Related Experiment Video For Anorexia nervosa
Updated: Feb 17, 2026

Assessing Activity-based Anorexia in Mice
Published on: May 14, 2018
Examining a staging model for anorexia nervosa: empirical exploration of a four stage model of severity
Sarah Maguire1, Lois J Surgenor2, Daniel Le Grange3
1Centre for Eating and Dieting Disorders, University of Sydney, Sydney, Australia.
Background:
An illness staging model for anorexia nervosa (AN) has received increasing attention, but assessing the merits of this concept is dependent on empirically examining a model in clinical samples. Building on preliminary findings regarding the reliability and validity of the Clinician Administered Staging Instrument for Anorexia Nervosa (CASIAN), the current study explores operationalising CASIAN severity scores into stages and assesses their relationship with other clinical features.
Method:
In women with DSM-IV-R AN and sub-threshold AN (all met AN criteria using DSM 5), receiver operating curve (ROC) analysis (n = 67) assessed the relationship between the sensitivity and specificity of each stage of the CASIAN. Thereafter chi-square and post-hoc adjusted residual analysis provided a preliminary assessment of the validity of the stages comparing the relationship between stage and treatment intensity and AN sub-types, and explored movement between stages after six months (Time 3) in a larger cohort (n = 171).
Results:
The CASIAN significantly distinguished between milder stages of illness (Stage 1 and 2) versus more severe stages of illness (Stages 3 and 4), and approached statistical significance in distinguishing each of the four stages from one other. CASIAN Stages were significantly associated with treatment modality and primary diagnosis, and CASIAN Stage at Time 1 was significantly associated with Stage at 6 month follow-up.
Conclusions:
Provisional support is provided for a staging model in AN. Larger studies with longer follow-up of cases are now needed to replicate and extend these findings and evaluate the overall utility of staging as well as optimal staging models.
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