For Clinicians

Personalized Trials can help clinicians select the best treatments for their patients, while fostering shared decision making and patient centered care. Below, you can find out about the conditions and treatments that are most suitable for Personalized Trials, and about patient preferences for Personalized Trials.

Benefits*†

Improves patient outcomes by identifying evidence-based treatments for individual patients
Improves patient-clinician relationship and satisfaction with care by making patients feel like they are being treated as unique
Increases patient engagement in care by helping patients attend to their own outcomes and think critically about treatments, personalized trials can awaken patients’ “Inner scientists” and give them a greater stake in the process of their clinical care
Improves patient understanding of health condition and treatment effect

Helps patients and clinicians identify the most effective therapies
Helps patients and clinicians recognize ineffective therapies, thus reducing polypharmacy, minimizing adverse effects, and conserving health care resources
Enhances systematic data collection on the comparative effectiveness of treatments by real health care professionals treating real patients

* Kravitz RL, Duan N, editors, and the DEcIDE Methods Center N-of-1 Guidance Panel (Duan N, Eslick I, Gabler NB, Kaplan HC, Kravitz RL, Larson EB, Pace WD, Schmid CH, Sim I, Vohra S). Design and Implementation of N-of-1 Trials: A User’s Guide. AHRQ Publication No. 13(14)-EHC122-EF. Rockville, M Agency for Healthcare Research and Quality; 2014. http://www.effectivehealthcare.ahrq.gov/N-1-Trials.cfm.

†Kronish IM, Alcantara C, Duer-Hefele J, St Onge T, Davidson KW, Carter EJ, et al. Patients and primary care providers identify opportunities for personalized (N-of-1) trials in the mobile health era. J Clin Epidemiol. 2017 Jun 23 [Epub ahead of print].

5.21.15

“This has the potential to increase patient investment in their care and moves us closer to patient-centered care.”

Clinician Participant E

5.21.15

“This can be very helpful in deciding what’s a better treatment for the patient.”

Clinician Participant H

5.04.15

“This is a way to really individualize treatment. I think that should be very appealing to patients.”

Clinician participant B

5.04.15

“Formally studying patient outcomes in an objective would make you believe in the results a bit more.”

Clinician Participant A

5.04.15

“I think the best trials are where the patient can actually see the symptoms and effects very quickly. If they’re not self-monitoring at home, they may not feel differently.”

Clinician Participant D

4.27.15

“We’ll be able to do evidence-based clinical assessment….”

Clinician Participant A

What does Personalized Trials mean for clinicians?

Personalized Trials, commonly referred to as N-of-1 trials in the published literature, belong to the family of Single Case Designs that have been widely used in psychology, education, and social work. Personalized Trials is a specific form of randomized or balanced designs characterized by periodic switching from active treatment to placebo or between active treatments (also known as multiple crossover or “withdrawal-reversal” designs). The experiments are designed to determine the relative benefits and harms of the candidate treatments for that one patient. In typical Personalized Trials, an individual is assigned to receive a sequence of treatments, often in a random order. For example, a patient might receive treatment A for 2 weeks, followed by treatment B for 2 weeks, and then treatment A again for 2 weeks, based on a random sequence of treatments A and B. Often, neither the patient nor the clinician knows which treatment that patient is receiving. Throughout the trial, the patient closely monitors the effects of the treatments. At the end of the trial, the treatment “code” is broken, the patient and clinician jointly review the results to see if the patient did better with A or B, and they then decide which one(s) would be best for that patient. By prescribing multiple episodes of treatment, Personalized Trials increases the precision of measurement and control for treatment-by-time interactions, that is, the possibility that the relative effects of two treatments vary over time.

Attribute

Treatment Comparison
Participants
Design
Blinding
Monitoring
Results

Conventional Trials

Treatments (or treatment versus control) are compared across groups of patients to determine average effects

Personalized Trials

Treatments are compared across time within each patient, to determine the relative benefits and harms of the candidate treatments for that one patient

Conventional Trials

A large number of patients are typically enrolled

Personalized Trials

Address significant heterogeneity in how treatments affect individual patients, hence, the need to compare treatments within individuals

Conventional Trials

Treatments are compared in two or more groups of patients with the same condition (patients are often assigned to one group and receive one treatment)

Personalized Trials

The individual is assigned to receive a sequence of treatments in a random order (e.g., treatment A for 2 weeks then treatment B for 2 weeks)

Conventional Trials

Patients/providers /researchers are blinded (i.e., they don’t know which treatment a patient is receiving)

Personalized Trials

Patients/providers are blinded (i.e., they don’t know which treatment a patient is receiving)

Conventional Trials

Success is measured by comparing how the groups respond to the different treatments

Personalized Trials

The patient closely monitors effects and/or harm of each treatment.

Conventional Trials

The results of the trial help clinicians and patients to decide which treatment is worth trying best on its effect on the average patient.

Personalized Trials

At the end, the treatment “code” is broken, and the patient and clinician jointly review the results to see if patient did better with A or B and they then decide which one is best for the patients

Can I conduct my own Personalized Trials?

While conducting the most rigorous Personalized Trials may require added resources (pharmacy to blind provider and patient, tools to collect data), one can conduct a simple Personalized Trials. A provider and patient could select their own but tell how they could conduct their own, challenges and limitations to pragmatic approach, but still advance over usual practice
Partner with personalized experts

How do I know when it is appropriate to test treatments using a Personalized Trials design?

The study design of Personalized Trials is not always appropriate or feasible. For example, if there is already strong evidence supporting the use of a treatment for a given patient, then it would not be ethical to compare this treatment with other treatments as part of Personalized Trials. The Table below highlights the circumstances that are required for Personalized Trials to be appropriate.

Guidelines for N-of-1

GUIDELINES FOR N-OF-1

State of knowledge
Nature of disorder
Nature of treatment
Outcome assessment
Willingness of Stakeholders
Availability of financial resources

N-of-1 appropriate

Clinical uncertainty or equipoise

N-of-1 NOT appropriate

Clear benefit of the treatment

Notes

N-of-1 appropriate

Chronic stable or slowly progressing, Washout period known and safe

N-of-1 NOT appropriate

Rapid progression of symptoms, Possible harm discontinuing active treatment

Notes

Time trends for symptoms should be considered

N-of-1 appropriate

Rapid efficacy, Minimal carryover effects across time, Significant individual differences in treatment response expected

N-of-1 NOT appropriate

Slow efficacy onset, Substantial carryover, Too complex, Small individual differences expected

Notes

Blinding ideal, but not always necessary

N-of-1 appropriate

Valid outcome measures assessed over multiple items

N-of-1 NOT appropriate

Primary outcome assessed at a single time

Notes

Repeated assessments ideal

N-of-1 appropriate

Patients, clinicians, scientist, pharmacist and statistician willing to expend effort

N-of-1 NOT appropriate

Some stakeholders not available/willing

Notes

All design features must be decided a priori to allow for IRB approval and fully informed consent

N-of-1 appropriate

Measurement devices for outcome, cost of compounding drug and multiple visits with clinician can be procured

N-of-1 NOT appropriate

Resources not available

Notes

Time trends for symptoms should be considered

What conditions are suitable for conducting Personalized Trials?

1. Nature of the Problem

Chronic stable, slowly progressive, or frequently recurring
Symptomatic conditions (e.g., osteoarthritis) or asymptomatic conditions with biomarkers that can be tracked over time (e.g., hypertension)

2. Nature of the treatment

Uncertainty about best treatment
Substantial differences in individual responses to treatment
Rapid onset
Rapid and safe washout

3. Outcome Assessment

Availability of valid, repeatable measures of treatment effects

4. Stakeholders

Patients, healthcare providers, and health system willing to engage in Personalized Trials

Checklist for designing Personal Trials

Guidance

Key Considerations

Check

Guidance

Determine whether n-of-1 methodology is applicable to the clinical question of interest

Key Considerations

Indications include:  (a) substantial clinical uncertainty; (b) chronic or frequently recurring symptomatic condition; (c) treatment with rapid onset and minimal carryover.
Indications include:  (a) substantial clinical uncertainty; (b) chronic or frequently recurring symptomatic condition; (c) treatment with rapid onset and minimal carryover.
Contraindications include:  (a) rapidly progressive condition; (b) treatment with slow onset or prolonged carryover; (c) patient or clinician insufficiently interested in reducing

Check

Guidance

Select trial duration, treatment period length, and sequencing scheme

Key Considerations

Longer trial duration delivers greater precision, but completion can be difficult or tedious, with the potential for extended exposure to inferior treatment during trial.
Longer trial duration delivers greater precision, but completion can be difficult or tedious, with the potential for extended exposure to inferior treatment during trial.
Treatment period length should be adjusted to fit the therapeutic half-life (of drug treatments) or treatment onset and duration (of nondrug treatments).
Simple randomization (e.g., AABABBBA) optimizes blinding (more difficult to guess treatment), while balanced sequencing (e.g., ABBABAAB) is a more reliable guarantor of validity.

Check

FAQ

Aren’t Personalized Trials too time consuming for patients?

In the past, adoption of N-of-1 trials in clinical practice was limited by the need for pencil and paper assessments of treatment effects, and in-person visits. Some of the early exuberance for Personalized Trials was dampened when trialists realized that a minority of patients were interested in the effort needed to collect data for Personalized Trials as a means of being more precise about their treatment selection. With the advent of smartphones and wireless devices, the effort needed by patients to conduct personalized trials for use cases in which treatment effects can be monitored using these devices is much lower. Thus, there is currently much enthusiasm for re-launching personalized trial in the mobile health era.

How can clinicians and researchers afford the set up costs of initiating Personalized Trials?

In the past, each time someone wanted to do a personalized trial with a patient, it required building much of the infrastructure from the ground-up. While some examples of personalized trials services had some success in engaging a small number of patients, these services were not self-sustaining and dissolved after an initial period of start-up funding. Currently, however, with the advent of mobile apps that can make it more scalable to conduct personalized trials at low cost, once the initial app is built. On-boarding, guiding patients through the personalized trial, tracking of treatment effects, data visualizations and statistical analyses can all be conducted through well-designed apps. Thus, there is hope that in our current mobile health era, Personalized Trials can be more broadly delivered at lower cost.

When should blinding be prioritized as a design feature of Personalized Trials?

If the goal of the Personalized Trials is to disentangle the biological effect from expectancy effects, then blinding may be necessary. One published example of such Personalized Trials was one in which patients perceived their statin medication to be causing myalgias. Such patients then compared statins to placebo, with both treatments blinded, to learn if the myalgias were truly attributable to the statin medication.

For Clinicians

For Clinicians

Benefits*†

†Kronish IM, Alcantara C, Duer-Hefele J, St Onge T, Davidson KW, Carter EJ, et al. Patients and primary care providers identify opportunities for personalized (N-of-1) trials in the mobile health era. J Clin Epidemiol. 2017 Jun 23 [Epub ahead of print].

Attribute

Conventional Trials

Personalized Trials

Conventional Trials

Personalized Trials

Conventional Trials

Personalized Trials

Conventional Trials

Personalized Trials

Conventional Trials

Personalized Trials

Conventional Trials

Personalized Trials

Guidelines for N-of-1

GUIDELINES FOR N-OF-1

N-of-1 appropriate

N-of-1 NOT appropriate

Notes

N-of-1 appropriate

N-of-1 NOT appropriate

Notes

N-of-1 appropriate

N-of-1 NOT appropriate

Notes

N-of-1 appropriate

N-of-1 NOT appropriate

Notes

N-of-1 appropriate

N-of-1 NOT appropriate

Notes

N-of-1 appropriate

N-of-1 NOT appropriate

Notes

What conditions are suitable for conducting Personalized Trials?

1. Nature of the Problem

2. Nature of the treatment

3. Outcome Assessment

4. Stakeholders

Checklist for designing Personal Trials

Guidance

Key Considerations

Check

Guidance

Key Considerations

Check

Guidance

Key Considerations

Check

Concerns

Recommendations

For more information on designing Personalized Trials

80-90% moderately to very interested in monitoring

How can my patient participate in Personalized Trials?

FAQ