Two distinct patterns of treatment resistance:clinical predictors of treatment resistance in first-episode schizophrenia spectrum psychoses

BACKGROUND: Clozapine remains the only evidence-based antipsychotic for treatment-resistant schizophrenia (TRS). The ability to predict which patients with their first onset of schizophrenia would subsequently meet criteria for treatment resistance (TR) could help to diminish the severe functional disability which may ensue if TR is not recognized and correctly treated. METHOD: This is a 5-year longitudinal assessment of clinical outcomes in a cohort of 246 first-episode schizophrenia spectrum patients recruited as part of the NIHR Genetics and Psychosis (GAP) study conducted in South London from 2005 to 2010. We examined the relationship between baseline demographic and clinical measures and the emergence of TR. TR status was determined from a review of electronic case records. We assessed for associations with early-, and late-onset TR, and non-TR, and differences between those TR patients treated with clozapine and those who were not. RESULTS: Seventy per cent (n = 56) of TR patients, and 23% of the total study population (n = 246) were treatment resistant from illness onset. Those who met criteria for TR during the first 5 years of illness were more likely to have an early age of first contact for psychosis (years) [odds ratio (OR) 2.49, 95% confidence interval (CI) 1.25-4.94] compared to those with non-TR. The relationship between an early age of first contact (years) and TR was significant in patients of Black ethnicity (OR 3.71, 95% CI 1.44-9.56); and patients of male gender (OR 3.13 95% CI 1.35-7.23). CONCLUSIONS: For the majority of the TR group, antipsychotic TR is present from illness onset, necessitating increased consideration for the earlier use of clozapine

Anticipated and experienced discrimination amongst people with schizophrenia, bipolar disorder and major depressive disorder: a cross-sectional study.

BACKGROUND: The unfair treatment of individuals with severe mental illness has been linked to poorer physical and mental health outcomes. Additionally, anticipation of discrimination may lead some individuals to avoid participation in particular life areas, leading to greater isolation and social marginalisation. This study aimed to establish the levels and clinical and socio-demographic associations of anticipated and experienced discrimination amongst those diagnosed with a schizophrenia and comparator severe mental illnesses (bipolar and major depressive disorders). METHODS: This study was a cross-sectional analysis of anticipated and experienced discrimination from 202 individuals in South London (47% with schizophrenia, 32% with depression and 20% with bipolar disorder). RESULTS: 93% of the sample anticipated discrimination and 87% of participants had experienced discrimination in at least one area of life in the previous year. There was a significant association between the anticipation and the experience of discrimination. Higher levels of experienced discrimination were reported by those of a mixed ethnicity, and those with higher levels of education. Women anticipated more discrimination than men. Neither diagnosis nor levels of functioning were associated with the extent of discrimination. Clinical symptoms of anxiety, depression and suspiciousness were associated with more experienced and anticipated discrimination respectively. CONCLUSIONS: The unfair treatment of individuals with severe mental illnesses remains unacceptably common. Population level interventions are needed to reduce levels of discrimination and to safeguard individuals. Interventions are also required to assist those with severe mental illness to reduce internalised stigma and social avoidance

Treatment-Resistant Schizophrenia: Treatment Response and Resistance in Psychosis (TRRIP) Working Group Consensus Guidelines on Diagnosis and Terminology

OBJECTIVE: Research and clinical translation in schizophrenia is limited by inconsistent definitions of treatment resistance and response. To address this issue, the authors evaluated current approaches and then developed consensus criteria and guidelines. METHODS: A systematic review of randomized antipsychotic clinical trials in treatment-resistant schizophrenia was performed, and definitions of treatment resistance were extracted. Subsequently, consensus operationalized criteria were developed through 1) a multiphase, mixed methods approach, 2) identification of key criteria via an online survey, and 3) meetings to achieve consensus. RESULTS: Of 2,808 studies identified, 42 met inclusion criteria. Of these, 21 studies (50%) did not provide operationalized criteria. In the remaining studies, criteria varied considerably, particularly regarding symptom severity, prior treatment duration, and antipsychotic dosage thresholds; only two studies (5%) utilized the same criteria. The consensus group identified minimum and optimal criteria, employing the following principles: 1) current symptoms of a minimum duration and severity determined by a standardized rating scale; 2) moderate or worse functional impairment; 3) prior treatment consisting of at least two different antipsychotic trials, each for a minimum duration and dosage; 4) systematic monitoring of adherence and meeting of minimum adherence criteria; 5) ideally at least one prospective treatment trial; and 6) criteria that clearly separate responsive from treatment-resistant patients. CONCLUSIONS: There is considerable variation in current approaches to defining treatment resistance in schizophrenia. The authors present consensus guidelines that operationalize criteria for determining and reporting treatment resistance, adequate treatment, and treatment response, providing a benchmark for research and clinical translation

Estimating Exposome Score for Schizophrenia Using Predictive Modeling Approach in Two Independent Samples: The Results From the EUGEI Study

Exposures constitute a dense network of the environment: exposome. Here, we argue for embracing the exposome paradigm to investigate the sum of nongenetic "risk" and show how predictive modeling approaches can be used to construct an exposome score (ES; an aggregated score of exposures) for schizophrenia. The training dataset consisted of patients with schizophrenia and controls, whereas the independent validation dataset consisted of patients, their unaffected siblings, and controls. Binary exposures were cannabis use, hearing impairment, winter birth, bullying, and emotional, physical, and sexual abuse along with physical and emotional neglect. We applied logistic regression (LR), Gaussian Naive Bayes (GNB), the least absolute shrinkage and selection operator (LASSO), and Ridge penalized classification models to the training dataset. ESs, the sum of weighted exposures based on coefficients from each model, were calculated in the validation dataset. In addition, we estimated ES based on meta-analyses and a simple sum score of exposures. Accuracy, sensitivity, specificity, area under the receiver operating characteristic, and Nagelkerke's R2 were compared. The ESMeta-analyses performed the worst, whereas the sum score and the ESGNB were worse than the ESLR that performed similar to the ESLASSO and ESRIDGE. The ESLR distinguished patients from controls (odds ratio [OR] = 1.94, P < .001), patients from siblings (OR = 1.58, P < .001), and siblings from controls (OR = 1.21, P = .001). An increase in ESLR was associated with a gradient increase of schizophrenia risk. In reference to the remaining fractions, the ESLR at top 30%, 20%, and 10% of the control distribution yielded ORs of 3.72, 3.74, and 4.77, respectively. Our findings demonstrate that predictive modeling approaches can be harnessed to evaluate the exposome

White Noise Speech Illusions: A Trait-Dependent Risk Marker for Psychotic Disorder?

Introduction: White noise speech illusions index liability for psychotic disorder in case-control comparisons. In the current study, we examined i) the rate of white noise speech illusions in siblings of patients with psychotic disorder and ii) to what degree this rate would be contingent on exposure to known environmental risk factors (childhood adversity and recent life events) and level of known endophenotypic dimensions of psychotic disorder [psychotic experiences assessed with the Community Assessment of Psychic Experiences (CAPE) scale and cognitive ability]. Methods: The white noise task was used as an experimental paradigm to elicit and measure speech illusions in 1,014 patients with psychotic disorders, 1,157 siblings, and 1,507 healthy participants. We examined associations between speech illusions and increasing familial risk (control -> sibling -> patient), modeled as both a linear and a categorical effect, and associations between speech illusions and level of childhood adversities and life events as well as with CAPE scores and cognitive ability scores. Results: While a positive association was found between white noise speech illusions across hypothesized increasing levels of familial risk (controls -> siblings -> patients) [odds ratio (OR) linear 1.11, 95% confidence interval (CI) 1.02-1.21, p = 0.019], there was no evidence for a categorical association with sibling status (OR 0.93, 95% CI 0.79-1.09, p = 0.360). The association between speech illusions and linear familial risk was greater if scores on the CAPE positive scale were higher (p interaction = 0.003; ORlow CAPE positive scale 0.96, 95% CI 0.85-1.07; ORhigh CAPE positive scale 1.26, 95% CI 1.09-1.46); cognitive ability was lower (p interaction < 0.001; ORhigh cognitive ability 0.94, 95% CI 0.84-1.05; ORlow cognitive ability 1.43, 95% CI 1.23-1.68); and exposure to childhood adversity was higher (p interaction < 0.001; ORlow adversity 0.92, 95% CI 0.82-1.04; ORhigh adversity 1.31, 95% CI 1.13-1.52). A similar, although less marked, pattern was seen for categorical patient-control and sibling-control comparisons. Exposure to recent life events did not modify the association between white noise and familial risk (p interaction = 0.232). Conclusion: The association between white noise speech illusions and familial risk is contingent on additional evidence of endophenotypic expression and of exposure to childhood adversity. Therefore, speech illusions may represent a trait-dependent risk marker

The Meaning of Body Experience Evaluation in Oncology

Evaluation of quality of life, psychic and bodily well-being is becoming increasingly important in oncology aftercare. This type of assessment is mainly carried out by medical psychologists. In this paper I will seek to show that body experience valuation has, besides its psychological usefulness, a normative and practical dimension. Body experience evaluation aims at establishing the way a person experiences and appreciates his or her physical appearance, intactness and competence. This valuation constitutes one’s ‘body image’. While, first, interpreting the meaning of body image and, second, indicating the limitations of current psychological body image assessment, I argue that the normative aspect of body image is related to the experience of bodily wholeness or bodily integrity. Since this experience is contextualized by a person’s life story, evaluation should also focus on narrative aspects. I finally suggest that the interpretation of body experience is not only valuable to assess a person’s quality of life after treatment, but that it can also be useful in counseling prior to interventions, since it can support patients in making decisions about interventions that will change their bodies. To apply this type of evaluation to oncology practice, a rich and tailored vocabulary of body experiences has to be developed

Cross-national variations in reported discrimination among people treated for major depression worldwide: The ASPEN/INDIGO international study

Background: No study has so far explored differences in discrimination reported by people with major depressive disorder (MDD) across countries and cultures. Aims: To (a) compare reported discrimination across different countries, and (b) explore the relative weight of individual and contextual factors in explaining levels of reported discrimination in people with MDD. Method: Cross-sectional multisite international survey (34 countries worldwide) of 1082 people with MDD. Experienced and anticipated discrimination were assessed by the Discrimination and Stigma Scale (DISC). Countries were classified according to their rating on the Human Development Index (HDI). Multilevel negative binomial and Poisson models were used. Results: People living in 'very high HDI' countries reported higher discrimination than those in 'medium/low HDI' countries. Variation in reported discrimination across countries was only partially explained by individual-level variables. The contribution of country-level variables was significant for anticipated discrimination only. Conclusions: Contextual factors play an important role in anticipated discrimination. Country-specific interventions should be implemented to prevent discrimination towards people with MDD