Relationships between early age at onset of psychotic symptoms and treatment resistant schizophrenia.

AIM: Early age at schizophrenia onset (EOS) has been associated with a worse clinical course, although previous studies reported substantial heterogeneity. Despite the relevance of the subject, the relationship between the age of onset and treatment resistant schizophrenia (TRS) is less clear. METHODS: We screened 197 non-affective psychotic patients. Of these, 99 suffered from schizophrenia and were putative TRS and were included in a prospective 4-to-8-week trial to assess their response to antipsychotics. According to status (TRS/nonTRS) and age-at-onset (early: ≤18 years, EOS; adult: >18 years, adult onset schizophrenia [AOS]) patients were subdivided in EOS-TRS, EOS-nonTRS, AOS-TRS, AOS-nonTRS. Multiple clinical variables were measured and compared by analysis of covariance (ANCOVA), using age as a covariate. Two-way analysis of variance (ANOVA) was used to assess whether significant differences were attributable to TRS status or age-at-onset. RESULTS: The rate of TRS patients was significantly higher in EOS compared to AOS. At the ANCOVA, EOS-TRS had significantly worse clinical, cognitive, and psychosocial outcomes compared to the other groups. Overall, EOS-TRS were more impaired than EOS-nonTRS, while significant differences with AOS-TRS were less consistent, albeit appreciable. Two-way ANOVA demonstrated that, in the majority of the investigated variables, the significant differences among groups were attributable to the TRS status effect rather than to age-at-onset or combined effects. CONCLUSIONS: These results suggest that refractoriness to antipsychotics may be strongly linked to the early onset of psychotic symptoms, possibly as a result of common neurobiology.

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.

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.

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.