The recovery index: A novel approach to measuring recovery and predicting remission in major depressive disorder

Waguih William IsHak; Wes Bonifay; Katherine Collison; Mark Reid; Haidy Youssef; Thomas Parisi; Robert M. Cohen; Li Cai

doi:10.1016/j.jad.2016.08.081

The recovery index: A novel approach to measuring recovery and predicting remission in major depressive disorder

Waguih William IsHak^*, Wes Bonifay, Katherine Collison, Mark Reid, Haidy Youssef, Thomas Parisi, Robert M. Cohen, Li Cai

^*Corresponding author for this work

The Family Institute at Northwestern University

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

Abstract

Background Clinicians view “recovery” as the reduction in severity of symptoms over time, whereas patients view it as the restoration of premorbid functioning level and quality of life (QOL). The main purpose of this study is to incorporate patient-reported measures of functioning and QOL into the assessment of patient outcomes in MDD and to use this data to define recovery. Method Using the STAR*D study of patients diagnosed with MDD, this present analysis grades patients' MDD severity, functioning level, and QOL at exit from each level of the study, as well as at follow-up. Using Item Response Theory, we combined patient data from functioning and QOL measures (WSAS, Q-LES-Q) in order to form a single latent dimension named the Recovery Index. Results Recovery Index – a latent measure assessing impact of illness on functioning and QOL – is able to predict remission of MDD in patients who participated in the STAR*D study. Conclusions By incorporating functioning and quality of life, the Recovery index creates a new dimension towards measuring restoration of health, in order to move beyond basic symptom measurement.

Original language	English (US)
Pages (from-to)	369-374
Number of pages	6
Journal	Journal of Affective Disorders
Volume	208
DOIs	https://doi.org/10.1016/j.jad.2016.08.081
State	Published - Jan 15 2017

Funding

Data used in the preparation of this article were obtained from the limited access datasets distributed from the NIH-supported, “Sequenced Treatment Alternatives to Relieve Depression” (STAR*D) study. The STAR*D study focused on non-psychotic major depressive disorder (MDD) in adults who are seen in outpatient settings. The primary purpose of this research study was to determine which treatments worked best if initial pharmacological treatment did not produce an acceptable response. The study was supported by NIMH Contract #N01MH90003 to the University of Texas Southwestern Medical Center. The ClinicalTrials.gov identifier is NCT00021528 . This manuscript reflects the views of the authors and may not reflect the opinions or views of the STAR*D study investigators or of the NIH.

Keywords

Depression
Functioning
Major depressive disorder
Quality of life
Recovery
Remission
STAR*D

ASJC Scopus subject areas

Clinical Psychology
Psychiatry and Mental health

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10.1016/j.jad.2016.08.081

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title = "The recovery index: A novel approach to measuring recovery and predicting remission in major depressive disorder",

abstract = "Background Clinicians view “recovery” as the reduction in severity of symptoms over time, whereas patients view it as the restoration of premorbid functioning level and quality of life (QOL). The main purpose of this study is to incorporate patient-reported measures of functioning and QOL into the assessment of patient outcomes in MDD and to use this data to define recovery. Method Using the STAR*D study of patients diagnosed with MDD, this present analysis grades patients' MDD severity, functioning level, and QOL at exit from each level of the study, as well as at follow-up. Using Item Response Theory, we combined patient data from functioning and QOL measures (WSAS, Q-LES-Q) in order to form a single latent dimension named the Recovery Index. Results Recovery Index – a latent measure assessing impact of illness on functioning and QOL – is able to predict remission of MDD in patients who participated in the STAR*D study. Conclusions By incorporating functioning and quality of life, the Recovery index creates a new dimension towards measuring restoration of health, in order to move beyond basic symptom measurement.",

keywords = "Depression, Functioning, Major depressive disorder, Quality of life, Recovery, Remission, STAR*D",

author = "IsHak, {Waguih William} and Wes Bonifay and Katherine Collison and Mark Reid and Haidy Youssef and Thomas Parisi and Cohen, {Robert M.} and Li Cai",

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year = "2017",

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AU - Youssef, Haidy

AU - Parisi, Thomas

AU - Cohen, Robert M.

AU - Cai, Li

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N2 - Background Clinicians view “recovery” as the reduction in severity of symptoms over time, whereas patients view it as the restoration of premorbid functioning level and quality of life (QOL). The main purpose of this study is to incorporate patient-reported measures of functioning and QOL into the assessment of patient outcomes in MDD and to use this data to define recovery. Method Using the STAR*D study of patients diagnosed with MDD, this present analysis grades patients' MDD severity, functioning level, and QOL at exit from each level of the study, as well as at follow-up. Using Item Response Theory, we combined patient data from functioning and QOL measures (WSAS, Q-LES-Q) in order to form a single latent dimension named the Recovery Index. Results Recovery Index – a latent measure assessing impact of illness on functioning and QOL – is able to predict remission of MDD in patients who participated in the STAR*D study. Conclusions By incorporating functioning and quality of life, the Recovery index creates a new dimension towards measuring restoration of health, in order to move beyond basic symptom measurement.

AB - Background Clinicians view “recovery” as the reduction in severity of symptoms over time, whereas patients view it as the restoration of premorbid functioning level and quality of life (QOL). The main purpose of this study is to incorporate patient-reported measures of functioning and QOL into the assessment of patient outcomes in MDD and to use this data to define recovery. Method Using the STAR*D study of patients diagnosed with MDD, this present analysis grades patients' MDD severity, functioning level, and QOL at exit from each level of the study, as well as at follow-up. Using Item Response Theory, we combined patient data from functioning and QOL measures (WSAS, Q-LES-Q) in order to form a single latent dimension named the Recovery Index. Results Recovery Index – a latent measure assessing impact of illness on functioning and QOL – is able to predict remission of MDD in patients who participated in the STAR*D study. Conclusions By incorporating functioning and quality of life, the Recovery index creates a new dimension towards measuring restoration of health, in order to move beyond basic symptom measurement.

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The recovery index: A novel approach to measuring recovery and predicting remission in major depressive disorder

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