Approximately one-third of individuals in a major depressive episode will not achieve sustained remission despite multiple, well-delivered treatments. These patients experience prolonged suffering and disproportionately utilize mental and general health care resources. The recently proposed clinical heuristic of ‘difficult-to-treat depression’ (DTD) aims to broaden our understanding and focus attention on the identification, clinical management, treatment selection, and outcomes of such individuals. Clinical trial methodologies developed to detect short-term therapeutic effects in treatment-responsive populations may not be appropriate in DTD. This report reviews three essential challenges for clinical intervention research in DTD: (1) how to define and subtype this heterogeneous group of patients; (2) how, when, and by what methods to select, acquire, compile, and interpret clinically meaningful outcome metrics; and (3) how to choose among alternative clinical trial design options to promote causal inference and generalizability. The boundaries of DTD are uncertain, and an evidence-based taxonomy and reliable assessment tools are preconditions for clinical research and subtyping. Traditional outcome metrics in treatment-responsive depression may not apply to DTD, as they largely reflect the only short-term symptomatic change and do not incorporate durability of benefit, side effect burden, or sustained impact on quality of life or daily function. The trial methodology will also require modification as trials will likely be of longer duration to examine the sustained impact, raising complex issues regarding control group selection, blinding and its integrity, and concomitant treatments.

Mental health research funding priorities in high-income countries must balance longer-term investment in identifying neurobiological mechanisms of disease with shorter-term funding of novel prevention and treatment strategies to alleviate the current burden of mental illness. Prioritising one area of science over others risks reduced returns on the entire scientific portfolio.

The National Institute of Mental Health (NIMH) has embarked upon a new venture—effectiveness trials, large-scale trials to test more than one treatment option for individuals affected with diverse major mental disorders. The launch follows a recent report by the NIMH National Advisory Mental Health Council, which emphasized the failure within routine clinical care to widely implement findings of randomized, controlled efficacy trials (RCTs)—perhaps, in part, because of reduced generalizability that leaves real-world application unclear.

Efficacy trials do not answer a number of key clinical questions, including: (1) Are the treatments as effective and safe in representative patient groups? (2) How does the new treatment fit within the treatment armamentarium? (3) When should the new treatment be combined with existing interventions? (4) What are the long-term benefits? (5) Do treatments differ regarding their effectiveness in patients with comorbid general medical or psychiatric disorders? (6) How do these newer treatments affect costs of routine care? Effectiveness trials can address a number of these issues and incorporate a broad range of outcomes, including symptom reduction, day-to-day function, side effect burden, and patient satisfaction.

With a major aim of effectiveness trials being increased generalizability, selection of participants is crucial. Since symptomatic volunteers, who are typically used in efficacy RCTs for major depressive disorder, may be more responsive to either the nonspecific aspects of treatment or to the treatment itself than self-declared patients with concomitant comorbidities, setting minimal exclusion criteria, recruiting large samples of patients from representative practices, and excluding symptomatic volunteers assures that patients are representative, while protecting the internal validity of the trial. In addition, treatments must be reasonably well delivered so that outcomes can be attributed to the treatment per se and not to improper implementation of an otherwise effective treatment. Frequent clinic visits, patient/family educational efforts, universal access to all protocol recommended treatments (including psychotherapy), and adequate provider compensation can ensure that treatments are reasonably well delivered.

Introduction: Major depressive disorder (MDD) is thought to negatively impact cognitive function; however, the relationship has not been well explored.

Objective: This study examined the association between depression severity and global cognitive function and memory in subjects with severe, treatment-resistant MDD.

Methods: We enrolled 66 subjects with Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnosed unipolar MDD in a multicenter trial to assess the efficacy and neurocognitive effects of electroconvulsive therapy (ECT). We measured depression severity with the 24 item Hamilton Rating Scale for Depression (HRSD24). Neuropsychologic measures included the Mini Mental State Examination (MMSE), Rey Auditory Verbal Learning Test (RAVLT), and the Complex Figure Test (CFT). Correlational and regression analyses were conducted to explore associations between depression severity and cognitive function.

Results: The mean age of the subjects was 53.6 years (SD=15.8), 65% were female, and mean HRSD24 was 33.9 (SD=6.7). Mean demographic-corrected T-scores for each neurocognitive measure were in the average to borderline range, and HRSD24 values were unrelated to performance on the MMSE, RAVLT immediate and delayed recall, and CFT immediate and delayed recall.

Conclusion: In this sample of severely depressed subjects referred for ECT, depression severity was unrelated to global cognitive function or memory. Future research should examine the interactions between other depressive characteristics and neurocognitive function.

Introduction: Concomitant psychotropic medication (CPM) treatment is common in persons with major depression (MDD). However, relationships with patient characteristics and response to treatment are unclear.

Methods: Participants with nonpsychotic MDD (N=2682) were treated with citalopram, 20–60 mg/day. Sociodemographic, clinical, and treatment outcome characteristics were compared between those using CPMs at study entry or during up to 14 weeks of citalopram treatment, and non-users.

Results: About 35% of participants used a CPM. Insomnia was the predominant indication (70.3%). CPM users were more likely to be seen in primary care settings (69.3% versus 30.7%), be white, of non-Hispanic ethnicity, married, and have a higher income, private insurance, and certain comorbid disorders. CPM users had greater depressive severity, poorer physical and mental functioning, and poorer quality of life than non-users. Response and remission rates were also lower. CPM users were more likely to achieve ≥50 mg/day of citalopram, to report greater side effect intensity, and to have serious adverse events, but less likely to be intolerant of citalopram.

Conclusion: CPMs are associated with greater illness burden, more Axis I comorbidities (especially anxiety disorders), and lower treatment effectiveness. This suggests that CPM use may identify a more difficult to treat population that needs more aggressive treatment.

Introduction: The clinical and self-report versions of the Quick Inventory of Depressive Symptomatology (QIDS-C16 and QIDS-SR16) have been well studied in patients with major depressive disorder and in one recent study using patients with bipolar disorder. This article examines these measures in a second sample of 141 outpatients with bipolar disorder in different phases of the illness.

Methods: At baseline, 61 patients were depressed and 30 were euthymic; at exit, 50 were depressed and 52 were euthymic. The remaining patients (at baseline or exit) were in either a manic or mixed phase and were pooled for statistical reasons.

Results: Similar results were found for the QIDS-C16 and QIDS-SR16. Scores were reasonably reliable to the extent that variability within groups permitted. As expected, euthymic patients showed less depressive symptomatology than depressed patients. Sad mood and general interest were tne most discriminating symptoms between depressed and euthymic phases. Changes in illness phase (baseline to exit) were associated with substantial changes in scores. The relation of individual depressive symptoms to the overall level of depression was consistent across phases.

Conclusion: Both the QIDS-SR16 and QIDS-C16 are suitable measures of depressive symptoms in patients with bipolar disorder.

Antidepressants are important in the treatment of depression, and selective serotonin reuptake inhibitors are first-line pharmacologic options. However, only 50% to 70% of patients respond to first treatment and <40% remit. Since depression is associated with substantial morbidity, mortality, and family burden, it is unfortunate and demanding on health resources that patients must remain on their prescribed medications for at least 4 weeks without knowing whether the particular antidepressant will be effective. Studies have suggested a number of predictors of treatment response, including clinical, psychophysiological, neuroimaging, and genetics, each with varying degrees of success and nearly all with poor prognostic sensitivity and specificity. Studies are yet to be conducted that use multiple measures from these different domains to determine whether sensitivity and specificity can be improved to predict individual treatment response. It is proposed that a focus on standardized testing methodologies across multiple testing modalities and their integration will be crucial for translation of research findings into clinical practice.

Introduction: Insomnia symptoms, which are common in depression, have a significant impact on function and quality of life. However, little is known about the prevalence and associated features of insomnia symptoms in representative treatment-seeking patients with depression.

Methods: Data from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial were analyzed. STAR*D recruited 3,743 adult outpatients diagnosed with nonpsychotic major depressive disorder (MDD) from primary (n=18) and psychiatric care (n=23) clinics across the United States. Baseline sociodemographic and clinical features were compared between those with insomnia symptoms (84.7%) and those without (15.3%).

Results: The most common presentation was the simultaneous presence of sleep onset, mid-nocturnal, and early morning insomnia symptoms (27.1%). Of these three types of insomnia symptoms, mid-nocturnal insomnia symptoms were the most commonly found alone (13.5%) and in combination with one or more other types (82.3%). Insomnia symptoms were associated with several indicators of a more severe depressive illness. Only a small proportion of participants with insomnia symptoms were receiving treatment for sleep disturbances at study initiation, and the vast majority of those receiving treatment still reported having insomnia symptoms.

Conclusion: In outpatients who seek treatment for nonpsychotic MDD in typical clinical settings, insomnia symptoms are very common, undertreated, and indicative of a more severe depression.

Background. Despite increasing adoption of clinical practice guidelines in psychiatry, there is little measurement of provider implementation of these recommendations, and the resulting impact on clinical outcomes. The current study describes one effort to measure these relationships in a cohort of public sector out-patients with bipolar disorder.

Method. Participants were enrolled in the algorithm intervention of the Texas Medication Algorithm Project (TMAP). Study methods and the adherence scoring algorithm have been described elsewhere. The current paper addresses the relationships between patient characteristics, provider experience with the algorithm, provider adherence, and clinical outcomes. Measurement of provider adherence includes evaluation of visit frequency, medication choice and dosing, and response to patient symptoms. An exploratory composite ‘adherence by visit’ score was developed for these analyses.

Results. A total of 1948 visits from 141 subjects were evaluated, and utilized a two-stage declining effects model. Providers with more experience using the algorithm tended to adhere less to treatment recommendations. Few patient factors significantly impacted provider adherence. Increased adherence to algorithm recommendations was associated with larger decreases in overall psychiatric symptoms and depressive symptoms over time, but did not impact either immediate or long-term reductions in manic symptoms.

Conclusions. Greater provider adherence to treatment guideline recommendations was associated with greater reductions in depressive symptoms and overall psychiatric symptoms over time. Additional research is needed to refine measurement and to further clarify these relationships.

We describe a study of the dynamics of hydrogen in Pr2Fe17H4, where isolated hexagons formed by the interstitial tetrahedral (t) sites of the metal lattice are populated by mobile hydrogen atoms. An activation energy of 0.10 eV has been determined for a localized jump process involving the hopping of these hydrogen atoms among adjacent vertices of each hexagon, slightly lower than that for hydrogen hopping in Pr2Fe17H5, where each hexagon is occupied by two hydrogen atoms.

Background. Anxious depression, defined as Major Depressive Disorder (MDD) with high levels of anxiety symptoms, may represent a relatively common depressive subtype, with distinctive features.

Objective. The objective of this study was to determine the prevalence of anxious depression and to define its clinical correlates and symptom patterns.

Method. Baseline clinical and sociodemographic data were collected on 1450 subjects participating in the STAR*D study. A baseline Hamilton Rating Scale for Depression (HAM-D) Anxiety/Somatization factor score of [ges ]7 was considered indicative of anxious depression. The types and degree of concurrent psychiatric symptoms were measured using the Psychiatric Diagnostic Screening Questionnaire (PDSQ), by recording the number of items endorsed by study participants for each diagnostic category. MDD symptoms were assessed by clinical telephone interview with the 30-item Inventory of Depressive Symptomatology (IDS-C30).

Results. The prevalence of anxious depression in this population was 46%. Patients with anxious MDD were significantly more likely to be older, unemployed, less educated, more severely depressed, and to have suicidal ideation before and after adjustment for severity of depression. As far as concurrent psychiatric symptoms are concerned, patients with anxious depression were significantly more likely to endorse symptoms related to generalized anxiety, obsessive compulsive, panic, post-traumatic stress, agoraphobia, hypochondriasis, and somatoform disorders before and after adjustment for severity of depression. Anxious-depression individuals were also significantly less likely to endorse IDS-C30 items concerning atypical features, and were significantly more likely to endorse items concerning melancholic/endogenous depression features.

Conclusion. This study supports specific clinical and sociodemographic correlates of MDD associated with high levels of anxiety (anxious depression).

Very-low-birthweight (VLBW) individuals are at high risk of brain injury in the perinatal period. We wished to determine how such early brain lesions affect brain structure in adulthood. Thirty-two VLBW adults (20 female, 12 male) and 18 term, normal birthweight sibling control individuals (nine female, nine male) underwent structural MRI at a mean age of 23 years 4 months (range 17 to 33 years; SD 3.4). Images were analyzed using an automated tissue segmentation algorithm in order to estimate whole brain tissue class volumes in native space. Images were then warped to a template image in standard space. There was no significant between-group difference in whole brain, grey matter, white matter, or total cerebral spinal fluid (CSF) volumes. However, lateral ventricular volume was significantly increased by 41% in those with VLBW. The ratio of grey to white matter was also significantly increased (by 10%) in those with VLBW. Group comparison maps showed widespread changes in the distribution of grey and white matter, and relative excess of ventricular CSF, in the brains of VLBW individuals. Increased ventricular volume predicted decreased grey matter in subcortical nuclei and limbic cortical structures, and decreased periventricular white matter. We conclude that these diffuse abnormalities of grey and white matter are a consequence of the interaction of perinatal brain injury and ongoing neurodevelopmental processes.