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Abstract Introduction Low-sodium oxybate (LXB) is approved for treatment of narcolepsy in patients aged 7 years and older and treatment of idiopathic hypersomnia in adults. LXB contains the same active moiety with 92% less sodium than sodium oxybate (SXB). As the indication for oxybate treatment in patients with idiopathic hypersomnia is new and allows for individualized dosing optimization, guidance for beginning LXB treatment is needed. In particular, clinicians may benefit from guidance regarding treatment initiation, dosing/regimen options, potential challenges, and treatment expectations. Additionally, pharmacokinetic profiles differ slightly between both treatments, and further guidance on transitioning from SXB to LXB in patients with narcolepsy may aid clinicians. Methods An expert panel of five sleep specialists was convened to obtain consensus on recommendations for these topics using a modified Delphi process. Results Across two virtual meetings, the panel agreed on 31 recommendations with a high degree of consensus that fell into four overarching topics: (1) introducing LXB to patients; (2) initiating LXB for adult narcolepsy and idiopathic hypersomnia; (3) addressing challenges in using LXB; and (4) transitioning from SXB to LXB. The panel recommended that clinicians provide a clear overview of how LXB works for treating symptoms in narcolepsy or idiopathic hypersomnia, as appropriate for their patients, explain safety aspects, and set expectations prior to initiating LXB treatment. Strategies for initial dosing and regimen are provided. Strategies for adjusting the dose, regimen, timing, and consideration of individual factors were developed for specific instances in which patients may have trouble staying asleep or waking up, as well as guidance for addressing potential adverse events, such as nausea, dizziness, anxiety, and depression. Discussion points based on existing literature and clinical experience were included as relevant for each statement. Conclusion Clinicians may use this resource to guide LXB dosing optimization with patients.

Objective/Background: Preference for extended-release, once-nightly sodium oxybate (ON-SXB, FT218) vs twice-nightly immediate-release (IR) oxybate was assessed in participants switching from IR oxybate to ON-SXB in an open-label/switch study, RESTORE (NCT04451668). Patients/Methods: Participants aged ≥16 years with narcolepsy who completed the phase 3 REST-ON trial, were oxybate-naive, or were on a stable IR oxybate dose (≥1 month) were eligible for RESTORE. For participants who switched from twice-nightly dosing to ON-SXB, initial doses were closest or equivalent to their previous nightly IR oxybate dose. These participants completed a questionnaire at baseline about nocturnal adverse events associated with the middle-of-the-night IR oxybate dose in the preceding 3 months, a preference questionnaire after 3 months of stable-dose ON-SXB, and an end-of-study (EOS) questionnaire. Results: There were 130 switch participants; 92/98 (93.9 %) who completed the preference questionnaire preferred ON-SXB. At baseline, 69.2 % reported missing their second IR oxybate dose at least once; in these cases, 80 % felt worse the next day. Approximately 39 % reported taking a second nightly IR oxybate dose >4 h after the first dose, 51 % of whom felt somewhat to extremely groggy/unsteady the next morning; 120 participants (92 %) reported getting out of bed after their second oxybate dose. Of those, 9 (8 %) reported falls and 5 (4 %) reported injuries. Of the switch participants who completed the EOS questionnaire, 91.2 % felt better able to follow the recommended ON-SXB dosing schedule. Conclusions: The second nightly IR oxybate dose presents significant treatment burdens and adherence concerns. Participants overwhelmingly preferred the once-nightly dosing regimen of ON-SXB.

Abstract Background There is a large population of restless legs syndrome (RLS) patients who are refractory to medication. Whereas experts recommend off-label opioids as an effective long-term treatment for refractory RLS, reducing opioid dose could substantially reduce side effects and risks. Tonic motor activation (TOMAC) is a nonpharmacological therapeutic device indicated for refractory RLS. Here, we investigated if TOMAC could enable opioid dose reduction for refractory RLS. Methods This prospective, open-label, single-arm clinical trial [NCT04698343] enrolled 20 adults taking ≤ 60 morphine milligram equivalents (MMEs) per day for refractory RLS. Participants self-administered 30-min TOMAC sessions bilaterally over the peroneal nerve when RLS symptoms presented. During TOMAC treatment, opioid dose was reduced iteratively every 2–3 weeks until Clinician Global Impression of Improvement (CGI-I) score relative to baseline exceeded 5. Primary endpoint was percent of participants who successfully reduced opioid dose ≥ 20% with CGI-I ≤ 5. Secondary endpoints included mean successful percent opioid dose reduction with CGI-I ≤ 5. Results On average, participants were refractory to 3.2 medications (SD 1.6) and were taking a stable dose of opioids for 5.3 years (SD 3.9). Seventy percent of participants (70%, 14 of 20) successfully reduced opioid dose ≥ 20% with CGI-I ≤ 5. Mean percent opioid dose reduction with CGI-I ≤ 5 was 29.9% (SD 23.7%, n = 20) from 39.0 to 26.8 MME per day. Mean CGI-I score at the reduced dose was 4.0 (SD 1.4), indicating no change to RLS severity. Conclusions For refractory RLS, TOMAC enabled substantial opioid dose reduction without increased RLS symptoms. These results suggest that TOMAC has the potential to reduce the risk profile associated with opioid therapy for refractory RLS. Trial registration ClinicalTrials.gov trial number NCT04698343 registered on January 6, 2021.

Abstract Introduction Tonic motor activation (TOMAC) therapy is a novel non-pharmacologic treatment approach for patients suffering from medication-refractory restless legs syndrome (RLS). The objective of this study was to explore the potential cost-effectiveness of TOMAC in the US healthcare system. Methods A decision-analytic Markov model was constructed to project strategy-specific treatment costs and benefits over 3 years and lifetime. Cohort characteristics (mean age 57.4 years, 39.8% male) and treatment effects were derived from the sham-controlled RESTFUL study. Study-observed International RLS Study Group (IRLS) scores were used to estimate changes in healthcare resource utilization and quality of life based on mapping algorithms informed by published data. The incremental cost-effectiveness ratio (ICER) was evaluated against established willingness-to-pay thresholds of $50,000/$150,000 per QALY to determine cost-effectiveness. Extensive scenario analyses were performed, including longer-term extension study data. Results TOMAC and sham reduced IRLS scores from baseline 25.3 to 18.10 and 21.60, respectively, at 4 weeks (treatment effect – 3.4 vs. sham), with an increase in utility from 0.80 to 0.84 (0.75–0.84 vs. baseline). Over 3 years and lifetime, the TOMAC vs. sham effect size corresponded to an added 0.10 and 0.49 QALYs (2.36 vs. 2.26; 12.59 vs. 12.10) at incremental costs of $8061 and $36,373 ($36,707 vs. $28,646; $224,040 vs.$187,667), resulting in ICER estimates of $83,822 and $73,600, respectively. Compared to baseline, TOMAC resulted in ICER estimates of $29,569 and $23,690 over 3 years and lifetime, respectively. TOMAC remained cost-effective or dominant across all scenarios, with ICERs ranging from $10,530–$83,822 and − $8061 to $29,569 vs. sham and baseline, respectively. Larger TOMAC effect sizes, achieved per extension study data, further increased cost-effectiveness. Conclusion Based on this exploratory analysis of published trial data, TOMAC therapy appears to offer meaningful improvements in patient health-related quality at net costs that render it a cost-effective intervention. Further analyses are warranted.

Abstract Background To reduce disruptions of processes and the cost of maintenance, predicting the onset of failure (or a similar event) of a physical system (or components of a physical system) has become important. Prediction of onset of failure would allow appropriate corrective actions at the right time. In this paper, we present a method to predict the “onset” of failure (the start of a degradation process or similar types of events) of a physical system that minimizes data collection and personalizes it for the physical system. The method applies to situations where one monitors the operating characteristics of the physical system at regular time intervals by means of attached sensors and other measurement instruments. It creates a model of the physical system, during normal operations, using the time-series data produced by the sensors and measurement instruments. However, it does not create or use any time-series models. It simply examines the distribution of time-series data across different time periods. It uses this model of normal operations in subsequent time periods to monitor the physical system for deviations from normality. Results We illustrate this method with an application to predict the “onset” of subsequent decompensated heart failures for patients already treated for a heart failure at a hospital. As part of an NIH study, these heart failure patients received two ECG patches, an accelerometer and a bio-impedance measurement device for regular monitoring for a period after their release from the hospital. Conclusions When dealing with non-homogenous, disparate physical systems, personalized models can be better predictors of a phenomenon compared to generalized models based on data collected from an assortment of such physical systems. In medicine such models can be a powerful addition to the set of medical diagnostic tools. And such personalized models can be built rather quickly without waiting for extensive data collection.