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Importance Antidepressants are commonly used to treat major depressive disorder (MDD). Antidepressant outcomes can vary based on individual differences; however, it is unclear whether specific factors determine this variability or whether it is at random. Objective To investigate the assumption of systematic variability in symptomatic response to antidepressants and to assess whether variability is associated with MDD severity, antidepressant class, or study publication year. Data Sources Data used were updated from a network meta-analysis of treatment with licensed antidepressants in adults with MDD. The Cochrane Central Register of Controlled Trials, CINAHL, Embase, LILACS database, MEDLINE, MEDLINE In-Process, and PsycInfo were searched from inception to March 21, 2019. Additional sources were international trial registries and sponsors, drug companies and regulatory agencies’ websites, and reference lists of published articles. Data were analyzed between June 8, 2020, and June 13, 2020. Study Selection Analysis was restricted to double-blind, randomized placebo-controlled trials with depression scores available at the study’s end point. Data Extraction and Synthesis Baseline means, number of participants, end point means and SDs of total depression scores, antidepressant type, and publication year were extracted. Main Outcomes and Measures Log SDs (blnσ̂)were derived for treatment groups (ie, antidepressant and placebo). A random-slope mixed-effects model was conducted to estimate the difference inblnσ̂ between treatment groups while controlling for end point mean. Secondary models determined whether differences in variability between groups were associated with baseline MDD severity; antidepressant class (selective serotonin reuptake inhibitors and other related drugs; serotonin and norepinephrine reuptake inhibitors; norepinephrine-dopamine reuptake inhibitors; noradrenergic agents; or other antidepressants); and publication year. Results In the 91 eligible trials (18 965 participants), variability in response did not differ significantly between antidepressants and placebo (blnσ̂, 1.02; 95% CI, 0.99-1.05;P = .19). This finding is consistent with a range of treatment effect SDs (up to 16.10), depending on the association between the antidepressant and placebo effects. Variability was not associated with baseline MDD severity or publication year. Responses to noradrenergic agents were 11% more variable than responses to selective serotonin reuptake inhibitors (blnσ̂, 1.11; 95% CI, 1.01-1.21;P = .02). Conclusions and Relevance Although this study cannot rule out the possibility of treatment effect heterogeneity, it does not provide empirical support for personalizing antidepressant treatment based solely on total depression scores. Future studies should explore whether individual symptom scores or biomarkers are associated with variability in response to antidepressants.

With the ongoing coronavirus disease 2019 (COVID-19) pandemic, psychiatrists find themselves in the clinical situation of being asked by patients, family members and patient advocacy societies to help ensure access to clozapine as a medication critical for ongoing patient care. To provide clozapine prescribing guidance and facilitate regulatory agencies modifying laboratory monitoring and/or dispensing requirements, an expert advisory subgroup of the Treatment Response and Resistance in Psychosis working group developed the following background, recommendations and rationale as a consensus statement.

We compliment the authors and journal for ensuring the “Consensus statement on the use of clozapine during the COVID-19 pandemic” was published in a timely fashion. Coronavirus disease 2019 (COVID-19) rapidly transformed into a pandemic, challenging medicine in ways initially not imagined; this is certainly the case not only for treatmentresistant schizophrenia and for reasons related to clozapine, but also the patient population.

Clear, accepted definitions of treatment resistance and response are needed so that clinical trials of treatments can be compared, and evidence can be meaningfully interpreted to inform clinical practice. In this chapter, we review the definitions of treatment response and resistance used in clinical trials, highlighting the variability in definitions used across studies, as well as a number of problems with the definitions used, including mixing treatment-intolerant patients with treatment-resistant patients and limited evaluation of the adequacy of treatment in many cases. The chapter then summarizes the work undertaken by the Treatment Response and Resistance in Psychosis working group to produce consensus guidelines and benchmarks to address these issues. Also reviewed are the principles underlying the concept of resistance developed by the working group. Finally, the chapter discusses the implications of these findings for clinical practice.

The early developments of brain positron emission tomography (PET), including the methodological advances that have driven progress, are outlined. The considerable past achievements of brain PET have been summarized in collaboration with contributing experts in specific clinical applications including cerebrovascular disease, movement disorders, dementia, epilepsy, schizophrenia, addiction, depression and anxiety, brain tumors, drug development, and the normal healthy brain. Despite a history of improving methodology and considerable achievements, brain PET research activity is not growing and appears to have diminished. Assessments of the reasons for decline are presented and strategies proposed for reinvigorating brain PET research. Central to this is widening the access to advanced PET procedures through the introduction of lower cost cyclotron and radiochemistry technologies. The support and expertize of the existing major PET centers, and the recruitment of new biologists, bio-mathematicians and chemists to the field would be important for such a revival. New future applications need to be identified, the scope of targets imaged broadened, and the developed expertize exploited in other areas of medical research. Such reinvigoration of the field would enable PET to continue making significant contributions to advance the understanding of the normal and diseased brain and support the development of advanced treatments.

Background: The glutamate model of schizophrenia proposes that altered glutamatergic neurotransmission is fundamental to the development of the disorder. In addition, its potential to mediate neurotoxicity raises the possibility that glutamate dysfunction could underlie neuroanatomic changes in schizophrenia. Here we determine whether changes in brain glutamate are present in subjects at ultra high risk of developing psychosis and whether these changes are related to reductions in cortical gray matter volume.Methods: Twenty-seven individuals with an at-risk mental state and a group of 27 healthy volunteers underwent proton magnetic resonance spectroscopy and volumetric proton magnetic resonance imaging using a 3-Tesla scanner. Glutamate and glutamine levels were measured in anterior cingulate, left hippocampus, and left thalamus. These measures were then related to cortical gray matter volume.Results: At-risk mental state (ARMS) subjects had significantly lower levels of glutamate than control subjects in the thalamus (p Conclusions: This study provides the first evidence that brain glutamate function is perturbed in people with prodromal signs of schizophrenia and that glutamatergic dysfunction is associated with a reduction in gray matter volume in brain regions thought to be critical to the pathogenesis of the disorder. These findings support the hypothesis that drugs affecting the glutamate system may be of benefit in the early stages of psychotic illness.