Background Disease trajectories of patients with anxiety disorders are highly diverse and approximately 60% remain chronically ill. The ability to predict disease course in individual patients... Show moreBackground Disease trajectories of patients with anxiety disorders are highly diverse and approximately 60% remain chronically ill. The ability to predict disease course in individual patients would enable personalized management of these patients. This study aimed to predict recovery from anxiety disorders within 2 years applying a machine learning approach. Methods In total, 887 patients with anxiety disorders (panic disorder, generalized anxiety disorder, agoraphobia, or social phobia) were selected from a naturalistic cohort study. A wide array of baseline predictors (N = 569) from five domains (clinical, psychological, sociodemographic, biological, lifestyle) were used to predict recovery from anxiety disorders and recovery from all common mental disorders (CMDs: anxiety disorders, major depressive disorder, dysthymia, or alcohol dependency) at 2-year follow-up using random forest classifiers (RFCs). Results At follow-up, 484 patients (54.6%) had recovered from anxiety disorders. RFCs achieved a cross-validated area-under-the-receiving-operator-characteristic-curve (AUC) of 0.67 when using the combination of all predictor domains (sensitivity: 62.0%, specificity 62.8%) for predicting recovery from anxiety disorders. Classification of recovery from CMDs yielded an AUC of 0.70 (sensitivity: 64.6%, specificity: 62.3%) when using all domains. In both cases, the clinical domain alone provided comparable performances. Feature analysis showed that prediction of recovery from anxiety disorders was primarily driven by anxiety features, whereas recovery from CMDs was primarily driven by depression features. Conclusions The current study showed moderate performance in predicting recovery from anxiety disorders over a 2-year follow-up for individual patients and indicates that anxiety features are most indicative for anxiety improvement and depression features for improvement in general. Show less
Remmerswaal, K.C.P.; Batelaan, N.M.; Hoogendoorn, A.W.; Wee, N.J.A. van der; Oppen, P. van; Balkom, A.J.L.M. van 2020
Objective Patients with obsessive compulsive disorder (OCD) have high disease burden. It is important to restore quality of life (QoL) in treatment, so that patients become able to live a... Show moreObjective Patients with obsessive compulsive disorder (OCD) have high disease burden. It is important to restore quality of life (QoL) in treatment, so that patients become able to live a fulfilling life. Little is known about the longitudinal course of QoL in patients with OCD, its association with remission from OCD, and about factors that contribute to an unfavourable course of QoL in remitting patients. Methods Study on the 4-year course of QoL of patients with chronic (n = 144), intermittent (n = 22), and remitting OCD (n = 73) using longitudinal data of the Netherlands Obsessive Compulsive Disorder Association (NOCDA; complete data:n = 239; imputed datan = 382). The EuroQol five-dimensional questionnaire (EQ-5D) utility score was used to assess QoL. In patients with remitting OCD, we examined patient characteristics that contributed to an unfavourable course of QoL, including sociodemographics, OCD characteristics, psychiatric comorbidity, and personality traits. Results Course of QoL was associated with course of OCD. QoL improved in those who remitted from OCD; however, even in these patients, QoL remained significantly below the population norms. The correlation between QoL and severity of OCD was only moderate:r = - 0.40 indicating that other factors besides OCD severity contribute to QoL. In remitters, more severe anxiety and depression symptoms were related to a lower QoL. Results were similar in complete and imputed data sets. Conclusions Remission from OCD is associated with improvement of QoL, but comorbid anxiety and depression symptoms hamper the improvement of QoL. QoL could be improved by reducing OCD symptoms in patients with OCD and by treating comorbid anxiety and depression symptoms in remitting patients. Show less
Scholten, W.D.; Batelaan, N.M.; Penninx, B.W.J.H.; Balkom, A.J.L.M. van; Smit, J.H.; Schoevers, R.A.; Oppen, P. van 2016
