To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
This study aimed to investigate general factors associated with prognosis regardless of the type of treatment received, for adults with depression in primary care.
We searched Medline, Embase, PsycINFO and Cochrane Central (inception to 12/01/2020) for RCTs that included the most commonly used comprehensive measure of depressive and anxiety disorder symptoms and diagnoses, in primary care depression RCTs (the Revised Clinical Interview Schedule: CIS-R). Two-stage random-effects meta-analyses were conducted.
Twelve (n = 6024) of thirteen eligible studies (n = 6175) provided individual patient data. There was a 31% (95%CI: 25 to 37) difference in depressive symptoms at 3–4 months per standard deviation increase in baseline depressive symptoms. Four additional factors: the duration of anxiety; duration of depression; comorbid panic disorder; and a history of antidepressant treatment were also independently associated with poorer prognosis. There was evidence that the difference in prognosis when these factors were combined could be of clinical importance. Adding these variables improved the amount of variance explained in 3–4 month depressive symptoms from 16% using depressive symptom severity alone to 27%. Risk of bias (assessed with QUIPS) was low in all studies and quality (assessed with GRADE) was high. Sensitivity analyses did not alter our conclusions.
When adults seek treatment for depression clinicians should routinely assess for the duration of anxiety, duration of depression, comorbid panic disorder, and a history of antidepressant treatment alongside depressive symptom severity. This could provide clinicians and patients with useful and desired information to elucidate prognosis and aid the clinical management of depression.
No evidence-based therapy for borderline personality disorder (BPD) exhibits a clear superiority. However, BPD is highly heterogeneous, and different patients may specifically benefit from the interventions of a particular treatment.
From a randomized trial comparing a year of dialectical behavior therapy (DBT) to general psychiatric management (GPM) for BPD, long-term (2-year-post) outcome data and patient baseline variables (n = 156) were used to examine individual and combined patient-level moderators of differential treatment response. A two-step bootstrapped and partially cross-validated moderator identification process was employed for 20 baseline variables. For identified moderators, 10-fold bootstrapped cross-validated models estimated response to each therapy, and long-term outcomes were compared for patients randomized to their model-predicted optimal v. non-optimal treatment.
Significant moderators surviving the two-step process included psychiatric symptom severity, BPD impulsivity symptoms (both GPM > DBT), dependent personality traits, childhood emotional abuse, and social adjustment (all DBT > GPM). Patients randomized to their model-predicted optimal treatment had significantly better long-term outcomes (d = 0.36, p = 0.028), especially if the model had a relatively stronger (top 60%) prediction for that patient (d = 0.61, p = 0.004). Among patients with a stronger prediction, this advantage held even when applying a conservative statistical check (d = 0.46, p = 0.043).
Patient characteristics influence the degree to which they respond to two treatments for BPD. Combining information from multiple moderators may help inform providers and patients as to which treatment is the most likely to lead to long-term symptom relief. Further research on personalized medicine in BPD is needed.
Psychotherapies for depression are equally effective on average, but individual responses vary widely. Outcomes can be improved by optimizing treatment selection using multivariate prediction models. A promising approach is the Personalized Advantage Index (PAI) that predicts the optimal treatment for a given individual and the magnitude of the advantage. The current study aimed to extend the PAI to long-term depression outcomes after acute-phase psychotherapy.
Data come from a randomized trial comparing cognitive therapy (CT, n = 76) and interpersonal psychotherapy (IPT, n = 75) for major depressive disorder (MDD). Primary outcome was depression severity, as assessed by the BDI-II, during 17-month follow-up. First, predictors and moderators were selected from 38 pre-treatment variables using a two-step machine learning approach. Second, predictors and moderators were combined into a final model, from which PAI predictions were computed with cross-validation. Long-term PAI predictions were then compared to actual follow-up outcomes and post-treatment PAI predictions.
One predictor (parental alcohol abuse) and two moderators (recent life events; childhood maltreatment) were identified. Individuals assigned to their PAI-indicated treatment had lower follow-up depression severity compared to those assigned to their PAI-non-indicated treatment. This difference was significant in two subsets of the overall sample: those whose PAI score was in the upper 60%, and those whose PAI indicated CT, irrespective of magnitude. Long-term predictions did not overlap substantially with predictions for acute benefit.
If replicated, long-term PAI predictions could enhance precision medicine by selecting the optimal treatment for a given depressed individual over the long term.
The Hamilton Depression Rating Scale (HAMD) and the Beck Depression Inventory (BDI) are the most frequently used observer-rated and self-report scales of depression, respectively. It is important to know what a given total score or a change score from baseline on one scale means in relation to the other scale.
We obtained individual participant data from the randomised controlled trials of psychological and pharmacological treatments for major depressive disorders. We then identified corresponding scores of the HAMD and the BDI (369 patients from seven trials) or the BDI-II (683 patients from another seven trials) using the equipercentile linking method.
The HAMD total scores of 10, 20 and 30 corresponded approximately with the BDI scores of 10, 27 and 42 or with the BDI-II scores of 13, 32 and 50. The HAMD change scores of −20 and −10 with the BDI of −29 and −15 and with the BDI-II of −35 and −16.
The results can help clinicians interpret the HAMD or BDI scores of their patients in a more versatile manner and also help clinicians and researchers evaluate such scores reported in the literature or the database, when scores on only one of these scales are provided. We present a conversion table for future research.
Major depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits.
Within an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics.
Five pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58).
A subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.
The influence of baseline severity has been examined for antidepressant
medications but has not been studied properly for cognitive–behavioural
therapy (CBT) in comparison with pill placebo.
To synthesise evidence regarding the influence of initial severity on
efficacy of CBT from all randomised controlled trials (RCTs) in which
CBT, in face-to-face individual or group format, was compared with
pill-placebo control in adults with major depression.
A systematic review and an individual-participant data meta-analysis
using mixed models that included trial effects as random effects. We used
multiple imputation to handle missing data.
We identified five RCTs, and we were given access to individual-level
data (n = 509) for all five. The analyses revealed that
the difference in changes in Hamilton Rating Scale for Depression between
CBT and pill placebo was not influenced by baseline severity (interaction
P = 0.43). Removing the non-significant interaction
term from the model, the difference between CBT and pill placebo was a
standardised mean difference of –0.22 (95% CI –0.42 to –0.02,
P = 0.03, I2 = 0%).
Patients suffering from major depression can expect as much benefit from
CBT across the wide range of baseline severity. This finding can help
inform individualised treatment decisions by patients and their
Controversy exists over antidepressant use in bipolar II depression.
To compare the safety and effectiveness of antidepressant v. mood stabiliser monotherapy for bipolar type II major depressive episodes.
Randomised, double-blind, parallel-group, 12-week comparison of venlafaxine (n = 65) v. lithium (n = 64) monotherapy in adult out-patients (trial registration number NCT00602537).
Primary outcome – venlafaxine produced a greater response rate (67.7%) v. lithium (34.4%, P<0.001). Secondary outcomes – venlafaxine produced a greater remission rate (58.5% v. 28.1%, P<0.001); greater decline in depression symptom scores over time (β=–5.32, s.e. = 1.16, χ2 = 21.19, P<0.001); greater reduction in global severity scores over time (β=–1.05, s.e. = 0.22, χ2 = 22.33, P<0.001); and greater improvement in global change scores (β=–1.31, s.e. = 0.32, χ2 = 16.95, P<0.001) relative to lithium. No statistically significant or clinically meaningful differences in hypomanic symptoms were observed between treatments.
These findings suggest that short-term venlafaxine monotherapy may provide effective antidepressant treatment for bipolar II depression without a statistically significant increase in hypomanic symptoms relative to lithium.
Depression can adversely affect employment status.
To examine whether there is a relative advantage of cognitive therapy or
antidepressant medication in improving employment status following
treatment, using data from a previously reported trial.
Random assignment to cognitive therapy (n = 48) or the
selective serotonin reuptake inhibitor paroxetine (n =
93) for 4 months; treatment responders were followed for up to 24 months.
Differential effects of treatment on employment status were examined.
At the end of 28 months, cognitive therapy led to higher rates of
full-time employment (88.9%) than did antidepressant medication among
treatment responders (70.8%), χ21 = 5.78, P = 0.02, odds ratio (OR) = 5.66,
95% CI 1.16–27.69. In the shorter-term, the main effect of treatment on
employment status was not significant following acute treatment
(χ21 = 1.74, P = 0.19, OR = 1.77, 95% CI
0.75–4.17); however, we observed a site×treatment interaction
(χ21 = 6.87, P = 0.009) whereby cognitive
therapy led to a higher rate of full-time employment at one site but not
at the other.
Cognitive therapy may produce greater improvements in employment
v. medication, particularly over the longer term.
There is conflicting evidence about comorbid personality pathology in depression treatments.
To test the effects of antidepressant drugs and cognitive therapy in people with depression distinguished by the presence or absence of personality disorder.
Random assignment of 180 out-patients with depression to 16 weeks of antidepressant medication or cognitive therapy. Random assignment of medication responders to continued medication or placebo, and comparison with cognitive therapy responders over a 12-month period.
Personality disorder status led to differential response at 16 weeks; 66% v. 44% (antidepressants v. cognitive therapy respectively) for people with personality disorder, and 49% v. 70% (antidepressants v. cognitive therapy respectively) for people without personality disorder. For people with personality disorder, sustained response rates over the 12-month follow-up were nearly identical (38%) in the prior cognitive therapy and continuation-medication treatment arms. People with personality disorder withdrawn from medication evidenced the lowest sustained response rate (6%). Despite the poor response of people with personality disorder to cognitive therapy, nearly all those who did respond sustained their response.
Comorbid personality disorder was associated with differential initial response rates and sustained response rates for two well-validated treatments for depression.
This chapter highlights the influence of psychosocial factors on the course and outcome of chronic and treatment-resistant mood disorders, and reviews the potentially important therapeutic role of psychosocial interventions. Many individuals with a chronic or treatment-resistant mood disorder who show a full or partial symptomatic response to pharmacotherapy still exhibit considerable impairment in their social, family and work role functioning. The chapter describes and identifies the evidence for the effectiveness of psychosocial approaches with this patient population, with an emphasis on cognitive therapy (CT) in chronic affective disorders. If a specific psychotherapy is to be introduced, it is preferable to choose one of the time-limited, 'manualized' therapies, such as CT or interpersonal therapy (IPT), that are of proven efficacy in acute mood disorders. Although CT has been described as a 'manualized' approach, most cognitive therapists employ considerable flexibility in developing a customized case conceptualization and treatment plan for each patient.
Email your librarian or administrator to recommend adding this to your organisation's collection.