Polysomnographic nighttime features of narcolepsy: A systematic review and meta-analysis

Distinguishing between children referred for assessment of excessive daytime sleepiness using polysomnographic measures

BACKGROUND

Currently, diagnosing narcolepsy and idiopathic hypersomnia (IH) in subjectively sleepy children requires an overnight polysomnographic sleep study followed by a daytime multiple sleep latency test (MSLT). We aimed to compare sleep macro-architecture to identify differences between these groups.

METHODS

All children referred for a MSLT between May 2010 to December 2023 whose parent consented for their data be used in research were eligible. Each child was age- and sex-matched to a control. Sleep stability was defined as the maintenance of a particular sleep stage before waking or transitioning to another sleep state. As a measure of sleep disturbance, the number and duration of bouts of each sleep stage was recorded.

RESULTS

28 children with Narcolepsy, 11 with IH and 26 with subjective sleepiness were included. Children with narcolepsy exhibited higher numbers of transitions to wake after sleep onset compared to their controls and to the subjectively sleepy group (p < 0.001 for both). The number of REM bouts was greater in the narcolepsy group compared to their control group (p < 0.001), the IH group (p < 0.05) and the subjectively sleepy group (p < 0.05), while the average duration of REM bouts was shorter in the narcolepsy group compared to both the IH group (p < 0.05) and subjectively sleepy group (p < 0.05). Mean sleep latency on the MSLT was correlated with a number of polysomnographic variables.

CONCLUSIONS

Our study suggests that specific sleep architecture patterns could potentially serve as diagnostic biomarkers for distinguishing paediatric narcolepsy from those with IH and those with a non-diagnostic MSLT.

Identifying time-resolved features of nocturnal sleep characteristics of narcolepsy using machine learning

The differential diagnosis of narcolepsy type 1, a rare, chronic, central disorder of hypersomnolence, is challenging due to overlapping symptoms with other hypersomnolence disorders. While recent years have seen significant growth in our understanding of nocturnal polysomnography narcolepsy type 1 features, there remains a need for improving methods to differentiate narcolepsy type 1 nighttime sleep features from those of individuals without narcolepsy type 1. We aimed to develop a machine learning framework for identifying sleep features to discriminate narcolepsy type 1 from clinical controls, narcolepsy type 2 and idiopathic hypersomnia. The population included polysomnography data from 350 drug-free individuals (114 narcolepsy type 1, 90 narcolepsy type 2, 105 idiopathic hypersomnia, and 41 clinical controls) collected at the National Reference Centers for Narcolepsy in Montpelier, France. Several sets of nocturnal sleep features were explored, as well as the value of time-resolving sleep architecture by analysing sleep per quarter-night. Several patterns of nighttime sleep evolution emerged that differed between narcolepsy type 1, clinical controls, narcolepsy type 2 and idiopathic hypersomnia, with increased nighttime instability observed in patients with narcolepsy type 1. Using machine learning models, we identified rapid eye movement sleep onset as the best single polysomnography feature to distinguish narcolepsy type 1 from controls, narcolepsy type 2 and idiopathic hypersomnia. By combining multiple feature sets capturing different aspects of sleep across quarter-night periods, we were able to further improve between-group discrimination and could identify the most discriminative sleep features. Our results highlight salient polysomnography features and the relevance of assessing their time-dependent changes during sleep that could aid diagnosis and measure the impact of novel therapeutics in future clinical trials.

Can EEG spectral analysis distinguish children with narcolepsy from those with idiopathic hypersomnia and subjective sleepiness?

EEG spectral analysis provides a more sensitive measure of sleep disruption than conventional sleep macro-architecture. We aimed to examine the use of this technique applied to overnight polysomnography in distinguishing children with narcolepsy and idiopathic hypersomnia (IH) from subjectively sleepy children with a non-diagnostic multiple sleep latency test. The relative power was calculated for delta (0.5-3.9 Hz), theta (4-7.9 Hz), alpha (8-11.9 Hz), sigma (12-13.9 Hz), and beta power (14-30 Hz). A mean value for each frequency was calculated for each 30 s epoch then averaged for each sleep stage within each child. Data are presented as median and interquartile range. Twenty-eight children with narcolepsy, 11 with IH, and 26 with subjective sleepiness were included and individually matched for age and sex with a control child. In N2, the F4 beta power was lower in the narcolepsy compared with the IH group (p < 0.05). The F4 theta power was higher in the narcolepsy compared with the subjectively sleepy group during wake (p < 0.001), N2 (p < 0.01), N3 (p < 0.05), and total sleep (p < 0.01). During total sleep the F4 delta power was lower in both the narcolepsy and IH groups compared with the subjectively sleepy group (p < 0.05 for both). Our study identified specific EEG frequencies which differed between groups of children referred for assessment of EDS. In particular, differences in theta and delta power in children with narcolepsy and IH compared with others with subjective sleepiness may provide insights into the pathophysiology associated these conditions.

REM sleep in narcolepsy

Narcolepsy is mainly associated with excessive daytime sleepiness, but the characteristic feature is abnormal rapid eye movement (REM) sleep phenomena. REM sleep disturbances can manifest as cataplexy (in narcolepsy type 1), sleep paralysis, sleep-related hallucinations, REM sleep behavior disorder, abnormal dreams, polysomnographic evidence of REM sleep disruption with sleep-onset REM periods, and fragmented REM sleep. Characterization of REM sleep and related symptoms facilitates the differentiation of narcolepsy from other central hypersomnolence disorders and aids in distinguishing between narcolepsy types 1 and 2. A circuit comprising regions within the brainstem, forebrain, and hypothalamus is involved in generating and regulating REM sleep, which is influenced by changes in monoamines, acetylcholine, and neuropeptides. REM sleep is associated with brainstem functions, including autonomic control, and REM sleep disturbances may be associated with increased cardiovascular risk. Medications used to treat narcolepsy (and REM-related symptoms of narcolepsy) include stimulants/wake-promoting agents, pitolisant, oxybates, and antidepressants; hypocretin agonists are a potential new class of therapeutics. The role of REM sleep disturbances in narcolepsy remains an area of active research in pathophysiology, symptom management, and treatment. This review summarizes the current understanding of the role of REM sleep and its dysfunction in narcolepsy.

Gender medicine and sleep disorders: from basic science to clinical research

Several pivotal differences in sleep and sleep disorders are recognized between women and men. This is not only due to changes in hormonal balance during women's reproductive life, such as in pregnancy and menopause. Women are more likely to report insomnia and non-specific symptoms of apneas, such as fatigue or mood disturbance, compared to men. Thus, it is important for clinicians and researchers to take sex and gender differences into account when addressing sleep disorders in order to acknowledge the biology unique to women. We present a narrative review that delves into the primary sleep disorders, starting from basic science, to explore the impact of gender differences on sleep and the current status of research on women's sleep health.

The Changed Nocturnal Sleep Structure and Higher Anxiety, Depression, and Fatigue in Patients with Narcolepsy Type 1

Purpose

This study aimed to evaluate nocturnal sleep structure and anxiety, depression, and fatigue in patients with narcolepsy type 1 (NT1).

Methods

Thirty NT1 patients and thirty-five healthy controls were enrolled and evaluated using the Epworth sleepiness scale (ESS), Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, Fatigue Severity Scale (FSS), polysomnography, multiple sleep latency test, and brain function state monitoring. Statistical analyses were performed using SPSS Statistics for Windows, version 23.0. Benjamini-Hochberg correction was performed to control the false discovery rate.

Results

Apart from typical clinical manifestations, patients with NT1 are prone to comorbidities such as nocturnal sleep disorders, anxiety, depression, and fatigue. Compared with the control group, patients with NT1 exhibited abnormal sleep structure, including increased total sleep time (P adj=0.007), decreased sleep efficiency (P adj=0.002), shortening of sleep onset latency (P adj<0.001), elevated wake after sleep onset (P adj=0.002), increased N1% (P adj=0.006), and reduced N2%, N3%, and REM% (P adj=0.007, P adj<0.001, P adj=0.013). Thirty-seven percent of patients had moderate to severe obstructive sleep apnea-hypopnea syndrome. And sixty percent of patients were complicated with REM sleep without atonia. Patients with NT1 displayed increased anxiety propensity (P adj<0.001), and increased brain fatigue (P adj=0.020) in brain function state monitoring. FSS scores were positively correlated with brain fatigue (P adj<0.001) and mean sleep latency was inversely correlated with FSS scores and brain fatigue (P adj=0.013, P adj=0.029). Additionally, ESS scores and brain fatigue decreased after 3 months of therapy (P=0.012, P=0.030).

Conclusion

NT1 patients had abnormal nocturnal sleep structures, who showed increased anxiety, depression, and fatigue. Excessive daytime sleepiness and fatigue improved after 3 months of treatment with methylphenidate hydrochloride prolonged-release tablets in combination with venlafaxine.

Machine learning-Based model for prediction of Narcolepsy Type 1 in Patients with Obstructive Sleep Apnea with Excessive Daytime Sleepiness

Background

Excessive daytime sleepiness (EDS) forms a prevalent symptom of obstructive sleep apnea (OSA) and narcolepsy type 1 (NT1), while the latter might always be overlooked. Machine learning (ML) models can enable the early detection of these conditions, which has never been applied for diagnosis of NT1.

Objective

The study aimed to develop ML prediction models to help non-sleep specialist clinicians identify high probability of comorbid NT1 in patients with OSA early.

Methods

Totally, clinical features of 246 patients with OSA in three sleep centers were collected and analyzed for the development of nine ML models. LASSO regression was used for feature selection. Various metrics such as the area under the receiver operating curve (AUC), calibration curve, and decision curve analysis (DCA) were employed to evaluate and compare the performance of these ML models. Model interpretability was demonstrated by Shapley Additive explanations (SHAP).

Results

Based on the analysis of AUC, DCA, and calibration curves, the Gradient Boosting Machine (GBM) model demonstrated superior performance compared to other machine learning (ML) models. The top five features used in the GBM model, ranked by feature importance, were age of onset, total limb movements index, sleep latency, non-REM (Rapid Eye Movement) sleep stage 2 and severity of OSA.

Conclusion

The study yielded a simple and feasible screening ML-based model for the early identification of NT1 in patients with OSA, which warrants further verification in more extensive clinical practices.

Orexins and primary headaches: an overview of the neurobiology and clinical impact

INTRODUCTION

Primary headaches, including migraines and cluster headaches, are highly prevalent disorders that significantly impact quality of life. Several factors suggest a key role for the hypothalamus, including neuroimaging studies, attack periodicity, and the presence of altered homeostatic regulation. The orexins are two neuropeptides synthesized almost exclusively in the lateral hypothalamus with widespread projections across the central nervous system. They are involved in an array of functions including homeostatic regulation and nociception, suggesting a potential role in primary headaches.

AREAS COVERED

This review summarizes current knowledge of the neurobiology of orexins, their involvement in sleep-wake regulation, nociception, and functions relevant to the associated symptomology of headache disorders. Preclinical reports of the antinociceptive effects of orexin-A in preclinical models are discussed, as well as clinical evidence for the potential involvement of the orexinergic system in headache.

EXPERT OPINION

Several lines of evidence support the targeted modulation of orexinergic signaling in primary headaches. Critically, orexins A and B, acting differentially via the orexin 1 and 2 receptors, respectively, demonstrate differential effects on trigeminal pain processing, indicating why dual-receptor antagonists failed to show clinical efficacy. The authors propose that orexin 1 receptor agonists or positive allosteric modulators should be the focus of future research.

Recommended protocols for the Multiple Sleep Latency Test and Maintenance of Wakefulness Test in children: guidance from the American Academy of Sleep Medicine

The American Academy of Sleep Medicine commissioned a task force of clinical experts in pediatric sleep medicine to review published literature on performing the Multiple Sleep Latency Test (MSLT) and Maintenance of Wakefulness Test for diagnosis and management of central disorders of hypersomnolence among children and adolescents. This paper follows a format similar to that of the paper "Recommended protocols for the Multiple Sleep Latency Test and Maintenance of Wakefulness Test in adults: guidance from the American Academy of Sleep Medicine" that was published in 2021. Since there is insufficient evidence to specify a recommended protocol for the Maintenance of Wakefulness Test in children and adolescents, this paper focuses only on the MSLT protocol. This protocol paper provides guidance to health care providers who order, sleep specialists who interpret, and technical staff who administer the MSLT to pediatric patients. Similar to the adult protocol paper, this document provides guidance based on pediatric expert consensus and evidence-based data when available. Topics include patient preparation, evaluation of medication and substance use, sleep needs before testing, scheduling considerations, optimal test conditions for youth, and documentation. Specific changes recommended for pediatric MSLT protocols include (1) provision of a minimum of 7 hours of sleep (with a minimum 8-hour recording time) on polysomnography the night before the MSLT, ideally meeting age-based needs; (2) use of clinical judgment to guide the need for sleep-disordered breathing treatments before polysomnography-MSLT testing; and (3) shared patient-health care provider decision-making regarding modifications in the protocol for children and adolescents with neurodevelopmental/neurological disorders, young age, and/or delayed sleep phase.

CITATION

Maski KP, Amos LB, Carter JC, Koch EE, Kazmi U, Rosen CL. Recommended protocols for the Multiple Sleep Latency Test and Maintenance of Wakefulness Test in children: guidance from the American Academy of Sleep Medicine. J Clin Sleep Med. 2024;20(4):631-641.

Sleep features of nocturnal enuresis: relationship between rapid eye movement sleep latency prolongation and nocturnal enuresis

Nocturnal enuresis, or bed wetting, is the involuntary urination during sleep. One of its causes is difficulty awakening during sleep, suggesting a relationship between Nocturnal enuresis (NE) and sleep. However, no studies have yet clarified the relationship between NE and sleep, and the effects of sleep structure in NE children are not yet known. Assuming that changes in sleep structure are related to NE, there would be a difference in sleep structure between days with and without NE. We measured the sleep electroencephalograms of 27 at home patients aged 6-16 years, evaluated the differences between days with and without NE, and examined the NE-associated sleep characteristics associated. The evaluation items were total sleep time, sleep efficiency, the ratio of rapid eye movement (REM) to non-REM sleep, REM sleep latency, and non-REM sleep latency. Factors influencing NE were examined by logistic regression analysis, with NE presence/absence as the dependent variable and each evaluation item as the independent variable. Given that 2-6 measurements were made for each patient, Generalized Estimating Equations was used in the analysis. NE positively correlated with prolonged REM sleep latency, but no significant differences were found in other sleep structures. A positive correlation exists between NE and prolonged REM sleep latency. Changes in sleep structure in the early stages of sleep may lead to increased nocturnal urine volume and increased NE frequency.

Patterns of polysomnography parameters in 27 neuropsychiatric diseases: an umbrella review

BACKGROUND

We provide an umbrella review of the reported polysomnographic changes in patients with neuropsychiatric diseases compared with healthy controls.

METHODS

An electronic literature search was conducted in EMBASE, MEDLINE, All EBM databases, CINAHL, and PsycINFO. Meta-analyses of case-control studies investigating the polysomnographic changes in patients with neuropsychiatric diseases were included. For each meta-analysis, we estimated the summary effect size using random effects models, the 95% confidence interval, and the 95% prediction interval. We also estimated between-study heterogeneity, evidence of excess significance bias, and evidence of small-study effects. The levels of evidence of polysomnographic changes in neuropsychiatric diseases were ranked as follows: not significant, weak, suggestive, highly suggestive, or convincing.

RESULTS

We identified 27 articles, including 465 case-control studies in 27 neuropsychiatric diseases. The levels of evidence of polysomnographic changes in neuropsychiatric diseases were highly suggestive for increased sleep latency and decreased sleep efficiency (SE) in major depressive disorder (MDD), increased N1 percentage, and decreased N2 percentage, SL and REML in narcolepsy, and decreased rapid eye movement (REM) sleep percentage in Parkinson's disease (PD). The suggestive evidence decreased REM latency in MDD, decreased total sleep time and SE in PD, and decreased SE in posttraumatic stress disorder and in narcolepsy.

CONCLUSIONS

The credibility of evidence for sleep characteristics in 27 neuropsychiatric diseases varied across polysomnographic variables and diseases. When considering the patterns of altered PSG variables, no two diseases had the same pattern of alterations, suggesting that specific sleep profiles might be important dimensions for defining distinct neuropsychiatric disorders.

Multivariate patterns of disrupted sleep longitudinally predict affective vulnerability to psychosis in 22q11.2 Deletion Syndrome

22q11.2 deletion syndrome (22q11DS) contributes dramatically to increased genetic risk for psychopathology, and in particular schizophrenia. Sleep disorders, including obstructive sleep apnea (OSA), are also highly prevalent, making 22q11DS a unique model to explore their impact on psychosis vulnerability. Still, the contribution of sleep disturbances to psychosis vulnerability remains unclear. We characterized the sleep phenotype of 69 individuals with 22q11DS and 38 healthy controls with actigraphy and sleep questionnaires. Psychiatric symptoms were measured concomitantly with the baseline sleep assessment and at longitudinal follow-up, 3.58±0.85 years later. We used a novel multivariate partial-least-square-correlation (PLSC) approach to identify sleep patterns combining objective and subjective variables, which correlated with psychiatric symptoms. We dissected longitudinal pathways linking sleep disturbances to psychosis, using multi-layer-network-analysis. 22q11DS was characterized by a non-restorative sleep pattern, combining increased daytime fatigue despite longer sleep duration. Non-restorative sleep combined with OSA symptoms correlated with both emotional and psychotic symptoms. Moreover, a sleep pattern evocative of OSA predicted longitudinal worsening of positive and negative symptoms, by accentuating the effects of emotional dysregulation. These results suggest that sleep disturbances could significantly increase psychosis risk, along an affective pathway. If confirmed, this suggests that systematic screening of sleep quality could mitigate psychosis vulnerability in 22q11DS.

Novel Objective Measures of Hypersomnolence

Purpose of review

To provide a brief overview of current objective measures of hypersomnolence, discuss proposed measure modifications, and review emerging measures.

Recent findings

There is potential to optimize current tools using novel metrics. High-density and quantitative EEG-based measures may provide discriminative informative. Cognitive testing may quantify cognitive dysfunction common to hypersomnia disorders, particularly in attention, and objectively measure pathologic sleep inertia. Structural and functional neuroimaging studies in narcolepsy type 1 have shown considerable variability but so far implicate both hypothalamic and extra-hypothalamic regions; fewer studies of other CDH have been performed. There is recent renewed interest in pupillometry as a measure of alertness in the evaluation of hypersomnolence.

Summary

No single test captures the full spectrum of disorders and use of multiple measures will likely improve diagnostic precision. Research is needed to identify novel measures and disease-specific biomarkers, and to define combinations of measures optimal for CDH diagnosis.

A systematic review and meta-analysis of the prevalence and correlation of mild cognitive impairment in sarcopenia

Sarcopenia is a progressive skeletal muscle disorder involving the loss of muscle mass and function, associated with an increased risk of disability and frailty. Though its prevalence in dementia has been studied, its occurrence in mild cognitive impairment (MCI) has not been well established. As MCI is often a prelude to dementia, our study aims to investigate the prevalence of MCI among individuals with sarcopenia and to also ascertain whether sarcopenia is independently associated with MCI. The Cochrane Library, PubMed, Ovid, Embase and Web of Science were systematically searched for articles on MCI and/or sarcopenia published from inception to 1 February 2022. We reviewed the available literature on the number of individuals with MCI and/or sarcopenia and calculated odds ratios (ORs) of sarcopenia in MCI and MCI in sarcopenia, respectively. Statistical analyses were performed using the meta package in Stata, Version 12.0. A total of 13 studies and 27 428 patients were included in our analysis. The pooled prevalence of MCI in participants with sarcopenia was 20.5% (95% confidence interval [CI]: 0.140-0.269) in a total sample of 2923 cases with a high level of heterogeneity (P < 0.001; I²  = 95.4%). The overall prevalence of sarcopenia with MCI was 9.1% (95% CI: 0.047-0.134, P < 0.001; I²  = 93.0%). For overall ORs, there were 23 364 subjects with a mean age of 73 years; the overall adjusted OR between MCI and sarcopenia was 1.46 (95% CI: 1.31-1.62). Slight heterogeneity in both adjusted ORs (P = 0.46; I²  = 0%) was noted across the studies. The prevalence of MCI is relatively high in patients with sarcopenia, and sarcopenia may be a risk factor for MCI.

Approach to a sleepy child: Diagnosis and treatment of excessive daytime sleepiness in children and adolescents

The aim of this review is to give updated information to pediatric neurologists on the correct diagnostic approach and treatment of excessive daytime sleepiness (EDS) in children and adolescents. Due to the change in the society habits, EDS is becoming an emerging problem for the health system. At the present there are few articles specifically devoted to the evaluation of EDS. EDS is often reported in several manuscripts as a side effect of other sleep disorders (obstructive sleep apnea, circadian disorders, etc.) or of the use of drugs or of the substance abuse or as a consequence of bad sleep habits and poor sleep hygiene. EDS, especially in children, may manifest with paradoxical symptoms like hyperactivity, inattention, and impulsiveness. However, common sign of EDS in children are the propensity to sleep longer than usual, the difficulty waking up in the morning, and falling asleep frequently during the day in monotonous situation. The diagnosis should include subjective (sleep diaries, questionnaires) and objective (polysomnography, multiple sleep latency test, etc.) instruments to avoid misdiagnosis. Narcolepsy is the most studied central disorder of hypersomnolence, and it is a predominantly pediatric disease with a peak age of onset in prepuberty but the diagnosis is often delayed especially in mild forms. The early and correct treatment of narcolepsy and of other form of EDS is extremely important since late and inappropriate treatments can affect the psychosocial development of the children and adolescents.

Polysomnographic nighttime features of Restless Legs Syndrome: A systematic review and meta-analysis

Background

Restless Legs Syndrome (RLS) is a common sleep disorder. Polysomnographic (PSG) studies have been used to explore the night sleep characteristics of RLS, but their relationship with RLS has not been fully analyzed and researched.

Methods

We searched the Cochrane Library electronic literature, PubMed, and EMBASE databases to identify research literature comparing the differences in polysomnography between patients with RLS and healthy controls (HCs).

Results

This review identified 26 studies for meta-analysis. Our research found that the rapid eye movement sleep (REM)%, sleep efficiency (SE)%, total sleep time (TST) min, and N2 were significantly decreased in patients with RLS compared with HCs, while sleep latency (SL) min, stage shifts (SS), awakenings number (AWN), wake time after sleep onset (WASO) min, N1%, rapid eye movement sleep latency (REML), and arousal index (AI) were significantly increased. Additionally, there was no significant difference among N3%, slow wave sleep (SWS)%, and apnea-hypopnea index (AHI).

Conclusion

Our findings demonstrated that architecture and sleep continuity had been disturbed in patients with RLS, which further illustrates the changes in sleep structure in patients with RLS. In addition, further attention to the underlying pathophysiological mechanisms of RLS and its association with neurodegenerative diseases is needed in future studies.

The Impact of Sleep Pattern in School/Work Performance During the COVID-19 Home Quarantine in Patients With Narcolepsy

Objectives

Narcolepsy patients were observed improvements in their academic performance during the COVID-19 home quarantine. Therefore, we aim to investigate the influence of sleep behavioral changes on school/work performance in narcolepsy patients during the home quarantine.

Methods

Patients admitted to Shandong Provincial Qianfoshan Hospital from Jan 1, 2017 to Jan 1, 2021 who were diagnosed with narcolepsy were studied by online questionnaires in two different periods (during and 1 year after the COVID-19 home quarantine), including five aspects: (1) changes in school/work performance (percentile ranking in class/Sheehan Disability Scale 1, SDS1); (2) daytime functions; (3) clinical symptoms; (4) psychological moods; (5) medication situations.

Results

A total of 46 narcolepsy patients 34 (73.9%) narcolepsy type 1, 12 (26.1%) narcolepsy type 2 with average age of 20.76 ± 8.99 years and an equal number of age and gender matched control subjects were enrolled. During the COVID-19 home quarantine, the narcolepsy patients were found that they altered sleep patterns, including later get up time (P < 0.001), longer total sleep time (TST, P = 0.001), better sleep quality (PSQI, P = 0.001), and lower anxiety level (P = 0.005). Their school/work performance improved parallelly [with better percentile ranking (P = 0.001) and lower SDS1 scores (P = 0.002)]. The results of multiple linear stepwise regression analysis showed a linear regression relationship between TST [efficient (95%) −7.356 (−13.570 to 1.143)], SDS1 score [efficient (95%) 6.580 (2.346–10.815), P = 0.004] and the percentile ranking after adjusting for potential effects. Both the improvements of sleep behavior and school/work performance disappeared after the end of COVID-19 home quarantine. No similar fluctuation was found in the control group.

Discussion

Changes in sleep pattern during the COVID-19 home quarantine, such as longer sleep time and later wake-up time, can reduce the degree of daytime sleepiness and increase the degree of daytime wakefulness of narcolepsy patients, which can alleviate the impact of the disease on school/work performance.

Effect of FT218, a Once-Nightly Sodium Oxybate Formulation, on Disrupted Nighttime Sleep in Patients with Narcolepsy: Results from the Randomized Phase III REST-ON Trial

BACKGROUND

Sodium oxybate has been recognized as a gold standard for the treatment of disrupted nighttime sleep due to narcolepsy. Its short half-life and immediate-release formulation require patients to awaken 2.5-4 h after their bedtime dose to take a second dose. A novel extended-release, once-nightly sodium oxybate formulation (ON-SXB; FT218) is under US Food and Drug Administration review for the treatment of adults with narcolepsy.

OBJECTIVE

A phase III trial of ON-SXB in individuals with narcolepsy type 1 (NT1) or 2 (NT2) [the REST-ON trial; NCT02720744] has been conducted and the primary results reported elsewhere. Secondary objectives from REST-ON were to assess the efficacy of ON-SXB on disrupted nighttime sleep; the results of this analysis are reported here.

METHODS

In the double-blind, phase III REST-ON trial, patients aged ≥ 16 years were randomly assigned 1:1 to ON-SXB (1 week, 4.5 g; 2 weeks, 6 g; 5 weeks, 7.5 g; 5 weeks, 9 g) or placebo. Secondary endpoints included polysomnographic measures of sleep stage shifts and nocturnal arousals and patient-reported assessments of sleep quality and refreshing nature of sleep at 6, 7.5, and 9 g; post hoc analyses included changes in time spent in each sleep stage, delta power, and assessments in stimulant-use subgroups for prespecified endpoints.

RESULTS

In total, 190 participants (n = 97, ON-SXB; n = 93, placebo) were included in the efficacy analyses. All three ON-SXB doses demonstrated a clinically meaningful, statistically significant decrease vs placebo in the number of transitions to wake/N1 from N1, N2, and rapid eye movement (REM) stages (all doses p < 0.001) and the number of nocturnal arousals (p < 0.05 ON-SXB 6 g; p < 0.001 7.5 and 9 g). Sleep quality and refreshing nature of sleep were significantly improved with all three ON-SXB doses vs placebo (p < 0.001). Post hoc analyses revealed a significant reduction in time spent in N1 (p < 0.05 ON-SXB 6 g; p < 0.001 7.5 and 9 g) and REM (all p < 0.001) and increased time spent in N3 with ON-SXB vs placebo (all p < 0.001), with a significant increase in delta power (p < 0.01 ON-SXB 6 g; p < 0.05 7.5 g; p < 0.001 9 g) and increased REM latency (ON-SXB 7.5 g vs placebo; p < 0.05). Significant improvements in disrupted nighttime sleep were observed regardless of concomitant stimulant use.

CONCLUSIONS

The clinically beneficial, single nighttime dose of ON-SXB significantly improved disrupted nighttime sleep in patients with narcolepsy.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT02720744.

Differential characteristics of repeated polysomnography and multiple sleep latency test parameters in narcolepsy type 1 and type 2 patients: a longitudinal retrospective study

PURPOSE

Narcolepsy is a chronic disorder and its phenotype is dichotomized into narcolepsy type 1 (NT1) and narcolepsy type 2 (NT2). The clinical course and pathophysiological mechanisms of these two clinical entities and their differences are not adequately defined. This study aimed to explore the differential longitudinal patterns of polysomnography (PSG) and multiple sleep latency test (MSLT) in NT1 and NT2.

METHODS

In this retrospective study demographic characteristics, PSG, and MSLT parameters at baseline and follow-up were compared between NT1 and NT2 patients. Patients with both follow-up MSLT and PSG were selected for sub-group analysis. Baseline and follow-up MSLT and PSG parameters were compared.

RESULTS

Of 55 patients with narcolepsy, mean follow-up periods were 7.4 ± 3.5 years for NT1 and 5.5 ± 2.9 for NT2. Demographic data showed increased body mass index and prevalence of sleep paralysis in NT1. Baseline PSG characteristics between NT1 and NT2 showed decreased sleep latency (p = 0.016) and REM latency (p = 0.046) in NT1 group when compared with NT2. Nocturnal SOREMP on PSG was more prevalent in NT1 (p = 0.017), and half of NT2 patients with nocturnal SOREMP on PSG changed their diagnoses to NT1. On follow-up PSG, NT1 displayed reductions in sleep stage N2 (p = 0.006) and N3 (p = 0.048), while wake after sleep onset (WASO) (p = 0.023) and apnea-hypopnea index (AHI) (p = 0.007) were significantly increased.

CONCLUSION

Differential MSLT and PSG characteristics of NT1 and NT2 in at baseline and follow-up indicate that NT1 and NT2 are distinct disease phenotypes, and that they present with a contrasting course of disease.