Course trajectories of unipolar depressive disorders identified by latent class growth analysis

Identification of latent classes in mood and anxiety disorders and their transitions over time: a follow-up study in the adult general population

BACKGROUND

Mood and anxiety disorders are heterogeneous conditions with variable course. Knowledge on latent classes and transitions between these classes over time based on longitudinal disorder status information provides insight into clustering of meaningful groups with different disease prognosis.

METHODS

Data of all four waves of the Netherlands Mental Health Survey and Incidence Study-2 were used, a representative population-based study of adults (mean duration between two successive waves = 3 years; N at T0 = 6646; T1 = 5303; T2 = 4618; T3 = 4007; this results in a total number of data points: 20 574). Presence of eight mood and anxiety DSM-IV disorders was assessed with the Composite International Diagnostic Interview. Latent class analysis and latent Markov modelling were used.

RESULTS

The best fitting model identified four classes: a healthy class (prevalence: 94.1%), depressed-worried class (3.6%; moderate-to-high proportions of mood disorders and generalized anxiety disorder (GAD)), fear class (1.8%; moderate-to-high proportions of panic and phobia disorders) and high comorbidity class (0.6%). In longitudinal analyses over a three-year period, the minority of those in the depressed-worried and high comorbidity class persisted in their class over time (36.5% and 38.4%, respectively), whereas the majority in the fear class did (67.3%). Suggestive of recovery is switching to the healthy class, this was 39.7% in the depressed-worried class, 12.5% in the fear class and 7.0% in the high comorbidity class.

CONCLUSIONS

People with panic or phobia disorders have a considerably more persistent and chronic disease course than those with depressive disorders including GAD. Consequently, they could especially benefit from longer-term monitoring and disease management.

Depressive symptoms' trajectories since adolescence and sleep quality in early adulthood: results from the EPITeen cohort

OBJECTIVES

We aimed to estimate the association between depressive symptoms' trajectories during adolescence and young adulthood and sleep quality in early adulthood.

METHODS

Data from 802 participants of the EPITeen study, evaluated at 13, 17 and 21 years of age, were analysed. Depressive symptoms were assessed using the Beck Depression Inventory-II and three trajectory classes from adolescence to adulthood were previously identified (High, Moderate, Low). The prevalences of poor sleep quality, overall (score>5) and in its specific dimensions: subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, use of sleep drugs and daytime dysfunction (score≥2), at 21 years of age were evaluated using the Pittsburgh Sleep Quality Index. Associations were estimated using adjusted odds ratio (OR) and the respective 95 % confidence intervals (CI).

RESULTS

At 21 years of age, 29.8 % young adults presented poor sleep quality, which was significantly different between those in the Low and High depressive trajectories (14.3 and 53.1 %, respectively, p<0.001). Compared with participants in the Low trajectory, those in the High trajectory were more likely to present poorer sleep quality at 21 years of age (OR=6.34 95 % CI: 3.94-10.21), particularly worse levels of sleep disturbance (OR=5.89 95 % CI: 2.84-12.21), daytime dysfunction (OR=7.63 95 % CI: 3.63-16.06) and subjective sleep quality (OR=6.61 95 % CI: 3.69-11.85).

CONCLUSIONS

Poor sleep quality in early adulthood was more frequent among individuals who had high levels of depressive symptoms since adolescence. Monitoring depression until adulthood may help to identify those at higher risk of sleep problems which, in turn, can lead to worse health outcomes over time.

Factors influencing the tendency of residual symptoms in patients with depressive disorders: a longitudinal study

BACKGROUND

Residual symptoms of depressive disorders are serious health problems. However, the progression process is hardly predictable due to high heterogeneity of the disease. This study aims to: (1) classify the patterns of changes in residual symptoms based on homogeneous data, and (2) identify potential predictors for these patterns.

METHODS

In this study, we conducted a data-driven Latent Class Growth Analysis (LCGA) to identify distinct tendencies of changes in residual symptoms, which were longitudinally quantified using the QIDS-SR16 at baseline and 1/3/6 months post-baseline for depressed patients. The association between baseline characteristics (e.g. clinical features and cognitive functions) and different progression tendencies were also identified.

RESULTS

The tendency of changes in residual symptoms was categorized into four classes: "light residual symptom decline (15.4%)", "residual symptom disappears (39.3%)", "steady residual symptom (6.3%)" and "severe residual symptom decline (39.0%)". We observed that the second class displayed more favorable recuperation outcomes than the rest of patients. The severity, recurrence, polypharmacy, and medication adherence of symptoms are intricately linked to the duration of residual symptoms' persistence. Additionally, clinical characteristics including sleep disturbances, depressive moods, alterations in appetite or weight, and difficulties with concentration have been identified as significant factors in the recovery process.

CONCLUSIONS

Our research findings indicate that certain clinical characteristics in patients with depressive disorders are associated with poor recovery from residual symptoms following acute treatment. This revelation holds significant value in the targeted attention to specific patients and the development of early intervention strategies for residual symptoms accordingly.

Coupled changes between ruminating thoughts and resting-state brain networks during the transition into adulthood

Perseverative negative thoughts, known as rumination, might arise from emotional challenges and preclude mental health when transitioning into adulthood. Due to its multifaceted nature, rumination can take several ruminative response styles, that diverge in manifestations, severity, and mental health outcomes. Still, prospective ruminative phenotypes remain elusive insofar. Longitudinal study designs are ideal for stratifying ruminative response styles, especially with resting-state functional MRI whose setup naturally elicits people's ruminative traits. Here, we considered self-rated questionnaires on rumination and psychopathology, along with resting-state functional MRI data in 595 individuals assessed at age 18 and 22 from the IMAGEN cohort. We conducted independent component analysis to characterize eight single static resting-state functional networks in each subject and session and furthermore conducted a dynamic analysis, tackling the time variations of functional networks during the entire scanning time. We then investigated their longitudinal mediation role between changes in three ruminative response styles (reflective pondering, brooding, and depressive rumination) and changes in internalizing and co-morbid externalizing symptoms. Four static and two dynamic networks longitudinally differentiated these ruminative styles and showed complemental sensitivity to internalizing and co-morbid externalizing symptoms. Among these networks, the right frontoparietal network covaried with all ruminative styles but did not play any mediation role towards psychopathology. The default mode, the salience, and the limbic networks prospectively stratified these ruminative styles, suggesting that maladaptive ruminative styles are associated with altered corticolimbic function. For static measures, only the salience network played a longitudinal causal role between brooding rumination and internalizing symptoms. Dynamic measures highlighted the default-mode mediation role between the other ruminative styles and co-morbid externalizing symptoms. In conclusion, we identified the ruminative styles' psychometric and neural outcome specificities, supporting their translation into applied research on young adult mental healthcare.

Prognostic Value of Pathological Personality Traits for Treatment Outcome in Anxiety and Depressive Disorders: The Leiden Routine Outcome Monitoring Study

ABSTRACT

Previous studies have failed to take baseline severity into account when assessing the effects of pathological personality traits (PPT) on treatment outcome. This study assessed the prognostic value of PPT (Dimensional Assessment of Personality Pathology-Short Form) on treatment outcome (Brief Symptom Inventory [BSI-posttreatment]) among patients with depressive and/or anxiety disorders ( N = 5689). Baseline symptom level (BSI-pretreatment) was taken into account as a mediator or moderator variable. Results showed significant effects of PPT on outcome, of which Emotional Dysregulation demonstrated the largest association ( β = 0.43, p < 0.001). When including baseline BSI score as a mediator variable, a direct effect ( β = 0.11, p < 0.001) remained approximately one-third of the total effect. The effects of Emotional Dysregulation (interaction effect β = 0.061, p < 0.001) and Inhibition (interaction effect β = 0.062, p < 0.001), but not Compulsivity or Dissocial Behavior, were moderated by the baseline symptom level. PPT predicts higher symptom levels, both before and after treatment, but yields relatively small direct effects on symptom decline when the effect of pretreatment severity is taken into account.

Effectiveness of treating depression with eye movement desensitization and reprocessing among inpatients–A follow-up study over 12 months

Increasing prevalence of depression poses a huge challenge to the healthcare systems, and the success rates of current standard therapies are limited. While 30% of treated patients do not experience a full remission after treatment, more than 75% of patients suffer from recurrent depressive episodes. Eye Movement Desensitization and Reprocessing (EMDR) therapy represents an emerging treatment option of depression, and preliminary studies show promising effects with a probably higher remission rate when compared to control-therapies such as cognitive behavioral therapy. In the present study, 49 patients with severe depression were treated with an integrated systemic treatment approach including EMDR therapy that followed a specific protocol with a treatment algorithm for depression in a naturalistic hospital setting. Following their discharge from the hospital, the patients were followed up by a structured telephone interview after 3 and 12 months. 27 of the 49 (55%) patients fulfilled the Beck’s depression criteria of a full remission when they were discharged. At the follow-up interview, 12 months after discharge, 7 of the 27 patients (26%) reported a relapse, while the remaining 20 patients (74%) had stayed relapse-free. The findings of our observational study confirm reports of earlier studies in patients with depression, showing that EMDR therapy leads to a high rate of remission, and is associated with a decreased number of relapses. Patients with depression receiving EMDR treatment may be more resilient to stressors.

Prediction of the trajectories of depressive symptoms among children in the adolescent brain cognitive development (ABCD) study using machine learning approach

BACKGROUND

Depression often first emerges during adolescence and evidence shows that the long-term patterns of depressive symptoms over time are heterogeneous. It is meaningful to predict the trajectory of depressive symptoms in adolescents to find early intervention targets.

METHODS

Based on the Adolescent Brain Cognitive Development Study, we included 4962 participants aged 9-10 who were followed-up for 2 years. Trajectories of depressive symptoms were identified by Latent Class Growth Analyses (LCGA). Four types of machine learning models were built to predict the identified trajectories and to obtain variables with predictive value based on the best performance model.

RESULTS

Of all participants, 536 (10.80%) were classified as increasing, 269 (5.42%) as persistently high, 433 (8.73%) as decreasing, and 3724 (75.05%) as persistently low by LCGA. Gradient Boosting Machine (GBM) model got the highest discriminant performance. Sleep quality, parental emotional state and family financial adversities were the most important predictors and three resting state functional magnetic resonance imaging functional connectivity data were also helpful to distinguish trajectories.

LIMITATION

We only have depressive symptom scores at three time points. Some valuable predictors are not specific to depression. External validation is an important next step. These predictors should not be interpreted as etiology and some variables were reported by parents/caregivers.

CONCLUSION

Using GBM combined with baseline characteristics, the trajectories of depressive symptoms with two years among adolescents aged 9-10 years can be well predicted, which might further facilitate the identification of adolescents at high risk of depressive symptoms and development of effective early interventions.

Exploration of the Moderating Effects of Physical Activity and Early Life Stress on the Relation between Brain-Derived Neurotrophic Factor (BDNF) rs6265 Variants and Depressive Symptoms among Adolescents

Depression affects one in five persons at 18 years of age. Allele A of the brain-derived neurotrophic factor (BDNF) rs6265 is considered to be a risk factor for depression. Previous studies of the interaction between BDNF rs6265, early adversity, and/or physical activity have shown mixed results. In this study, we explored the relation between BDNF rs6265 polymorphism and childhood stress, as well as the moderating effect of physical activity in relation to depressive symptoms using binary logistic regressions and process models 1, 2 and 3 applied to data obtained at three times (waves 1, 2 and 3) from the Survey of Adolescent Life in Västmanland cohort study (SALVe). Results revealed that both childhood stress and physical activity had a moderation effect; physical activity in wave 1 with an R2 change = 0.006, p = 0.013, and the Johnson−Neyman regions of significance (RoS) below 1.259, p = 0.05 for 11.97%; childhood stress in wave 2 with the R2 change = 0.008, p = 0 002, and RoS below 1.561 with 26.71% and >4.515 with 18.20%; and a three-way interaction in wave 1 in genotype AA carriers. These results suggest that allele A is susceptible to physical activity (positive environment) and childhood stress (negative environment).

Psychological resources and flexibility predict resilient mental health trajectories during the French covid-19 lockdown

The implementation of lockdowns and the Covid-19 pandemic situation have negatively impacted mental health (anxiety, depression). However, little is known about individual differences in the longitudinal reactions to lockdown. We designed a longitudinal study (a) to identify the various trajectories of symptoms of depression and anxiety in the general population during and after lockdown; (b) to determine which positive psychological resources prevent individuals from falling into groups with the most severe trajectories; (c) to test the mediating role of psychological flexibility. We collected and analysed longitudinal data on a sample of French participants (N = 1399, M_age = 43.4; SD_age = 12; 87.8% women) during the end of the first lockdown. Participants were asked to report their psychological resources and (in)flexibility at baseline and symptoms of anxiety and depression at each measurment occasion (five weekly observations from 17 March to 11 May 2020, including baseline). Using growth mixture modelling, seven dynamic profiles of symptoms were identified: four for depression and three for anxiety. Resilience emerged as the most frequent trajectory. Wisdom, optimism, hope, self-efficacy and peaceful disengagement significantly prevented individuals from belonging to the symptomatic groups. Moreover, psychological flexibility emerged as a significant mediator of these effects. This study highlights the importance of cultivating protective factors and psychological flexibility to prevent mental health damage during potentially traumatic events (PTE) and to favour resilience trajectories.

Trajectories of depressive symptoms among community-dwelling Korean older adults: findings from the Korean longitudinal study of aging (2006-2016)

BACKGROUND

Depression among older adults is an important public health concern associated with increased risk of suicide and decreased physical, cognitive, and social functioning. This study identified trajectories of depressive symptoms and investigated predictive variables of group-based trajectory modeling among Korean community-dwelling older adults.

METHODS

Participants comprised 2016 community-dwelling Korean adults over 65 years. Data from the years 2006-2016 of the Korean Longitudinal Study of Aging, a nationally representative panel survey that has been conducted every two years since 2006, were used. We employed a group-based trajectory modeling analysis to identify depressive symptom trajectories. Multinomial logistic regression analysis was conducted to identify predictors of each class of depressive symptoms.

RESULTS

Five depressive symptom trajectory groups were identified: Group 1, "None" (28.9%); Group 2, "Slowly worsening" (24.3%); Group 3, "Rapidly worsening" (17.5%); Group 4 "Improving" (12.4%); and Group 5, "Persistently severe" (16.9%). Older adults followed five distinct depressive symptom trajectories over 10 years. Mini-Mental State Examination scores, number of chronic diseases, educational level, and social activity were predictors associated with increasing depressive symptoms.

CONCLUSIONS

This study showed that many older adults living in the community have depressive symptoms. To prevent and treat depression and aid successful mental health aging among older adults, the development of interventions should be tailored to target specific needs for each symptom trajectory. It is necessary to develop community-based interventions and strategies to identify and prevent depressive symptom trajectories among older adults.

Predicting non-response to multimodal day clinic treatment in severely impaired depressed patients: a machine learning approach

A considerable number of depressed patients do not respond to treatment. Accurate prediction of non-response to routine clinical care may help in treatment planning and improve results. A longitudinal sample of N = 239 depressed patients was assessed at admission to multi-modal day clinic treatment, after six weeks, and at discharge. First, patient’s treatment response was modelled by identifying longitudinal trajectories using the Hamilton Depression Rating Scale (HDRS-17). Then, individual items of the HDRS-17 at admission as well as individual patient characteristics were entered as predictors of response/non-response trajectories into the binary classification model (eXtremeGradient Boosting; XGBoost). The model was evaluated on a hold-out set and explained in human-interpretable form by SHapley Additive explanation (SHAP) values. The prediction model yielded a multi-class AUC = 0.80 in the hold-out set. The predictive power for the binary classification yielded an AUC = 0.83 (sensitivity = .80, specificity = .77). Most relevant predictors for non-response were insomnia symptoms, younger age, anxiety symptoms, depressed mood, being unemployed, suicidal ideation and somatic symptoms of depressive disorder. Non-responders to routine treatment for depression can be identified and screened for potential next-generation treatments. Such predictors may help personalize treatment and improve treatment response.

Childhood trauma and current depression among Chinese university students: a moderated mediation model of cognitive emotion regulation strategies and neuroticism

BACKGROUND

Childhood trauma (CT) is considered as a highly risk factor for depression. Although the pathway of CT to depression, especially the mediating or moderating effects of cognitive emotion regulation strategies (CERS) or neuroticism, have investigated by several studies, the results were inconsistent and there is a paucity of full models among these interactive factors. This study aims to examine the relationships among CT, adaptive / maladaptive CERS, neuroticism, and current depression symptoms in university students.

METHODS

We recruited 3009 freshman of 2019, aged averagely 18.00 (SD = 0.772) years, from universities in Hunan province in 2019. A moderated mediation model was built to examine the relationships among CT, CERS, neuroticism, and current depression using the SPSS PROCESS 3.5 macro. We conducted bootstrapping of regression estimates with 5000 samples and 95% confidence interval.

RESULTS

Results revealed that the significant mediating effects of adaptive CERS (β = 0.012; 95% CI: 0.006 to 0.018) and maladaptive CERS (β = 0.028; 95% CI: 0.016 to 0.040) between CT and depression were observed, accounting for 5.69% and 13.52% of the total effect respectively. Then, moderated mediation analyses results showed that neuroticism simultaneously moderated the direct effect of CT on current depression (β = 0.035; 95% CI: 0.001 to 0.009), and the indirect effects of CT on current depression through adaptive CERS (adaptive CERS - current depression: β = - 0.034; 95% CI: - 0.007 to - 0.001) and maladaptive CERS (maladaptive CERS - current depression: β = 0.157; 95% CI: 0.017 to 0.025). However, the moderating effects of neuroticism in the indirect paths from CT to adaptive CERS (β = 0.037; 95% CI: 0.000 to 0.014) and maladaptive CERS (β = - 0.001; 95% CI: - 0.006 to 0.005) were not significant.

CONCLUSIONS

This study provides powerful evidences through a large university students sample for the mediating role of adaptive / maladaptive CERS and the moderating role of neuroticism between CT and current depression. This manifests that cognitive emotion regulation may be a vital factor for people who suffered from CT and current depression. Furthermore, the influence of neuroticism in this process cannot be ignored.

Development and Validation of a Brief Form of the Childhood Adversities Questionnaire Among a Population of Mood Disorders

Childhood adversities have significantly negative consequences on physical and mental health. The Childhood Experience of Care and Abuse Questionnaire, Version 3 (CECA.Q3) interview, as an extended version of the CECA.Q, is widely used in the assessment of childhood adversities. Although its reliability and validity have been demonstrated, the application of CECA.Q3 is limited due to its intensive and lengthy interview. This article aimed to develop and validate a brief form of the CECA.Q3 (CECA.Q3-BF) among a population of mood disorders. Data analyzed were from a clinical sample of 210 patients with mood disorders. Data were randomly split into training and testing datasets. The training data set was used for scale reduction by applying principal component factor analysis, while the testing one was used for cross-validation to examine whether the CECA.Q3-BF could have a good yield of accuracy. The optimal cutoff points of the CECA.Q3 were also tested. Overall, four out of eight subscales had items reduction without compromising their accuracy of measurements for childhood adversities. They are Antipathy (reduced by four items), Neglect (reduced by five items), Psychological Abuse (reduced by 15 items), and Role Reversal (reduced by 11 items). The CECA.Q3-BF removed 35 items (35/100, 35%) from the full CECA.Q3. The accuracy of CECA.Q3-BF was validated in the testing dataset. The CECA.Q3-BF offers a brief but good accuracy of measure for childhood adversities. Future studies are warranted to further validate this brief form. The CECA.Q3-BF is expected to improve the application of CECA.Q3 in clinical and epidemiological surveys, as it significantly reduces the length of the interview and therefore has better compliance.

Transdiagnostic and functional predictors of depression severity and trajectory in the Penn state psychiatry clinical assessment and rating evaluation system (PCARES) registry

BACKGROUND

Timely, accurate diagnosis and subsequent identification of risk factors for depression that is difficult-to-treat can aid in decreasing the burden of depressive illness and reducing probability of future disability. We aimed to identify sociodemographic, clinical, and functional factors that predict depression severity over one year in a real-world, naturalistic, transdiagnostic clinical sample. A subset sample with moderate depression was examined to determine the magnitude of improvement.

METHODS

The Penn State Psychiatry Clinical Assessment and Rating System (PCARES) Registry houses data from systematically-structured patient-reported outcomes and clinical data from an Electronic Medical Record (EMR) gathered during routine clinical care of patients seeking mental health care at a mid-Atlantic clinic. Self-report symptom and functional measures were obtained, and sociodemographic features and clinical diagnoses were extracted from the EMR from 1,766 patients between 2/6/2016 to 9/30/2019. The Patient Health Questionnaire 9 (PHQ-9) depression scale was obtained at each visit. Using a discrete mixture clustering model, the study population was divided into five longitudinal trajectory groups, termed depression severity groups, based on intra-individual PHQ-9 score trajectories over one year. Multinomial logistic regression models were estimated to evaluate associations between characteristics and the likelihood of depression severity group membership. To determine the magnitude of improvement, predictors of the slope of the PHQ-9 trajectory were examined for patients with moderate depression.

RESULTS

The strongest predictors of high depression severity over one year were poor functioning, high transdiagnostic DSM-5 Level 1 crosscutting symptom score, diagnosis of Post-Traumatic Stress Disorder (PTSD), public/self-pay insurance, female gender, and non-White race. Among the subset of patients with moderate depression, strong predictors of improvement were commercial insurance and exposure to trauma; the strongest predictors of worsening were high functional impairment, high transdiagnostic Level 1 symptom score, diagnosis of PTSD, diagnosis of bipolar disorder, and marital status of single or formerly married; depression-specific symptom measures were not predictive.

LIMITATIONS

Limitations include inferring education and income status from zip code level-data, the non-random missingness of data, and the use of diagnoses collected from the electronic medical record.

CONCLUSION

Functional impairment, transdiagnostic measures of symptom burden, and insurance status are strong predictors of depression severity and poor outcome.

The Association of Childhood Maltreatment, Sex, and Hair Cortisol Concentrations With Trajectories of Depressive and Anxious Symptoms Among Adult Psychiatric Inpatients

OBJECTIVE

Depression and anxiety symptoms are commonly observed among clinical populations, especially among women and maltreated individuals. Few investigations have, however, assessed the existence of distinct symptoms trajectories among clinical populations and how these relate to childhood maltreatment, sex differences, and stress physiology indexed by hair cortisol concentrations (HCCs). The current study a) identified distinct depression and anxious trajectories in a sample of psychiatric inpatients followed up prospectively from their admission to a psychiatric emergency service, and b) examined whether HCC, childhood maltreatment, and sex independently and jointly predict these trajectories.

METHODS

Adult inpatients (n = 402; 55% women) were recruited upon admission to psychiatric emergency service (T1) during which HCC (reflecting cortisol secretion for the last 3 months), childhood maltreatment, and depression and anxiety symptoms were assessed. Symptoms were reevaluated when patients were discharged from the hospital (T2), admitted to outpatient clinics (T3), and 12 months later or at the end of outpatient treatment (T4).

RESULTS

Three trajectories were identified for depression and anxiety symptoms. Among men, higher HCC predicted higher odds of evincing chronic depressive symptoms compared with a low stable trajectory (odds ratio [OR] = 3.46, 95% confidence interval [CI] = 1.43-8.40). Greater childhood maltreatment among men predicted higher chances of exhibiting chronic anxious symptoms than the low stable (OR = 1.47, 95% CI = 1.07-2.02) and the high decreasing trajectories (OR = 0.70, 95% CI = 0.51-0.95). Opposite findings were noted for women.

CONCLUSIONS

Childhood maltreatment and HCC should be further investigated as predictors of anxious and depressive trajectories, during which sex-specific associations ought to be considered.

Sleep disorders mediate the link between childhood trauma and depression severity in children and adolescents with depression

BACKGROUND

Childhood trauma is closely related to the onset of depression and more severe depressive symptoms; however, the specific mechanisms are unclear. We aimed to examine the relationship between childhood trauma and sleep disorders in children and adolescents with depression and to explore further the role of sleep disorders in the relationship between childhood trauma and depression severity.

METHODS

A total of 285 children and adolescents with depression completed all scale assessments, including the Childhood Trauma Questionnaire, Self-Reported Insomnia Severity Index and Epworth Sleepiness Scale, and the Center for Epidemiologic Studies Depression Scale. A simple mediation model was used as a theoretical model to examine whether sleep disorders could mediate the relationship between childhood trauma and depression severity.

RESULTS

Among children and adolescents with depression, childhood trauma is about 78.9%. Compared with patients without childhood trauma, patients with childhood trauma had a higher incidence of sleep disorders (Z = 17.59, P < 0.001), which were characterized by insomnia (Z = 14.45, P < 0.001), not hypersomnia (Z = 2.77, P = 0.096). Different childhood trauma subtypes significantly affected sleep disorders and insomnia (all P < 0.05). Insomnia partially mediated the relationship between childhood trauma and depression severity, and the mediating effect accounted for 35.90%.

CONCLUSION

This study found a high rate of concurrent childhood trauma and insomnia among children and adolescents with depression. Insomnia, as a mediator between childhood trauma and depression severity, partially mediates the relationship.

Patterns of adverse childhood experiences and depressive symptom trajectories in young adults: A longitudinal study of college students in China

BACKGROUND

Adverse childhood experiences (ACEs) tend to cluster together in daily life, and most studies focus on the level of depression at certain points, but the dynamic process of depression is often neglected. Thus, research is urgently needed to explore the relationship between ACEs pattern and trajectory of depressive symptom levels at multiple time points in order to provides early targeted interventions to those who are most at risk.

OBJECTIVE

We aimed to explore patterns of ACEs, including types and timing, associated with depression trajectories in college students.

METHODS

A school-based health survey was used to collect data as part of a longitudinal study in two medical college in Anhui province, China. Questionnaires were issued to 3,662 participants aged 17-22 and recorded details of ACEs (types and timing) and depression. Latent class analysis (LCA) was used to identify "patterns" of ACEs type and timing. Depressive symptom trajectories employed latent class growth analysis (LCGA). Multiple logistic regressions were employed to evaluate the relationships between ACEs patterns and depressive symptom trajectories.

RESULTS

We identified five ACEs patterns: "High neglect/emotional abuse/community violence," "High neglect/emotional abuse," "High neglect/family dysfunction," "High neglect," "Low ACEs." We traced three depression trajectories: "High depressive symptom" "Moderate depressive symptom," "Low depressive symptom." "High neglect/emotional abuse/community violence," "High neglect/emotional abuse" and "High neglect/family dysfunction" demonstrated a high risk for "High depressive symptom" and "Moderate depressive symptom." "High neglect" showed a high risk for "Moderate depressive symptom" but not for "High depressive symptom" (P < 0.05).

CONCLUSIONS

The findings address the need for a comprehensive consideration of exposure to childhood adversity associated with the risk of depression in young adults through identifying more problematic ACEs patterns amongst exposed children.

The 9-year clinical course of depressive and anxiety disorders: New NESDA findings

BACKGROUND

In longitudinal research, switching between diagnoses should be considered when examining patients with depression and anxiety. We investigated course trajectories of affective disorders over a nine-year period, comparing a categorical approach using diagnoses to a dimensional approach using symptom severity.

METHOD

Patients with a current depressive and/or anxiety disorder at baseline (N = 1701) were selected from the Netherlands Study of Depression and Anxiety (NESDA). Using psychiatric diagnoses, we described 'consistently recovered,' 'intermittently recovered,' 'intermittently recurrent', and 'consistently chronic' at two-, four-, six-, and nine-year follow-up. Additionally, latent class growth analysis (LCGA) using depressive, anxiety, fear, and worry symptom severity scores was used to identify distinct classes.

RESULTS

Considering the categorical approach, 8.5% were chronic, 32.9% were intermittently recurrent, 37.6% were intermittently recovered, and 21.0% remained consistently recovered from any affective disorder at nine-year follow-up. In the dimensional approach, 66.6% were chronic, 25.9% showed partial recovery, and 7.6% had recovered.

LIMITATIONS

30.6% of patients were lost to follow-up. Diagnoses were rated by the interviewer and questionnaires were completed by the participant.

CONCLUSIONS

Using diagnoses alone as discrete categories to describe clinical course fails to fully capture the persistence of affective symptoms that were observed when using a dimensional approach. The enduring, fluctuating presence of subthreshold affective symptoms likely predisposes patients to frequent relapse. The commonness of subthreshold symptoms and their adverse impact on long-term prognoses deserve continuous clinical attention in mental health care as well further research.

Characterisation of age and polarity at onset in bipolar disorder

BACKGROUND

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

AIMS

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

METHOD

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

RESULTS

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = -0.34 years, s.e. = 0.08), major depression (β = -0.34 years, s.e. = 0.08), schizophrenia (β = -0.39 years, s.e. = 0.08), and educational attainment (β = -0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

CONCLUSIONS

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Trajectories of symptoms of anxiety and depression among people on sick leave with mood or anxiety disorders: Secondary analysis from a randomized controlled trial

BACKGROUND

Depression and anxiety are heterogenous disorders often combined into one entity in studies. Few studies have compared trajectories of depression and anxiety among clinically ill. We aimed to identify specific trajectories of depression, and anxiety and predictors of trajectory membership.

METHODS

Latent growth mixture modelling was carried out on data from the IPS-MA trial (n = 261), a supported employment intervention for people with mood or anxiety, to identify trajectories of depression and anxiety. Logistic regression was used to estimate predictors for trajectory membership. Associations between trajectory class and remission of comorbid depression or anxiety and return to work were also tested.

RESULTS

We identified three trajectories of depression and anxiety symptoms respectively; moderate-decreasing (60%), moderate-stable (26%), and low-stable (14%) depression and mild-decreasing (59%), moderate-decreasing (33%), and moderate-stable (8%) anxiety. The depression model showed low precision in class separation (entropy 0.66), hence, predictors of class membership were not estimated. For anxiety, lower age and higher levels of depressive symptoms were associated with a less desirable trajectory. Remission of comorbid depressive symptoms after two years differed significantly between classes (p < 0.000). Fewer had returned to work in the two moderate classes compared to the mild-decreasing anxiety class.

LIMITATIONS

Depression model not reliable. Only 80% of participants from original study included. Not able to distinguish between anxiety disorders.

CONCLUSION

Trajectories of anxiety confirm that, even after two years, a rather large proportion in the moderate-stable class had symptoms of moderate anxiety, moderate comorbid depressive symptoms, and less probability of having returned to work.

TRIAL REGISTRATION

ClinicalTrials.govNCT01721824.

Trajectories of suicidal ideation after first-episode psychosis: a growth mixture modeling approach

OBJECTIVE

The period immediately after the onset of first-episode psychosis (FEP) may present with high risk for suicidal ideation (SI) and attempts, although this risk may differ among patients. Thus, we aimed to identify trajectories of SI in a 2-years follow-up FEP cohort and to assess baseline predictors and clinical/functional evolution for each trajectory of SI.

METHODS

We included 334 FEP participants with data on SI. Growth mixture modeling was used to identify trajectories of SI. Putative sociodemographic, clinical, and cognitive predictors of the distinct trajectories were examined using multinomial logistic regression.

RESULTS

We identified three distinct trajectories: Non-SI trajectory (85.53% sample), Improving SI trajectory (9.58%), and Worsening SI trajectory (6.89%). Multinomial logistic regression model revealed that greater baseline pessimistic thoughts, anhedonia, and worse perceived family environment were associated with higher baseline SI followed by an Improving trajectory. Older age, longer duration of untreated psychosis, and reduced sleep predicted Worsening SI trajectory. Regarding clinical/functional evolution, individuals within the Improving SI trajectory displayed moderate depression at baseline which ameliorated during the study period, while the Worsening SI subgroup exhibited persistent mild depressive symptoms and greater functional impairment at follow-up assessments.

CONCLUSION

Our findings delineated three distinct trajectories of SI among participants with FEP, one experiencing no SI, another in which SI might depend on acute depressive symptomatology, and a last subset where SI might be associated with mild but persistent clinical and functional impairments. These data provide insights for the early identification and tailored treatment of suicide in this at-risk population.

Latent Class Analysis of Adolescent Psychosocial Functioning and Course of Major Depression

There are few studies on the predictors of long-term course of major depressive disorder (MDD) with an onset in childhood and adolescence. Studies have relied on variable-centered methods, utilizing psychosocial and clinical characteristics to predict depression outcomes. However, fewer studies have used person-centered approaches that rely on profiles of functioning to predict course and outcomes of depression. This study examined the long-term course and outcome of early onset depression as a function of profiles of psychosocial and clinical characteristics in adolescence. Participants from the Oregon Adolescent Depression Project with a history of MDD by study entry (M_age = 16.29 years) and who had follow-up assessments at age 30 were included (n = 215). Psychosocial and clinical constructs, including domains of internalizing problems, externalizing problems, correlates of internalizing problems, adolescent stress, and social support, were assessed in adolescence. Latent profile analyses found a 3-class solution with Low Negative Cognitive Style (LNCS; 27.9%); Internalizing and High Negative Cognitive Style (INT/HNCS; 53.9%); and Internalizing and High Negative Cognitive Style plus Poor Interpersonal Functioning and High Stress (INT/HNCS+ ; 18.1%). Overall, classes differed in depression morbidity, such that the INT/HNCS+ class had the greatest depression morbidity across follow-up assessments. Social adjustment differed between all classes, with the INT/HNCS+ class showing the worst functioning, the LNCS class showing the best functioning, and the INT/HNCS class falling in the middle. Patterns of clinical and psychosocial functioning were differentially associated with long-term depression and social adjustment among youth with depression.

Fractures in the framework: limitations of classification systems in psychiatry

This article examines the limitations of existing classification systems from the historical, cultural, political, and legal perspectives. It covers the evolution of classification systems with particular emphasis on the DSM and ICD systems. While pointing out the inherent Western bias in these systems, it highlights the potential of misuse of these systems to subserve other agendas. It raises concerns about the reliability, validity, comorbidity, and heterogeneity within diagnostic categories of contemporary classification systems. Finally, it postulates future directions in alternative methods of diagnosis and classification factoring in advances in artificial intelligence, machine learning, genetic testing, and brain imaging. In conclusion, it emphasizes the need to go beyond the limitations inherent in classifications systems to provide more relevant diagnoses and effective treatments.


Approaches to Defining Common and Dissociable Neurobiological Deficits Associated With Psychopathology in Youth

Psychiatric disorders show high rates of comorbidity and nonspecificity of presenting clinical symptoms, while demonstrating substantial heterogeneity within diagnostic categories. Notably, many of these psychiatric disorders first manifest in youth. We review progress and next steps in efforts to parse heterogeneity in psychiatric symptoms in youths by identifying abnormalities within neural circuits. To address this fundamental challenge in psychiatry, a number of methods have been proposed. We provide an overview of these methods, broadly organized into dimensional versus categorical approaches and single-view versus multiview approaches. Dimensional approaches including factor analysis and canonical correlation analysis aim to capture dimensional associations between psychopathology and brain measures across a continuous spectrum from health to disease. In contrast, categorical approaches, such as clustering and community detection, aim to identify subtypes of individuals within a class of symptoms or brain features. We highlight several studies that apply these methods to samples of youths and discuss issues to consider when using these approaches. Finally, we end by highlighting avenues for future research.

Child maltreatment and depression: A meta-analysis of studies using the Childhood Trauma Questionnaire

BACKGROUND

Researchers have documented that child maltreatment is associated with adverse long-term consequences for mental health, including increased risk for depression. Attempts to conduct meta-analyses of the association between different forms of child maltreatment and depressive symptomatology in adulthood, however, have been limited by the wide range of definitions of child maltreatment in the literature.

OBJECTIVE

We sought to meta-analyze a single, widely-used dimensional measure of child maltreatment, the Childhood Trauma Questionnaire, with respect to depression diagnosis and symptom scores.

PARTICIPANTS AND SETTING

192 unique samples consisting of 68,830 individuals.

METHODS

We explored the association between total scores and scores from specific forms of child maltreatment (i.e., emotional abuse, physical abuse, sexual abuse, emotional neglect, and physical neglect) and depression using a random-effects meta-analysis.

RESULTS

We found that higher child maltreatment scores were associated with a diagnosis of depression (g = 1.07; 95 % CI, 0.95-1.19) and with higher depression symptom scores (Z = .35; 95 % CI, .32-.38). Moreover, although each type of child maltreatment was positively associated with depression diagnosis and scores, there was variability in the size of the effects, with emotional abuse and emotional neglect demonstrating the strongest associations.

CONCLUSIONS

These analyses provide important evidence of the link between child maltreatment and depression, and highlight the particularly larger association with emotional maltreatment in childhood.

Predicting individual clinical trajectories of depression with generative embedding

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Patients with major depressive disorder (MDD) show variable clinical trajectories.

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Generative embedding (GE) is used to predict clinical trajectories in MDD patients.

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GE classifies patients with chronic depression vs. fast remission with 79% accuracy.

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GE provides mechanistic interpretability and outperforms conventional measures.

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Proof-of-concept that illustrates the potential of GE for clinical prediction.

Patients with major depressive disorder (MDD) show heterogeneous treatment response and highly variable clinical trajectories: while some patients experience swift recovery, others show relapsing-remitting or chronic courses. Predicting individual clinical trajectories at an early stage is a key challenge for psychiatry and might facilitate individually tailored interventions. So far, however, reliable predictors at the single-patient level are absent. Here, we evaluated the utility of a machine learning strategy – generative embedding (GE) – which combines interpretable generative models with discriminative classifiers. Specifically, we used functional magnetic resonance imaging (fMRI) data of emotional face perception in 85 MDD patients from the NEtherlands Study of Depression and Anxiety (NESDA) who had been followed up over two years and classified into three subgroups with distinct clinical trajectories. Combining a generative model of effective (directed) connectivity with support vector machines (SVMs), we could predict whether a given patient would experience chronic depression vs. fast remission with a balanced accuracy of 79%. Gradual improvement vs. fast remission could still be predicted above-chance, but less convincingly, with a balanced accuracy of 61%. Generative embedding outperformed classification based on conventional (descriptive) features, such as functional connectivity or local activation estimates, which were obtained from the same data and did not allow for above-chance classification accuracy. Furthermore, predictive performance of GE could be assigned to a specific network property: the trial-by-trial modulation of connections by emotional content. Given the limited sample size of our study, the present results are preliminary but may serve as proof-of-concept, illustrating the potential of GE for obtaining clinical predictions that are interpretable in terms of network mechanisms. Our findings suggest that abnormal dynamic changes of connections involved in emotional face processing might be associated with higher risk of developing a less favorable clinical course.

Childhood Adversity Impairs Theory of Mind Abilities in Adult Patients With Major Depressive Disorder

Background: Patients with major depressive disorder (MDD) have various theory of mind (ToM) impairments which often predict a poor outcome. However, findings on ToM deficits in MDD are inconsistent and suggest the role of moderating factors. Child abuse and neglect are strong predictors of adult MDD and are often associated with a poorer clinical course trajectory. Objective: Because early-life adversities result in various forms of ToM deficits in clinical and nonclinical samples, our aim was to investigate if they are significant confounding factors of ToM impairments in MDD. Methods: We investigated 60 mildly or moderately depressed, nonpsychotic adult patients with MDD during an acute episode, and 32 matched healthy controls. The mental state decoding subdomain of ToM was examined with the Reading the Mind in the Eyes Test (RMET). Childhood adversities were assessed with the childhood trauma questionnaire (CTQ) and the early trauma inventory. Results: There was no difference between the control and MDD groups in RMET performance. However, when we divided the MDD group into two subgroups, one (N = 30) with high and the other (N = 30) with low levels of childhood adversities, a significant difference emerged between the controls and the highly maltreated MDD subgroup in RMET performance. A series of 3 (group) × 3 (valence) mixed-model analyses of covariance (ANCOVAs) revealed that childhood emotional and physical neglect had a significant negative impact on the response accuracy in RMET in general, whereas emotional abuse specifically interfered with the accuracy in the positive and negative valences if it co-occurred with early-life neglect. To test the dose-response relationship between the number of childhood adversities and RMET capacities, we subjected RMET data of the MDD group to multiple hierarchical regressions: the number of childhood adversities was a significant predictor of RMET total scores and RMET scores in the negative valence after controlling for age, sex, years of education, and the severity of current depression. Conclusion: Childhood adversities impair ToM capacities in MDD. Exposure to early-life emotional abuse and neglect have a negative impact on the performance in the emotional valences of RMET. Multiple early-life adversities have a dose-dependent association with mental state decoding deficits.

Trajectories of major depression in middle-aged and older adults: A population-based study

OBJECTIVES

This study aimed to examine depression trajectories and correlates in a nationally representative sample of middle-aged and older adults in the United States.

METHODS

The study sample consisted of 15 661 participants aged over 50 years from the US Health and Retirement Study. Major depression was assessed using the Composite International Diagnostic Interview (CIDI-SF). Depression trajectories were identified using a group-based trajectory modeling enhanced to account for nonrandom attrition. Multinomial logistic regression was conducted to investigate predictors of depression trajectories.

RESULTS

Four depression trajectory groups were identified: "never" (85.8%), "increasing" (6.3%), "decreasing" (3.2%), and "persistently moderate/high" (4.7%). Baseline depressive symptom severity was a strong predictor of depression trajectories. Older age, male sex, and non-Hispanic African American race were associated with a lower risk of the three trajectories with small to high depression burden, whereas chronic disease count was associated with a higher risk of these trajectories. The risk of being on the increasing trajectory increased with mobility difficulties. Difficulties in household activities predicted membership in the persistently moderate/high group.

CONCLUSIONS

A small but nonignorable proportion of middle-aged and older adults have chronic major depression. Initial symptom severity and chronic disease burden are consistent risk factors for unfavorable depression trajectories and potential targets for screening and intervention.

Progress in psychoradiology, the clinical application of psychiatric neuroimaging

Psychoradiology is an emerging field that applies radiological imaging technologies to psychiatric conditions. In the past three decades, brain imaging techniques have rapidly advanced understanding of illness and treatment effects in psychiatry. Based on these advances, radiologists have become increasingly interested in applying these advances for differential diagnosis and individualized patient care selection for common psychiatric illnesses. This shift from research to clinical practice represents the beginning evolution of psychoradiology. In this review, we provide a summary of recent progress relevant to this field based on their clinical functions, namely the (1) classification and subtyping; (2) prediction and monitoring of treatment outcomes; and (3) treatment selection. In addition, we provide guidelines for the practice of psychoradiology in clinical settings and suggestions for future research to validate broader clinical applications. Given the high prevalence of psychiatric disorders and the importance of increased participation of radiologists in this field, a guide regarding advances in this field and a description of relevant clinical work flow patterns help radiologists contribute to this fast-evolving field.

Lower versus higher frequency of sessions in starting outpatient mental health care and the risk of a chronic course; a naturalistic cohort study

BACKGROUND

An adequate frequency of treatment might be a prerequisite for a favorable outcome. Unfortunately, there is a diversity of factors that interfere with an adequate frequency of sessions. This occurs especially in the first phase of treatment, while the first phase seems vital for the rest of treatment. The aim of this naturalistic study was to explore the impact of the initial frequency of treatment sessions on treatment outcome in a diverse mental health care population.

METHODS

Anonymized data were analyzed from 2,634 patients allocated for anxiety disorders, depressive disorders, and personality disorders to outpatient treatment programs in a large general mental health care facility. Patients' treatment outcome was routinely monitored with the Outcome Questionnaire-45 (OQ-45.2), every 12 weeks. Frequency of sessions was assessed for the first three months of treatment. Using Cox-proportional-hazard models, we explored the associations between initial frequency and improvement (reliable significant change) and recovery (reliable and clinically significant change).

RESULTS

Improvement and recovery were associated with symptom severity and functional impairment at start of treatment, the year the treatment started, number of measurements, the treatment program (anxiety disorders, depressive disorders, and personality disorders) and receiving group therapy other than psychotherapy. In all diagnostic groups, both improvement and recovery were associated with a higher frequency of sessions during the first three months of treatment. For improvement, this effect diminished after three years in treatment; however, for recovery this association was sustained.

CONCLUSIONS

In addition to severity at start of treatment and other predictors of outcome, a low frequency of initial treatment sessions might lead to a less favorable outcome and a more chronic course of the mental disorder. This association seems not to be limited to a specific diagnostic group, but was found in a large group of patients with common mental disorders (depression and anxiety disorders) and patients with a personality disorder. Despite organizational obstacles, more effort should be made to start treatment quickly by an effective frequency of session.

Extraversion modulates cortisol responses to acute social stress in chronic major depression

BACKGROUND

Chronic Major Depressive Disorder (CMDD) is a common, disabling illness that is often complicated by high reactivity to social stress. To further elucidate the nature of this reactivity, the current study evaluated whether the personality dimensions of neuroticism and extraversion influenced cortisol responses to a social challenge in CMDD patients vs. controls.

METHODS

Fifty participants with CMDD and 58 healthy controls completed the Trier Social Stress Test (TSST) using a standard protocol. Neuroticism and extraversion were measured using the Revised NEO Personality Inventory. Hierarchical linear regressions assessed associations between independent variables neuroticism and extraversion and dependent variable cortisol area-under-the-curve increase (AUCi) in response to the TSST in the two study groups.

RESULTS

The extraversion-by-group interaction was a significant predictor of cortisol AUCi, while no significant findings related to neuroticism were found. Simple slopes analysis revealed a significant negative association between extraversion and AUCi in the CMDD group, but not in healthy controls. Post-hoc analysis of the raw cortisol data over time found that CMDD participants with higher extraversion scores had significantly higher pre-challenge cortisol levels than did other study participants, however this did not explain or confound the AUCi results.

CONCLUSIONS

In participants with CMDD but not in controls, higher levels of extraversion were associated with higher pre-challenge cortisol levels and decreased cortisol reactivity during the TSST, however these two findings were statistically independent. These findings underline the importance of considering personality factors when studying stress biology in CMDD patients. Extraversion may prove to be an important intermediate target for both research and clinical work in this complex, heterogenous and often treatment-resistant population.

Distinct Profiles on Subjective and Objective Adherence Measures in Patients Prescribed Antidepressants

Objective

A recurrent observation is that associations between self-reported and objective medication adherence measures are often weak to moderate. Our aim was therefore to identify patients with different profiles on self-reported and objective adherence measures.

Study Design and Setting

This was an observational study of 221 community pharmacy patients who were dispensed antidepressants. Adherence profiles were estimated with Latent Profile Analysis (LPA) using data on self-reported adherence (Medication Adherence Rating Scale) complemented with data on medication beliefs (perceived necessity and concerns measured with the Beliefs about Medicines Questionnaire) and data from objective adherence measures (electronic monitoring of medication taking and the Medication Possession Ratio calculated from pharmacy dispensing data).

Results

‘Goodness-of-fit’ statistics indicated the presence of three classes: “concordantly high adherent” (83%, high adherence on all measures), “concordantly suboptimal adherent” (11%, low adherence on all measures), and “discordant” (6%, high self-reported adherence but lower adherence on objective measures).

Conclusion

Most patients had concordant outcomes on self-reported and objective measures of adherence. A small discordant class had high self-reported but low objective adherence. LPA will enable sensitivity analyses in future studies, for example excluding patients from the discordant class.

Predicting trajectories of recovery in prostate cancer patients undergone Robot-Assisted Radical Prostatectomy (RARP)

OBJECTIVE

To identify trends of patients' urinary and sexual dysfunctions from a clinical and psychological perspective and understand whether sociodemographic and medical predictors could differentiate among patients following different one-year longitudinal trajectories.

METHODS

An Italian sample of 478 prostate cancer patients undergone Robot-Assisted Radical Prostatectomy completed the EPIC-26 survey between July 2015 and July 2016 at the pre-hospitalization (T0), 45 days (T1) and 3 (T2), 6 (T3), 9 (T4), and 12 months (T5) after surgery. Sociodemographic and clinical characteristics (age, BMI, diabetes, nerve-sparing procedure) were also collected. Latent Class Growth Analysis was conducted separately for sexual dysfunction and urinary incontinence EPIC-26 subscales. The association between membership in the two longitudinal trajectories of urinary and sexual dysfunctions was assessed by considering Chi-square test and its related contingency table.

RESULTS

People who have a high level of urinary incontinence at T1 are likely to have a worse recovery. Age, BMI and pre-surgical continence may affect the level of incontinence at T1 and the recovery trajectories. Patients with low and moderate sexual problems at T1 can face a moderate linear recovery, while people with high level of impotence immediately after surgery may take a longer period to solve sexual dysfunctions. Age and the pre-surgical sexual condition may impact the recovery. Finally, a great proportion of patients reported both steady problems in sexual function and constant high levels of urinary incontinence over time.

CONCLUSIONS

This study highlights different categories of patients at risk who may be important to know in order to develop personalized medical pathways and predictive models in a value-based healthcare.

Characterizing Developmental Trajectories and the Role of Neuropsychiatric Genetic Risk Variants in Early-Onset Depression

Importance

Depression often first manifests in adolescence. Thereafter, individual trajectories vary substantially, but it is not known what shapes depression trajectories in youth. Adult studies suggest that genetic risk for schizophrenia, a psychiatric disorder with a neurodevelopmental component, may contribute to an earlier onset of depression.

Objective

To test the hypothesis that there are distinct trajectories of depressive symptoms and that genetic liability for neurodevelopmental psychiatric disorders (eg, schizophrenia, attention deficit/hyperactivity disorder [ADHD]), as well as for major depressive disorder (MDD), contribute to early-onset depression.

Design, Setting, and Participants

The Avon Longitudinal Study of Parents and Children is an ongoing, prospective, longitudinal, population-based cohort that has been collecting data since September 6, 1990, including data on 7543 adolescents with depressive symptoms at multiple time points. The present study was conducted between November 10, 2017, and August 14, 2018.

Main Outcomes and Measures

Trajectories based on self-reported depressive symptoms dichotomized by the clinical cutpoint; MDD, schizophrenia, and ADHD polygenic risk score (PRS) were predictors.

Results

In 7543 adolescents with depression data on more than 1 assessment point between a mean (SD) age of 10.64 (0.25) years and 18.65 (0.49) years (3568 [47.3%] male; 3975 [52.7%] female), 3 trajectory classes were identified: persistently low (73.7%), later-adolescence onset (17.3%), and early-adolescence onset (9.0%). The later-adolescence-onset class was associated with MDD genetic risk only (MDD PRS: odds ratio [OR], 1.27; 95% CI, 1.09-1.48; P = .003). The early-adolescence-onset class was also associated with MDD genetic risk (MDD PRS: OR, 1.24; 95% CI, 1.06-1.46; P = .007) but additionally with genetic risk for neurodevelopmental disorders (schizophrenia PRS: OR, 1.22; 95% CI, 1.04-1.43; P = .01; ADHD PRS: OR, 1.32; 95% CI, 1.13-1.54; P < .001) and childhood ADHD (χ21 = 6.837; P = .009) and neurodevelopmental traits (pragmatic language difficulties: OR, 1.31; P = .004; social communication difficulties: OR, 0.68; P < .001).

Conclusions and Relevance

The findings of this study appear to demonstrate evidence of distinct depressive trajectories, primarily distinguished by age at onset. The more typical depression trajectory with onset of clinically significant symptoms at age 16 years was associated with MDD genetic risk. The less-common depression trajectory, with a very early onset, was particularly associated with ADHD and schizophrenia genetic risk and, phenotypically, with childhood ADHD and neurodevelopmental traits. Findings are consistent with emerging evidence for a neurodevelopmental component in some cases of depression and suggest that the presence of this component may be more likely when the onset of depression is very early.

Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach

Many variables have been linked to different course trajectories of depression. These findings, however, are based on group comparisons with unknown translational value. This study evaluated the prognostic value of a wide range of clinical, psychological, and biological characteristics for predicting the course of depression and aimed to identify the best set of predictors. Eight hundred four unipolar depressed patients (major depressive disorder or dysthymia) patients were assessed on a set involving 81 demographic, clinical, psychological, and biological measures and were clinically followed-up for 2 years. Subjects were grouped according to (i) the presence of a depression diagnosis at 2-year follow-up (yes n = 397, no n = 407), and (ii) three disease course trajectory groups (rapid remission, n = 356, gradual improvement n = 273, and chronic n = 175) identified by a latent class growth analysis. A penalized logistic regression, followed by tight control over type I error, was used to predict depression course and to evaluate the prognostic value of individual variables. Based on the inventory of depressive symptomatology (IDS), we could predict a rapid remission course of depression with an AUROC of 0.69 and 62% accuracy, and the presence of an MDD diagnosis at follow-up with an AUROC of 0.66 and 66% accuracy. Other clinical, psychological, or biological variables did not significantly improve the prediction. Among the large set of variables considered, only the IDS provided predictive value for course prediction on an individual level, although this analysis represents only one possible methodological approach. However, accuracy of course prediction was moderate at best and further improvement is required for these findings to be clinically useful.

Classes of depression symptom trajectories in patients with major depression receiving a collaborative care intervention

PURPOSE

Collaborative care is effective in improving symptoms of patients with depression. The aims of this study were to characterize symptom trajectories in patients with major depression during one year of collaborative care and to explore associations between baseline characteristics and symptom trajectories.

METHODS

We conducted a cluster-randomized controlled trial in primary care. The collaborative care intervention comprised case management and behavioral activation. We used the Patient Health Questionnaire-9 (PHQ-9) to assess symptom severity as the primary outcome. Statistical analyses comprised latent growth mixture modeling and a hierarchical binary logistic regression model.

RESULTS

We included 74 practices and 626 patients (310 intervention and 316 control recipients) at baseline. Based on a minimum of 12 measurement points for each intervention recipient, we identified two latent trajectories, which we labeled 'fast improvers' (60.5%) and 'slow improvers' (39.5%). At all measurements after baseline, 'fast improvers' presented higher PHQ mean values than 'slow improvers'. At baseline, 'fast improvers' presented fewer physical conditions, higher health-related quality of life, and had made fewer suicide attempts in their history.

CONCLUSIONS

A notable proportion of 39.5% of patients improved only 'slowly' and probably needed more intense treatment. The third follow-up in month two could well be a sensible time to adjust treatment to support 'slow improvers'.

A Six-Year Prospective Study of the Prognosis and Predictors in Patients With Late-Life Depression

OBJECTIVES

To examine the six-year prognosis of patients with late-life depression and to identify prognostic factors of an unfavorable course.

DESIGN AND SETTING

The Netherlands Study of Depression in Older Persons (NESDO) is a multisite naturalistic prospective cohort study with six-year follow-up.

PARTICIPANTS

Three hundred seventy-eight clinically depressed patients (according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition Text Revision criteria) and 132 nondepressed comparisons were included at baseline between 2007 and 2010.

MEASUREMENTS

Depression was measured by the Inventory of Depressive Symptomatology at 6-month intervals and a diagnostic interview at 2- and 6-year follow-up. Multinomial regression and mixed model analyses were both used to identify depression-related clinical, health, and psychosocial prognostic factors of an unfavorable course.

RESULTS

Among depressed patients at baseline, 46.8% were lost to follow-up; 15.9% had an unfavorable course, i.e., chronic or recurrent; 24.6% had partial remission; and 12.7% had full remission at six-year follow-up. The relative risk of mortality in depressed patients was 2.5 (95% confidence interval 1.26-4.81) versus nondepressed comparisons. An unfavorable course of depression was associated with a younger age at depression onset; higher symptom severity of depression, pain, and neuroticism; and loneliness at baseline. Additionally, partial remission was associated with chronic diseases and loneliness at baseline when compared with full remission.

CONCLUSIONS

The long-term prognosis of late-life depression is poor with regard to mortality and course of depression. Chronic diseases, loneliness, and pain may be used as putative targets for optimizing prevention and treatment strategies for relapse and chronicity.

Failure to Respond after Reinstatement of Antidepressant Medication: A Systematic Review

BACKGROUND

Following remission of an anxiety disorder or a depressive disorder, antidepressants are frequently discontinued and in the case of symptom occurrence reinstated. Reinstatement of antidepressants seems less effective in some patients, but an overview is lacking. This systematic review aimed to provide insight into the magnitude and risk factors of response failure after reinstatement of antidepressants in patients with anxiety disorders, depressive disorders, obsessive-compulsive disorder (OCD), or posttraumatic stress disorder (PTSD).

METHOD

PubMed, Embase, and trial registers were systematically searched for studies in which patients: (1) had an anxiety disorder, a depressive disorder, OCD, or PTSD and (2) experienced failure to respond after reinstatement of a previously effective antidepressant.

RESULTS

Ten studies reported failure to respond following antidepressant reinstatement. The phenomenon was observed in 16.5% of patients with a depressive disorder, OCD, and social phobia and occurred in all common classes of antidepressants. The range of response failure was broad, varying between 3.8 and 42.9% across studies. No risk factors for failure to respond were investigated. The overall study quality was limited.

CONCLUSION

Research investigating response failure is scarce and the study quality limited. Response failure occurred in a substantial minority of patients. Contributors to the relevance of this phenomenon are the prevalence of the investigated disorders, the number of patients being treated with antidepressants, and the occurrence of response failure for all common classes of antidepressants. This systematic review highlights the need for studies systematically investigating this phenomenon and associated risk factors.

Interpersonal Callousness from Childhood to Adolescence: Developmental Trajectories and Early Risk Factors

Youth with a callous interpersonal style, consistent with features of adult psychopathy (e.g., lack of guilt, deceitful), are at risk for exhibiting severe and protracted antisocial behaviors. However, no studies have examined changes that occur in interpersonal callousness (IC) from childhood to adolescence, and little is known about the influence of early child, social, and contextual factors on trajectories of IC. The current study examined distinct patterns of IC across childhood and adolescence and associations with early risk factors. Participants were an at-risk sample of 503 boys (56% African American) assessed annually from around ages 7-15. Analyses examined child (anger dysregulation, fearfulness), social (peer, family, maltreatment), and contextual (psychosocial adversity) factors associated with teacher-reported IC trajectories across childhood and adolescence. Using latent class growth analysis, five trajectories of IC were identified (early-onset chronic, childhood-limited, adolescent-onset, moderate, low). Approximately 10% of boys followed an early-onset chronic trajectory, and a roughly equal percent of youth followed childhood-limited trajectory (10%) or an adolescent-onset trajectory (12%) of IC across development. Specifically, half of the boys with high IC in childhood did not continue to exhibit significant levels of these features into adolescence, whereas an equal proportion of youth with low IC in childhood demonstrated increasing levels during the transition to adolescence. Boys in the early-onset chronic group were characterized by the most risk factors and were differentiated from those with childhood-limited and adolescent-onset IC only by higher conduct problems, fearlessness, and emotional abuse/neglect. Findings are discussed in terms of developmental models of IC and several avenues for early targeted interventions.

Transdiagnostic Symptom Clusters and Associations With Brain, Behavior, and Daily Function in Mood, Anxiety, and Trauma Disorders

IMPORTANCE

The symptoms that define mood, anxiety, and trauma disorders are highly overlapping across disorders and heterogeneous within disorders. It is unknown whether coherent subtypes exist that span multiple diagnoses and are expressed functionally (in underlying cognition and brain function) and clinically (in daily function). The identification of cohesive subtypes would help disentangle the symptom overlap in our current diagnoses and serve as a tool for tailoring treatment choices.

OBJECTIVE

To propose and demonstrate 1 approach for identifying subtypes within a transdiagnostic sample.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study analyzed data from the Brain Research and Integrative Neuroscience Network Foundation Database that had been collected at the University of Sydney and University of Adelaide between 2006 and 2010 and replicated at Stanford University between 2013 and 2017. The study included 420 individuals with a primary diagnosis of major depressive disorder (n = 100), panic disorder (n = 53), posttraumatic stress disorder (n = 47), or no disorder (healthy control participants) (n = 220). Data were analyzed between October 2016 and October 2017.

MAIN OUTCOMES AND MEASURES

We followed a data-driven approach to achieve the primary study outcome of identifying transdiagnostic subtypes. First, machine learning with a hierarchical clustering algorithm was implemented to classify participants based on self-reported negative mood, anxiety, and stress symptoms. Second, the robustness and generalizability of the subtypes were tested in an independent sample. Third, we assessed whether symptom subtypes were expressed at behavioral and physiological levels of functioning. Fourth, we evaluated the clinically meaningful differences in functional capacity of the subtypes. Findings were interpreted relative to a complementary diagnostic frame of reference.

RESULTS

Four hundred twenty participants with a mean (SD) age of 39.8 (14.1) years were included in the final analysis; 256 (61.0%) were female. We identified 6 distinct subtypes characterized by tension (n=81; 19%), anxious arousal (n=55; 13%), general anxiety (n=38; 9%), anhedonia (n=29; 7%), melancholia (n=37; 9%), and normative mood (n=180; 43%), and these subtypes were replicated in an independent sample. Subtypes were expressed through differences in cognitive control (F5,383 = 5.13, P < .001, ηp2 = 0.063), working memory (F5,401 = 3.29, P = .006, ηp2 = 0.039), electroencephalography-recorded β power in a resting paradigm (F5,357 = 3.84, P = .002, ηp2 = 0.051), electroencephalography-recorded β power in an emotional paradigm (F5,365 = 3.56, P = .004, ηp2 = 0.047), social functional capacity (F5,414 = 21.33, P < .001, ηp2 = 0.205), and emotional resilience (F5,376 = 15.10, P < .001, ηp2 = 0.171).

CONCLUSIONS AND RELEVANCE

These findings offer a data-driven framework for identifying robust subtypes that signify specific, coherent, meaningful associations between symptoms, behavior, brain function, and observable real-world function, and that cut across DSM-IV-defined diagnoses of major depressive disorder, panic disorder, and posttraumatic stress disorder.

Seeing the signs: Using the course of residual depressive symptomatology to predict patterns of relapse and recurrence of major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is characterized by high relapse/recurrence rates. Predicting individual patients' relapse/recurrence risk has proven hard, possibly due to course heterogeneity among patients. This study aimed to (1) identify homogeneous data-driven subgroups with different patterns of relapse/recurrence and (2) identify associated predictors.

METHODS

For a year, we collected weekly depressive symptom ratings in 213 primary care MDD patients. Latent class growth analyses (LCGA), based on symptom-severity during the 24 weeks after no longer fulfilling criteria for the initial major depressive episode (MDE), were used to identify groups with different patterns of relapse/recurrence. Associations of baseline predictors with these groups were investigated, as were the groups' associations with 3- and 11-year follow-up depression outcomes.

RESULTS

LCGA showed that heterogeneity in relapse/recurrence after no longer fulfilling criteria for the initial MDE was best described by four classes: "quick symptom decline" (14.0%), "slow symptom decline" (23.3%), "steady residual symptoms" (38.7%), and "high residual symptoms" (24.1%). The latter two classes showed lower self-esteem at baseline, and more recurrences and higher severity at 3-year follow-up than the first two classes. Moreover, the high residual symptom class scored higher on neuroticism and lower on extraversion and self-esteem at baseline. Interestingly, the steady residual symptoms and high residual symptoms classes still showed higher severity of depressive symptoms after 11 years.

CONCLUSION

Some measures were associated with specific patterns of relapse/recurrence. Moreover, the data-driven relapse/recurrence groups were predictive of long-term outcomes, suggesting that patterns of residual symptoms could be of prognostic value in clinical practice.

Low emotion-oriented coping and informal help-seeking behaviour as major predictive factors for improvement in major depression at 5-year follow-up in the adult community

PURPOSE

Given the broad range of biopsychosocial difficulties resulting from major depressive disorder (MDD), reliable evidence for predictors of improved mental health is essential, particularly from unbiased prospective community samples. Consequently, a broad spectrum of potential clinical and non-clinical predictors of improved mental health, defined as an absence of current major depressive episode (MDE) at follow-up, were examined over a 5-year period in an adult community sample.

METHODS

The longitudinal population-based PsyCoLaus study from the city of Lausanne, Switzerland, was used. Subjects having a lifetime MDD with a current MDE at baseline assessment were selected, resulting in a subsample of 210 subjects. Logistic regressions were applied to the data.

RESULTS

Coping styles were the most important predictive factors in the present study. More specifically, low emotion-oriented coping and informal help-seeking behaviour at baseline were associated with the absence of an MDD diagnosis at follow-up. Surprisingly, neither formal help-seeking behaviour, nor psychopharmacological treatment, nor childhood adversities, nor depression subtypes turned out to be relevant predictors in the current study.

CONCLUSIONS

The paramount role of coping styles as predictors of improvement in depression found in the present study might be a valuable target for resource-oriented therapeutic models. On the one hand, the positive impact of low emotion-oriented coping highlights the utility of clinical interventions interrupting excessive mental ruminations during MDE. On the other hand, the importance of informal social networks raises questions regarding how to enlarge the personal network of affected subjects and on how to best support informal caregivers.

Childhood Abuse and the Two-Year Course of Late-Life Depression

OBJECTIVES

Late-life depression often has a chronic course, with debilitating effects on functioning and quality of life; there is still no consensus on important risk factors explaining this chronicity. Cross-sectional studies have shown that childhood abuse is associated with late-life depression, and in longitudinal studies with chronicity of depression in younger adults. We aim to investigate the impact of childhood abuse on the course of late-life depression.

DESIGN

Two-year longitudinal cohort study.

SETTING

Data were derived from the Netherlands Study of Depression in Older Persons (NESDO).

PARTICIPANTS

282 participants with a depression diagnosis in the previous 6 months (mean age: 70.6 years), of whom 152 (53.9%) experienced childhood abuse.

MEASUREMENTS

Presence of childhood abuse (yes/no) and a frequency-based childhood abuse index (CAI) were calculated. Dependent variable was depression diagnosis after 2 years.

RESULTS

Multivariable mediation analysis showed an association between childhood abuse and depression diagnosis at follow-up. Depression severity, age at onset, neuroticism, and number of chronic diseases were important mediating variables of this association, which then lost statistical significance. For childhood abuse (yes/no), loneliness was an additional, significant mediator. Depression severity was the main mediating variable, reducing the direct effect by 26.5% to 33.3% depending on the definition of abuse (respectively, 'yes/no" abuse and CAI).

CONCLUSIONS

More depressive symptoms at baseline, lower age at depression onset, higher levels of neuroticism and loneliness, and more chronic diseases explain a poor course of depression in older adults who reported childhood abuse. When treating late-life depression it is important to detect childhood abuse and consider these mediating variables.

Depressive symptom trajectories in late adolescence and early adulthood: A systematic review

OBJECTIVE

In adolescents and young adults, depressive symptoms are highly prevalent and dynamic. For clinicians, it is difficult to determine whether a young person reporting depressive symptoms is at risk of developing ongoing mood difficulties or whether symptoms form part of a transient maturational process. Trajectory analyses of longitudinally assessed symptoms in large cohorts have the potential to untangle clinical heterogeneity by determining subgroups or classes of symptom course and their risk factors, by interrogating the impact of known or suspected risk factors on trajectory slope and intercept and by tracing the interrelation between depressive symptoms and other clinical outcomes over time.

METHOD

We conducted a systematic review of trajectory studies conducted in cohorts including people aged between 15 and 25 years.

RESULTS

We retrieved 47 relevant articles. These studies suggest that young people fall into common mood trajectory classes and that class membership and symptom course are mediated by biological and environmental risk factors. Furthermore, studies provide evidence that high and persistent depressive symptoms are associated with a range of concurrent health and behavioral outcomes.

CONCLUSION

Findings could assist in the formulation of novel concepts of depressive disorders in young people and inform preventive strategies and predictive models for clinical practice.

Childhood Adversities and Depression in Adulthood: Current Findings and Future Directions

Considerable support exists supporting a relationship between childhood adversities and adult depression. Consistent evidence has emerged linking early life adversities with a more chronic course for depression, as well as to poorer treatment outcomes. What remain decidedly less clear, however, are the moderators and mediating mechanisms underlying this association. This article provides a review of the existing research relating early adversities to adult depression, as well as recent studies suggestive of potential mediators and moderators of this relation. Advances in these areas are important for their potential to lead to the identification of new targets for clinical intervention for adults with a history of childhood adversities, as well as to the development of individually tailored prevention and treatment strategies.

World Health Organization disability assessment schedule 2.0: An international systematic review

PURPOSE

This systematic review examines research and practical applications of the World Health Organization Disability Assessment Schedule (WHODAS 2.0) as a basis for establishing specific criteria for evaluating relevant international scientific literature. The aims were to establish the extent of international dissemination and use of WHODAS 2.0 and analyze psychometric research on its various translations and adaptations. In particular, we wanted to highlight which psychometric features have been investigated, focusing on the factor structure, reliability, and validity of this instrument.

METHOD

Following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology, we conducted a search for publications focused on "whodas" using the ProQuest, PubMed, and Google Scholar electronic databases.

RESULTS

We identified 810 studies from 94 countries published between 1999 and 2015. WHODAS 2.0 has been translated into 47 languages and dialects and used in 27 areas of research (40% in psychiatry).

CONCLUSIONS

The growing number of studies indicates increasing interest in the WHODAS 2.0 for assessing individual functioning and disability in different settings and individual health conditions. The WHODAS 2.0 shows strong correlations with several other measures of activity limitations; probably due to the fact that it shares the same disability latent variable with them. Implications for Rehabilitation WHODAS 2.0 seems to be a valid, reliable self-report instrument for the assessment of disability. The increasing interest in use of the WHODAS 2.0 extends to rehabilitation and life sciences rather than being limited to psychiatry. WHODAS 2.0 is suitable for assessing health status and disability in a variety of settings and populations. A critical issue for rehabilitation is that a single "minimal clinically important .difference" score for the WHODAS 2.0 has not yet been established.

Beyond Lumping and Splitting: A Review of Computational Approaches for Stratifying Psychiatric Disorders

Heterogeneity is a key feature of all psychiatric disorders that manifests on many levels, including symptoms, disease course, and biological underpinnings. These form a substantial barrier to understanding disease mechanisms and developing effective, personalized treatments. In response, many studies have aimed to stratify psychiatric disorders, aiming to find more consistent subgroups on the basis of many types of data. Such approaches have received renewed interest after recent research initiatives, such as the National Institute of Mental Health Research Domain Criteria and the European Roadmap for Mental Health Research, both of which emphasize finding stratifications that are based on biological systems and that cut across current classifications. We first introduce the basic concepts for stratifying psychiatric disorders and then provide a methodologically oriented and critical review of the existing literature. This shows that the predominant clustering approach that aims to subdivide clinical populations into more coherent subgroups has made a useful contribution but is heavily dependent on the type of data used; it has produced many different ways to subgroup the disorders we review, but for most disorders it has not converged on a consistent set of subgroups. We highlight problems with current approaches that are not widely recognized and discuss the importance of validation to ensure that the derived subgroups index clinically relevant variation. Finally, we review emerging techniques-such as those that estimate normative models for mappings between biology and behavior-that provide new ways to parse the heterogeneity underlying psychiatric disorders and evaluate all methods to meeting the objectives of such as the National Institute of Mental Health Research Domain Criteria and Roadmap for Mental Health Research.

Heterogeneity in the three-year course of major depression among older adults

OBJECTIVE

The objective of this research was to identify distinct trajectories of recovery in older depressed patients in order to identify optimal samples and points for interventions.

METHODS

The sample was 368 patients ages 60 years and older diagnosed with major depression and enrolled in a naturalistic treatment study and followed for up to 3 years.

RESULTS

A model with four trajectory classes fit the data best: a quick recovery class (43%), a persistent moderate symptom class (27%), a persistent high symptom class (15%), and a slow recovery class (15%). Compared with patients in the quick recovery class, patients in the persistent moderate symptom class had more instrumental activities of daily living/mobility limitations and lower levels of subjective social support. Patients in the persistent high symptom class had higher levels of perceived stress and lower levels of social support compared with those with a quick recovery. Patients in the slow recovery class had a younger age of onset compared with those in the quick recovery group. In multinomial logistic regression, levels of perceived stress and social support at baseline significantly differed across classes controlling for demographic and health variables.

CONCLUSIONS

Older patients diagnosed with major depression can have varying patterns of response to treatment. Interventions targeting those patients with higher levels of perceived stress and lower levels of subjective social support at the time of the index episode may lead to more favorable long-term trajectories. Copyright © 2015 John Wiley & Sons, Ltd.

Heterogeneity in 10-Year Course Trajectories of Moderate to Severe Major Depressive Disorder: A Danish National Register-Based Study

IMPORTANCE

Evidence suggests that long-term trajectories of major depressive disorder (MDD) are heterogeneous. The Danish Psychiatric Central Research Register (DPCRR) provides a rare opportunity to examine patterns and correlates of long-term trajectories in a large sample of patients with moderate to severe MDD.

OBJECTIVE

To characterize patterns and correlates of 10-year course trajectories of MDD in the DPCRR.

DESIGN, SETTING, AND PARTICIPANTS

A cohort containing 11 640 individuals born in Denmark in 1955 or later with their first recorded MDD diagnosis in the DPCRR between 1995 and 2002 was established. Patients were followed for 10 years from the date of their initial MDD diagnosis. Data were obtained from Danish civil and psychiatric national registers in June 2013 and were analyzed from April 4, 2014, to December 17, 2015. Correlates of trajectory class membership were sex, characteristics of the first recorded MDD episode (ie, age, severity, inpatient treatment, and record of suicide attempt or self-harm), and psychiatric diagnoses in parents (ie, depression, bipolar disorder, schizophrenia-spectrum disorders, substance abuse, and anxiety or somatoform disorders).

MAIN OUTCOMES AND MEASURES

The outcome variable was past-year contact at a psychiatric hospital with a main diagnosis of MDD during each of the 10 years following the initial MDD diagnosis. Trajectories were modeled using latent class growth analysis.

RESULTS

The sample included 11 640 individuals (7493 [64.4%] women) aged 18 to 48 years (mean [SD], 31.4 [7.3]) at their first recorded MDD diagnosis. Four trajectory classes were identified: brief contact (77.0%) (characterized by low probability of contact after 2 years); prolonged initial contact (12.8%) (characterized by high decreasing probability of contact during the first 5 years); later reentry (7.1%) (characterized by moderate probability of contact during the second 5 years); and persistent contact (3.1%) (characterized by high or moderate probability of contact throughout). Female sex (odds ratio [OR] range, 1.82-2.22), inpatient treatment (OR range, 1.40-1.50), and severity at first recorded MDD episode (OR range: moderate, 1.61-1.84; severe, 1.93-2.23; and psychotic, 2.73-3.07) were associated with more severe trajectories. Parental anxiety (OR, 1.34 [95% CI, 1.10-1.63]) and depression (OR, 1.63 [95% CI, 1.28-2.09]) were associated with the prolonged initial contact and later reentry classes, respectively. Parental schizophrenia was associated with the persistent contact class (OR range, 2.55-3.04).

CONCLUSIONS AND RELEVANCE

Most people treated for moderate to severe MDD in Danish psychiatric hospitals do not receive additional MDD treatment after 2 years; however, a minority receive specialty treatment for up to a decade. Observable heterogeneity in the course may be indicative of underlying etiologic differences.

Trajectory Pathways for Depressive Symptoms and Their Associated Factors in a Chinese Primary Care Cohort by Growth Mixture Modelling

Background

The naturalistic course for patients suffering from depressive disorders can be quite varied. Whilst some remit with little or no intervention, others may suffer a more prolonged course of symptoms. The aim of this study was to identify trajectory patterns for depressive symptoms in a Chinese primary care cohort and their associated factors.

Methods and Results

A 12-month cohort study was conducted. Patients recruited from 59 primary care clinics across Hong Kong were screened for depressive symptoms using the Centre for Epidemiologic Studies Depression Scale (CES-D) and monitored over 12 months using the Patient Health Questionnaire-9 items (PHQ-9) administered at 12, 26 and 52 weeks. 721 subjects were included for growth mixture modelling analysis. Using Akaike Information Criterion, Bayesian Information Criterion, Entropy and Lo-Mendell-Rubin adjusted likelihood ratio test, a seven-class trajectory path model was identified. Over 12 months, three trajectory groups showed improvement in depressive symptoms, three remained static, whilst one deteriorated. A mild severity of depressive symptoms with gradual improvement was the most prevalent trajectory identified. Multivariate, multinomial regression analysis was used to identify factors associated with each trajectory. Risk factors associated with chronicity included: female gender; not married; not in active employment; presence of multiple chronic disease co-morbidities; poor self-rated general health; and infrequent health service use.

Conclusions

Whilst many primary care patients may initially present with a similar severity of depressive symptoms, their course over 12 months can be quite heterogeneous. Although most primary care patients improve naturalistically over 12 months, many do not remit and it is important for doctors to be able to identify those who are at risk of chronicity. Regular follow-up and greater treatment attention is recommended for patients at risk of chronicity.