Assessing patient-rated vs. clinician-rated adherence to the therapy in treatment resistant schizophrenia, schizophrenia responders, and non-schizophrenia patients

Neuropsychological differences between treatment-resistant and treatment-responsive schizophrenia: a meta-analysis

Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia. Of those affected, 70-84% are reported to be treatment resistant from the outset. This raises the possibility that the neurobiological mechanisms of treatment resistance emerge before the onset of psychosis and have a neurodevelopmental origin. Neuropsychological investigations can offer important insights into the nature, origin and pathophysiology of treatment-resistant schizophrenia (TRS), but methodological limitations in a still emergent field of research have obscured the neuropsychological discriminability of TRS. We report on the first systematic review and meta-analysis to investigate neuropsychological differences between TRS patients and treatment-responsive controls across 17 published studies (1864 participants). Five meta-analyses were performed in relation to (1) executive function, (2) general cognitive function, (3) attention, working memory and processing speed, (4) verbal memory and learning, and (5) visual-spatial memory and learning. Small-to-moderate effect sizes emerged for all domains. Similarly to previous comparisons between unselected, drug-naïve and first-episode schizophrenia samples v. healthy controls in the literature, the largest effect size was observed in verbal memory and learning [dl = -0.53; 95% confidence interval (CI) -0.29 to -0.76; z = 4.42; p < 0.001]. A sub-analysis of language-related functions, extracted from across the primary domains, yielded a comparable effect size (dl = -0.53, 95% CI -0.82 to -0.23; z = 3.45; p < 0.001). Manipulating our sampling strategy to include or exclude samples selected for clozapine response did not affect the pattern of findings. Our findings are discussed in relation to possible aetiological contributions to TRS.

Clinical evaluation of functional capacity in treatment resistant schizophrenia patients: Comparison and differences with non-resistant schizophrenia patients

Treatment resistant schizophrenia (TRS) is defined by poor or non-response to conventional antipsychotic agents. Functional capacity is defined as the baseline potential of a patient to function in the community, irrespective of actual achievements gained, and has never been studied in TRS. Here, we screened 182 patients with psychotic symptoms and separated them in TRS (n = 28) and non-TRS (n = 32) ones, to evaluate whether they exhibited differential extents and predictive clinical variables of functional capacity. Functional capacity was measured by the UCSD Performance-Based Skills Assessment (UPSA). Psychotic symptoms by PANSS, social functioning by PSP and SLOF, clinical severity of the illness, cognitive functioning, and neurological soft signs (NSS) were assessed. TRS patients had non-significant lower UPSA scores compared to non-TRS (t-test: p > 0.05). In TRS, UPSA score correlated with multiple clinical variables. The highest effect sizes were observed for PANSS negative score (r = -0.67, p < 0.005); SLOF Area1 score (r = 0.66, p < 0.005); NSS severity (r = -0.61, p < 0.005). Multivariate analysis showed that main predictors of UPSA score in TRS patients were PANSS negative score, education years, NSS, Problem Solving performances, and PSP score (F = 11.12, R² = 0.75, p < 0.0005). These variables were not predictive of UPSA score in non-TRS patients. Hierarchical analysis found that variance in UPSA score mainly depended on negative symptoms, NSS, and problem solving (F = 15.21, R² = 0.65, p < 0.0005). Path analysis individuated two separate paths to UPSA score. These results delineate a limited and independent group of candidate predictors to be putatively accounted for therapeutic interventions to improve functional capacity, and possibly social functioning, in TRS patients.

Evaluation of a few discrete clinical markers may predict categorization of actively symptomatic non-acute schizophrenia patients as treatment resistant or responders: A study by ROC curve analysis and multivariate analyses

Here, we used Receiver Operating Characteristic (ROC) curve analysis to determine whether clinical factors may aid predicting the categorization of schizophrenia patients as Treatment Resistant (TRS) or antipsychotic responsive schizophrenia (ARS). Patients with an established condition of TRS or ARS were assessed for: clinical presentation and course; neurological soft signs (NES); psychopathology by PANSS; cognitive performances; quality of life scale (QLS); functional capacity; social functioning (PSP and SLOF scales). In ROC curve analysis, significance indicated that the Area under curve (AUC) allowed distinguishing between TRS and ARS. Multivariate analyses were additionally used to provide independent predictive analysis. Multiple clinical variables showed significant AUCs. The largest significant AUCs were found for: NES total score; SLOF Area2; QLS subscale; antipsychotic doses. The highest sensitivity was found for NES total score, the highest specificity for previous hospitalizations. The highest Odds Ratio of being included within the TRS category were found for: NES total score (7.5); QLS total score (5.49); and previous hospitalizations (4.76). This same circumscribed group of variables was also found to be predictive of TRS when adopting stepwise logistic regression or discriminant analysis. We concluded that the evaluation of few clinical factors may provide reliable and accurate predictions on whether one schizophrenia patient may be categorized as a TRS.

Treatment resistant schizophrenia and neurological soft signs may converge on the same pathology: Evidence from explanatory analysis on clinical, psychopathological, and cognitive variables

Here, we investigated neurological soft signs (NSSs) in treatment resistant schizophrenia (TRS) vs treatment responder schizophrenia (SZ) patients. TRS is a severe condition, affecting approximately one-third of schizophrenia patients and representing a relevant clinical challenge. NSSs are neurological abnormalities reportedly described in schizophrenia patients and linked to dysregulated network connections. We explored the possibility that NSSs may be: i) more severe in TRS patients; ii) differentially associated to clinical/cognitive variables in TRS vs SZ; iii) predictive of having TRS. In addition, we evaluated whether diagnosis may mediate NSSs associations with the above-mentioned variables. Consecutive patients with schizophrenia diagnosis underwent stringent assessment for TRS diagnosis. Demographics and clinical variables were recorded. Psychopathology (by Positive and Negative Syndrome Scale, PANSS), cognitive performances, and NSSs (by Neurological Evaluation Scale, NES) were tested. TRS had higher scores than SZ patients in total NES score and in almost all NES subscales, even after correction for duration of illness and antipsychotic dose (ANCOVA, p<0.05). NSSs significantly correlated with multiple clinical, psychopathological, and cognitive variables (above all: duration of disease and negative symptoms) in TRS but not in SZ patients. Two-way ANOVA showed NSS-x-diagnosis interaction in determining outcomes on multiple cognitive performances, but not in other clinical variables. However, simple main effect analysis detected a significant relationship between high severity NSSs and TRS diagnosis on multiple clinical and cognitive outcomes. Hierarchical regression analysis showed that diagnosis was among a discrete number of predictors yielding significant increases in variance explained on NES total, Sensory Integration and Other Signs subscales' scores. NSSs, together with antipsychotic dose and disease severity, were found to be significantly predictive of TRS diagnosis in a binary logistic regression model. These results suggest a stringent association between NSSs and TRS diagnosis, and may imply that NSSs association with clinical, psychopathological, and cognitive variables may be in part mediated by TRS diagnosis.

Disease Severity in Treatment Resistant Schizophrenia Patients Is Mainly Affected by Negative Symptoms, Which Mediate the Effects of Cognitive Dysfunctions and Neurological Soft Signs

This post-hoc study was aimed at assessing whether disease severity was higher in a sample of Treatment Resistant Schizophrenia patients (TRS) compared to schizophrenia patients responsive to antipsychotics (non-TRS). Determinants of disease severity were also investigated in these groups. Eligible patients were screened by standardized diagnostic algorithm to categorize them as TRS or non-TRS. All patients underwent the following assessments: CGI-S; PANSS; DAI; NES; a battery of cognitive tests. Socio-demographic and clinical variables were also recorded. TRS patients exhibited significantly higher disease severity and psychotic symptoms, either as PANSS total score or subscales' scores. A preliminary correlation analysis ruled out clinical and cognitive variables not associated with disease severity in the two groups. Hierarchical linear regression showed that negative symptoms were the clinical variable explaining the highest part of variation in disease severity in TRS, while in non-TRS patients PANSS-General Psychopathology was the variable explaining the highest variation. Mediation analysis showed that negative symptoms mediate the effects of verbal fluency dysfunctions and high-level neurological soft signs (NSS) on TRS' disease severity. These results show that determinants of disease severity sharply differ in TRS and non-TRS patients, and let hypothesize that TRS may stem from cognitive disfunctions and putatively neurodevelopmental aberrations.