A clinical predictive score for mood disorder risk in low-income primary care settings

Abstract

BACKGROUND: Despite availability of validated screening tests for mood disorders, busy general practitioners (GPs) often lack the time to use them routinely. This study aimed to develop a simplified clinical predictive score to help screen for presence of current mood disorder in low-income primary care settings. METHODS: In a cross-sectional study, 197 patients seen at 10 primary care centers in Santiago, Chile completed self-administered screening tools for mood disorders: the Patient Health questionnaire (PHQ-9) and the Mood Disorder Questionnaire (MDQ). To determine participants' current-point mood disorder status, trained clinicians applied a gold-standard diagnostic interview (SCID-I). A simplified clinical predictive model (CM) was developed based on clinical features and selected questions from the screening tools. Using CM, a clinical predictive score (PS) was developed. Full PHQ-9 and GP assessment were compared with PS. RESULTS: Using multivariate logistic regression, clinical and demographic variables predictive of current mood disorder were identified for a simplified 8-point predictive score (PS). PS had better discrimination than GP assessment (auROC-statistic=0.80 [95% CI 0.72, 0.85] vs. 0.58 [95% CI 0.52, 0.62] p-value <0.0001), but not as good as the full PHQ-9 (0.89 [95% CI 0.85, 0.93], p-value=0.03). Compared with GP assessment, PS increased sensitivity by 50% at a fixed specificity of 90%. Administered in a typical primary care clinical population, it correctly predicted almost 80% of cases. LIMITATIONS: Further research must verify external validity of the PS. CONCLUSION: An easily administered clinical predictive score determined, with reasonable accuracy, the current risk of mood disorders in low-income primary care settings.