Prognostic and predictive analysis of effectiveness of pharmacological and non-pharmaceutical treatment approaches for chronic insomnia

Abstract

Background. Limited access to cognitive behavioral therapy for insomnia (CBT-I) which is the most effective and safe treatment approach for chronic insomnia leads to the elaboration of shortened and interned delivered CBT-I methods. Investigation of effectiveness predictors of the new methods is important for their better result.
 Aim. Investigation of effectiveness predictors for pharmacotherapy and CBT-I based brief behavioral therapy for insomnia (BBT-I).
 Materials and methods. The data for the analysis were acquired from a randomized study of 42 participants with chronic insomnia who received either zopiclone 7.5 mg or BBT-I for 2 weeks. The difference of the insomnia severity index from pre- to post-treatment was the main outcome measure. Potential predictors included demographic and medical history data, objective sleep characteristics, baseline scores of Beck depression inventory (BDI), Spielberger anxiety scale, Toronto alexithymia scale, sleep hygiene index, dysfunctional beliefs and attitudes about sleep scale, Epworth sleepiness scale. Univariate linear regression analysis was used for prognostic analysis. To identify predictors of treatment outcome after the treatment course and after the 2 weeks follow-up we used multiple linear regression models with interaction.
 Results. In the prognostic analysis higher amount of awakenings during the night and a higher proportion of the 1 stage NREM sleep measured objectively correlated with better outcome E=0.2202 (p=0.05) and E=0.55 (p=0.039) respectively. Older age and higher baseline BDI score significantly worsened the outcome: E=0.233 (p=0.047) and E=0.2 (р=1.55e-06) respectively. Clinical predictors of the BBT-I effectiveness were an absence of the sleep onset problems and absence of GABA hypnotics use in medical history and the higher baseline daytime sleepiness.
 Conclusion. Neurophysiological (frequency of awakenings, percentage of the sleep stage N1) and clinical (severity of depression, age, daytime sleepiness) predictors of the effectiveness of BBT-I were revealed. This findings will help to select the patients who should undergo a shortened course of CBT-I.