Impact of placebo arms on outcomes in antidepressant trials: systematic review and meta-regression analysis

Uncertainty of treatment efficacy moderates placebo effects on reinforcement learning

The placebo-reward hypothesis postulates that positive effects of treatment expectations on health (i.e., placebo effects) and reward processing share common neural underpinnings. Moreover, experiments in humans and animals indicate that reward uncertainty increases striatal dopamine, which is presumably involved in placebo responses and reward learning. Therefore, treatment uncertainty analogously to reward uncertainty may affect updating from rewards after placebo treatment. Here, we address whether different degrees of uncertainty regarding the efficacy of a sham treatment affect reward sensitivity. In an online between-subjects experiment with N = 141 participants, we systematically varied the provided efficacy instructions before participants first received a sham treatment that consisted of listening to binaural beats and then performed a probabilistic reinforcement learning task. We fitted a Q-learning model including two different learning rates for positive (gain) and negative (loss) reward prediction errors and an inverse gain parameter to behavioral decision data in the reinforcement learning task. Our results yielded an inverted-U-relationship between provided treatment efficacy probability and learning rates for gain, such that higher levels of treatment uncertainty, rather than of expected net efficacy, affect presumably dopamine-related reward learning. These findings support the placebo-reward hypothesis and suggest harnessing uncertainty in placebo treatment for recovering reward learning capabilities.

Antidepressants in the acute treatment of post-traumatic stress disorder in adults: a systematic review and meta-analysis

Currently, there are few pharmacotherapy options for clinicians treating post-traumatic stress disorder (PTSD), and antidepressants are usually the medication of choice. This meta-analysis aimed to review the efficacy of antidepressants in the acute treatment of PTSD in adults while investigating the contribution of study design and placebo response to the findings of these studies. Randomized, double-blind, placebo-controlled clinical trials that compared antidepressants with placebo for acute treatment of PTSD were selected. Standardized mean difference (SMD) in change in Clinician-Administered PTSD Scale scores were pooled after examining for heterogeneity. A random-effects meta-analysis was performed. Twenty-nine antidepressant-placebo comparisons, involving 4575 subjects, were analyzed. The SMD among all studies was 0.25, a small to medium effect size, lower than that in studies of antidepressants in adult major depressive disorder. The SMDs for low and high mean placebo responses, were 0.27 and 0.22, respectively. The overall SMD for paroxetine studies was in the moderate range (0.43) and that for sertraline studies was in the small range (0.12). Our findings suggest that antidepressants have modest efficacy in alleviating PTSD symptoms. Patient-level meta-analyses are required to further explore the potential clinical relevance of sertraline for PTSD.

Differential Outcomes of Placebo Treatment Across 9 Psychiatric Disorders: A Systematic Review and Meta-Analysis

Importance

Placebo is the only substance systematically evaluated across common psychiatric diagnoses, but comprehensive cross-diagnostic comparisons are lacking.

Objective

To compare changes in placebo groups in recent high-quality randomized clinical trials (RCTs) across a broad spectrum of psychiatric disorders in adult patients.

Data Sources

MEDLINE and the Cochrane Database of Systematic Reviews were systematically searched in March 2022 for the latest systematic reviews meeting predetermined high-quality criteria for 9 major psychiatric diagnoses.

Study Selection

Using these reviews, the top 10 highest-quality (ie, lowest risk of bias, according to the Cochrane Risk of Bias tool) and most recent placebo-controlled RCTs per diagnosis (totaling 90 RCTs) were selected, adhering to predetermined inclusion and exclusion criteria.

Data Extraction and Synthesis

Following the Cochrane Handbook, 2 authors independently carried out the study search, selection, and data extraction. Cross-diagnosis comparisons were based on standardized pre-post effect sizes (mean change divided by its SD) for each placebo group. This study is reported following the Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guideline.

Main Outcome and Measure

The primary outcome, pooled pre-post placebo effect sizes (dav) with 95% CIs per diagnosis, was determined using random-effects meta-analyses. A Q test assessed statistical significance of differences across diagnoses. Heterogeneity and small-study effects were evaluated as appropriate.

Results

A total of 90 RCTs with 9985 placebo-treated participants were included. Symptom severity improved with placebo in all diagnoses. Pooled pre-post placebo effect sizes differed across diagnoses (Q = 88.5; df = 8; P < .001), with major depressive disorder (dav = 1.40; 95% CI, 1.24-1.56) and generalized anxiety disorder (dav = 1.23; 95% CI, 1.06-1.41) exhibiting the largest dav. Panic disorder, attention-deficit/hyperactivity disorder, posttraumatic stress disorder, social phobia, and mania showed dav between 0.68 and 0.92, followed by OCD (dav = 0.65; 95% CI, 0.51-0.78) and schizophrenia (dav = 0.59; 95% CI, 0.41-0.76).

Conclusion and Relevance

This systematic review and meta-analysis found that symptom improvement with placebo treatment was substantial in all conditions but varied across the 9 included diagnoses. These findings may help in assessing the necessity and ethical justification of placebo controls, in evaluating treatment effects in uncontrolled studies, and in guiding patients in treatment decisions. These findings likely encompass the true placebo effect, natural disease course, and nonspecific effects.

Estimating the smallest worthwhile difference of antidepressants: a cross-sectional survey

BACKGROUND

Approximately 30% of patients experience substantial improvement in depression after 2 months without treatment, and 45% with antidepressants. The smallest worthwhile difference (SWD) refers to an intervention's smallest beneficial effect over a comparison patients deem worthwhile given treatment burdens (harms, expenses and inconveniences), but is undetermined for antidepressants.

OBJECTIVE

Estimating the SWD of commonly prescribed antidepressants for depression compared to no treatment.

METHODS

The SWD was estimated as a patient-required difference in response rates between antidepressants and no treatment after 2 months. An online cross-sectional survey using Prolific, MQ Mental Health and Amazon Mechanical Turk crowdsourcing services in the UK and USA between October 2022 and January 2023 garnered participants (N=935) that were a mean age of 44.1 (SD=13.9) and 66% women (n=617).

FINDINGS

Of 935 participants, 124 reported moderate-to-severe depressive symptoms but were not in treatment, 390 were in treatment and 495 reported absent-to-mild symptoms with or without treatment experiences. The median SWD was a 20% (IQR=10-30%) difference in response rates for people with moderate-to-severe depressive symptoms, not in treatment, and willing to consider antidepressants, and 25% (IQR=10-35%) for the full sample.

CONCLUSIONS

Our observed SWDs mean that the current 15% antidepressant benefit over no treatment was sufficient for one in three people to accept antidepressants given the burdens, but two in three expected greater treatment benefits.

IMPLICATIONS

While a minority may be satisfied with the best currently available antidepressants, more effective and/or less burdensome medications are needed, with more attention given to patient perspectives.

Escitalopram versus other antidepressive agents for major depressive disorder: a systematic review and meta-analysis

BACKGROUND

Escitalopram is selective serotonin reuptake inhibitors (SSRIs) and one of the most commonly prescribed newer antidepressants (ADs) worldwide. We aimed to explore the efficacy, acceptability and tolerability of escitalopram in comparison with other ADs in the acute-phase treatment of major depressive disorder (MDD).

METHODS

Medline/PubMed, EMBASE, the Cochrane Library, CINAHL, and Clinical Trials.gov were searched from inception to July 10, 2023. Trial databases of drug-approving agencies were hand-searched for published, unpublished and ongoing controlled trials. All randomized controlled trials comparing escitalopram against any other antidepressant for patients with MDD. Responders and remitters to treatment were calculated on an intention-to-treat basis. For dichotomous data, risk ratios (RRs) were calculated with 95% confidence intervals (CI). Continuous data were analyzed using standardized mean differences (with 95% CI) using the random effects model.

RESULTS

A total of 30 studies were included in this meta‑analysis, among which sixteen trials compared escitalopram with another SSRI and 14 compared escitalopram with a newer AD. Escitalopram was shown to be significantly more effective than citalopram in achieving acute response (RR 0.67, 95% CI 0.50-0.87). Escitalopram was also more effective than citalopram in terms of remission (RR 0.53, 95% CI 0.30-0.93).

CONCLUSIONS

Escitalopram was superior to other ADs for the acute phase treatment of MDD in terms of efficacy, acceptability and tolerability. However, no significant difference was found between escitalopram and other ADs in early response or follow-up response to treatment of MDD.

A new method for analyzing clinical trials in depression based on individual propensity to respond to placebo estimated using artificial intelligence

One of the major reasons for trial failures in major depressive disorders (MDD) is the presence of unpredictable levels of placebo response as the individual baseline propensity to respond to placebo is not adequately controlled by the current randomization and statistical methodologies. The individual propensity to respond to any treatment or intervention assessed at baseline was considered as a major non-specific prognostic and confounding effect. The objective of this paper was to apply the propensity score methodology to control for potential imbalance at baseline in the propensity to respond to placebo in clinical trials in MDD. Individual propensity was estimated using artificial intelligence (AI) applied to observations collected in two pre-randomization occasions. Cases study are presented using data from two randomized, placebo-controlled trials to evaluate the efficacy of paroxetine in MDD. AI models were used to estimate the individual propensity probability to show a treatment non-specific placebo effect. The inverse of the estimated probability was used as weight in the mixed-effects analysis to assess treatment effect. The comparison of the results obtained with and without propensity weight indicated that the weighted analysis provided an estimate of treatment effect and effect size significantly larger than the conventional analysis.

Artificial intelligence approach for the analysis of placebo-controlled clinical trials in major depressive disorders accounting for individual propensity to respond to placebo

Treatment effect in clinical trials for major depressive disorders (RCT) can be viewed as the resultant of treatment specific and non-specific effects. Baseline individual propensity to respond non-specifically to any treatment or intervention can be considered as a major non-specific confounding effect. The greater is the baseline propensity, the lower will be the chance to detect any treatment-specific effect. The statistical methodologies currently applied for analyzing RCTs doesn't account for potential unbalance in the allocation of subjects to treatment arms due to heterogenous distributions of propensity. Hence, the groups to be compared may be imbalanced, and thus incomparable. Propensity weighting methodology was used to reduce baseline imbalances between arms. A randomized, double-blind, placebo controlled, three arms, parallel group, 8-week, fixed-dose study to evaluate efficacy of paroxetine CR 12.5 and 25 mg/day is presented as a cases study. An artificial intelligence model was developed to predict placebo response at week 8 in subjects assigned to placebo arm using changes from screening to baseline of individual Hamilton Depression Rating Scale items. This model was used to predict the probability to respond to placebo in each subject. The inverse of the probability was used as weight in the mixed-effects model applied to assess treatment effect. The analysis with and without propensity weight indicated that the weighted analysis provided an estimate of treatment effect and effect-size about twice larger than the non-weighted analysis. Propensity weighting provides an unbiased strategy to account for heterogeneous and uncontrolled placebo effect making patients' data comparable across treatment arms.

Predictors of placebo response in three large clinical trials of the V1a receptor antagonist balovaptan in autism spectrum disorder

High rates of placebo response are increasingly implicated in failed autism spectrum disorder (ASD) clinical trials. Despite this, there are limited investigations of placebo response in ASD. We sought to identify baseline predictors of placebo response and quantify their influence on clinical scales of interest for three harmonized randomized clinical trials of balovaptan, a V1a receptor antagonist. We employed a two-step approach to identify predictors of placebo response on the Vineland-II two-domain composite (2DC) (primary outcome and a caregiver measure) and Clinical Global Impression (CGI) scale (secondary outcome and a clinician measure). The initial candidate predictor set of variables pertained to participant-level, site-specific, and protocol-related factors. Step 1 aimed to identify influential predictors of placebo response using Least Absolute Shrinkage and Selection Operator (LASSO) regression, while Step 2 quantified the influence of predictors via linear regression. Results were validated through statistical bootstrapping approaches with 500 replications of the analysis dataset. The pooled participant-level dataset included individuals with ASD aged 5 to 62 years (mean age 21 [SD 10]), among which 263 and 172 participants received placebo at Weeks 12 and 24, respectively. Although no influential predictors were identified for CGI, findings for Vineland-II 2DC are robust and informative. Decreased placebo response was predicted by higher baseline Vineland-II 2DC (i.e., more advanced adaptive function), longer trial duration, and European (vs United States) sites, while increased placebo response was predicted by commercial (vs academic) sites, attention deficit hyperactivity disorder and depression. Identification of these factors may be useful in anticipating and mitigating placebo response in drug development efforts in ASD and across developmental and psychiatric conditions.

Influence of active versus placebo control on treatment responses in randomised controlled trials in rheumatoid arthritis

OBJECTIVES

To investigate whether treatment effects of pharmaceutical compounds compared with placebo controls are systematically different to the effects of the same compounds compared with active treatment controls in rheumatoid arthritis (RA) clinical trials.

METHODS

We systematically identified randomised controlled trials (RCTs) in RA, and matched active treatment arms with comparable regimens, populations, background therapy, and outcome reporting, by the nature of their control group (active comparator or placebo). Medline, EMBASE and CENTRAL were used to identify RCTs investigating disease modifying anti-rheumatic drug therapies until December 2021. Using mixed-model logistic regression we estimated OddsRatios (OR) for achieving an American College of Rheumatology (ACR) 20/50/70% response at weeks 12 and 24. Risk of bias was assessed using the Cochrane Tool.

RESULTS

We screened 8328 studies and included 40 for analysis after detailed review of 590 manuscripts; unique compounds had significantly higher responses in active comparator trials compared with their effects observed in placebo controlled trials, with ORs of 1.67 (95% CI 1.46 to 1.91; p<0.001) for ACR20, 1.50 (95% CI 1.29 to 1.75; p<0.001) for ACR50 and 1.65 (95% CI 1.30 to 2.10; p<0.001) for ACR70 (week 12); corresponding ORs for ACR 20, 50, and 70 (week 24) were 1.93 (95% CI 1.50 to 2.48; p<0.001), 1.75 (95% CI 1.32 to 2.33; p<0.001) and 1.68 (95% CI 1.21 to 2.34; p<0.001), respectively. Sensitivity analyses showed consistent results.

CONCLUSION

Placebo controlled trials lead to smaller effect sizes of active compounds in RCTs compared with the same compound in head-to-head trials. This difference may be explained by potential nocebo effects in placebo-controlled settings and needs to be considered when interpreting head-to-head and placebo-controlled trials, by patients, investigators, sponsors and regulatory agencies.

Placebo: a brief updated review

Our aims were to provide updated information on placebo/nocebo effect and the potential use of placebo in clinical practice. This article can only provide a rough overview on the placebo and nocebo effect and is intended to serve as a starting point for the reader to go deeper into the corresponding literature. The placebo effect has been observed in multiple medical conditions, after oral administration, with manual therapies as well as with surgery and invasive procedures. The use of placebo in clinical trials is fundamental, although the ethics of its use is under discussion. The placebo may behave like a drug from the pharmacokinetic and pharmacodynamic point of view and can also be associated with adverse events (nocebo effect). Placebo can modify treatment by increasing or decreasing the effects of drugs. The factors associated with the occurrence of placebo effect are multiple, but in addition to those that depend on the placebo itself, the doctor-patient relationship would be the most important. As a result of findings that were published in the last two decades, the psycho-neurobiological basis of placebo is becoming better understood, although further studies are needed. In conclusion, the placebo effect in the clinic exhibits weak to moderate intensity. Placebo, in addition to its use in the clinical trial, should be considered another therapeutic remedy either as stand alone or in association with treatment, and could be useful in certain circumstances. The use of placebo should be regulated by the European health authorities through a guide in clinical practice that will improve patient care.

The intestinal microbiota as a predictor for antidepressant treatment outcome in geriatric depression: a prospective pilot study

OBJECTIVES

(1) To investigate if gut microbiota can be a predictor of remission in geriatric depression and to identify features of the gut microbiota that is associated with remission. (2) To determine if changes in gut microbiota occur with remission in geriatric depression.

DESIGN

Secondary analysis of a parent randomized placebo-controlled trial (NCT02466958).

SETTING

Los Angeles, CA, USA (2016-2018).

PARTICIPANTS

Seventeen subjects with major depressive disorder, over 60 years of age, 41.2% female.

INTERVENTION

Levomilacipran (LVM) or placebo.

MEASUREMENTS

Remission was defined by Hamilton Depression Rating Scale score of 6 or less at 12 weeks. 16S-ribosomal RNA sequencing based fecal microbiota composition and diversity were measured at baseline and 12 weeks. Differences in fecal microbiota were evaluated between remitters and non-remitters as well as between baseline and post-treatment samples. LVM and placebo groups were combined in all the analyses.

RESULTS

Baseline microbiota showed no community level α-diversity or β-diversity differences between remitters and non-remitters. At the individual taxa level, a random forest classifier created with nine genera from the baseline microbiota was highly accurate in predicting remission (AUC = .857). Of these, baseline enrichment of Faecalibacterium, Agathobacter and Roseburia relative to a reference frame was associated with treatment outcome of remission. Differential abundance analysis revealed significant genus level changes from baseline to post-treatment in remitters, but not in non-remitters.

CONCLUSIONS

This is the first study demonstrating fecal microbiota as a potential predictor of treatment response in geriatric depression. Our findings need to be confirmed in larger prospective studies.

Initial treatment choices to achieve sustained response in major depression: a systematic review and network meta-analysis

Major depression is often a relapsing disorder. It is therefore important to start its treatment with therapies that maximize the chance of not only getting the patients well but also keeping them well. We examined the associations between initial treatments and sustained response by conducting a network meta-analysis of randomized controlled trials (RCTs) in which adult patients with major depression were randomized to acute treatment with a psychotherapy (PSY), a protocolized antidepressant pharmacotherapy (PHA), their combination (COM), standard treatment in primary or secondary care (STD), or pill placebo, and were then followed up through a maintenance phase. By design, acute phase treatment could be continued into the maintenance phase, switched to another treatment or followed by discretionary treatment. We included 81 RCTs, with 13,722 participants. Sustained response was defined as responding to the acute treatment and subsequently having no depressive relapse through the maintenance phase (mean duration: 42.2±16.2 weeks, range 24-104 weeks). We extracted the data reported at the time point closest to 12 months. COM resulted in more sustained response than PHA, both when these treatments were continued into the maintenance phase (OR=2.52, 95% CI: 1.66-3.85) and when they were followed by discretionary treatment (OR=1.80, 95% CI: 1.21-2.67). The same applied to COM in comparison with STD (OR=2.90, 95% CI: 1.68-5.01 when COM was continued into the maintenance phase; OR=1.97, 95% CI: 1.51-2.58 when COM was followed by discretionary treatment). PSY also kept the patients well more often than PHA, both when these treatments were continued into the maintenance phase (OR=1.53, 95% CI: 1.00-2.35) and when they were followed by discretionary treatment (OR=1.66, 95% CI: 1.13-2.44). The same applied to PSY compared with STD (OR=1.76, 95% CI: 0.97-3.21 when PSY was continued into the maintenance phase; OR=1.83, 95% CI: 1.20-2.78 when PSY was followed by discretionary treatment). Given the average sustained response rate of 29% on STD, the advantages of PSY or COM over PHA or STD translated into risk differences ranging from 12 to 16 percentage points. We conclude that PSY and COM have more enduring effects than PHA. Clinical guidelines on the initial treatment choice for depression may need to be updated accordingly.

Determining maximal achievable effect sizes of antidepressant therapies in placebo-controlled trials

OBJECTIVE

Antidepressants outperform placebo with an effect size of around 0.30. It has been suggested that effect sizes as high as 0.875 are necessary for a minimal clinically important difference. Whether such effect sizes are achievable in placebo-controlled trials is unknown. Therefore, we aimed to assess what effect sizes are theoretically achievable in placebo-controlled trials of antidepressants.

METHODS

Patient-level analyses comparing Hamilton Depression Rating Scale (HDRS-17) outcomes for simulated antidepressant therapies to placebo-treated participants (n = 2201) from clinical trials of selective serotonin reuptake inhibitors.

RESULTS

An optimally effective antidepressant, where all treated participants achieve HDRS-17 scores comparable to those displayed by healthy volunteers (remission-type model), had a maximum effect size of 1.75, with a mean difference of 11.6 points on the HDRS-17. In simulations where patients received an additional 50% symptom reduction over that obtained with placebo (improvement-type model), the maximum effect size was 1.08 with a mean HDRS-17 difference of 7.2. When adjusting for normal rates of treatment discontinuation, maximum effect sizes were 1.10 (remission-type model) and 0.76 (improvement-type model) with HDRS-17 mean differences of 8.8 and 5.6, respectively.

CONCLUSIONS

Three methodological issues (i) a large and variable placebo response, (ii) a high rate of dropout and (iii) HDRS-17-ratings significantly larger than zero in healthy volunteers, reduce the degree of treatment-placebo separation achievable in depression trials. Assuming that those who discontinue treatment have only partial response, even a highly effective antidepressant would have difficulties surpassing such effect size cut-offs as have been suggested to signify a minimal clinically important difference.

Antidepressant prescriptions have not fully reflected evolving evidence from cumulative network meta-analyses and guideline recommendations

OBJECTIVES

This study compares three major elements of evidence-based medicine (EBM) practices, namely evidence synthesis, clinical practice guidelines (CPGs), and real-world prescriptions in the United States, regarding antidepressant treatments of major depression over the past 3 decades.

STUDY DESIGN AND SETTING

We conducted network meta-analyses (NMAs) of antidepressants every 5 years up to 2016 based on a comprehensive data set of double-blind randomized controlled trials. We identified CPGs and extracted their recommendations. We surveyed the prescriptions in the United States at 5-year intervals up to 2015.

RESULTS

Most drugs recommended by CPGs presented favorable performance in efficacy and acceptability in NMAs. However, CPG recommendations were often in terms of drug classes rather than individual drugs, whereas NMAs suggested distinctive difference between drugs within the same class. The update intervals of all CPGs were longer than 5 years. All the antidepressants prescribed frequently in the United States were recommended by CPGs. However, changes in prescriptions did not correspond to alterations in CPGs or to apparent changes in the effects indicated by NMAs. Many factors including marketing efforts, regulations, or patient values may have played a role.

CONCLUSION

Enhancements including accelerating CPG updates and monitoring the impact of marketing on prescriptions should be considered in future EBM implementation.

Trajectories of Function and Symptom Change in Desvenlafaxine Clinical Trials: Toward Personalized Treatment for Depression

PURPOSE/BACKGROUND

Heterogeneity has been documented in trajectories of symptom change during antidepressant treatment for major depressive disorder (MDD). It is unclear whether distinct trajectories of change exist for functioning during antidepressant treatment.

METHODS/PROCEDURES

This analysis explored distinct trajectories of functioning in MDD and tested whether they corresponded to trajectories of symptom change. Data were from 4317 patients and were pooled from 9 randomized placebo-controlled trials. Growth mixture modeling was used to identify trajectories of Hamilton Rating Scale for Depression (HRSD) and Sheehan Disability Scale (SDS) for placebo- and desvenlafaxine-treated patients.

FINDINGS/RESULTS

Three trajectories were identified for symptoms (HRSD) in patients receiving placebo (mean reduction baseline to week 8, -18.4 [most favorable] to -2.6 points [least favorable]). Four HRSD trajectories were identified for patients receiving desvenlafaxine (mean reduction from baseline to week 8, -17.2 [most favorable] to -2.6 points [least favorable]). Four trajectories were identified for functioning (SDS) in patients receiving placebo (mean reduction baseline to week 8, -13.6 [most favorable] to -0.8 points [least favorable]), and 3 for desvenlafaxine (-12.8 to -1.4 points, respectively). Percentages of agreement between most favorable HRSD and SDS trajectories were 75% (placebo) and 85% (desvenlafaxine), and for least favorable trajectories were 88% (placebo) and 80% (desvenlafaxine).

IMPLICATIONS/CONCLUSIONS

Distinct trajectories of change based on symptoms and functioning were identified among patients with MDD receiving desvenlafaxine and among patients with MDD receiving placebo. Differentiating subpopulations of patients has the potential to provide a more personalized treatment of patients with MDD.ClinicalTrials.govIdentifiers: NCT00072774; NCT00277823; NCT00300378; NCT00384033; NCT00798707; NCT00863798; NCT01121484; NCT00824291; NCT01432457.

Visualizing the evolution of evidence: Cumulative network meta-analyses of new generation antidepressants in the last 40 years

It is often challenging to present the available evidence in a timely and comprehensible manner. We aimed to visualize the evolution of evidence about antidepressants for depression by conducting cumulative network meta-analyses (NMAs) and to examine whether it could have helped the selection of optimal drugs. We built a Shiny web application that performs and presents cumulative NMAs based on R netmeta. We used a comprehensive dataset of double-blind randomized controlled trials of 21 antidepressants in the acute treatment of major depression. The primary outcomes were efficacy (treatment response) and acceptability (all-cause discontinuation), and treatment effects were summarized via odds ratios. We evaluated the confidence in evidence using the CINeMA (Confidence in Network Meta-Analysis) framework for a series of consecutive NMAs. Users can change several conditions for the analysis, such as the period of synthesis, among the others. We present the league tables and two-dimensional plots that combine efficacy, acceptability and level of confidence in the evidence together, for NMAs conducted in 1990, 1995, 2000, 2005, 2010, and 2016. They reveal that through the past four decades, newly approved drugs often showed initially exaggerated results, which tended to diminish and stabilize after approximately a decade. Over the years, the drugs with relative superiority changed dramatically; but as the evidence network grew larger and better connected, the overall confidence improved. The Shiny app visualizes how evidence evolved over years, emphasizing the need for a careful interpretation of relative effects between drugs, especially for the potentially amplified performance of newly approved drugs. HIGHLIGHTS: Network meta-analysis is considered to be a proper way of demonstrating the available evidence, since it allows comparisons between multiple interventions, and has been proved to be statistically powerful. It is challenging to present the voluminous results of NMA in an efficient and comprehendible manner. Evidence evolution based on the relatively new method NMA has not been investigated yet. The results of NMA should not only include the effects but also the confidence in the evidence, which can help interpret the findings appropriately. Effective use of rapidly developing statistical analysis and presentation tools such as Shiny package in R, may facilitate and simplify the visualization of NMA output. We should stay conservative towards new drugs, as their performance was often shown to be exaggerated initially, and it took time to become stable.

Network meta-analysis results against a fictional treatment of average performance: Treatment effects and ranking metric

BACKGROUND

Network meta-analysis (NMA) produces complex outputs as many comparisons between interventions are of interest. The estimated relative treatment effects are usually displayed in a forest plot or in a league table and several ranking metrics are calculated and presented.

METHODS

In this article, we estimate relative treatment effects of each competing treatment against a fictional treatment of average performance using the "deviation from the means" coding that has been used to parametrize categorical covariates in regression models. We then use this alternative parametrization of the NMA model to present a ranking metric (PreTA: Preferable Than Average) interpreted as the probability that a treatment is better than a fictional treatment of average performance.

RESULTS

We illustrate the alternative parametrization of the NMA model using two networks of interventions, a network of 18 antidepressants for acute depression and a network of four interventions for heavy menstrual bleeding. We also use these two networks to highlight differences among PreTA and existing ranking metrics. We further examine the agreement between PreTA and existing ranking metrics in 232 networks of interventions and conclude that their agreement depends on the precision with which relative effects are estimated.

CONCLUSIONS

A forest plot with NMA relative treatment effects using "deviation from means" coding could complement presentation of NMA results in large networks and in absence of an obvious reference treatment. PreTA is a viable alternative to existing probabilistic ranking metrics that naturally incorporates uncertainty.

Cortical Connectivity Moderators of Antidepressant vs Placebo Treatment Response in Major Depressive Disorder: Secondary Analysis of a Randomized Clinical Trial

IMPORTANCE

Despite the widespread awareness of functional magnetic resonance imaging findings suggesting a role for cortical connectivity networks in treatment selection for major depressive disorder, its clinical utility remains limited. Recent methodological advances have revealed functional magnetic resonance imaging-like connectivity networks using electroencephalography (EEG), a tool more easily implemented in clinical practice.

OBJECTIVE

To determine whether EEG connectivity could reveal neural moderators of antidepressant treatment.

DESIGN, SETTING, AND PARTICIPANTS

In this nonprespecified secondary analysis, data were analyzed from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinic Care study, a placebo-controlled, double-blinded randomized clinical trial. Recruitment began July 29, 2011, and was completed December 15, 2015. A random sample of 221 outpatients with depression aged 18 to 65 years who were not taking medication for depression was recruited and assessed at 4 clinical sites. Analysis was performed on an intent-to-treat basis. Statistical analysis was performed from November 16, 2018, to May 23, 2019.

INTERVENTIONS

Patients received either the selective serotonin reuptake inhibitor sertraline hydrochloride or placebo for 8 weeks.

MAIN OUTCOMES AND MEASURES

Electroencephalographic orthogonalized power envelope connectivity analyses were applied to resting-state EEG data. Intent-to-treat prediction linear mixed models were used to determine which pretreatment connectivity patterns were associated with response to sertraline vs placebo. The primary clinical outcome was the total score on the 17-item Hamilton Rating Scale for Depression, administered at each study visit.

RESULTS

Of the participants recruited, 9 withdrew after first dose owing to reported adverse effects, and 221 participants (150 women; mean [SD] age, 37.8 [12.7] years) underwent EEG recordings and had high-quality pretreatment EEG data. After correction for multiple comparisons, connectome-wide analyses revealed moderation by connections within and between widespread cortical regions-most prominently parietal-for both the antidepressant and placebo groups. Greater alpha-band and lower gamma-band connectivity predicted better placebo outcomes and worse antidepressant outcomes. Lower connectivity levels in these moderating connections were associated with higher levels of anhedonia. Connectivity features that moderate treatment response differentially by treatment group were distinct from connectivity features that change from baseline to 1 week into treatment. The group mean (SD) score on the 17-item Hamilton Rating Scale for Depression was 18.35 (4.58) at baseline and 26.14 (30.37) across all time points.

CONCLUSIONS AND RELEVANCE

These findings establish the utility of EEG-based network functional connectivity analyses for differentiating between responses to an antidepressant vs placebo. A role emerged for parietal cortical regions in predicting placebo outcome. From a treatment perspective, capitalizing on the therapeutic components leading to placebo response differentially from antidepressant response should provide an alternative direction toward establishing a placebo signature in clinical trials, thereby enhancing the signal detection in randomized clinical trials.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01407094.

Investigating Knowledge, Attitude, and Beliefs Regarding Placebo Interventions in Clinical Practice: A Comparative Study of Nursing and Medical University Students

BACKGROUND

Placebo interventions are commonly used in medical practice for alleviating symptoms of illnesses. Placebo is considered a pseudo-medication and its use is debatable ethically, professionally, and legally. Despite that there is also a lack of evidence on understanding of placebo interventions among health profession students. Further, no previous studies have been conducted to investigate whether future nurses and physicians differ in their knowledge, attitudes, and beliefs regarding placebo intervention.

MATERIALS AND METHODS

A comparative cross-sectional study was carried out for exploring knowledge, attitude, and beliefs about placebo interventions among a convenient sample of 187 medical and nursing students at King Saud bin Abdulaziz University for Health Sciences. Data were collected using a sociodemographic data sheet and a 32-item placebo knowledge, beliefs, and attitude scale, which was developed from the evidence-based literature. Validity and reliability were ensured through utilizing a panel of experts and internal consistency analysis.

RESULTS

Overall mean participants' knowledge score was 7.68±2.07 (out of 15). Nursing students showed significantly higher knowledge than medical students (P=0.028). More nursing than medical students believed in the effectiveness of placebo (P˂0.001). Medical students had a stronger belief that the placebo effect is mental, while nursing students reported that it is both mental and physiologic (P˂0.006). Concerning placebo attitude, medical students significantly pointed out that it should generally be prohibited and should not be permitted unless research supports its use (P˂0.001). Both groups agreed that impure placebo intervention involves deception.

CONCLUSION

Participants' overall placebo knowledge was low. Inconsistencies in attitude and beliefs were shown among students. Current study findings offered a unique opportunity to better study misunderstandings for placebo, which might open the gate for misuse and place patients at risk of deception. Additionally, study findings were imperative as a relevant evidence-based recommendation for nursing and medical educators could be achieved.

Comparative Efficacy and Acceptability of Pharmacological, Psychotherapeutic, and Combination Treatments in Adults With Posttraumatic Stress Disorder: A Network Meta-analysis

IMPORTANCE

Posttraumatic stress disorder (PTSD) is a prevalent mental disorder, with a high risk of chronicity, comorbidity, and functional impairment; PTSD is complicated to treat, and the debate on the best treatment approach is ongoing.

OBJECTIVE

To examine comparative outcomes and acceptability of psychotherapeutic and pharmacological treatments and their combinations in adults with PTSD.

DATA SOURCES

Embase, MEDLINE, PsycINFO, Cochrane Controlled Trials Register, and PSYNDEX were searched for studies published from January 1, 1980, to February 28, 2018. Reference lists of included studies and of previously published guidelines and systematic reviews were also searched.

STUDY SELECTION

Of 11 417 records identified, 12 published randomized clinical trials (RCTs) comprising 922 participants, contributing 23 direct comparisons between psychotherapeutic and pharmacological treatments or their combinations were included.

DATA EXTRACTION AND SYNTHESIS

Standardized mean differences (SMDs) and odds ratios were aggregated using random-effects network and pairwise meta-analyses. Risk of bias and indirectness was rated for each study, and network confidence was rated using the Confidence in Network Meta-Analysis framework.

MAIN OUTCOMES AND MEASURES

The primary outcome was the comparative benefit between 2 treatment approaches to PTSD symptom improvement, and secondary outcome was the comparative acceptability of the treatment approaches, as indicated by patient dropout rates before treatment termination.

RESULTS

No treatment approach was found to be superior at the end of treatment (for all, 95% CI included 0). At the last follow-up, psychotherapeutic treatments showed greater benefit than pharmacological treatments in both network (SMD, -0.83; 95% CI, -1.59 to -0.07) and pairwise (SMD, -0.63; 95% CI, -1.18 to -0.09, 3 RCTs) meta-analyses. No difference was found between combined treatments and psychotherapeutic treatments at long-term follow-up, and combined treatments were associated with better outcomes than pharmacological treatments in the network meta-analysis (SMD, -0.96; 95% CI, -1.87 to -0.04), but not in the pairwise meta-analysis, which included 2 RCTs (SMD, -1.02; 95% CI, -2.77 to 0.72). No evidence was found for differential acceptability of the 3 treatment approaches.

CONCLUSIONS AND RELEVANCE

These results suggest superiority of psychotherapeutic treatments over pharmacological treatments; network, but not pairwise, meta-analyses suggest superiority of combined treatments over pharmacological treatments in improving PTSD symptom severity in the long term. The scarcity of reported long-term findings hampers definite conclusions and demonstrates the need for robust evidence from large-scaled comparative trials providing long-term follow-up data.

Dismantling, personalising and optimising internet cognitive-behavioural therapy for depression: a study protocol for individual participant data component network meta-analysis

INTRODUCTION

Psychotherapy is a complex intervention, consisting of various components and being implemented flexibly in consideration of individual patient's characteristics. It is then of utmost importance to know which of the various components or combinations thereof are more efficacious, what their specific effect sizes are and which types of patients may benefit more from different components or their combinations.

METHODS AND ANALYSIS

Internet-delivered cognitive-behavioural therapy (iCBT) offers a unique opportunity to systematically review and quantitatively disentangle the efficacy of various components because, unlike face-to-face cognitive-behavioural therapy, it allows identification of constituent components that are actually delivered to patients. We will systematically identify all randomised controlled trials that compared any form of iCBT against another form or a control intervention in the acute phase treatment of adult depression. We will apply component network meta-analysis (cNMA) to dismantle efficacy of individual components. We will use individual participant data in the cNMA to identify participant-level prognostic factors and effect modifiers for different components.

ETHICS AND DISSEMINATION

The investigators of the primary trials will have obtained ethical approval for the data used in the present study and for sharing the data, if this was necessary, according to local requirements and was not covered from the initial ethic assessment. Results from this study will be published in peer-reviewed journals and presented at relevant conferences.

PROSPERO REGISTRATION NUMBER

CRD42018104683.

Development and validation of a prediction model for the probability of responding to placebo in antidepressant trials: a pooled analysis of individual patient data

BACKGROUND

Identifying potential placebo responders among apparent drug responders is critical to dissect drug-specific and nonspecific effects in depression.

OBJECTIVE

This project aimed to develop and test a prediction model for the probability of responding to placebo in antidepressant trials. Such a model will allow us to estimate the probability of placebo response among drug responders in antidepressants trials.

METHODS

We identified all placebo-controlled, double-blind randomised controlled trials (RCTs) of second generation antidepressants for major depressive disorder conducted in Japan and requested their individual patient data (IPD) to pharmaceutical companies. We obtained IPD (n=1493) from four phase II/III RCTs comparing mirtazapine, escitalopram, duloxetine, paroxetine and placebo. Out of 1493 participants in the four clinical trials, 440 participants allocated to placebo were included in the analyses. Our primary outcome was response, defined as 50% or greater reduction on Hamilton Rating Scale for Depression at study endpoint. We used multivariable logistic regression to develop a prediction model. All available candidate of predictor variables were tested through a backward variable selection and covariates were selected for the prediction model. The performance of the model was assessed by using Hosmer-Lemeshow test for calibration and the area under the ROC curve for discrimination.

FINDINGS

Placebo response rates differed between 31% and 59% (grand average: 43%) among four trials. Four variables were selected from all candidate variables and included in the final model: age at onset, age at baseline, bodily symptoms, and study-level difference. The final model performed satisfactorily in terms of calibration (Hosmer-Lemeshow p=0.92) and discrimination (the area under the ROC curve (AUC): 0.70).

CONCLUSIONS

Our model is expected to help researchers discriminate individuals who are more likely to respond to placebo from those who are less likely so.

CLINICAL IMPLICATIONS

A larger sample and more precise individual participant information should be collected for better performance. Examination of external validity in independent datasets is warranted.

TRIAL REGISTRATION NUMBER

CRD42017055912.

Evidence synthesis, practice guidelines and real-world prescriptions of new generation antidepressants in the treatment of depression: a protocol for cumulative network meta-analyses and meta-epidemiological study

INTRODUCTION

Depressive disorders are the most common, burdensome and costly mental disorders. Their treatments have developed through the past decades and we now have more than a dozen new generation antidepressants, while a series of guidelines have been published to provide recommendations over the years. However, there still may exist important gaps in this evidence synthesis and implementation process. Systematic reviews may not have been conducted in the most unbiased, informative and timely manners; guidelines may not have reflected the most up-to-date evidence; clinicians may not have changed their clinical decision-makings in accordance with the relevant evidence. The aim of this study is to examine the gaps between the ideally synthesised evidence, guideline recommendations and real-world clinical practices in the prescription of new generation antidepressants for major depression through the past three decades.

METHODS AND ANALYSIS

We will conduct cumulative network meta-analyses (cNMAs) based on the comprehensive systematic review which has identified published and unpublished head-to-head randomised controlled trials comparing the following antidepressants in the acute phase treatment of major depression: agomelatine, amitriptyline, bupropion, citalopram, clomipramine, desvenlafaxine, duloxetine, escitalopram, fluoxetine, fluvoxamine, levomilnacipran, milnacipran, mirtazapine, nefazodone, paroxetine, reboxetine, sertraline, trazodone, venlafaxine, vilazodone and vortioxetine. The primary outcomes will be the proportions of patients who responded (efficacy) and who withdrew from treatment for any reasons (acceptability). We will conduct a random effects cNMA to synthesise evidence and obtain a comprehensive ranking of all new generation antidepressants based on their surface under the cumulative ranking curves. We will identify series of international clinical practice guidelines for the treatment of major depression of adults and summarise their recommendations. We will estimate real-world prescription patterns of antidepressants in the nationally representative samples in USA in the Medical Expenditure Panel Survey. We will compare and evaluate the gaps between the rankings according to cNMAs conducted at 5-year intervals between 1990 and 2015, recommendations in guidelines published in the ensuing 5 years and actual practices thereafter.

ETHICS AND DISSEMINATION

This review does not require ethical approval. We will disseminate our findings through publications in peer-reviewed journals and presentations at conferences.

TRIAL REGISTRATION NUMBER

UMIN000031898.