Predicting depression in rheumatoid arthritis: The signal importance of pain extent and fatigue, and comorbidity

Frederick Wolfe, Kaleb Michaud

Research output: Contribution to journalArticle

110 Citations (Scopus)

Abstract

To determine the incidence of self-reported depression (SRD) in rheumatoid arthritis and to identify and rank clinically useful predictors of depression. Methods. We assessed 22,131 patients for SRD between 1999 and 2008. We collected demographic, clinical and treatment data, household income, employment and work disability status, comorbidity, scales for function, pain, global, and fatigue, the Regional Pain Scale (RPS), the Symptom Intensity (SI) scale (a linear combination of the RPS and the fatigue scales) and linear combinations of the Health Assessment Questionnaire, pain and global severity. We used logistic regression analyses with multivariable fractional polynomial predictors, and Random Forest analysis to determine the importance of the predictors. Results. The cross-sectional prevalence of self-reported depression was 15.2% (95% confidence interval [95% CI] 14.7- 15.7%) and the incidence rate was 5.5 (95% CI 5.3-5.7) per 100 patient years of observation. The cumulative risk of SRD after 9 years was 38.3% (95% CI 36.6-40.1%). Almost all variables were significant predictors in logistic models. In Random Forest analyses, the SI scale, followed by comorbidity, best predicted self-reported depression, and no other variable or combination of variables improved prediction compared with the SI scale. Conclusion. Pain extent and fatigue (SI scale) are the dominant predictors of SRD. These variables, also of central importance in the symptomatology of fibromyalgia, are powerful markers of distress. A strong case can be made for the inclusion of these assessments in routine rheumatology practice. In addition, actual knowledge of comorbidity provides important insights into the patient's global health and associated perceptions.

Original languageEnglish (US)
Pages (from-to)667-673
Number of pages7
JournalArthritis Care and Research
Volume61
Issue number5
DOIs
StatePublished - May 15 2009

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Fatigue
Comorbidity
Rheumatoid Arthritis
Depression
Pain
Confidence Intervals
Logistic Models
Fibromyalgia
Incidence
Rheumatology
Pain Measurement
Regression Analysis
Observation
Demography
Health

ASJC Scopus subject areas

  • Rheumatology

Cite this

Predicting depression in rheumatoid arthritis : The signal importance of pain extent and fatigue, and comorbidity. / Wolfe, Frederick; Michaud, Kaleb.

In: Arthritis Care and Research, Vol. 61, No. 5, 15.05.2009, p. 667-673.

Research output: Contribution to journalArticle

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abstract = "To determine the incidence of self-reported depression (SRD) in rheumatoid arthritis and to identify and rank clinically useful predictors of depression. Methods. We assessed 22,131 patients for SRD between 1999 and 2008. We collected demographic, clinical and treatment data, household income, employment and work disability status, comorbidity, scales for function, pain, global, and fatigue, the Regional Pain Scale (RPS), the Symptom Intensity (SI) scale (a linear combination of the RPS and the fatigue scales) and linear combinations of the Health Assessment Questionnaire, pain and global severity. We used logistic regression analyses with multivariable fractional polynomial predictors, and Random Forest analysis to determine the importance of the predictors. Results. The cross-sectional prevalence of self-reported depression was 15.2{\%} (95{\%} confidence interval [95{\%} CI] 14.7- 15.7{\%}) and the incidence rate was 5.5 (95{\%} CI 5.3-5.7) per 100 patient years of observation. The cumulative risk of SRD after 9 years was 38.3{\%} (95{\%} CI 36.6-40.1{\%}). Almost all variables were significant predictors in logistic models. In Random Forest analyses, the SI scale, followed by comorbidity, best predicted self-reported depression, and no other variable or combination of variables improved prediction compared with the SI scale. Conclusion. Pain extent and fatigue (SI scale) are the dominant predictors of SRD. These variables, also of central importance in the symptomatology of fibromyalgia, are powerful markers of distress. A strong case can be made for the inclusion of these assessments in routine rheumatology practice. In addition, actual knowledge of comorbidity provides important insights into the patient's global health and associated perceptions.",
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