Innova4Health: an integrated approach for prevention of recurrence and personalized treatment of Major Depressive Disorder

Background

Major Depressive Disorder (MDD) is a prevalent mental health condition characterized by persistent low mood, cognitive and physical symptoms, anhedonia (loss of interest in activities), and suicidal ideation. The World Health Organization (WHO) predicts depression will become the leading cause of disability by 2030. While biological markers remain essential for understanding MDD's pathophysiology, recent advancements in social signal processing and environmental monitoring hold promise. Wearable technologies, including smartwatches and air purifiers with environmental sensors, can generate valuable digital biomarkers for depression assessment in real-world settings. Integrating these with existing physical, psychopathological, and other indices (autoimmune, inflammatory, neuroradiological) has the potential to improve MDD recurrence prevention strategies.

Methods

This prospective, randomized, interventional, and non-pharmacological integrated study aims to evaluate digital and environmental biomarkers in adolescents and young adults diagnosed with MDD who are currently taking medication. The study implements a sensor-integrated platform built around an open-source "Pothos" air purifier system. This platform is designed for scalability and integration with third-party devices. It accomplishes this through software interfaces, a dedicated app, sensor signal pre-processing, and an embedded deep learning AI system. The study will enroll two experimental groups (10 adolescents and 30 young adults each). Within each group, participants will be randomly allocated to Group A or Group B. Only Group B will receive the technological equipment (Pothos system and smartwatch) for collecting digital biomarkers. Blood and saliva samples will be collected at baseline (T0) and endpoint (T1) to assess inflammatory markers and cortisol levels.

Results

Following initial age-based stratification, the sample will undergo detailed classification at the 6-month follow-up based on remission status. Digital and environmental biomarker data will be analyzed to explore intricate relationships between these markers, depression symptoms, disease progression, and early signs of illness.

Conclusion

This study seeks to validate an AI tool for enhancing early MDD clinical management, implement an AI solution for continuous data processing, and establish an AI infrastructure for managing healthcare Big Data. Integrating innovative psychophysical assessment tools into clinical practice holds significant promise for improving diagnostic accuracy and developing more specific digital devices for comprehensive mental health evaluation.

Treatment persistence with aripiprazole once monthly: a 4-year follow-up

OBJECTIVES

Treatment persistence refers to the act of continuing a treatment as prescribed and reflects the patient's or doctor's judgment about efficacy, tolerability, and acceptability. In patients with schizophrenia, antipsychotic persistence is often poor, because of issues such as lack or loss of efficacy, side effects, and poor adherence, which is often related to the degree to which patients find the medication and overall intervention to be helpful, tolerable, fair, reasonable, appropriate, and consistent with expectations of treatment. Despite the poor antipsychotic persistence that has been reported to date in patients with schizophrenia, we previously observed a relatively high (86%) 6 months persistence with aripiprazole once-monthly (AOM) in a group of patients with schizophrenia, treated in the real world Italian clinical practice. The present study explores the longer term persistence with AOM, over a mean follow-up period of 48 months.

METHODS

This was a multicenter, retrospective, non-interventional follow-up study, aimed at evaluating the longer term persistence with AOM in a group of patients with schizophrenia who had already shown persistence over a period of at least 6 months. The study included 161 individuals who had participated in our previous study, where 86% of participating individuals had shown persistence with AOM for at least 6 months. Non-persistence was defined as discontinuing the medication for any reason. Baseline demographic and clinical characteristics of patients who continued AOM were then compared to those of patients who discontinued the medication.

RESULTS

Study subjects were predominantly male (64.4%) and their mean age was 39.7 (SD: 12.24). Treatment persistence with AOM was 69.6% and 112 out of 161 patients were still receiving AOM treatment at the last follow-up visit. The mean duration of AOM treatment until the last recorded observation was 55.87 months (median 56.17, SD6.23) for the 112 persistent patients and 32.23 (median 28.68.SD 15.09) months for the 49 non-persistent individuals. The mean observation period for all patients (persistent and non-persistent) was 48.78 months (median 52.54, SD 14.64). For non-persistent subjects, the observation period ended with the discontinuation of AOM. Subjects treated with AOM at 400 mg presented a 69.6% lower risk of all-cause treatment discontinuation when compared with patients treated with 300 mg (HR: 0.314; 95% confidence interval [CI] 0.162-0.608; P = 0.001). The main reasons for discontinuation were lack of efficacy (30.6%), patient/caregiver choice (18.4%), physician's choice (16.3%), non-adherence (12.2%) and inconvenience (6.1%). Only 3 patients (6.1%) discontinued AOM for tolerability issues.

CONCLUSIONS

In subjects with schizophrenia, who had already shown a 6 months persistence with AOM, a high number of patients (69.6%) continued to be persistent over a 4-year follow-up period. This may reflect a favourable profile of efficacy, tolerability, and acceptability. Larger and prospective studies are warranted to confirm our observations.

Investigating the Relationships of P3b with Negative Symptoms and Neurocognition in Subjects with Chronic Schizophrenia

Neurocognitive deficits and negative symptoms (NS) have a pivotal role in subjects with schizophrenia (SCZ) due to their impact on patients' functioning in everyday life and their influence on goal-directed behavior and decision-making. P3b is considered an optimal electrophysiological candidate biomarker of neurocognitive impairment for its association with the allocation of attentional resources to task-relevant stimuli, an important factor for efficient decision-making, as well as for motivation-related processes. Furthermore, associations between P3b deficits and NS have been reported. The current research aims to fill the lack of studies investigating, in the same subjects, the associations of P3b with multiple cognitive domains and the expressive and motivation-related domains of NS, evaluated with state-of-the-art instruments. One hundred and fourteen SCZ and 63 healthy controls (HCs) were included in the study. P3b amplitude was significantly reduced and P3b latency prolonged in SCZ as compared to HCs. In SCZ, a positive correlation was found between P3b latency and age and between P3b amplitude and the Attention-vigilance domain, while no significant correlations were found between P3b and the two NS domains. Our results indicate that the effortful allocation of attention to task-relevant stimuli, an important component of decision-making, is compromised in SCZ, independently of motivation deficits or other NS.

How Is the History of Early Traumatic Exposure Associated With the Psychopathological Outcomes of COVID-19 Related Lockdown and Subsequent Re-opening in People With Eating Disorders?

The negative impact of COVID-19 pandemic on people with Eating Disorders (EDs) has been documented. The aim of this study was to evaluate whether a history of traumatic experiences during childhood or adolescence was associated with a higher degree of psychopathological worsening during COVID-19 related lockdown and in the following re-opening period in this group of people. People with EDs undergoing a specialist ED treatment in different Italian services before the spreading of COVID-19 pandemic (n = 312) filled in an online survey to retrospectively evaluate ED specific and general psychopathology changes after COVID-19 quarantine. Based on the presence of self-reported traumatic experiences, the participants were split into three groups: patients with EDs and no traumatic experiences, patients with EDs and childhood traumatic experiences, patients with EDs and adolescent traumatic experiences. Both people with or without early traumatic experiences reported retrospectively a worsening of general and ED-specific psychopathology during the COVID 19-induced lockdown and in the following re-opening period. Compared to ED participants without early traumatic experiences, those with a self-reported history of early traumatic experiences reported heightened anxious and post-traumatic stress symptoms, ineffectiveness, body dissatisfaction, and purging behaviors. These differences were seen before COVID-19 related restrictions as well as during the lockdown period and after the easing of COVID-19 related restrictions. In line with the "maltreated ecophenotype" theory, these results may suggest a clinical vulnerability of maltreated people with EDs leading to a greater severity in both general and ED-specific symptomatology experienced during the exposure to the COVID-19 pandemic.

Risk and resilience factors for specific and general psychopathology worsening in people with Eating Disorders during COVID-19 pandemic: a retrospective Italian multicentre study

PURPOSE

The COVID-19 pandemic restrictions had negative impact on the psychopathology of people with Eating Disorders (EDs). Factors involved in the vulnerability to stressful events have been under-investigated in this population. We aimed to assess which factors contributed to COVID-19-induced worsening in both general and specific psychopathology.

METHODS

Three-hundred and twelve people with a clinically defined diagnosis of an ED and undergoing a specialist ED treatment in different Italian ED services before the spreading of COVID-19 pandemic filled in an online survey. ED specific and general psychopathology changes after COVID-19 quarantine were retrospectively evaluated. Factors related to COVID-19 concerns (financial condition, fear of contagion, perceived social isolation/support, satisfaction in peer, family or sentimental relationships), illness duration and treatment-related variables (type of treatment provided, type of access to care, satisfaction with therapeutic relationships) were included as predicting factors in a structural equational model, which included latent variables consisting of general and ED psychopathology items as outcomes.

RESULTS

A perceived low quality of therapeutic relationships, fear of contagion and increased isolation were positively associated with psychopathology worsening. Reduced satisfaction with family and with friends' relationships and reduced perceived social support were associated with ED and general symptoms deterioration, respectively. No significant effect emerged for intimate relationships, illness duration, economic condition and type of treatment.

CONCLUSIONS

This study provides a comprehensive evaluation of clinical variables associated with psychopathological changes during the COVID-19 lockdown period highlighting potential risk and resilience factors and, possibly, informing treatment as well as prevention strategies for EDs.

LEVEL OF EVIDENCE IV

Evidence obtained from multiple time series analysis such as case studies.

[The management of long-term treatment of patient with schizophrenia: results of a survey carried out in Italy]

The management plan of patients with schizophrenia includes a multidimensional and integrated approach, consisting of pharmacological, psychological and psychosocial interventions. Among pharmacological approaches, the development of long-acting injectable antipsychotics (LAI) has radically changed the treatment plan of patients with schizophrenia. LAI can be successfully used in patients with multiple episodes, with partial or poor adherence to treatments and are very useful also in first episode patients. LAIs have been proven to be effective and with a good safety and tolerability profile, but they are still used in a few cases in the clinical routine practice. Therefore, the present study aims to evaluate attitudes and preferences of psychiatrists in the Italian routine care towards LAI and to identify the communication skills adopted in the routine care for the prescription of LAI. The final sample consists of 274 clinicians, recruited by phone call (n=257) and online (n=17). The main findings are: the psychoeducational approach is essential for improving patients' adherence to pharmacological treatments and their personal and social functioning; the involvement of family members is essential for improving adherence to treatments; LAIs are frequently used due to their efficacy and good tolerability profile, compared to first generation depot antipsychotics. Based on our findings, the ideal patient to be switched to LAI treatment is represented by a person with poor adherence to treatments, at the onset of the disorder, or with a poor tolerability to side effects.

Prevalence of antipsychotic-induced extrapyramidal symptoms and their association with neurocognition and social cognition in outpatients with schizophrenia in the "real-life"

First generation antipsychotics (FGAs) are more likely to induce extrapyramidal side-effects (EPS) than second generation antipsychotics (SGAs), and EPS have been shown associated to cognitive deficits in schizophrenia. So far, no study has explored the relationships between EPS and social cognition (SC) in people with schizophrenia. Therefore, we assessed the prevalence of EPS in a large sample of drug-treated community-dwelling persons with schizophrenia and explored their relationships with patients' neurocognitive and SC abilities. 875 patients underwent EPS, psychopathological, neurocognitive and SC assessments by means of standardized measures. Relationships between EPS, psychopathology and neurocognitive and SC measures were investigated by correlation tests. Moreover, a partial correlation network was computed by means of a network analysis. 256 patients were treated with FGAs alone or in combination with SGA and 619 with SGAs. EPS were significantly more frequent in FGA-treated group than in the SGA-treated one. Patients with EPS disclosed a more severe psychopathology and were more impaired in neurocognitive and SC measures compared to those without EPS. Disorganization, expressive deficit, and duration of illness were significantly associated to both neurocognitive and SC measures while EPS were associated to neurocognitive measures only. The network analysis showed that parkinsonism was the sole EPS directly connected to both psychopathological and neurocognitive indices whereas no direct connection emerged between EPS and SC measures. Present findings confirm that EPS are still present in the era of SGAs and contribute, together with other clinical variables, to the neurocognitive but not to the SC impairment of patients with schizophrenia.

Investigation of electrophysiological markers to predict clinical and functional outcome of schizophrenia using sparse partial least square regression

Introduction

Despite innovative treatments, the impairment in real-life functioning in subjects with schizophrenia (SCZ) remains an unmet need in the care of these patients. Recently, real-life functioning in SCZ was associated with abnormalities in different electrophysiological indices. It is still not clear whether this relationship is mediated by other variables, and how the combination of different EEG abnormalities influences the complex outcome of schizophrenia.

Objectives

The purpose of the study was to find EEG patterns which can predict the outcome of schizophrenia and identify recovered patients.

Methods

Illness-related and functioning-related variables were measured in 61 SCZ at baseline and after four-years follow-up. EEGs were recorded at the baseline in resting-state condition and during two auditory tasks. We performed Sparse Partial Least Square (SPLS) Regression, using EEG features, age and illness duration to predict clinical and functional features at baseline and follow up. Through a Linear Support Vector Machine (Linear SVM) we used electrophysiological and clinical scores derived from SPLS regression, in order to classify recovered patients at follow-up.

Results

We found one significant latent variable (p<0.01) capturing correlations between independent and dependent variables at follow-up (RHO=0.56). Among individual predictors, age and illness-duration showed the highest scores; however, the score for the combination of the EEG features was higher than all other predictors. Within dependent variables, negative symptoms showed the strongest correlation with predictors. Scores resulting from SPLS Regression classified recovered patients with 90.1% of accuracy.

Conclusions

A combination of electrophysiological markers, age and illness-duration might predict clinical and functional outcome of schizophrenia after 4 years of follow-up.

Multivariate approach to identify electrophysiological markers for diagnosis and prognosis of schizophrenia

Introduction

Different electrophysiological indices have been investigated to identify diagnostic and prognostic markers of schizophrenia (SCZ). However, these indices have limited use in clinical practice, since both specificity and association with illness outcome remain unclear. In recent years, machine learning techniques, through the combination of multidimensional data, have been used to better characterize SCZ and to predict illness course.

Objectives

The aim of the present study is to identify multimodal electrophysiological biomarkers that could be used in clinical practice in order to improve precision in diagnosis and prognosis of SCZ.

Methods

Illness-related and functioning-related variables were measured at baseline in 113 subjects with SCZ and 57 healthy controls (HC), and after four-year follow-up in 61 SCZ. EEGs were recorded at baseline in resting-state condition and during two auditory tasks (MMN-P3a and N100-P3b). Through a Linear Support Vector Machine, using EEG data as predictors, four models were generated in order to classify SCZ and HC. Then, we combined unimodal classifiers’ scores through a stacking procedure. Pearson’s correlations between classifiers score with illness-related and functioning-related variables, at baseline and follow-up, were performed.

Results

Each EEG model produced significant classification (p < 0.05). Global classifier discriminated SCZ from HC with accuracy of 75.4% (p < 0.01). A significant correlation (r=0.40, p=0.002) between the global classifier scores with negative symptoms at follow-up was found. Within negative symptoms, blunted affect showed the strongest correlation.

Conclusions

Abnormalities in electrophysiological indices might be considered trait markers of schizophrenia. Our results suggest that multimodal electrophysiological markers might have prognostic value for negative symptoms.

COVID-19 pandemic and eating disorders: What impact on specific and general psychopathology?

Introduction

The coronavirus disease 2019 (COVID-19) pandemic and the resulting containment measures, such as “lockdown” and “social distancing”, have had important consequences on people’s mental and physical health.

Objectives

We aimed to study the effect of social isolation and subsequent re- exposure and eventual changes in general and ED-specific psychopathology in people with Eating Disorders (EDs).

Methods

Three-hundred twelve Italian people with EDs (179 Anorexia Nervosa, 83 Bulimia Nervosa, 48 Binge Eating Disorder and 22 Other Specific Feeding Eating Disorder) were asked to fill-in an online survey to explore several dimensions such as: anxiety, depression, panic, insomnia, suicide ideation, stress, post-traumatic stress and obsessive-compulsive symptoms. Differences in ED specific and general symptoms among the 3 investigated time periods (before, during and after the end of lockdown) were assessed with a one-way ANOVA with repeated measures. Subsequently, ED diagnosis was introduced as covariate in the analysis in order to investigate the possible contribution on psychopathological changes.

Results

ED core symptoms increased during the lockdown but most of them returned to pre-COVID19 levels at re-opening. The severity of general psychopathology also increased during the lockdown and persisted high in the following phase, except for depression and suicide ideation. None of this symptoms was affected by ED diagnosis, participants’age and illness duration.

Conclusions

People with EDs showed worsening of both general and specific psychopathology; moreover, changes in general psychopathology persisted in the re-opening period suggesting a higher stress vulnerability in this kind of patients.

Disclosure

No significant relationships.

Keyword

COVID19 and Eating Disorders

Pharmacogenetics of Carbamazepine and Valproate: Focus on Polymorphisms of Drug Metabolizing Enzymes and Transporters

Pharmacogenomics can identify polymorphisms in genes involved in drug pharmacokinetics and pharmacodynamics determining differences in efficacy and safety and causing inter-individual variability in drug response. Therefore, pharmacogenomics can help clinicians in optimizing therapy based on patient's genotype, also in psychiatric and neurological settings. However, pharmacogenetic screenings for psychotropic drugs are not routinely employed in diagnosis and monitoring of patients treated with mood stabilizers, such as carbamazepine and valproate, because their benefit in clinical practice is still controversial. In this review, we summarize the current knowledge on pharmacogenetic biomarkers of these anticonvulsant drugs.

The Gut Microbiome and Metabolomics Profiles of Restricting and Binge-Purging Type Anorexia Nervosa

Alterations in the gut microbiome and fecal metabolites have been detected in anorexia nervosa (AN), but differences in those profiles between restricting AN (ANR) and binge-purging AN (ANBP) type have not been explored. We made a secondary analysis of our previous data concerning microbiome and metabolomics profiles of 17 ANR women, six ANBP women and 20 healthy controls (HC). Twelve fecal metabolites differentiating ANR patients, ANBP patients and HC were identified. Both patient groups showed decreased intra-individual bacterial richness with respect to healthy controls (HC). Compared to ANR subjects, ANBP patients had a significant increase in relative abundances of Bifidobacterium, Bifidobacteriaceae, Bifidobacteriales, and Eubacteriacae and a significant decrease in relative abundances of Odoribacter, Haemophilus, Pasteurellaceae, and Pasteurellales. The heatmaps of the relationships of selected fecal metabolites with microbial families showed different structures among the three groups, with the heatmap of ANBP patients being drastically different from that of HC, while that of ANR patients resulted more similar to HC. These findings, although preliminary because of the relatively small sample size, confirm the occurrence of different gut dysbiosis in ANR and ANBP and demonstrate different connections between gut microorganisms and fecal metabolites in the two AN types.

Genome, Environment, Microbiome and Metabolome in Autism (GEMMA) Study Design: Biomarkers Identification for Precision Treatment and Primary Prevention of Autism Spectrum Disorders by an Integrated Multi-Omics Systems Biology Approach

Autism Spectrum Disorder (ASD) affects approximately 1 child in 54, with a 35-fold increase since 1960. Selected studies suggest that part of the recent increase in prevalence is likely attributable to an improved awareness and recognition, and changes in clinical practice or service availability. However, this is not sufficient to explain this epidemiological phenomenon. Research points to a possible link between ASD and intestinal microbiota because many children with ASD display gastro-intestinal problems. Current large-scale datasets of ASD are limited in their ability to provide mechanistic insight into ASD because they are predominantly cross-sectional studies that do not allow evaluation of perspective associations between early life microbiota composition/function and later ASD diagnoses. Here we describe GEMMA (Genome, Environment, Microbiome and Metabolome in Autism), a prospective study supported by the European Commission, that follows at-risk infants from birth to identify potential biomarker predictors of ASD development followed by validation on large multi-omics datasets. The project includes clinical (observational and interventional trials) and pre-clinical studies in humanized murine models (fecal transfer from ASD probands) and in vitro colon models. This will support the progress of a microbiome-wide association study (of human participants) to identify prognostic microbiome signatures and metabolic pathways underlying mechanisms for ASD progression and severity and potential treatment response.

Multi-omics data integration in anorexia nervosa patients before and after weight regain: A microbiome-metabolomics investigation

BACKGROUND & AIMS

We have recently reported specific fecal metabolomic changes in acute and short-term weight restored patients with anorexia nervosa (AN). In this study we explored the association between those metabolomic changes and patients' gut microbiome composition.

METHODS

The gut microbiome of AN women was sequenced in both the underweight phase (n = 21) and after short-term weight restoration (n = 16) and compared to that of 20 healthy women. According to a multi-omics approach, microbiome data were correlated with 49 relevant fecal metabolites previously characterized in our participants by an untargeted metabolomic procedure.

RESULTS

Compared to healthy women, AN patients showed a decreased intra-individual bacterial richness, an increased Bacteroidetes-to-Firmicutes abundance ratio and significant changes in the relative abundances of several bacteria at phylum, class, order, family and genus levels. These changes were observed in both the underweight and weight-restored condition. Moreover, the relationships among the 49 previously selected fecal metabolites and bacteria genera showed structures of different complexity among the 3 groups. In particular, a quarter of those relationships showed a divergent direction in the acutely ill patients with respect to the weight-restored ones or normal controls. Finally, in acutely ill patients 70% of those correlations showed a negative sign suggesting a prevalent metabolites consummation by gut microbiome.

CONCLUSIONS

These data confirm a profound perturbation in the gut microbiome composition of AN patients. Moreover, for the first time, they provide the evidence that in AN gut bacteria are connected with several fecal metabolites in a different way from normal controls and with divergent directions in the acute phase with respect to the weight-restored phase.

The role of shared decision-making in improving adherence to pharmacological treatments in patients with schizophrenia: a clinical review

Shared decision-making (SDM) is a process in which the doctor provides clear and complete medical information to patients about their treatment, and patients provide information on his/her preferences. Patients and clinicians bring different, but equally important, knowledge to the decision-making process. Through the adoption of SDM, it should be possible to overcome the barriers that hinder the acceptance of long-acting injectable antipsychotics (LAIs) by patients, and often also by psychiatrists. The present paper is a critical appraisal of recent literature on the impact of SDM in improving adherence to pharmacological treatments and in implementing the use of LAIs in the treatment of patients with schizophrenia. SDM is recognized as a promising strategy to improve collaboration between clinicians and patients in achieving recovery. When considering drug treatments, clinicians must evaluate the patient's preferences, expectations and concerns towards the development of a personalized treatment strategy. Moreover, an active involvement in the decision process could reduce the patient's perception of being coerced into the use of LAIs. Involving patients in the choice of therapy is not sufficient to increase pharmacological adherence if, at the same time, there is no constant work of comparison and communication with the reference psychiatric team. SDM can be particularly effective for LAI prescription, since patient can have prejudices and unjustified fears related to the LAI formulation, which the doctor must resolve.

Real-world effectiveness of long acting aripiprazole: Treatment persistence and its correlates in the Italian clinical practice

OBJECTIVES

To identify the variables that are associated with persistence to Aripiprazole-Long Acting (A-LAI), in adult patients with schizophrenia.

METHODS

Observational, retrospective, non-interventional study involving 261 patients with schizophrenia.

RESULTS

Eighty-six percent of study subjects were persistent for at least 6 months. All subjects with baseline CGI-S of 1 or 2, 95% of subjects with CGI-S of 3, 86% with CGI-S of 4, 82% of subjects with CGI-S of 5, 73% of subjects with CGI of 6 and 90% of subjects with CGI of 7 were persistent. A-LAI treatment continuation rate was higher in patients with: 1) baseline CGI score ≤ 4; 2) schizophrenia dimension (LDPS) mania score ≤ 5; 3) psychotic spectrum schizoid score ≤ 11.

CONCLUSIONS

A relatively high number of patients (n = 225, 86%) were persistent to A-LAI for at least 6 months. Not surprisingly, very severe patients were more unlikely to be persistent. However, it is noteworthy that a large number of subjects with high CGI score at the time when A-LAI was started (82% of subjects with CGI-S of 5, 73% of subjects with CGI of 6 and 90% of subjects with CGI of 7) were persistent. Larger, controlled, prospective and longer studies are warranted.

Paliperidone palmitate in non-acute patients with schizophrenia previously unsuccessfully treated with risperidone long-acting therapy or frequently used conventional depot antipsychotics

PALMFlexS, a prospective multicentre, open-label, 6-month, phase IIIb interventional study, explored tolerability, safety and treatment response in adults (n = 231) with non-acute but symptomatic schizophrenia switching to flexibly dosed paliperidone palmitate (PP) after unsuccessful treatment with risperidone long-acting injectable therapy (RLAT) or conventional depot antipsychotics (APs). Treatment response was measured by change in Positive and Negative Syndrome Scale (PANSS) total score from baseline (BL) to last-observation-carried-forward (LOCF) endpoint (EP). Safety and tolerability assessments included Extrapyramidal Symptom Rating Scale (ESRS) total score and treatment-emergent adverse events. Significant reductions in mean PANSS total score were observed for all groups (-7.5 to -10.6; p ⩽ 0.01 [BL to LOCF EP]). After switching to PP, more than 50% of all patients achieved ⩾20% and one-third of RLAT-treated patients even achieved ⩾50% improvement in PANSS total score. Across groups, there were significant improvements (p < 0.05) in symptom severity as measured by Clinical Global Impression-Severity (CGI-S; trend for improvement with RLAT; p = 0.0568), subjective well-being, medication satisfaction, and patient functioning with PP. PP was generally well tolerated. Clinically relevant benefits were observed in non-acute patients with schizophrenia switched from RLAT or conventional depot APs to PP.