Symptoms predicting remission after divalproex augmentation with olanzapine in partially nonresponsive patients experiencing mixed bipolar I episode: a post-hoc analysis of a randomized controlled study

Predicting treatment outcome in depression: an introduction into current concepts and challenges

Improving response and remission rates in major depressive disorder (MDD) remains an important challenge. Matching patients to the treatment they will most likely respond to should be the ultimate goal. Even though numerous studies have investigated patient-specific indicators of treatment efficacy, no (bio)markers or empirical tests for use in clinical practice have resulted as of now. Therefore, clinical decisions regarding the treatment of MDD still have to be made on the basis of questionnaire- or interview-based assessments and general guidelines without the support of a (laboratory) test. We conducted a narrative review of current approaches to characterize and predict outcome to pharmacological treatments in MDD. We particularly focused on findings from newer computational studies using machine learning and on the resulting implementation into clinical decision support systems. The main issues seem to rest upon the unavailability of robust predictive variables and the lacking application of empirical findings and predictive models in clinical practice. We outline several challenges that need to be tackled on different stages of the translational process, from current concepts and definitions to generalizable prediction models and their successful implementation into digital support systems. By bridging the addressed gaps in translational psychiatric research, advances in data quantity and new technologies may enable the next steps toward precision psychiatry.

Repeated Cortisol Awakening Response as Predictor of Antidepressant Treatment Outcome with Duloxetine

BACKGROUND

Despite considerably extended knowledge about the mechanism of action of antidepressants, physicians would greatly benefit from reliable biological predictors identifying those patients who will respond poorly to a given treatment. The aim of the present study was to assess whether repeated testing of the cortisol awakening response (CAR) between baseline and after 10 days of duloxetine treatment is able to predict antidepressant treatment outcome after 6 weeks of treatment.

METHODS

12 patients with a major depressive episode were treated with duloxetine 90 mg/day for 6 weeks. At baseline and after 10 days of duloxetine treatment, the CAR was assessed, and changes between baseline and day 10 were categorized as improved or unimproved according to the change in cortisol area under the concentration-time curve total concentrations. Depression severity was assessed with the 21-item Hamilton Depression Rating Scale (HDRS-21).

RESULTS

Non-remission after 6 weeks of treatment with duloxetine was predicted by an unfavourable saliva cortisol change between baseline and 10 days of duloxetine treatment. Linear regression analysis revealed that patients with a higher decrease in saliva cortisol measures between baseline and 10 days of treatment show a higher decrease in HDRS-21 scores.

CONCLUSION

Repeated CAR during early treatment is a putative predictive marker of antidepressant treatment outcome with duloxetine. © 2015 S. Karger AG, Basel.

Early improvement of psychotic symptoms with lithium monotherapy as a predictor of later response in mania

Although lithium has been the first line agent in the treatment of bipolar disorder (BD), few studies have evaluated lithium's efficacy in mania with psychosis and its association with later response. Furthermore, given the widespread concern about antipsychotic side effects, answering a question about whether lithium alone can manage to treat both psychotic and non-psychotic mania seems a very relevant one. The present study addresses the antipsychotic efficacy of lithium monotherapy in acute mania and early improvement of psychotic symptoms as a predictor of later response of manic symptoms. Forty-six patients presenting a manic episode (32 with psychotic features and 14 subjects without psychotic features) were treated for 4 weeks with lithium monotherapy and evaluated weekly using the Young Mania Rating Scale (YMRS). Subjects with rapid cycling, substance abuse/dependence, or mixed episodes were excluded. The overall antimanic efficacy of lithium in psychosis vs. non-psychosis groups was evaluated. In addition, early improvement of psychotic symptoms and its prediction of subsequent response (>50% decrease in total YMRS scores) or remission were evaluated. Lithium showed a similar efficacy in both psychosis and non-psychosis mania. Early improvement of psychotic symptoms was associated with clinical response and remission at endpoint.

Signs and symptoms of acute mania: a factor analysis

BACKGROUND

The major diagnostic classifications consider mania as a uni-dimensional illness. Factor analytic studies of acute mania are fewer compared to schizophrenia and depression. Evidence from factor analysis suggests more categories or subtypes than what is included in the classification systems. Studies have found that these factors can predict differences in treatment response and prognosis.

METHODS

The sample included 131 patients consecutively admitted to an acute psychiatry unit over a period of one year. It included 76 (58%) males. The mean age was 44.05 years (SD = 15.6). Patients met International Classification of Diseases-10 (ICD-10) clinical diagnostic criteria for a manic episode. Patients with a diagnosis of mixed bipolar affective disorder were excluded. Participants were evaluated using the Young Mania Rating Scale (YMRS). Exploratory factor analysis (principal component analysis) was carried out and factors with an eigenvalue > 1 were retained. The significance level for interpretation of factor loadings was 0.40. The unrotated component matrix identified five factors. Oblique rotation was then carried out to identify three factors which were clinically meaningful.

RESULTS

Unrotated principal component analysis extracted five factors. These five factors explained 65.36% of the total variance. Oblique rotation extracted 3 factors. Factor 1 corresponding to 'irritable mania' had significant loadings of irritability, increased motor activity/energy and disruptive aggressive behaviour. Factor 2 corresponding to 'elated mania' had significant loadings of elevated mood, language abnormalities/thought disorder, increased sexual interest and poor insight. Factor 3 corresponding to 'psychotic mania' had significant loadings of abnormalities in thought content, appearance, poor sleep and speech abnormalities.

CONCLUSIONS

Our findings identified three clinically meaningful factors corresponding to 'elated mania', 'irritable mania' and 'psychotic mania'. These findings support the multidimensional nature of manic symptoms. Further evidence is needed to support the existence of corresponding clinical subtypes.