by A/Prof. Jane Nikles and Dr Suzanne McDonald.

See also

Related Research Articles

Evidence-based medicine (EBM) is "the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients." The aim of EBM is to integrate the experience of the clinician, the values of the patient, and the best available scientific information to guide decision-making about clinical management. The term was originally used to describe an approach to teaching the practice of medicine and improving decisions by individual physicians about individual patients.

<span class="mw-page-title-main">Randomized controlled trial</span> Form of scientific experiment

A randomized controlled trial is a form of scientific experiment used to control factors not under direct experimental control. Examples of RCTs are clinical trials that compare the effects of drugs, surgical techniques, medical devices, diagnostic procedures or other medical treatments.

<span class="mw-page-title-main">Clinical trial</span> Phase of clinical research in medicine

Clinical trials are prospective biomedical or behavioral research studies on human participants designed to answer specific questions about biomedical or behavioral interventions, including new treatments and known interventions that warrant further study and comparison. Clinical trials generate data on dosage, safety and efficacy. They are conducted only after they have received health authority/ethics committee approval in the country where approval of the therapy is sought. These authorities are responsible for vetting the risk/benefit ratio of the trial—their approval does not mean the therapy is 'safe' or effective, only that the trial may be conducted.

In a blind or blinded experiment, information which may influence the participants of the experiment is withheld until after the experiment is complete. Good blinding can reduce or eliminate experimental biases that arise from a participants' expectations, observer's effect on the participants, observer bias, confirmation bias, and other sources. A blind can be imposed on any participant of an experiment, including subjects, researchers, technicians, data analysts, and evaluators. In some cases, while blinding would be useful, it is impossible or unethical. For example, it is not possible to blind a patient to their treatment in a physical therapy intervention. A good clinical protocol ensures that blinding is as effective as possible within ethical and practical constraints.

<span class="mw-page-title-main">Personalized medicine</span> Medical model that tailors medical practices to the individual patient

Personalized medicine, also referred to as precision medicine, is a medical model that separates people into different groups—with medical decisions, practices, interventions and/or products being tailored to the individual patient based on their predicted response or risk of disease. The terms personalized medicine, precision medicine, stratified medicine and P4 medicine are used interchangeably to describe this concept though some authors and organisations use these expressions separately to indicate particular nuances.

Clinical study design is the formulation of trials and experiments, as well as observational studies in medical, clinical and other types of research involving human beings. The goal of a clinical study is to assess the safety, efficacy, and / or the mechanism of action of an investigational medicinal product (IMP) or procedure, or new drug or device that is in development, but potentially not yet approved by a health authority. It can also be to investigate a drug, device or procedure that has already been approved but is still in need of further investigation, typically with respect to long-term effects or cost-effectiveness.

<span class="mw-page-title-main">Confounding</span> Variable or factor in causal inference

In causal inference, a confounder is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlations or associations. The existence of confounders is an important quantitative explanation why correlation does not imply causation. Some notations are explicitly designed to identify the existence, possible existence, or non-existence of confounders in causal relationships between elements of a system.

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Zelen's design is an experimental design for randomized clinical trials proposed by Harvard School of Public Health statistician Marvin Zelen (1927-2014). In this design, patients are randomized to either the treatment or control group before giving informed consent. Because the group to which a given patient is assigned is known, consent can be sought conditionally.

<span class="mw-page-title-main">Observational study</span> Study with uncontrolled variable of interest

In fields such as epidemiology, social sciences, psychology and statistics, an observational study draws inferences from a sample to a population where the independent variable is not under the control of the researcher because of ethical concerns or logistical constraints. One common observational study is about the possible effect of a treatment on subjects, where the assignment of subjects into a treated group versus a control group is outside the control of the investigator. This is in contrast with experiments, such as randomized controlled trials, where each subject is randomly assigned to a treated group or a control group. Observational studies, for lacking an assignment mechanism, naturally present difficulties for inferential analysis.

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In medical research, a dynamic treatment regime (DTR), adaptive intervention, or adaptive treatment strategy is a set of rules for choosing effective treatments for individual patients. Historically, medical research and the practice of medicine tended to rely on an acute care model for the treatment of all medical problems, including chronic illness. Treatment choices made for a particular patient under a dynamic regime are based on that individual's characteristics and history, with the goal of optimizing his or her long-term clinical outcome. A dynamic treatment regime is analogous to a policy in the field of reinforcement learning, and analogous to a controller in control theory. While most work on dynamic treatment regimes has been done in the context of medicine, the same ideas apply to time-varying policies in other fields, such as education, marketing, and economics.

The experience sampling method (ESM), also referred to as a daily diary method, or ecological momentary assessment (EMA), is an intensive longitudinal research methodology that involves asking participants to report on their thoughts, feelings, behaviors, and/or environment on multiple occasions over time. Participants report on their thoughts, feelings, behaviors, and/or environment in the moment or shortly thereafter. Participants can be given a journal with many identical pages. Each page can have a psychometric scale, open-ended questions, or anything else used to assess their condition in that place and time. ESM studies can also operate fully automatized on portable electronic devices or via the internet. The experience sampling method was developed by Suzanne Prescott during doctoral work at University of Chicago's Committee on Human Development with assistance from her dissertation advisor Mihaly Csikszentmihalyi. Early studies that used ESM were coauthored by fellow students Reed W. Larson and Ronald Graef, whose dissertations both used the method.

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<span class="mw-page-title-main">Placebo-controlled study</span>

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<span class="mw-page-title-main">Phases of clinical research</span> Clinical trial stages using human subjects

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<span class="mw-page-title-main">Adaptive design (medicine)</span> Concept in medicine referring to design of clinical trials

In an adaptive design of a clinical trial, the parameters and conduct of the trial for a candidate drug or vaccine may be changed based on an interim analysis. Adaptive design typically involves advanced statistics to interpret a clinical trial endpoint. This is in contrast to traditional single-arm clinical trials or randomized clinical trials (RCTs) that are static in their protocol and do not modify any parameters until the trial is completed. The adaptation process takes place at certain points in the trial, prescribed in the trial protocol. Importantly, this trial protocol is set before the trial begins with the adaptation schedule and processes specified. Adaptions may include modifications to: dosage, sample size, drug undergoing trial, patient selection criteria and/or "cocktail" mix. The PANDA provides not only a summary of different adaptive designs, but also comprehensive information on adaptive design planning, conduct, analysis and reporting.

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References

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Further reading