Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia.
J Clin Sleep Med
; 20(6): 921-931, 2024 Jun 01.
Article
em En
| MEDLINE
| ID: mdl-38300822
ABSTRACT
STUDY OBJECTIVES:
The standard of care for military personnel with insomnia is cognitive behavioral therapy for insomnia (CBT-I). However, only a minority seeking insomnia treatment receive CBT-I, and little reliable guidance exists to identify those most likely to respond. As a step toward personalized care, we present results of a machine learning (ML) model to predict CBT-I response.METHODS:
Administrative data were examined for n = 1,449 nondeployed US Army soldiers treated for insomnia with CBT-I who had moderate-severe baseline Insomnia Severity Index (ISI) scores and completed 1 or more follow-up ISIs 6-12 weeks after baseline. An ensemble ML model was developed in a 70% training sample to predict clinically significant ISI improvement (reduction of at least 2 standard deviations on the baseline ISI distribution). Predictors included a wide range of military administrative and baseline clinical variables. Model accuracy was evaluated in the remaining 30% test sample.RESULTS:
19.8% of patients had clinically significant ISI improvement. Model area under the receiver operating characteristic curve (standard error) was 0.60 (0.03). The 20% of test-sample patients with the highest probabilities of improvement were twice as likely to have clinically significant improvement compared with the remaining 80% (36.5% vs 15.7%; χ21 = 9.2, P = .002). Nearly 85% of prediction accuracy was due to 10 variables, the most important of which were baseline insomnia severity and baseline suicidal ideation.CONCLUSIONS:
Pending replication, the model could be used as part of a patient-centered decision-making process for insomnia treatment. Parallel models will be needed for alternative treatments before such a system is of optimal value. CITATION Gabbay FH, Wynn GH, Georg MW, et al. Toward personalized care for insomnia in the US Army a machine learning model to predict response to cognitive behavioral therapy for insomnia. J Clin Sleep Med. 2024;20(6)921-931.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Terapia Cognitivo-Comportamental
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Medicina de Precisão
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Aprendizado de Máquina
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Distúrbios do Início e da Manutenção do Sono
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Militares
Tipo de estudo:
Guideline
/
Prognostic_studies
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Risk_factors_studies
Limite:
Adult
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Female
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Humans
/
Male
País/Região como assunto:
America do norte
Idioma:
En
Revista:
J Clin Sleep Med
Ano de publicação:
2024
Tipo de documento:
Article