Quantifying Sleep in the Real World

ActiGraph recently published a white paper presenting several examples of how wearables have been used for the assessment of sleep in the treatment of sleep disturbances. In this installment of the Digital Endpoints Journal Club, we’re taking a deep dive into one of these case studies, which focused on chronic insomnia. This study not only revealed encouraging efficacy of medical cannabis on chronic insomnia, but it also shed unique insights on the approach to monitor sleep quality in clinical trials.


In clinical research, sleep is commonly assessed by three approaches -- self-reported questionnaires, actigraphy, and polysomnography (PSG). There are pros and cons associated with each method, and the research community has not reached consensus regarding which of these provides the best endpoints for therapeutics development across different clinical conditions.

A research team from Western Australia, led by Dr. Jennifer Walsh, decided to deploy all three approaches in this randomized control trial (RCT) to rigorously examine the treatment effect on sleep behaviors. I had the pleasure of speaking with Dr. Jennifer Walsh, the lead author of this study, on the ins and outs of their findings.

With the exact 12 hour difference, we connected at 7pm US Eastern Standard Time and 7am Australia Western Standard Time and conversed over a dinner/breakfast meeting.

Q&A with Dr. Jennifer Walsh

Christine Guo: Thank you so much for your time today, Jen. Can you start by telling me a bit about your research journey in sleep?

Jennifer Walsh: I started my research training in 2004, beginning in exercise research and then gradually getting more and more involved with sleep research. Some of my work has been conducted on the Raine Study, one of the largest prospective cohort studies in the world, where we used ActiGraph wearables for lifestyle monitoring.


First RCT to Study Cannabis on Sleep

CG: How did this study came about?

JW: Zelira Therapeutics (Zelda at that time) approached us around the end of 2016 to discuss their interest in sponsoring an RCT to formally study the effect of their medical cannabis formulation on sleep. While there are some anecdotal reports about cannabis on sleep, no rigorous study has been conducted to demonstrate this. Through the discussion, we were impressed that Zelira was willing to do this study “properly" so we designed a study for them, executed the study, and performed the data analysis.


Measurement Approach for Sleep Endpoints: Self-Report, Actigraphy, and PSG

CG: What exactly do you mean when you say “properly”?

JW: We suggested that we go in parallel with all three approaches because of the pros and cons associated with each. Self-reported assessments are known to be prone to subjective bias. But it is patients’ own voice, so it's important -- especially for insomnia, which is a sleep disorder diagnosed from subjective reports. PSG is supposed to be the gold standard objective measure. However, its laboratory setup, with multiple instruments attached to the body, creates an unnatural environment for sleep. It is also difficult to collect many data points during the trial due to the cost and burden.


CG: I definitely sleep poorly when I am somewhere foreign.

JW: Yes, most people do. This is especially an issue with insomnia, although in some people there can be an intriguing paradoxical "good sleep" effect -- some patients actually sleep better in a foreign environment. This could be related to the habitual association between their home and poor sleep. But in any case, the point is that an unnatural environment is not ideal for understanding the normal sleep habit. And on this point, actigraphy is advantageous, as it is both objective and non-intrusive. Many nights of measurements can also be made, all while people are sleeping in their natural environment.


Do the Sleep Endpoints Detect Treatment Responses?

CG: That is interesting. So it makes sense that PSG data did not show anything in the study. But the self-report and actigraphy data are somewhat consistent, correct?

JW: They are consistent from the treatment efficacy perspective. However, if you look at the individual data, they are not at all. Especially sleep latency -- people with insomnia tend to overestimate latency and underestimate total sleep. But people tend to be biased in the same way over time, so the longitudinal analysis of effect was consistent with objective measure via actigraphy.


CG: Was the study properly double blinded?

JW: Yes. In fact, the company went through a lot of effort to create a placebo that closely mimics the smell, taste, and appearance of the active ingredient. However, probably because of the very obvious (positive) effect on sleep, some patients said they could tell they received the treatment.


CG: From my perspective, that makes it even more important to have objective measures of sleep since self reports are more likely to be influenced by the perception of treatment groups.

JW: Absolutely!

 

CG: I noticed that this is quite a small study. How did you decide the sample size?

JW: It is a reasonable size for a phase 1b study. We did our power calculation based on previously published data on the effect of other interventions on ISI and powered the study accordingly to detect the effect. The effect size was quite substantial with this cannabinoid formulation, so we did not need a huge study to demonstrate an improvement. Although we would definitely like to do further trials in a larger population.

 

CG: Is the product commercially available in Australia?

JW: Yes, the product (Zenivol) is available commercially under the Special Access Scheme (SAS-B) and Authorised Prescriber Scheme (AP).

 

We thank Dr. Walsh for sharing these insights into the design of sleep endpoints in this RCT. Actigraphy measures of sleep quality provide an objective and continuous approach to assess sleep in the natural home environment. As illustrated in our discussion today, these digital measures can provide key clinical insights into the effect of sleep treatments with minimal confounding effects from placebo.


References

Walsh JH, Maddison KJ, Rankin T, Murray K, McArdle N, Ree MJ, Hillman DR, Eastwood PR.

Treating insomnia symptoms with medicinal cannabis: a randomized, crossover trial of the efficacy of a cannabinoid medicine compared with placebo. Sleep. 2021 Nov 12;44(11):zsab149. doi: 10.1093/sleep/zsab149. PMID: 34115851; PMCID: PMC8598183.

 

 

Do you know of a research study that involves the use of digital endpoints in a unique or innovative way? If so, please contact us at science@theactigraph.com.

 


 

Related White Paper

Actigraphy for Sleep Measurement: Three ActiGraph Use Cases 

Disturbed or impaired sleep is a growing area of research focus, both as a primary disorder and in cases where disturbed sleep is a symptom of another disease. Actigraphy monitoring with wearables provides a low-burden and remote approach to objectively quantify participants’ sleep behavior in their natural environment, often revealing meaningful insights that might not be available with polysomnography or self-report data. In this white paper, we present three use cases for collecting actigraphy-derived sleep measures during an interventional clinical trial. 

AG_Marketing_SocialMedia_WhitePapers_2021_ActigraphyForSleepMeasurements_FINAL_WEB


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