Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA).

A 2018–2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample.

In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors.

Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.

Antidepressant medication and interpersonal psychotherapy (IPT) are both recommended interventions in depression treatment guidelines based on literature reviews and meta-analyses. However, ‘conventional’ meta-analyses comparing their efficacy are limited by their reliance on reported study-level information and a narrow focus on depression outcome measures assessed at treatment completion. Individual participant data (IPD) meta-analysis, considered the gold standard in evidence synthesis, can improve the quality of the analyses when compared with conventional meta-analysis.

We describe the protocol for a systematic review and IPD meta-analysis comparing the efficacy of antidepressants and IPT for adult acute-phase depression across a range of outcome measures, including depressive symptom severity as well as functioning and well-being, at both post-treatment and follow-up (PROSPERO: CRD42020219891).

We will conduct a systematic literature search in PubMed, PsycINFO, Embase and the Cochrane Library to identify randomised clinical trials comparing antidepressants and IPT in the acute-phase treatment of adults with depression. We will invite the authors of these studies to share the participant-level data of their trials. One-stage IPD meta-analyses will be conducted using mixed-effects models to assess treatment effects at post-treatment and follow-up for all outcome measures that are assessed in at least two studies.

This will be the first IPD meta-analysis examining antidepressants versus IPT efficacy. This study has the potential to enhance our knowledge of depression treatment by comparing the short- and long-term effects of two widely used interventions across a range of outcome measures using state-of-the-art statistical techniques.

Although cognitive-behavioural therapy (CBT) is a well-established treatment for adult depression, its efficacy and efficiency may be enhanced by better understanding its mechanism(s) of action. According to the theoretical model of CBT, symptom improvement occurs via reductions in maladaptive cognition. However, previous research has not established clear evidence for this cognitive mediation model.

The present study investigated the cognitive mediation model of CBT in the context of a randomized controlled trial of CBT v. antidepressant medication (ADM) for adult depression. Participants with major depressive disorder were randomized to receive 16 weeks of CBT (n = 54) or ADM (n = 50). Depression symptoms and three candidate cognitive mediators (dysfunctional attitudes, cognitive distortions and negative automatic thoughts) were assessed at week 0 (pre-treatment), week 4, week 8 and week 16 (post-treatment). Longitudinal associations between cognition and depression symptoms, and mediation of treatment outcome, were evaluated in structural equation models.

Both CBT and ADM produced significant reductions in maladaptive cognition and depression symptoms. Cognitive content and depression symptoms were moderately correlated within measurement waves, but cross-lagged associations between the variables and indirect (i.e. mediated) treatment effects were non-significant.

The results provide support for concurrent relationships between cognitive and symptom change, but not the longitudinal relationships hypothesized by the cognitive mediation model. Results may be indicative of an incongruence between the timing of measurement and the dynamics of cognitive and symptom change.

This study aims to investigate existing evidence for the effectiveness of psychological treatments and/or antidepressant medication as a treatment for those diagnosed with moderate levels of depression.

A PRISMA systematic review of articles using electronic research databases (2000–2014) was conducted to identify studies investigating the effectiveness of psychotherapy and/or medication as a treatment for people with moderate levels of depression. Search terms included moderate depression, psychotherapy and/or medication, depressive disorders, antidepressants, psychotherapy, mental health services, and randomized-controlled trial (RCT). The included studies were then assessed, extracted, and synthesised.

A total of 14 studies met the inclusion criteria (11 RCTs and three additional studies) for this review. The findings of the systematic review indicate that there is limited evidence available specific to the treatment of moderate depression and that this research seems to suggest that psychotherapy or combined treatment has a beneficial effect.

Given that depression is one of the biggest challenges the world faces at present, further research is required to examine the effectiveness of treatment for different levels of depression severity.

It has been proposed that non-steroidal anti-inflammatory drugs (NSAIDs) may interfere with the efficacy of antidepressants and contribute to treatment resistance in major depressive disorder (MDD). This effect requires replication and a test of whether it is specific to serotonin-reuptake inhibiting (SRI) antidepressants.

We tested the effect of concomitant medication with NSAIDs on the efficacy of escitalopram, a SRI antidepressant, and nortriptyline, a tricyclic antidepressant, among 811 subjects with MDD treated for up to 12 weeks in the GENDEP study. Effects of NSAIDs on improvement of depressive symptoms were tested in mixed-effect linear models. Effects on remission were tested in logistic regression. Age, sex, baseline severity and centre of recruitment were considered as potential confounding factors.

Ten percent (n=78) of subjects were taking NSAIDs during the antidepressant treatment. Older subjects were significantly more likely to take NSAIDs. After controlling for age, sex, centre of recruitment and baseline severity, concomitant medication with NSAIDs did not significantly influence the efficacy of escitalopram [β=0.035, 95% confidence interval (CI) −0.145 to 0.215, p=0.704] or nortriptyline (β=0.075, 95% CI −0.131 to 0.281, p=0.476). Although slightly fewer subjects who took NSAIDs reached remission [odds ratio (OR) 0.80, 95% CI 0.49–1.31, p=0.383], this non-significant effect was reversed after controlling for age, sex, baseline severity and recruitment centre effects (OR 1.04, 95% CI 0.61–1.77, p=0.882).

NSAIDs are unlikely to affect the efficacy of SRI or other antidepressants. Concurrent use of NSAIDs and antidepressants does not need to be avoided.

Symptom dimensions have not yet been comprehensively tested as predictors of the substantial heterogeneity in outcomes of antidepressant treatment in major depressive disorder.

We tested nine symptom dimensions derived from a previously published factor analysis of depression rating scales as predictors of outcome in 811 adults with moderate to severe depression treated with flexibly dosed escitalopram or nortriptyline in Genome-based Therapeutic Drugs for Depression (GENDEP). The effects of symptom dimensions were tested in mixed-effect regression models that controlled for overall initial depression severity, age, sex and recruitment centre. Significant results were tested for replicability in 3637 adult out-patients with non-psychotic major depression treated with citalopram in level I of Sequenced Treatment Alternatives to Relieve Depression (STAR*D).

The interest-activity symptom dimension (reflecting low interest, reduced activity, indecisiveness and lack of enjoyment) at baseline strongly predicted poor treatment outcome in GENDEP, irrespective of overall depression severity, antidepressant type and outcome measure used. The prediction of poor treatment outcome by the interest-activity dimension was robustly replicated in STAR*D, independent of a comprehensive list of baseline covariates.

Loss of interest, diminished activity and inability to make decisions predict poor outcome of antidepressant treatment even after adjustment for overall depression severity and other clinical covariates. The prominence of such symptoms may require additional treatment strategies and should be accounted for in future investigations of antidepressant response.

The aim of the present study was to determine whether a combination of baseline features and early post-baseline depressive symptom changes have clinical value in predicting out-patient non-response in depressed out-patients after 8 weeks of medication treatment.

We analysed data from the Combining Medications to Enhance Depression Outcomes study for 447 participants with complete 16-item Quick Inventory of Depressive Symptomatology – Self-Report (QIDS-SR16) ratings at baseline and at treatment weeks 2, 4 and 8. We used a multi-time point, recursive subsetting approach that included baseline features and changes in QIDS-SR16 scores from baseline to weeks 2 and 4, to identify non-responders (<50% reduction in QIDS-SR16) at week 8 with a pre-specified accuracy level.

Pretreatment clinical features alone were not clinically useful predictors of non-response after 8 weeks of treatment. Baseline to week 2 symptom change identified 48 non-responders (of which 36 were true non-responders). This approach gave a clinically meaningful negative predictive value of 0.75. Symptom change from baseline to week 4 identified 79 non-responders (of which 60 were true non-responders), achieving the same accuracy. Symptom change at both weeks 2 and 4 identified 87 participants (almost 20% of the sample) as non-responders with the same accuracy. More participants with chronic than non-chronic index episodes could be accurately identified by week 4.

Specific baseline clinical features combined with symptom changes by weeks 2–4 can provide clinically actionable results, enhancing the efficiency of care by personalizing the treatment of depression.

Bulimia nervosa (BN) is a serious psychiatric disorder characterized by frequent episodes of binge eating and inappropriate compensatory behavior. Numerous trials have found that antidepressant medications are efficacious for the treatment of BN. Early response to antidepressant treatment, in the first few weeks after medication is initiated, may provide clinically useful information about an individual's likelihood of ultimately benefitting or not responding to such treatment. The purpose of this study was to examine the relationship between initial and later response to fluoxetine, the only antidepressant medication approved by the US Food and Drug Administration (FDA) for the treatment of BN, with the goal of developing guidelines to aid clinicians in deciding when to alter the course of treatment.

Data from the two largest medication trials conducted in BN (n=785) were used. Receiver operating characteristic (ROC) curves were constructed to assess whether symptom change during the first several weeks of treatment was associated with eventual non-response to fluoxetine at the end of the trial.

Eventual non-responders to fluoxetine could be reliably identified by the third week of treatment.

Patients with BN who fail to report a ⩾60% decrease in the frequency of binge eating or vomiting at week 3 are unlikely to respond to fluoxetine. As no reliable relationships between pretreatment characteristics and eventual response to pharmacotherapy have been identified for BN, early response is one of the only available indicators to guide clinical management.

Painful physical symptoms (PPS) are both common and reduce the likelihood of remission in major depressive disorder (MDD), based upon results of clinical trials in selected populations. Whether PPS significantly contribute to poorer treatment outcome overall in primary or specialty psychiatric care settings remains unclear.

Out-patients (n=2876) with MDD were treated in the first step of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial with citalopram up to 60 mg/day for up to 14 weeks. Presence of painful symptoms, as well as severity of depression, physical illness, and demographic and treatment factors were examined. Time to and overall rates of remission were analysed in relation to the presence of PPS.

Of the participants, 80% complained of PPS. These patients, both in primary and specialty psychiatric settings, had significantly lower remission rates and took longer to remit. Increasing severity of PPS was associated with greater physical illness burden, lower socio-economic status, absence of private insurance and being female, African-American or Hispanic. After adjustment for these factors, patients with PPS no longer had significantly poorer treatment outcomes.

Presence and severity of PPS is an indicator of MDD that may have poorer treatment outcome with an initial selective serotonin reuptake inhibitor. These poorer treatment outcomes are multifactorial, however, and are not explained by the presence and severity of pain per se.