Use of the single-item Patient Global Impression-Severity scale as a self-reported assessment of insomnia severity.
Ellen S SnyderPeining TaoVladimir SvetnikChristopher LinesW Joseph HerringPublished in: Journal of sleep research (2020)
We evaluated a single-item Patient Global Impression-Severity (PGI-S) scale for assessing insomnia severity during the clinical development programme for suvorexant. The analyses used data from two randomised, double-blind, placebo-controlled, 3-month, Phase III clinical trials of suvorexant in patients with Diagnostic and Statistical Manual of Mental Disorders IV criteria insomnia. Patients assessed insomnia severity during the previous week using the PGI-S, a one-item questionnaire containing six response options ranging from 0 (none) to 5 (very severe), at baseline and at Week 2, and Months 1, 2, and 3 after randomisation. The seven-item Insomnia Severity Index (ISI) and other subjective and objective assessments were also completed by patients. PGI-S responses were compared primarily with the ISI using descriptive statistics and correlations. The PGI-S demonstrated favourable measurement characteristics (validity, reliability, responsiveness and sensitivity). PGI-S scores decreased from baseline to Month 3 in a similar pattern to the ISI total score, and the Spearman correlation coefficient between PGI-S and the ISI was .73. An improvement of ≥2 points on the PGI-S defined a treatment responder, based on comparison to the ISI definition of a responder (improvement of ≥6 points). Our present findings suggest that the PGI-S is a simple but valid, reliable, responsive, sensitive, and meaningful patient-reported assessment of insomnia severity. The PGI-S may be particularly useful as a companion outcome to sleep monitoring using wearable sleep devices or smartphones in at-home settings.
Keyphrases
- placebo controlled
- sleep quality
- double blind
- clinical trial
- phase iii
- patient reported
- end stage renal disease
- open label
- phase ii
- newly diagnosed
- ejection fraction
- psychometric properties
- chronic kidney disease
- study protocol
- peritoneal dialysis
- prognostic factors
- case report
- depressive symptoms
- physical activity
- squamous cell carcinoma
- magnetic resonance imaging
- blood pressure
- machine learning
- heart rate
- computed tomography
- artificial intelligence
- early onset
- patient reported outcomes
- phase ii study
- electronic health record
- combination therapy