Alternative remedies for insomnia: a proposed method for personalized therapeutic trials

Abstract

Insomnia is a common symptom, with chronic insomnia being diagnosed in 5-10% of adults. Although many insomnia patients use prescription therapy for insomnia, the health benefits remain uncertain and adverse risks remain a concern. While similar effectiveness and risk concerns exist for herbal remedies, many individuals turn to such alternatives to prescriptions for insomnia. Like prescription hypnotics, herbal remedies that have undergone clinical testing often show subjective sleep improvements that exceed objective measures, which may relate to interindividual heterogeneity and/or placebo effects. Response heterogeneity can undermine traditional randomized trial approaches, which in some fields has prompted a shift toward stratified trials based on genotype or phenotype, or the so-called n-of-1 method of testing placebo versus active drug in within-person alternating blocks. We reviewed six independent compendiums of herbal agents to assemble a group of over 70 reported to benefit sleep. To bridge the gap between the unfeasible expectation of formal evidence in this space and the reality of common self-medication by those with insomnia, we propose a method for guided self-testing that overcomes certain operational barriers related to inter- and intraindividual sources of phenotypic variability. Patient-chosen outcomes drive a general statistical model that allows personalized self-assessment that can augment the open-label nature of routine practice. The potential advantages of this method include flexibility to implement for other (nonherbal) insomnia interventions.

Keywords: alternative remedy; herbal; insomnia; over the counter; supplement.

Figure 1

Natural remedies (alphabetical, A–J) listed by at least one of the six sources as possibly useful for sleep. Notes: Green indicates direct reference to insomnia. Yellow indicates indirect terminologies. Gray indicates the resource mentioned the remedy for reasons other than sleep. “-” indicates the remedy was not mentioned in the resource. Abbreviations: Encyc, encyclopedia; Misc, miscellaneous; PDR, Physician’s Desk Reference for Herbal Medicines; NIH, National Institutes of Health; NCCIH, National Center for Complementary and Integrative Health Database.

Figure 2

Natural remedies (alphabetical, J–Z) listed by at least one of the six sources as possibly useful for sleep. Notes: Green indicates direct reference to insomnia. Yellow indicates indirect terminologies. Gray indicates the resource mentioned the remedy for reasons other than sleep. “-” indicates the remedy was not mentioned in the resource. Abbreviations: Encyc, encyclopedia; Misc, miscellaneous; PDR, Physician’s Desk Reference for Herbal Medicines; NIH, National Institutes of Health; NCCIH, National Center for Complementary and Integrative Health Database.

Figure 3

Flow chart describing the steps of guided self-testing. Note: Dotted lines indicate optional recursive paths depending on self-assessment of goal achievement.

Figure 4

Observable proportions of good nights, assuming binary outcome (good vs bad) across a range of 1–10 nights. Notes: The X-axis is the percentage of good nights. The Y-axis is the number of nights in a trial of self-testing. The gray bars in each row indicate the possible observed percentage of good nights. For example, in a two-night trial, the only observable proportions are 0, 50, and 100% good nights.

Figure 5

Histograms of binomial distributions across different true probabilities of a good night and different number of nights tested. Notes: The binomial distribution is shown under the assumption of two self-testing goals: 70% chance of a good night (left column) and 90% chance of a good night (right column). For each of these goal proportions, the distribution is shown for different number of nights of assessment (4, 7, 10, and 20; rows). In each case, the gray bars indicate a buffer around the goal proportion that might be considered acceptably close; this assumed a 10% buffer on either side of the goal, but for four- and seven-night tests, the resolution does not allow thus, and hence the buffer extends to the next nearest histogram bin. By convention, bins are centered around the actual observed value, resulting in half-sized bins at the edges of 0 and 1 probability. The y-axes are fractions of occurrences in each panel.