Clozapine response trajectories and predictors of non-response in treatment-resistant schizophrenia: a chart review study

Response to clozapine and its predictors in treatment-resistant schizophrenia spectrum disorders: A retrospective chart review

The response rate to clozapine in patients with treatment-resistant schizophrenia spectrum disorders (TRSS) is around 40 %. But, in general, a better prognosis is noted for schizophrenia in developing countries, including India. Given the scarcity of related literature from India, this study aimed to evaluate the response rates to clozapine in TRSS and explore predictors of response. Sociodemographic and clinical information from randomly selected 250 patients on clozapine for TRSS was collected through a retrospective chart review. Clozapine response was determined using the Clinical Global Impression-Schizophrenia scale at 6, 12, 24 weeks, and one year of initiating clozapine. Elastic net logistic regression analysis was performed to identify predictors of clozapine response. A total of 54 % responded to clozapine, with much or very much improvement in positive and overall symptoms of schizophrenia by the end of 12 weeks of clozapine initiation. Among all the responders at 12 weeks, 94 % continued to maintain response at one-year follow-up, and among non-responders, 34.2 % showed clinical improvement by 1-year follow-up. Lower symptom severity at baseline, good response to clozapine at six weeks, history of more suicidal attempts, and few other clinical symptoms like delusions and sociodemographic factors predicted a response to clozapine. A higher response rate (54 %) to clozapine is noted in 3rd month of clozapine, contrasting with the existing literature. Persistence of treatment could elicit further response over a year in early non-responders. Our study findings revealed that the demographic profile and clinical determinants may have an effect on clozapine response.

Predicting treatment resistance in positive and negative symptom domains from first episode psychosis: Development of a clinical prediction model

BACKGROUND

Treatment resistance (TR) in schizophrenia may be defined by the persistence of positive and/or negative symptoms despite adequate treatment. Whilst previous investigations have focused on positive symptoms, negative symptoms are highly prevalent, impactful, and difficult to treat. In the current study we aimed to develop easily employable prediction models to predict TR in positive and negative symptom domains from first episode psychosis (FEP).

METHODS

Longitudinal cohort data from 1027 individuals with FEP was utilised. Using a robust definition of TR, n = 51 (4.97 %) participants were treatment resistant in the positive domain and n = 56 (5.46 %) treatment resistant in the negative domain 12 months after first presentation. 20 predictor variables, selected by existing evidence and availability in clinical practice, were entered into two LASSO regression models. We estimated the models using repeated nested cross-validation (NCV) and assessed performance using discrimination and calibration measures.

RESULTS

The prediction model for TR in the positive domain showed good discrimination (AUC = 0.72). Twelve predictor variables (male gender, cannabis use, age, positive symptom severity, depression and academic and social functioning) were retained by each outer fold of the NCV procedure, indicating importance in prediction of the outcome. However, our negative domain model failed to discriminate those with and without TR, with results only just over chance (AUC = 0.56).

CONCLUSIONS

Treatment resistance of positive symptoms can be accurately predicted from FEP using routinely collected baseline data, however prediction of negative domain-TR remains a challenge. Detailed negative symptom domains, clinical data, and biomarkers should be considered in future longitudinal studies.

Clozapine treatment and astrocyte activity in treatment resistant schizophrenia: A proton magnetic resonance spectroscopy study

Clozapine is the only antipsychotic approved for treating treatment-resistant schizophrenia (TRS), characterized by persistent positive symptoms despite adequate antipsychotic treatment. Unfortunately, clozapine demonstrates clinical efficacy in only ~30-60 % of patients with TRS (clozapine-responders; ClzR+), while the remaining ~40-70 % are left with no pharmacological recourse for improvement (clozapine-resistant; ClzR-). Mechanism(s) underlying clozapine's superior efficacy remain unclear. However, in vitro evidence suggests clozapine may mitigate glutamatergic dysregulations observed in TRS, by modulating astrocyte activity in ClzR+, but not ClzR-. A factor that if proven correct, may help the assessment of treatment response and development of more effective antipsychotics. To explore the presence of clozapine-astrocyte interaction and clinical improvement, we used 3 T proton-magnetic resonance spectroscopy to quantify levels of myo-Inositol, surrogate biomarker of astrocyte activity, in regions related to schizophrenia neurobiology: Dorsal-anterior-cingulate-cortex (dACC), left-dorsolateral-prefrontal-cortex (left-DLPFC), and left-striatum (left-striatum) of 157 participants (ClzR- = 30; ClzR+ = 37; responders = 38; controls = 52). Clozapine treatment was assessed using clozapine to norclozapine plasma levels, 11-12 h after last clozapine dose. Measures for symptom severity (i.e., Positive and Negative Symptoms Scale) and cognition (i.e., Mini-Mental State Examination) were also recorded. Higher levels of myo-Inositol were observed in TRS groups versus responders and controls (dACC (p < 0.001); left-striatum (p = 0.036); left-DLPFC (p = 0.023)). In ClzR+, but not ClzR-, clozapine to norclozapine ratios were positively associated with myo-Inositol levels (dACC (p = 0.004); left-DLPFC (p < 0.001)), and lower positive symptom severity (p < 0.001). Our results support growing in vitro evidence of clozapine-astrocyte interaction in clozapine-responders. Further research may determine the viability of clozapine-astrocyte interactions as an early marker of clozapine response.

Elevated intrinsic cortical curvature in treatment-resistant schizophrenia: Evidence of structural deformation in functional connectivity areas and comparison with alternate indices of structure

BACKGROUND

Research suggests structural and connectivity abnormalities in patients with treatment-resistant schizophrenia (TRS) compared to first-line responders and healthy-controls. However, measures of these abnormalities are often influenced by external factors like nicotine and antipsychotics, limiting their clinical utility. Intrinsic-cortical-curvature (ICC) presents a millimetre-scale measure of brain gyrification, highly sensitive to schizophrenia differences, and associated with TRS-like traits in early stages of the disorder. Despite this evidence, ICC in TRS remains unexplored. This study investigates ICC as a marker for treatment resistance in TRS, alongside structural indices for comparison.

METHODS

We assessed ICC in anterior cingulate, dorsolateral prefrontal, temporal, and parietal cortices of 38 first-line responders, 30 clozapine-resistant TRS, 37 clozapine-responsive TRS, and 52 healthy-controls. For comparative purposes, Fold and Curvature indices were also analyzed.

RESULTS

Adjusting for age, sex, nicotine-use, and chlorpromazine equivalence, principal findings indicate ICC elevations in the left hemisphere dorsolateral prefrontal (p < 0.001, η2partial = 0.142) and temporal cortices (LH p = 0.007, η2partial = 0.060; RH p = 0.011, η2partial = 0.076) of both TRS groups, and left anterior cingulate cortex of clozapine-resistant TRS (p = 0.026, η2partial = 0.065), compared to healthy-controls. Elevations that correlated with reduced cognition (p = 0.001) and negative symptomology (p < 0.034) in clozapine-resistant TRS. Fold and Curvature indices only detected group differences in the right parietal cortex, showing interactions with age, sex, and nicotine use. ICC showed interactions with age.

CONCLUSION

ICC elevations were found among patients with TRS, and correlated with symptom severity. ICCs relative independence from sex, nicotine-use, and antipsychotics, may support ICC's potential as a viable marker for TRS, though age interactions should be considered.

Aberrant connectivity in the hippocampus, bilateral insula and temporal poles precedes treatment resistance in first-episode psychosis: a prospective resting-state functional magnetic resonance imaging study with connectivity concordance mapping

Functional connectivity resting-state functional magnetic resonance imaging has been proposed to predict antipsychotic treatment response in schizophrenia. However, only a few prospective studies have examined baseline resting-state functional magnetic resonance imaging data in drug-naïve first-episode schizophrenia patients with regard to subsequent treatment response. Data-driven approaches to conceptualize and measure functional connectivity patterns vary broadly, and model-free, voxel-wise, whole-brain analysis techniques are scarce. Here, we apply such a method, called connectivity concordance mapping to resting-state functional magnetic resonance imaging data acquired from an Asian sample (n = 60) with first-episode psychosis, prior to pharmaceutical treatment. Using a longitudinal design, 12 months after the resting-state functional magnetic resonance imaging, we measured and classified patients into two groups based on psychometric testing: treatment responsive and treatment resistant. Next, we compared the two groups' connectivity concordance maps that were derived from the resting-state functional magnetic resonance imaging data at baseline. We have identified consistently higher functional connectivity in the treatment-resistant group in a network including the left hippocampus, bilateral insula and temporal poles. These data-driven novel findings can help researchers to consider new regions of interest and facilitate biomarker development in order to identify treatment-resistant schizophrenia patients early, in advance of treatment and at the time of their first psychotic episode.

Deconstructing the genetic architecture of treatment-resistant schizophrenia in East Asian ancestry

BACKGROUND

Treatment-resistant schizophrenia (TRS) affects a substantial proportion of patients who do not respond adequately to antipsychotic medications, yet the underlying biological mechanism remains poorly understood. This study investigates the link between the genetic predisposition to schizophrenia and TRS.

METHODS

857 individuals diagnosed with schizophrenia were divided into TRS (n = 142) and non-TRS (n = 715) based on well-defined TRS criteria. Polygenic risk scores (PRS) were calculated using schizophrenia genome-wide association summary statistics from East-Asian and European ancestry populations. PRS was estimated using both P-value thresholding and Bayesian framework methods. Logistic regression analyses were performed to differentiate between TRS and non-TRS individuals.

RESULTS

The schizophrenia PRS derived from the East-Asian training dataset effectively distinguished between TRS and non-TRS individuals (R2 = 0.029, p = 4.86 ×10-5, pT = 0.1, OR = 1.52, 95% CI = 1.242-1.861), with higher PRS values observed in the TRS group. Similar PRS analysis was conducted based on the European ancestry GWAS summary statistics, but we found superior prediction based on the East-Asian ancestry discovery data.

CONCLUSION

This study reveals an association between common risk variants for schizophrenia and TRS status, suggesting that the genetic burden of schizophrenia may partly contribute to treatment resistance in individuals with schizophrenia. These findings propose the potential use of genetic risk factors for early TRS identification and timely access to clozapine. However, the ancestral background of the discovery sample is crucial for successfully implementing PRS in clinical settings.

Enhancing Predictive Power: Integrating a Linear Support Vector Classifier with Logistic Regression for Patient Outcome Prognosis in Virtual Reality Therapy for Treatment-Resistant Schizophrenia

(1) Background: Approximately 30% of schizophrenia patients are known to be treatment-resistant. For these cases, more personalized approaches must be developed. Virtual reality therapeutic approaches such as avatar therapy (AT) are currently undergoing investigations to address these patients' needs. To further tailor the therapeutic trajectory of patients presenting with this complex presentation of schizophrenia, quantitative insight about the therapeutic process is warranted. The aim of the study is to combine a classification model with a regression model with the aim of predicting the therapeutic outcomes of patients based on the interactions taking place during their first immersive session of virtual reality therapy. (2) Methods: A combination of a Linear Support Vector Classifier and logistic regression was conducted over a dataset comprising 162 verbatims of the immersive sessions of 18 patients who previously underwent AT. As a testing dataset, 17 participants, unknown to the dataset, had their first immersive session presented to the combinatory model to predict their clinical outcome. (3) Results: The model accurately predicted the clinical outcome for 15 out of the 17 participants. Classification of the therapeutic interactions achieved an accuracy of 63%. (4) Conclusion: To our knowledge, this is the first attempt to predict the outcome of psychotherapy patients based on the content of their interactions with their therapist. These results are important as they open the door to personalization of psychotherapy based on quantitative information about the interactions taking place during AT.

Antipsychotic Use: Cross-Sectional Opinion Survey of Psychiatrists in India and United Kingdom

The aim of this survey of psychiatrists from the UK and India was to compare their opinions on antipsychotic medication choice and their experiences of such medications' effectiveness and tolerability in patients who were newly diagnosed with acute schizophrenia. Following ethical approval, a cross-sectional online survey of psychiatrists from the UK and India was conducted. Ninety-five responses were received from each country. The most selected first-line APDs in both countries were olanzapine (47.5%), risperidone (42.8%) and aripiprazole (25.3%). A total of 60% of psychiatrists from India (60%) and 48% from the UK (48%) selected 'medication efficacy' as the main factor in their choice. Reassessment and consideration to switch most often took place within 4-6 weeks (53.7%) and 3-6 months (11.6%). The major reasons for switching antipsychotic medications were poor clinical efficacy (69%) and lack of tolerability (45%). Nonadherence was the most common reason for relapse (90% of UK psychiatrists and 70% of Indian psychiatrists), followed by illicit drug use (27.6%). The most commonly reported side effects that led to nonadherence were weight gain (10.8%), drowsiness (10.4%), erectile dysfunction and movement disorders (equally 8.7%). It was concluded that olanzapine, risperidone and aripiprazole are the most commonly selected as the initial treatment choice by psychiatrists from India and the UK. They are perceived as widely effective and well tolerated.

Developing prediction models for symptom severity around the time of discharge from a tertiary-care program for treatment-resistant psychosis

Antipsychotics are the only therapeutic class indicated in the symptomatic management of psychotic disorders. However, individuals diagnosed with schizophrenia or schizoaffective disorder may not always benefit from these first-line agents. This refractoriness to conventional treatment can be difficult to address in most clinical settings. Therefore, a referral to a tertiary-care program that is better able to deliver specialized care in excess of the needs of most individuals may be necessary. The average outcome following a period of treatment at these programs tends to be one of improvement. Nonetheless, accurate prognostication of individual-level responses may be useful in identifying those who are unlikely to improve despite receiving specialized care. Thus, the main objective of this study was to predict symptom severity around the time of discharge from the Refractory Psychosis Program in British Columbia, Canada using only clinicodemographic information and prescription drug data available at the time of admission. To this end, a different boosted beta regression model was trained to predict the total score on each of the five factors of the Positive and Negative Syndrome Scale (PANSS) using a data set composed of 320 hospital admissions. Internal validation of these prediction models was then accomplished by nested cross-validation. Insofar as it is possible to make comparisons of model performance across different outcomes, the correlation between predictions and observations tended to be higher for the negative and disorganized factors than the positive, excited, and depressed factors on internal validation. Past scores had the greatest effect on the prediction of future scores across all 5 factors. The results of this study serve as a proof of concept for the prediction of symptom severity using this specific approach.

Long-Term Outcome of Clozapine in Treatment-Resistant Schizophrenia

PURPOSE/BACKGROUND

The favorable effect of clozapine on psychotic symptoms in patients with treatment-resistant (TR) schizophrenia (SCZ) in short-term studies is well established. However, prospective studies of the long-term outcome of clozapine treatment on psychopathology, cognition, quality of life, and functional outcome in TR-SCZ are limited.

METHODS/PROCEDURES

Here, we have examined the long-term (mean duration of follow-up 14 years) effects of clozapine on those outcomes in a prospective, open label study in 54 TR-SCZ patients. Assessments were performed at baseline, 6 weeks, 6 months, and at the last follow-up.

FINDINGS/RESULTS

Brief Psychiatric Rating Scale (BPRS) total, positive symptoms, and anxiety/depression at the last follow-up improved significantly from baseline, as well as from the 6-month evaluation ( P < 0.0001), with a 70.5% responder rate (≥20% improvement at the last follow-up from baseline). Quality of Life Scale (QLS) total improved by 72% at the last follow-up, with 24% of patients rated as having "good" functioning compared with 0% at baseline. Suicidal thoughts/behavior was significantly reduced at the last follow-up from the baseline. No significant change in negative symptoms was found at the last follow-up in the total sample. Short-term memory function declined at the last follow-up from baseline, but there was no significant change in processing speed. The QLS total showed a significant negative correlation with BPRS positive symptoms but not with cognitive measures, or negative symptoms, at the last follow-up.

IMPLICATIONS/CONCLUSIONS

For patients with TR-SCZ, improving psychotic symptoms with clozapine seems to have a more significant impact than negative symptoms or cognition on improving psychosocial function.

Lost in Translation: Challenges in the Diagnosis and Treatment of Early-Onset Schizophrenia

Early-onset schizophrenia (EOS) is a heterogeneous condition that has a serious, insidious clinical course and poor long-term mental health outcomes. The clinical presentations are highly complex due to the overlapping symptomatology with other illnesses, which contributes to a delay in the diagnosis. The objective of the review is to study if an earlier age of onset (AAO) of EOS has poor clinical outcomes, the diagnostic challenges of EOS, and effective treatment strategies. The review provides a comprehensive literature search of 5966 articles and summarizes 126 selected for empirical evidence to methodically consider challenges in diagnosing and treating EOS for practicing clinicians. The risk factors of EOS are unique but have been shared with many other neuropsychiatric illnesses. Most of the risk factors, including genetics and obstetric complications, are nonmodifiable. The role of early diagnosis in reducing the duration of untreated psychosis (DUP) remains critical to reducing overall morbidity. Many specific issues contribute to the risk and clinical outcomes. Therefore, issues around diagnostic ambiguity, treatment resistance, nonadherence, and rehospitalizations further extend the DUP. There is hesitancy to initiate clozapine early, even though the empirical evidence strongly supports its use. There is a growing body of research that suggests the use of long-acting injectables to address nonadherence, and these measures are largely underutilized in acute settings. The clinical presentations of EOS are complex. In addition to the presence of specific risk factors, patients with an early onset of illness are also at a higher risk for treatment resistance. While there is a need to develop tools for early diagnosis, established evidence-based measures to address nonadherence, psychoeducation, and resistance must be incorporated into the treatment planning.

Second to none: rationale, timing, and clinical management of clozapine use in schizophrenia

Despite its enduring relevance as the single most effective and important evidence-based treatment for schizophrenia, underutilization of clozapine remains considerable. To a substantial degree, this is attributable to a reluctance of psychiatrists to offer clozapine due to its relatively large side-effect burden and the complexity of its use. This underscores the necessity for continued education regarding both the vital nature and the intricacies of clozapine treatment. This narrative review summarizes all clinically relevant areas of evidence, which support clozapine's wide-ranging superior efficacy - for treatment-resistant schizophrenia (TRS) and beyond - and make its safe use eminently feasible. Converging evidence indicates that TRS constitutes a distinct albeit heterogeneous subgroup of schizophrenias primarily responsive to clozapine. Most importantly, the predominantly early onset of treatment resistance and the considerable decline in response rates associated with its delayed initiation make clozapine an essential treatment option throughout the course of illness, beginning with the first psychotic episode. To maximize patients' benefits, systematic early recognition efforts based on stringent use of TRS criteria, a timely offer of clozapine, thorough side-effect screening and management as well as consistent use of therapeutic drug monitoring and established augmentation strategies for suboptimal responders are crucial. To minimize permanent all-cause discontinuation, re-challenges after neutropenia or myocarditis should be considered. Owing to clozapine's unique efficacy, comorbid conditions including substance use and most somatic disorders should not dissuade but rather encourage clinicians to consider clozapine. Moreover, treatment decisions need to be informed by the late onset of clozapine's full effects, which for reduced suicidality and mortality rates may not even be readily apparent. Overall, the singular extent of its efficacy combined with the high level of patient satisfaction continues to distinguish clozapine from all other available antipsychotics.

Dopamine supersensitivity psychosis and delay of clozapine treatment in patients with treatment-resistant schizophrenia

Both the underutilization of clozapine and treatment resistance of patients to clozapine are serious problems worldwide. Identifying clinical markers predicting response to clozapine would help clinicians more effectively utilize clozapine treatment. The present study retrospectively assessed dopamine supersensitivity psychosis (DSP) in addition to other measures such as age at disease onset and delay of clozapine introduction for a total of 47 treatment-resistant schizophrenia (TRS) patients. The response to clozapine was judged with CGI-C at 1 and 2 years from clozapine introduction. Results revealed that the DSP group tended to have a longer delay between designation of TRS and introduction of clozapine and continued to have slightly more severe psychopathology after treatment with clozapine, showing only slight improvement. The logistic regression analysis showed that the age at disease onset was the only significant indicator, predicting responsiveness to clozapine: patients with an onset age <20 years had a significantly better response to clozapine than patients with an onset age ≥20 years. The present study suggests that DSP might be related to a longer delay in clozapine introduction and the persistence of refractory symptoms despite clozapine treatment, whereas early age of disease onset might be related to a better response to clozapine.

Feasibility and Effect of Increasing Clozapine Plasma Levels in Long-Stay Patients With Treatment-Resistant Schizophrenia

BACKGROUND

It is unknown whether increasing the clozapine plasma level to 400, 750, or even 1000 ng/mL is a feasible and effective strategy in patients with treatment-resistant schizophrenia (TRS). We investigated this in long-stay patients with TRS.

METHODS

In long-stay TRS patients, doses of clozapine were increased gradually to reach target plasma levels of 400, 750, or 1000 ng/mL, depending on the clinical response and tolerability. After an effective or tolerated level was reached, positive and negative syndrome scale scores were evaluated after 3 months and 1 year.

RESULTS

Twenty-eight patients were included. Overall, 54% of the patients, and especially patients 60 years and older, could not achieve one of the clozapine target levels because of adverse effects. Three physically vulnerable patients died, probably not directly related to clozapine use. Although only 21% of patients achieved a more than 20% reduction in total symptoms at the 1-year follow-up, the mean severity of positive symptoms decreased from 18.18 to 15.10 ( P < 0.01). The largest decrease in positive symptoms was seen in TRS patients who achieved a plasma level of 750 ng/mL of clozapine.

CONCLUSIONS

Most TRS patients older than 60 years could not tolerate high clozapine levels and so this should not be attempted in older or otherwise physically vulnerable patients. Increasing clozapine levels to approximately 750 ng/mL in middle-aged patients with longstanding TRS may modestly reduce the severity of positive symptoms and improve the response rate.

Decreased cortical gyrification and surface area in the left medial parietal cortex in patients with treatment-resistant and ultratreatment-resistant schizophrenia

AIM

Validating the vulnerabilities and pathologies underlying treatment-resistant schizophrenia (TRS) is an important challenge in optimizing treatment. Gyrification and surface area (SA), reflecting neurodevelopmental features, have been linked to genetic vulnerability to schizophrenia. The aim of this study was to identify gyrification and SA abnormalities specific to TRS.

METHODS

We analyzed 3T magnetic resonance imaging findings of 24 healthy controls (HCs), 20 responders to first-line antipsychotics (FL-Resp), and 41 patients with TRS, including 19 clozapine responders (CLZ-Resp) and 22 FL- and clozapine-resistant patients (patients with ultratreatment-resistant schizophrenia [URS]). The local gyrification index (LGI) and associated SA were analyzed across groups. Diagnostic accuracy was verified by receiver operating characteristic curve analysis.

RESULTS

Both CLZ-Resp and URS had lower LGI values than HCs (P = 0.041, Hedges g [g_H ] = 0.75; P = 0.013, g_H  = 0.96) and FL-Resp (P = 0.007, g_H  = 1.00; P = 0.002, g_H  = 1.31) in the left medial parietal cortex (Lt-MPC). In addition, both CLZ-Resp and URS had lower SA in the Lt-MPC than FL-Resp (P < 0.001, g_H  = 1.22; P < 0.001, g_H  = 1.75). LGI and SA were positively correlated in non-TRS (FL-Resp) (ρ = 0.64, P = 0.008) and TRS (CLZ-Resp + URS) (ρ = 0.60, P < 0.001). The areas under the receiver operating characteristic curve for non-TRS versus TRS with LGI and SA in the Lt-MPC were 0.79 and 0.85, respectively. SA in the Lt-MPC was inversely correlated with negative symptoms (ρ = -0.40, P = 0.018) and clozapine plasma levels (ρ = -0.35, P = 0.042) in TRS.

CONCLUSION

LGI and SA in the Lt-MPC, a functional hub in the default-mode network, were abnormally reduced in TRS compared with non-TRS. Thus, altered LGI and SA in the Lt-MPC might be structural features associated with genetic vulnerability to TRS.

Gamma-aminobutyric acid (GABA) levels in the midcingulate cortex and clozapine response in patients with treatment-resistant schizophrenia: A proton magnetic resonance spectroscopy (1 H-MRS) study

BACKGROUND

Gamma-Aminobutyric Acid (GABA) is the primary inhibitory neurotransmitter in the central nervous system. GABAergic dysfunction has been implicated in the pathophysiology of schizophrenia. Clozapine, the only approved drug for treatment-resistant schizophrenia (TRS), involves the GABAergic system as one of its targets. However, no studies have investigated the relationship between brain GABA levels, as measured by proton magnetic resonance spectroscopy (¹ H-MRS), and clozapine response in patients with TRS.

METHODS

This study enrolled patients with TRS who did not respond to clozapine (ultra-resistant schizophrenia: URS) and who responded to clozapine (non-URS), patients with schizophrenia who responded to first-line antipsychotics (first-line responders: FLR), and healthy controls (HCs). We measured GABA levels in the midcingulate cortex (MCC) using 3T ¹ H-MRS and compared these levels among the groups. The associations between GABA levels and symptom severity were also explored within the patient groups.

RESULTS

A total of 98 participants (URS: n = 22; non-URS: n = 25; FLR: n = 16; HCs: n = 35) completed the study. We found overall group differences in MCC GABA levels (F(3,86) = 3.25, P = 0.04). Specifically, patients with URS showed higher GABA levels compared to those with non-URS (F(1,52) = 8.40, P = 0.03, Cohen's d = 0.84). MCC GABA levels showed no associations with any of the symptom severity scores within each group or the entire patient group.

CONCLUSION

Our study is the first to report elevated GABA levels in the MCC in patients with schizophrenia resistant to clozapine treatment compared with those responsive to clozapine. Longitudinal studies are required to evaluate if GABA levels are a suitable biomarker to predict clozapine resistance.

Pharmacogenomics of Clozapine-induced agranulocytosis: a systematic review and meta-analysis

Although clozapine is the most effective pharmacotherapy for treatment-resistant schizophrenia, it is under-utilized, and initiation is often delayed. One reason is the occurrence of a potentially fatal adverse reaction, clozapine-induced agranulocytosis (CIA). Identifying genetic variations contributing to CIA would help predict patient risk of developing CIA and personalize treatment. Here, we (1) review existing pharmacogenomic studies of CIA, and (2) conduct meta-analyses to identify targets for clinical implementation. A systematic literature search identified studies that included individuals receiving clozapine who developed CIA and controls who did not. Results showed that individuals carrying the HLA-DRB1*04:02 allele had nearly sixfold (95% CI 2.20–15.80, p_corrected = 0.03) higher odds of CIA with a negative predictive value of 99.3%. Previously unreplicated alleles, TNFb5, HLA-B*59:01, TNFb4, and TNFd3 showed significant associations with CIA after multiple-testing corrections. Our findings suggest that a predictive HLA-DRB1*04:02-based pharmacogenomic test may be promising for clinical implementation but requires further investigation.

Factors Associated With Poor Response to Clozapine in Schizophrenia: A Study From Northern India

PURPOSE/BACKGROUND

Limited numbers of studies have assessed the predictors of clozapine nonresponse. This study aimed to assess the demographic and clinical factors associated with an inadequate response to clozapine in patients with treatment-resistant schizophrenia (TRS).

METHODS/PROCEDURES

Two hundred eighty-seven outpatients with TRS receiving clozapine for more than 1 year were divided into 2 groups based on the need for a second antipsychotic medication and/or electroconvulsive therapy after receiving clozapine in the maximum tolerable dose for at least 3 months.

RESULTS/FINDINGS

One hundred two patients (35.4%) were considered to be clozapine nonresponders. Compared with responders, clozapine nonresponders were more often unemployed at the time of starting clozapine (P = 0.04), had a longer duration of untreated psychosis (P = 0.007), had received significantly higher number of adequate antipsychotic trials in the past (P = 0.02), had received antipsychotic polypharmacy in the past (P = 0.01), had experienced adverse effects with first- (P < 0.001) and second-generation antipsychotics (P = 0.01), and had more medical comorbidities (P = 0.03). The nonresponders more frequently had visual hallucinations (P = 0.001), and feelings/acts or impulses attributed to some external source (P = 0.03) in the lifetime, and had a significantly higher Clinical Global Impression severity score at the time of starting of clozapine (P < 0.001). While on clozapine, nonresponders received significantly higher dose of clozapine (P = 0.001) and higher proportion of them experienced constipation (P = 0.04), hypersalivation (P = 0.002), and obsessive-compulsive symptoms (P = 0.05) as adverse effects of clozapine.

CONCLUSIONS/IMPLICATIONS

The present study shows that approximately one-third of patients with TRS do not respond to clozapine. However, clozapine nonresponders, although broadly similar in sociodemographic profile to clozapine responders, differ from clozapine responders on past treatment profile.

Dopaminergic dysfunction and excitatory/inhibitory imbalance in treatment-resistant schizophrenia and novel neuromodulatory treatment

Antipsychotic drugs are the mainstay in the treatment of schizophrenia. However, one-third of patients do not show adequate improvement in positive symptoms with non-clozapine antipsychotics. Additionally, approximately half of them show poor response to clozapine, electroconvulsive therapy, or other augmentation strategies. However, the development of novel treatment for these conditions is difficult due to the complex and heterogenous pathophysiology of treatment-resistant schizophrenia (TRS). Therefore, this review provides key findings, potential treatments, and a roadmap for future research in this area. First, we review the neurobiological pathophysiology of TRS, particularly the dopaminergic, glutamatergic, and GABAergic pathways. Next, the limitations of existing and promising treatments are presented. Specifically, this article focuses on the therapeutic potential of neuromodulation, including electroconvulsive therapy, repetitive transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation. Finally, we propose multivariate analyses that integrate various perspectives of the pathogenesis, such as dopaminergic dysfunction and excitatory/inhibitory imbalance, thereby elucidating the heterogeneity of TRS that could not be obtained by conventional statistics. These analyses can in turn lead to a precision medicine approach with closed-loop neuromodulation targeting the detected pathophysiology of TRS.

Relationship between plasma clozapine/N-desmethylclozapine and changes in basal forebrain-dorsolateral prefrontal cortex coupling in treatment-resistant schizophrenia

Clozapine (CLZ) demonstrates a unique clinical efficacy relative to other antipsychotic drugs. Previous work has linked the plasma ratio of CLZ and its major metabolite, N-desmethylclozapine (NDMC), to an inverse relationship with cognition via putative action on the cholinergic system. However, neuroimaging correlates of CLZ/NDMC remain unknown. Here, we examined changes in basal forebrain functional connectivity with the dorsolateral prefrontal cortex, and secondly, cognition in relation to the CLZ/NDMC ratio. A cohort of nineteen chronically ill participants with treatment-resistant schizophrenia (TRS) undergoing 12 weeks of CLZ treatment were included. Measures of cognition and plasma CLZ/NDMC ratios were obtained in addition to resting-state functional neuroimaging scans, captured at baseline and after 12 weeks of CLZ treatment. We observed a significant correlation between basal forebrain-DLPFC connectivity and CLZ/NDMC ratios across CLZ treatment (p = 0.02). Consistent with previous findings, we also demonstrate a positive relationship between CLZ/NDMC ratio and working memory (p = 0.03). These findings may reflect the action of CLZ and NDMC on the muscarinic cholinergic system, highlighting a possible neural correlate of cognition across treatment.

Using a statistical learning approach to identify sociodemographic and clinical predictors of response to clozapine

BACKGROUND

A proportion of people with treatment-resistant schizophrenia fail to show improvement on clozapine treatment. Knowledge of the sociodemographic and clinical factors predicting clozapine response may be useful in developing personalised approaches to treatment.

METHODS

This retrospective cohort study used data from the electronic health records of the South London and Maudsley (SLaM) hospital between 2007 and 2011. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression statistical learning approach, we examined 35 sociodemographic and clinical factors' predictive ability of response to clozapine at 3 months of treatment. Response was assessed by the level of change in the severity of the symptoms using the Clinical Global Impression (CGI) scale.

RESULTS

We identified 242 service-users with a treatment-resistant psychotic disorder who had their first trial of clozapine and continued the treatment for at least 3 months. The LASSO regression identified three predictors of response to clozapine: higher severity of illness at baseline, female gender and having a comorbid mood disorder. These factors are estimated to explain 18% of the variance in clozapine response. The model's optimism-corrected calibration slope was 1.37, suggesting that the model will underfit when applied to new data.

CONCLUSIONS

These findings suggest that women, people with a comorbid mood disorder and those who are most ill at baseline respond better to clozapine. However, the accuracy of the internally validated and recalibrated model was low. Therefore, future research should indicate whether a prediction model developed by including routinely collected data, in combination with biological information, presents adequate predictive ability to be applied in clinical settings.

Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia

IMPORTANCE

About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts.

OBJECTIVE

To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples.

DESIGN, SETTING, AND PARTICIPANTS

Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]).

MAIN OUTCOMES AND MEASURES

GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition.

RESULTS

The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04).

CONCLUSIONS AND RELEVANCE

In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.

Managing treatment resistance in schizophrenia: A joint study in Hong Kong and Singapore

OBJECTIVE

This study surveyed clinicians in psychiatry in Hong Kong and Singapore to understand their familiarity and prescribing practices in treatment-resistant schizophrenia (TRS) and clozapine-resistant schizophrenia (CRS).

MATERIALS AND METHODS

All clinicians in psychiatry in both regions were invited through email to participate in an anonymous online survey. The survey collected information on the participants' characteristics, their familiarity and experience with clozapine use, and their treatment practices in TRS and CRS. Data collection took place between September 2019 and February 2020 in Hong Kong and December 2018 and March 2019 in Singapore.

RESULTS

261 clinicians responded to the survey, with response rates of 19% (105 out of 556 participants) in Hong Kong and 50% (156 out of 309 participants) in Singapore. The majority of respondents (99.0% in Hong Kong; 87.9% in Singapore) were familiar with treatment guidelines for TRS. However, approximately half (54.2% in Hong Kong; 41.7% in Singapore) delayed the prescription of clozapine when indicated. In terms of alternatives to clozapine, approximately half or more of the clinicians in both regions would use high dose antipsychotics, long-acting injectable antipsychotics, antipsychotic polypharmacy, while the adjuvant use of mood stabilizers and electroconvulsive therapy differed between the two regions. In those with CRS, between 10 and 20% of the respondents added adjuvant mood stabilizers or antipsychotics, and 3-10% would use an antidepressant.

CONCLUSION

Clozapine delays occur in spite of clinicians' familiarity with treatment guidelines. More research is needed to guide the use of augmentation strategies and the search for effective treatments beyond clozapine.

A predictor model of treatment resistance in schizophrenia using data from electronic health records

OBJECTIVES

To develop a prognostic tool of treatment resistant schizophrenia (TRS) in a large and diverse clinical cohort, with comprehensive coverage of patients using mental health services in four London boroughs.

METHODS

We used the Least Absolute Shrinkage and Selection Operator (LASSO) for time-to-event data, to develop a risk prediction model from the first antipsychotic prescription to the development of TRS, using data from electronic health records.

RESULTS

We reviewed the clinical records of 1,515 patients with a schizophrenia spectrum disorder and observed that 253 (17%) developed TRS. The Cox LASSO survival model produced an internally validated Harrel's C index of 0.60. A Kaplan-Meier curve indicated that the hazard of developing TRS remained constant over the observation period. Predictors of TRS were: having more inpatient days in the three months before and after the first antipsychotic, more community face-to-face clinical contact in the three months before the first antipsychotic, minor cognitive problems, and younger age at the time of the first antipsychotic.

CONCLUSIONS

Routinely collected information, readily available at the start of treatment, gives some indication of TRS but is unlikely to be adequate alone. These results provide further evidence that earlier onset is a risk factor for TRS.

Clinical predictors of response to clozapine in Tunisian patients with treatment resistant schizophrenia

INTRODUCTION

Treatment resistant schizophrenia (TRS), affecting approximately one-third of patients with schizophrenia, is associated with a serious impairment in global psychosocial functioning. Clozapine is the only licensed drug for TRS. However its prescription remains limited by its side effects requiring mandatory monitoring. The need to identify clinical factors associated with good response to clozapine in TRS has been established. The presence of ethnic differences in these factors and the scarcity of data on the Tunisian or more generally the North-African population warrants the conduct of a clinical study on the subject. The aim of this study was to investigate demographic, clinical, and biochemical patient characteristics as potential predictors of response to clozapine.

METHODS

This is a cross-sectional and retrospective study, at the "F and A psychiatry departments" of Razi Hospital in Manouba, Tunisia. All patients, with DSM 5 diagnosis of schizophrenia in its resistant form, on clozapine for at least 12 months and who consulted from June 1, 2018 to November 30, 2018 were included. We investigated premorbid functioning by the premorbid adjusment scale, demographic and clinical characteristics, and clozapine plasma level as potential clozapine response predictors. The response to clozapine was defined by a total BPRS score of 35 or less.

RESULTS

Sixty-three patients were included in the study. The mean age at clozapine introduction was 30,84 ±9,25 years. The mean duration of clozapine treatment was 7,22 ± 4,02 years. There were 16 clozapine responders (25%) who had BPRS total scores below or equal to 35 and 47 non-responders (75%). A higher premorbid social functioning in childhood (p = 0,018) and early adolescence (p = 0,024) was associated with better response to clozapine. A delay clozapine initiation shorter than 7 years(p = 0,036), one atypical antipsychotic trial (p = 0,029) and schizophrenia paranoid subtype (p< 0.01) were found to be significantly predictive of good clozapine response. None of the demographic factors or biochemical characteristics were associated with clozapine response.

CONCLUSIONS

Our work is consistent with previous studies suggesting the need for clinicians to be aware of the clinical predictors of a good response to clozapine to overcome their reluctance to prescribe it. It also highlighted the major prognostic role of premorbid adjustment in the clinical response to treatment. However, prospective studies including therapeutic drug monitoring would be very useful to better delineate the sub-group of patients to whom clozapine would benefit the most and to improve prescription modalities.

Longitudinal course of cognition in schizophrenia: Does treatment resistance play a role?

Treatment-resistant schizophrenia (TRS) represents a main clinical issue, associated with worse functional outcome and higher healthcare costs. Clozapine is the most effective antipsychotic for TRS, although 40% of resistant patients, defined as ultra-treatment resistant (UTR), are clozapine-refractory. Previous literature suggests that TRS is characterized by worse cognitive functioning and a more disrupted neurobiological substrate, but only few studies focused on UTR schizophrenia. Moreover, despite this evidence and the central role of cognition, to date no study has investigated long-term cognitive outcome in TRS. Based on these premises, this study aims to analyze cross-sectional and long-term cognitive functioning of patients with schizophrenia, stratified according to antipsychotic response: first-line responders (FLRs), clozapine responders (CRs) and UTRs. We analyzed cross-sectional and retrospective cognitive evaluations of 93 patients with schizophrenia (32 FLRs, 42 CRs, 19 UTRs) over a mean follow-up period of 9 years, also taking into account possible influencing factors such as clinical severity and antipsychotic load. Analyses showed that UTR is associated with overall impaired cognitive functioning and represents the main predictor of long-term cognitive decline. We observed no significant differences between FLR and CR patients, which showed moderate cognitive improvement over time. This is the first study to report an association of treatment resistance with longitudinal cognitive course in schizophrenia, indicating that UTR is correlated with cognitive decline over time. This decline may either be a consequence of the persistence of psychotic symptoms or depend on a distinct and more disrupted neurobiological substrate affecting both cognition and antipsychotic response.

Prevalence and predictors of treatment-resistant schizophrenia in a tertiary hospital in Northeast Brazil

OBJECTIVE

To investigate epidemiological factors related to treatment-resistant schizophrenia (TRS) in Northeast Brazil, a region where data about mental health are still scarce.

METHODS

This retrospective cross-sectional study included all patients with schizophrenia currently receiving treatment at the outpatient psychiatric clinic of a tertiary hospital in Northeast Brazil. They were divided into TRS and treatment-responsive groups, and epidemiological characteristics of both groups were compared. A logistic regression model investigated factors related to treatment resistance.

RESULTS

Two hundred and five patients were included, 155 treatment-resistant and 50 treatment-responsive. The TRS group had higher use of benzodiazepines (36.1 vs. 18%, p = 0.017) and antiepileptics (36.8 vs. 8.0%, p < 0.001), antipsychotic polypharmacy (28.6 vs. 8%, p = 0.003) and suicide attempts (35.6 vs. 20%, p = 0.04). Age at onset was younger (19.7±7.3 vs. 24.6±8.6 years, p = 0.001) and CGI was higher in TRS (3.72±1.00 vs. 3.16±1.00, p = 0.001). In logistic regression, being married was a protector (odds ratio [OR] = 0.248, 95% confidence interval [95%CI] 0.091-0.679, p = 0.007) and younger age at onset was a predictor (OR = 1.076, 95%CI 1.034-1.120, p < 0.001) of treatment resistance.

CONCLUSION

Early onset of disease was associated with more treatment resistance, while being married with less resistance. Clinicians should identify early predictors of resistance in order to reduce unfavorable outcomes.

Demographic and clinical variables associated with response to clozapine in schizophrenia: a systematic review and meta-analysis

Clozapine is the only licensed pharmacotherapy for treatment-resistant schizophrenia. However, response to clozapine is variable. Understanding the demographic and clinical features associated with response to clozapine may be useful for patient stratification for clinical trials or for identifying patients for earlier initiation of clozapine. We systematically reviewed the literature to investigate clinical and demographic factors associated with variation in clozapine response in treatment-resistant patients with schizophrenia spectrum disorders. Subsequently, we performed a random-effects meta-analysis to evaluate differences in duration of illness, age at clozapine initiation, age of illness onset, body weight and years of education between clozapine responders and non-responders. Thirty-one articles were eligible for qualitative review and 17 of these were quantitatively reviewed. Shorter duration of illness, later illness onset, younger age at clozapine initiation, fewer hospitalisations and fewer antipsychotic trials prior to clozapine initiation showed a trend to be significantly associated with a better response to clozapine. Meta-analysis of seven studies, totalling 313 subjects, found that clozapine responders had a significantly shorter duration of illness compared to clozapine non-responders [g = 0.31; 95% confidence interval (CI) 0.06-0.56; p = 0.01]. The results imply that a delay in clozapine treatment may result in a poorer response and that a focus on prompt treatment with clozapine is warranted.

Possible pharmacogenetic factors in clozapine treatment failure: a case report

There is still much to learn about the predictors of therapeutic response in psychiatry, but progress is gradually being made and precision psychiatry is an exciting and emerging subspeciality in this field. This is critically important in the treatment of refractory psychotic disorders, where clozapine is the only evidence-based treatment but only about half the patients experience an adequate response. In this case report, we explore the possible biological mechanisms underlying treatment failure and discuss possible ways of improving clinical outcomes. Further work is required to fully understand why some patients fail to respond to the most effective treatment in refractory schizophrenia. Therapeutic drug monitoring together with early pharmacogenetic testing may offer a path for some patients with refractory psychotic symptoms unresponsive to clozapine treatment.

Predictors of Treatment-Resistant and Clozapine-Resistant Schizophrenia: A 12-Year Follow-up Study of First-Episode Schizophrenia-Spectrum Disorders

Studies on the long-term development and early predictors of treatment-resistant schizophrenia (TRS) and clozapine-resistant TRS (CR-TRS) in patients with first-episode schizophrenia-spectrum disorders (FES) are limited and have not considered the impact of early intervention services (EIS). This study aimed to explore the development of TRS and CR-TRS among patients with FES over 12 years of follow-up. Of the 1234 patients with FES, 15% developed TRS. A total of 450 patients with schizophrenia or schizoaffective disorder were included in a nested case-control study (157 TRS and 293 non-TRS). Younger age of onset, poorer premorbid social adjustment during adulthood, longer duration of first episode, a greater number of relapses, and a higher antipsychotic dose in the first 24 months were associated with earlier TRS. CR-TRS patients, constituting 25% of TRS patients, had a poorer premorbid social adjustment in late adolescence and longer delay before clozapine initiation compared with non-CR-TRS. CR-TRS had poorer clinical and functional outcomes at 12-year follow-up. However, TRS patients on clozapine had a lower mortality rate compared with non-TRS patients. EIS did not have a significant impact on the development of TRS, but patients in the EIS group had a shorter delay of clozapine initiation. Results suggested that neurodevelopmental factors, early clinical characteristics, and requirement for higher antipsychotic dose may be associated with TRS development, highlighting multiple pathways leading to this form of illness. Specific interventions including relapse prevention and early initiation of clozapine during the early course of illness may reduce the rate of TRS and improve patient outcomes.

Quantitative biomarkers to predict response to clozapine treatment using resting EEG data

Clozapine is an anti-psychotic drug that is known to be effective in the treatment of patients with chronic treatment-resistant schizophrenia (TRS-SCZ), commonly estimated to be around one third of all cases. However, clinicians sometimes delay the initiation of this drug because of its adverse side-effects. Therefore, identification of predictive biomarkers of clozapine response is extremely valuable to aid on-time initiation of clozapine treatment. In this study, we develop a machine learning (ML) algorithm based on the pre-treatment electroencephalogram (EEG) data sets to predict response to clozapine treatment in TRS-SCZs, where the treatment outcome, after at least one-year follow-up is determined using the Positive and Negative Syndrome Scale (PANSS). The ML algorithm has two steps: 1) an effective connectivity named symbolic transfer entropy (STE) is applied to resting state EEG waveforms, 2) the ML algorithm is applied to STE matrix to determine whether a set of features can be found to discriminate most responder (MR) SCZ patients from least responder (LR) ones. The findings of this study revealed that the STE features could achieve an accuracy of 89.90%. This finding implies that analysis of pre-treatment EEG could contribute to our ability to distinguish MR from LR SCZs, and that the STE matrix may prove to be a promising tool for the prediction of the clinical response to clozapine.