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Nord J Psychiatry. 2015 Apr;69(3):210-5. doi: 10.3109/08039488.2014.962612. Epub 2014 Oct 7.

Bayesian prediction of treatment outcome in anorexia nervosa: a preliminary study.

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Veera Pohjolainen, Hospital District of Helsinki and Uusimaa, Department of Psychiatry, Helsinki, Health Centre, Department of Psychiatry, Helsinki, and University of Helsinki , Helsinki , Finland.



Knowledge of the prognostic factors predicting treatment outcome in anorexia nervosa (AN) measured with health-related quality of life (HRQoL) is limited.


We performed a novel statistical analysis to identify factors predicting treatment outcome in AN.


39 patients entering treatment of an ICD-10-defined AN completed the 15D HRQoL survey, the Eating Disorder Inventory (EDI) and a questionnaire evaluating self reported health status and eating habits before and 2 years after the start of treatment. The analysis was based on a Bayesian approach, which allows analyses of small data sets, and was performed using a naïve Bayes classifier.


An impaired follow-up HRQoL score was associated with three baseline risk factors: low self-reported vitality, high scores in eating control and a poor reported health status. Low baseline body mass index (BMI) and a high score in the eating dimension of the 15D predicted low follow-up BMI.


In our preliminary study, we identified a set of variables predicting poor HRQoL in AN. An effort to treat these symptoms effectively in the beginning of AN treatment may influence the outcome.


Anorexia nervosa; Bayes theorem; Bayesian prediction; Eating disorders; Health-related quality of life (HRQoL)

[Indexed for MEDLINE]

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