Objective sleep disturbance is associated with poor response to cognitive and behavioral treatments for insomnia in postmenopausal women

Kalmbach, David A.; Cheng, Philip; Roth, Thomas; Sagong, Chaewon; Drake, Christopher L.

doi:10.1016/j.sleep.2020.04.024

Cited by 24 publications

(15 citation statements)

References 38 publications

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“…Firstly, this was a secondary analysis of existing RCT data, which was not specifically powered to identify polysomnographic predictors of treatment-response to CBTi. However, as previous studies with smaller sample sizes have detected statistically significant effects of objective sleep duration ( Bathgate et al, 2017 ), sleep efficiency ( Kalmbach et al, 2020 ), sleep onset latency ( Troxel et al, 2013 ), and qEEG predictors ( Krystal and Edinger, 2010 ) on response to CBTi in patients with insomnia, it is unlikely that our exploratory study was under-powered to detect an effect of these specific polysomnographic predictors on treatment-response.…”

Section: Limitationsmentioning

confidence: 73%

“…Previous studies have investigated the effect of short objective sleep duration (i.e., total sleep time < 6 h) and objective sleep efficiency on treatment-response to CBTi in patients with insomnia ( Bathgate et al, 2017 ; Galbiati et al, 2019 ; Kalmbach et al, 2020 ). It has been postulated that insomnia patients with short objective sleep duration may experience an insomnia phenotype characterized by underlying biological mechanisms, rather than psychological/behavioral mechanisms that may be less responsive to CBTi ( Vgontzas et al, 2013 ).…”

Section: Discussionmentioning

confidence: 99%

“…Polysomnographic sleep study data have previously been used to predict response to CBTi in patients with insomnia ( Bathgate et al, 2017 ; Miller et al, 2018 ; Kalmbach et al, 2020 ). For example, studies have reported that shorter sleep duration ( Bathgate et al, 2017 ), lower objective sleep efficiency ( Kalmbach et al, 2020 ; percentage of time in bed spent asleep), shorter sleep onset latency ( Troxel et al, 2013 ), specific quantitative electroencephalography (qEEG) parameters ( Krystal and Edinger, 2010 ), and co-morbid OSA ( Sweetman et al, 2017b ) are associated with a reduced response to CBTi.…”

Section: Introductionmentioning

confidence: 99%

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Polysomnographic Predictors of Treatment Response to Cognitive Behavioral Therapy for Insomnia in Participants With Co-morbid Insomnia and Sleep Apnea: Secondary Analysis of a Randomized Controlled Trial

et al. 2021

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ObjectiveCo-morbid insomnia and sleep apnea (COMISA) is a common and debilitating condition that is more difficult to treat compared to insomnia or sleep apnea-alone. Emerging evidence suggests that cognitive behavioral therapy for insomnia (CBTi) is effective in patients with COMISA, however, those with more severe sleep apnea and evidence of greater objective sleep disturbance may be less responsive to CBTi. Polysomnographic sleep study data has been used to predict treatment response to CBTi in patients with insomnia-alone, but not in patients with COMISA. We used randomized controlled trial data to investigate polysomnographic predictors of insomnia improvement following CBTi, versus control in participants with COMISA.MethodsOne hundred and forty five participants with insomnia (ICSD-3) and sleep apnea [apnea-hypopnea index (AHI) ≥ 15] were randomized to CBTi (n = 72) or no-treatment control (n = 73). Mixed models were used to investigate the effect of pre-treatment AHI, sleep duration, and other traditional (AASM sleep macrostructure), and novel [quantitative electroencephalography (qEEG)] polysomnographic predictors of between-group changes in Insomnia Severity Index (ISI) scores from pre-treatment to post-treatment.ResultsCompared to control, CBTi was associated with greater ISI improvement among participants with; higher AHI (interaction p = 0.011), less wake after sleep onset (interaction p = 0.045), and less N3 sleep (interaction p = 0.005). No quantitative electroencephalographic, or other traditional polysomnographic variables predicted between-group ISI change (all p > 0.09).DiscussionAmong participants with COMISA, higher OSA severity predicted a greater treatment-response to CBTi, versus control. People with COMISA should be treated with CBTi, which is effective even in the presence of severe OSA and objective sleep disturbance.

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Section: Limitationsmentioning

confidence: 73%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Polysomnographic Predictors of Treatment Response to Cognitive Behavioral Therapy for Insomnia in Participants With Co-morbid Insomnia and Sleep Apnea: Secondary Analysis of a Randomized Controlled Trial

et al. 2021

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“…There have been several attempts to identify electroencephalographic, or polysomnographic predictive markers for treatment response in ID ( Espie et al, 2001 ; Kalmbach et al, 2020 ; Sweetman et al, 2021 ). A reliable predictor of outcome across treatment modalities has not yet been found.…”

Section: Discussionmentioning

confidence: 99%

Connectomic disturbances underlying insomnia disorder and predictors of treatment response

Zhang

Yan

et al. 2022

Front. Hum. Neurosci.

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ObjectiveDespite its prevalence, insomnia disorder (ID) remains poorly understood. In this study, we used machine learning to analyze the functional connectivity (FC) disturbances underlying ID, and identify potential predictors of treatment response through recurrent transcranial magnetic stimulation (rTMS) and pharmacotherapy.Materials and methods51 adult patients with chronic insomnia and 42 healthy age and education matched controls underwent baseline anatomical T1 magnetic resonance imaging (MRI), resting-stage functional MRI (rsfMRI), and diffusion weighted imaging (DWI). Imaging was repeated for 24 ID patients following four weeks of treatment with pharmacotherapy, with or without rTMS. A recently developed machine learning technique, Hollow Tree Super (HoTS) was used to classify subjects into ID and control groups based on their FC, and derive network and parcel-based FC features contributing to each model. The number of FC anomalies within each network was also compared between responders and non-responders using median absolute deviation at baseline and follow-up.ResultsSubjects were classified into ID and control with an area under the receiver operating characteristic curve (AUC-ROC) of 0.828. Baseline FC anomaly counts were higher in responders than non-responders. Response as measured by the Insomnia Severity Index (ISI) was associated with a decrease in anomaly counts across all networks, while all networks showed an increase in anomaly counts when response was measured using the Pittsburgh Sleep Quality Index. Overall, responders also showed greater change in all networks, with the Default Mode Network demonstrating the greatest change.ConclusionMachine learning analysis into the functional connectome in ID may provide useful insight into diagnostic and therapeutic targets.

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“…Our results are interesting but far from conclusive, as indicated in the title of our report. Notably, 4 studies consisting of retrospective secondary analyses of previously published RCTs have found lower insomnia remission rates after cognitivebehavioral therapy for insomnia in the insomnia with objective short sleep duration phenotype than in the insomnia with normal sleep duration phenotype, [8][9][10][11] and 3 other studies have found equivalent insomnia remission rates in these 2 phenotypes. [12][13][14] Similarly, despite this preliminary evidence, the issue of the relative efficacy of cognitive-behavioral therapy for insomnia in our proposed insomnia phenotypes remains inconclusive but should fuel scientific inquiry for well-designed, adequately powered, prospective RCTs using a personalized medicine, phenotype-matching approach.…”

mentioning

confidence: 99%

Response to: Real effect vs placebo effect

Vgontzas

Puzino

Fernández-Mendoza

2021

Journal of Clinical Sleep Medicine

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Objective sleep disturbance is associated with poor response to cognitive and behavioral treatments for insomnia in postmenopausal women

Cited by 24 publications

References 38 publications

Polysomnographic Predictors of Treatment Response to Cognitive Behavioral Therapy for Insomnia in Participants With Co-morbid Insomnia and Sleep Apnea: Secondary Analysis of a Randomized Controlled Trial

Polysomnographic Predictors of Treatment Response to Cognitive Behavioral Therapy for Insomnia in Participants With Co-morbid Insomnia and Sleep Apnea: Secondary Analysis of a Randomized Controlled Trial

Connectomic disturbances underlying insomnia disorder and predictors of treatment response

Response to: Real effect vs placebo effect

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