O R Maarsingh1, M W Heymans2, P F Verhaak3, B W J H Penninx4, H C Comijs4. 1. Department of General Practice & Elderly Care Medicine, Amsterdam Public Health Research Institute, VU University Medical Center, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands. Electronic address: o.maarsingh@vumc.nl. 2. Department of Epidemiology & Biostatistics, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands. 3. University of Groningen, University Medical Center Groningen, Department of General Practice, Groningen, The Netherlands; NIVEL, Netherlands Institute of Health Services Research, The Netherlands. 4. Department of Psychiatry, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands.
Abstract
BACKGROUND: Given the poor prognosis of late-life depression, it is crucial to identify those at risk. Our objective was to construct and validate a prediction rule for an unfavourable course of late-life depression. METHODS: For development and internal validation of the model, we used The Netherlands Study of Depression in Older Persons (NESDO) data. We included participants with a major depressive disorder (MDD) at baseline (n = 270; 60-90 years), assessed with the Composite International Diagnostic Interview (CIDI). For external validation of the model, we used The Netherlands Study of Depression and Anxiety (NESDA) data (n = 197; 50-66 years). The outcome was MDD after 2 years of follow-up, assessed with the CIDI. Candidate predictors concerned sociodemographics, psychopathology, physical symptoms, medication, psychological determinants, and healthcare setting. Model performance was assessed by calculating calibration and discrimination. RESULTS: 111 subjects (41.1%) had MDD after 2 years of follow-up. Independent predictors of MDD after 2 years were (older) age, (early) onset of depression, severity of depression, anxiety symptoms, comorbid anxiety disorder, fatigue, and loneliness. The final model showed good calibration and reasonable discrimination (AUC of 0.75; 0.70 after external validation). The strongest individual predictor was severity of depression (AUC of 0.69; 0.68 after external validation). LIMITATIONS: The model was developed and validated in The Netherlands, which could affect the cross-country generalizability. CONCLUSIONS: Based on rather simple clinical indicators, it is possible to predict the 2-year course of MDD. The prediction rule can be used for monitoring MDD patients and identifying those at risk of an unfavourable outcome.
BACKGROUND: Given the poor prognosis of late-life depression, it is crucial to identify those at risk. Our objective was to construct and validate a prediction rule for an unfavourable course of late-life depression. METHODS: For development and internal validation of the model, we used The Netherlands Study of Depression in Older Persons (NESDO) data. We included participants with a major depressive disorder (MDD) at baseline (n = 270; 60-90 years), assessed with the Composite International Diagnostic Interview (CIDI). For external validation of the model, we used The Netherlands Study of Depression and Anxiety (NESDA) data (n = 197; 50-66 years). The outcome was MDD after 2 years of follow-up, assessed with the CIDI. Candidate predictors concerned sociodemographics, psychopathology, physical symptoms, medication, psychological determinants, and healthcare setting. Model performance was assessed by calculating calibration and discrimination. RESULTS: 111 subjects (41.1%) had MDD after 2 years of follow-up. Independent predictors of MDD after 2 years were (older) age, (early) onset of depression, severity of depression, anxiety symptoms, comorbid anxiety disorder, fatigue, and loneliness. The final model showed good calibration and reasonable discrimination (AUC of 0.75; 0.70 after external validation). The strongest individual predictor was severity of depression (AUC of 0.69; 0.68 after external validation). LIMITATIONS: The model was developed and validated in The Netherlands, which could affect the cross-country generalizability. CONCLUSIONS: Based on rather simple clinical indicators, it is possible to predict the 2-year course of MDD. The prediction rule can be used for monitoring MDDpatients and identifying those at risk of an unfavourable outcome.
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