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Original Research

A Multidimensional Tool to Quantify Treatment Resistance in Depression: The Maudsley Staging Method

Abebaw Fekadu, MD; Sarah Wooderson, PhD; Catherine Donaldson, DClinPsy; Kalypso Markopoulou, MD; Brendan Masterson, PgDip; Lucia Poon, RMN; and Anthony J. Cleare, PhD

Published: January 27, 2009

Article Abstract

Objective: Treatment resistance is a common clinical phenomenon in depression. However, current unitary models of staging fail to represent its complexity. We aimed to devise a model to stage treatment-resistant depression, taking into account the core factors contributing to treatment failure.

Method: We reviewed the literature to identify factors consistently associated with treatment resistance. We also analyzed data from a subgroup of patients discharged from a specialist inpatient unit for whom adequate data were obtainable.

Results: We present a points-based staging model incorporating 3 factors: treatment, severity of illness, and duration of presenting episode. In this model, the rating of symptom severity ranges from subsyndromal depression (score 1) to severe syndromal depression with psychosis (score 5). Antidepressant treatment is rated on a 5-point subscale based on number of medications used, while duration of the presenting episode is rated on a 3-point subscale. The overall level of resistance estimated using this model varies from minimal resistance (score of 3) to severe resistance (score of 15). The rating system allows the overall severity of treatment resistance to be summarized either as a single numeric score or under a single descriptive category. It may also be possible to specify categories (mild, moderate, and severe) based on severity of resistance. Analysis of inpatient data indicates that the factors incorporated in the model and the model itself have some predictive validity.

Conclusion: This staging model has reasonable face and predictive validity and may have better utility in staging treatment resistance than currently available methods.

Volume: 70

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