Transcranial direct current stimulation (tDCS) combined with cognitive training in adolescent boys with ADHD: a double-blind, randomised, sham-controlled trial.

BACKGROUND: Transcranial direct current stimulation (tDCS) could be a side-effect-free alternative to psychostimulants in attention-deficit/hyperactivity disorder (ADHD). Although there is limited evidence for clinical and cognitive effects, most studies were small, single-session and stimulated left dorsolateral prefrontal cortex (dlPFC). No sham-controlled study has stimulated the right inferior frontal cortex (rIFC), which is the most consistently under-functioning region in ADHD, with multiple anodal-tDCS sessions combined with cognitive training (CT) to enhance effects. Thus, we investigated the clinical and cognitive effects of multi-session anodal-tDCS over rIFC combined with CT in double-blind, randomised, sham-controlled trial (RCT, ISRCTN48265228). METHODS: Fifty boys with ADHD (10-18 years) received 15 weekday sessions of anodal- or sham-tDCS over rIFC combined with CT (20 min, 1 mA). ANCOVA, adjusting for baseline measures, age and medication status, tested group differences in clinical and ADHD-relevant executive functions at posttreatment and after 6 months. RESULTS: ADHD-Rating Scale, Conners ADHD Index and adverse effects were significantly lower at post-treatment after sham relative to anodal tDCS. No other effects were significant. CONCLUSIONS: This rigorous and largest RCT of tDCS in adolescent boys with ADHD found no evidence of improved ADHD symptoms or cognitive performance following multi-session anodal tDCS over rIFC combined with CT. These findings extend limited meta-analytic evidence of cognitive and clinical effects in ADHD after 1-5 tDCS sessions over mainly left dlPFC. Given that tDCS is commercially and clinically available, the findings are important as they suggest that rIFC stimulation may not be indicated as a neurotherapy for cognitive or clinical remediation for ADHD.

Double-Blind, Sham-Controlled Randomized Trial Testing the Efficacy of fMRI Neurofeedback on Clinical and Cognitive Measures in Children With ADHD.

OBJECTIVE: Functional MRI neurofeedback (fMRI-NF) could potentially be a novel, safe nonpharmacological treatment for attention deficit hyperactivity disorder (ADHD). A proof-of-concept randomized controlled trial of fMRI-NF of the right inferior frontal cortex (rIFC), compared to an active control condition, showed promising improvement of ADHD symptoms (albeit in both groups) and in brain function. However, comparison with a placebo condition in a larger trial is required to test efficacy. METHODS: This double-blind, sham-controlled randomized controlled trial tested the effectiveness and efficacy of fMRI-NF of the rIFC on symptoms and executive functions in 88 boys with ADHD (44 each in the active and sham arms). To investigate treatment-related changes, groups were compared at the posttreatment and 6-month follow-up assessments, controlling for baseline scores, age, and medication status. The primary outcome measure was posttreatment score on the ADHD Rating Scale (ADHD-RS). RESULTS: No significant group differences were found on the ADHD-RS. Both groups showed similar decreases in other clinical and cognitive measures, except for a significantly greater decrease in irritability and improvement in motor inhibition in sham relative to active fMRI-NF at the posttreatment assessment, covarying for baseline. There were no significant side effects or adverse events. The active relative to the sham fMRI-NF group showed enhanced activation in rIFC and other frontal and temporo-occipital-cerebellar self-regulation areas. However, there was no progressive rIFC upregulation, correlation with ADHD-RS scores, or transfer of learning. CONCLUSIONS: Contrary to the hypothesis, the study findings do not suggest that fMRI-NF of the rIFC is effective in improving clinical symptoms or cognition in boys with ADHD.

Clinical correlates of early onset antipsychotic treatment resistance.

BACKGROUND: There is evidence of heterogeneity within treatment-resistant schizophrenia (TRS), with some people not responding to antipsychotic treatment from illness onset and others becoming treatment-resistant after an initial response period. These groups may have different aetiologies. AIM: This study investigates sociodemographic and clinical correlates of early onset of TRS. METHOD: Employing a retrospective cohort design, we do a secondary analysis of data from a cohort of people with TRS attending the South London and Maudsley. Regression analyses were conducted to identify the correlates of the length of treatment to TRS. Predictors included the following: gender, age, ethnicity, problems with positive symptoms, problems with activities of daily living, psychiatric comorbidities, involuntary hospitalisation and treatment with long-acting injectable antipsychotics. RESULTS: In a cohort of 164 people with TRS (60% were men), the median length of treatment to TRS was 3 years and 8 months. We observed no cut-off on the length of treatment until TRS presentation differentiating between early and late TRS (i.e. no bimodal distribution). Having mild to very severe problems with hallucinations and delusions at the treatment start was associated with earlier TRS (~19 months earlier). In sensitivity analyses, including only complete cases (subject to selection bias), treatment with a long-acting injectable antipsychotic was additionally associated with later TRS (~15 months later). CONCLUSION: Our findings do not support a clear separation between early and late TRS but rather a continuum of the length of treatment before TRS onset. Having mild to very severe problems with positive symptoms at treatment start predicts earlier onset of TRS.

Clinical predictors of antipsychotic treatment resistance: Development and internal validation of a prognostic prediction model by the STRATA-G consortium.

INTRODUCTION: Our aim was to, firstly, identify characteristics at first-episode of psychosis that are associated with later antipsychotic treatment resistance (TR) and, secondly, to develop a parsimonious prediction model for TR. METHODS: We combined data from ten prospective, first-episode psychosis cohorts from across Europe and categorised patients as TR or non-treatment resistant (NTR) after a mean follow up of 4.18 years (s.d. = 3.20) for secondary data analysis. We identified a list of potential predictors from clinical and demographic data recorded at first-episode. These potential predictors were entered in two models: a multivariable logistic regression to identify which were independently associated with TR and a penalised logistic regression, which performed variable selection, to produce a parsimonious prediction model. This model was internally validated using a 5-fold, 50-repeat cross-validation optimism-correction. RESULTS: Our sample consisted of N = 2216 participants of which 385 (17 %) developed TR. Younger age of psychosis onset and fewer years in education were independently associated with increased odds of developing TR. The prediction model selected 7 out of 17 variables that, when combined, could quantify the risk of being TR better than chance. These included age of onset, years in education, gender, BMI, relationship status, alcohol use, and positive symptoms. The optimism-corrected area under the curve was 0.59 (accuracy = 64 %, sensitivity = 48 %, and specificity = 76 %). IMPLICATIONS: Our findings show that treatment resistance can be predicted, at first-episode of psychosis. Pending a model update and external validation, we demonstrate the potential value of prediction models for TR.

Evaluating how treatment adherence influences cognitive remediation outcomes.

BACKGROUND: There is evidence that Cognitive Remediation (CR) is an efficacious approach to reduce cognitive and functioning difficulties in people with schizophrenia. However, there is still a limited understanding of what influences different treatment responses. Treatment adherence has been suggested as one factor but has not been investigated systematically. AIM: To investigate how the number of CR sessions completed influences treatment outcomes. METHOD: This study used data from six randomised controlled trials comparing CR to a control condition. Instrumental variable analysis was used to evaluate the effect of number of treatment sessions on cognitive and functional outcomes. Logistic regression analysis was conducted to identify significant predictors of session attendance. RESULTS: A total of 440 participants with schizophrenia spectrum diagnosis were considered. Participants were mostly men (71.6%) and had a mean age of 39.6 (SD 10.69). A higher number of CR sessions led to larger improvements in executive function and processing speed at end of therapy. However, number of sessions did not influence outcomes for working memory and functioning. Younger age and higher levels of negative symptoms at baseline were associated with higher treatment attendance. CONCLUSION: These findings highlight the importance of treatment adherence and underscore the importance of massed practice, at least for some cognitive outcomes. While it may be complex to assess a single session's contribution to outcome in a dose-response fashion, accessing more sessions seems associated with some cognitive benefits. Observing a relationship to functioning may require longer therapy.

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.

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.

Development and validation of prediction model to estimate 10-year risk of all-cause mortality using modern statistical learning methods: a large population-based cohort study and external validation.

BACKGROUND: In increasingly ageing populations, there is an emergent need to develop a robust prediction model for estimating an individual absolute risk for all-cause mortality, so that relevant assessments and interventions can be targeted appropriately. The objective of the study was to derive, evaluate and validate (internally and externally) a risk prediction model allowing rapid estimations of an absolute risk of all-cause mortality in the following 10 years. METHODS: For the model development, data came from English Longitudinal Study of Ageing study, which comprised 9154 population-representative individuals aged 50-75 years, 1240 (13.5%) of whom died during the 10-year follow-up. Internal validation was carried out using Harrell's optimism-correction procedure; external validation was carried out using Health and Retirement Study (HRS), which is a nationally representative longitudinal survey of adults aged ≥50 years residing in the United States. Cox proportional hazards model with regularisation by the least absolute shrinkage and selection operator, where optimisation parameters were chosen based on repeated cross-validation, was employed for variable selection and model fitting. Measures of calibration, discrimination, sensitivity and specificity were determined in the development and validation cohorts. RESULTS: The model selected 13 prognostic factors of all-cause mortality encompassing information on demographic characteristics, health comorbidity, lifestyle and cognitive functioning. The internally validated model had good discriminatory ability (c-index=0.74), specificity (72.5%) and sensitivity (73.0%). Following external validation, the model's prediction accuracy remained within a clinically acceptable range (c-index=0.69, calibration slope ß=0.80, specificity=71.5% and sensitivity=70.6%). The main limitation of our model is twofold: 1) it may not be applicable to nursing home and other institutional populations, and 2) it was developed and validated in the cohorts with predominately white ethnicity. CONCLUSIONS: A new prediction model that quantifies absolute risk of all-cause mortality in the following 10-years in the general population has been developed and externally validated. It has good prediction accuracy and is based on variables that are available in a variety of care and research settings. This model can facilitate identification of high risk for all-cause mortality older adults for further assessment or interventions.

Exploring the role of age as a moderator of cognitive remediation for people with schizophrenia.

BACKGROUND: While Cognitive Remediation (CR) is effective in reducing cognitive and functioning difficulties in people with schizophrenia, there is variability in treatment response. Previous research suggested that participants' age may be a significant moderator of CR response. AIM: To examine the impact of participants' age on CR outcomes. METHOD: Individual participant data were accessed from fourteen CR randomised controlled trials. We tested the moderating effect of participants' age on cognitive and functioning outcomes using multivariate linear models. RESULTS: Data from 1084 people with a diagnosis of schizophrenia were considered. Participants had a mean age of 36.6 years (SD 11), with 11.6 years of education (SD 2.8), and an average duration of illness of 13.5 years (SD 10.7). Multivariate models showed that participants' age, when considered as a continuous variable, was not a significant moderator of treatment effect for cognitive and functioning outcomes. However, when participants were split by median age, younger participants showed higher gains in executive functions following CR compared to older participants (p=0.02). CONCLUSION: These results suggest that participants' age does not moderate most CR outcomes. However, larger age differences may influence the effect of CR on executive function. This may suggest some adaptation of CR practice according to participants' age. These findings inform the CR personalisation agenda.

Can IQ moderate the response to cognitive remediation in people with schizophrenia?

BACKGROUND: IQ and IQ decline are considered risk factors for poor prognosis in people with a diagnosis of schizophrenia. However, it is still not clear if, at least in part, IQ and IQ decline influence long-term outcomes via a negative effect on interventions. AIM: To identify whether current IQ, estimated premorbid IQ, or IQ decline moderate the response to cognitive remediation (CR). METHOD: Individual participant data from twelve randomised controlled trials of CR were considered. Hierarchical and k-means analyses were carried out to identify different IQ clusters. The moderating effect of estimated premorbid IQ, current IQ, and different IQ clusters (preserved, deteriorated and compromised trajectories) on cognitive outcomes at post-therapy and follow-up were evaluated using multiple linear regression. RESULTS: Data from 984 participants (CR = 544, control = 440) with schizophrenia and schizoaffective disorders were considered. The sample had a mean current IQ of 84.16 (SD 15.61) and estimated premorbid IQ of 95.82 (SD 10.63). Current IQ moderated working memory outcomes: people with higher IQ had larger working memory gains after therapy compared to those with a lower IQ. Those with a preserved IQ had better cognitive outcomes compared to either the deteriorated or compromised IQ groups, and those with a deteriorated IQ had better outcomes compared to those in the compromised IQ group. CONCLUSION: Current IQ is a significant moderator of cognitive gains after CR. These findings highlight the need to evaluate whether therapy adaptations (e.g. offering more sessions) can attenuate this effect so that those with lower IQ may derive benefit similar to those with higher IQ.

Predicting onset of early- and late-treatment resistance in first-episode schizophrenia patients using advanced shrinkage statistical methods in a small sample.

Evidence suggests there are two treatment-resistant schizophrenia subtypes (i.e. early treatment resistant (E-TR) and late-treatment resistant (L-TR)). We aimed to develop prediction models for estimating individual risk for these outcomes by employing advanced statistical shrinkage methods. 239 first-episode schizophrenia (FES) patients were followed-up for approximately 5 years after first presentation to psychiatric services; of these, n=56 (25.2%) were defined as E-TR and n=24 (12.6%) were defined as L-TR. Using known risk factors for poor schizophrenia outcomes, we developed prediction models for E-TR and L-TR using LASSO and RIDGE logistic regression models. Models' internal validation was performed employing Harrell's optimism-correction with repeated cross-validation; their predictive accuracy was assessed through discrimination and calibration. Both LASSO and RIDGE models had high discrimination, good calibration. While LASSO had moderate sensitivity for estimating an individual risk for E-TR and L-TR, sensitivity estimated for RIDGE model for these outcomes was extremely low, which was due to having a very large estimated optimism. Although it was possible to discriminate with sufficient accuracy who would meet criteria for E-TR and L-TR during the 5-year follow-up after first contact with mental health services for schizophrenia, further work is necessary to improve sensitivity for these models.

Acupuncture for irritable bowel syndrome: 2-year follow-up of a randomised controlled trial.

BACKGROUND: A recent randomised controlled trial (RCT) of acupuncture as a treatment for irritable bowel syndrome (IBS) demonstrated sustained benefits over a period of 12 months post-randomisation. AIM: To extend the trial follow-up to evaluate the effects of acupuncture at 24 months post-randomisation. METHODS: Patients in primary care with ongoing IBS were recruited to a two-arm pragmatic RCT of acupuncture for IBS. Participants were randomised to the offer of up to 10 weekly sessions of acupuncture plus usual care (n=116 patients) or to continue with usual care alone (n=117). The primary outcome was the self-reported IBS symptom severity score (IBS SSS) measured at 24 months post-randomisation. Analysis was by intention-to-treat using an unstructured multivariate linear model incorporating all repeated measures. RESULTS: The overall response rate was 61%. The adjusted difference in mean IBS SSS at 24 months was -18.28 (95% CI -40.95 to 4.40) in favour of the acupuncture arm. Differences at earlier time points estimated from the multivariate model were: -27.27 (-47.69 to -6.86) at 3 months; -23.69 (-45.17 to -2.21) at 6 months; -24.09 (-45.59 to -2.59) at 9 months; and -23.06 (-44.52 to -1.59) at 12 months. CONCLUSIONS: There were no statistically significant differences between the acupuncture and usual care groups in IBS SSS at 24 months post-randomisation, and the point estimate for the mean difference was approximately 80% of the size of the statistically significant results seen at 6, 9 and 12 months. TRIAL REGISTRATION NUMBER: ISRCTN08827905.

The long-term effectiveness of cognitive behavior therapy for psychosis within a routine psychological therapies service.

Randomised controlled trials (RCTs) have shown the efficacy of CBTp, however, few studies have considered its long-term effectiveness in routine services. This study reports the outcomes of clients seen in a psychological therapies clinic, set up following positive results obtained from an RCT (Peters et al., 2010). The aims were to evaluate the effectiveness of CBTp, using data from the service's routine assessments for consecutive referrals over a 12 years period, and assess whether gains were maintained at a 6+ months' follow-up. Of the 476 consenting referrals, all clients (N = 358) who received ≥5 therapy sessions were offered an assessment at four time points (baseline, pre-, mid-, and end of therapy) on measures assessing current psychosis symptoms, emotional problems, general well-being and life satisfaction. A sub-set (N = 113) was assessed at a median of 12 months after finishing therapy. Following the waiting list (median of 3 months) clients received individualized, formulation-based CBTp for a median number of 19 sessions from 121 therapists with a range of experience receiving regular supervision. Clients showed no meaningful change on any measure while on the waiting list (Cohen's d <= 0.23). In contrast, highly significant improvements following therapy, all of which were significantly greater than changes during the waiting list, were found on all domains assessed (Cohen's d: 0.44-0.75). All gains were maintained at follow-up (Cohen's d: 0.29-0.82), with little change between end of therapy and follow-up (Cohen's d <= 0.18). Drop-out rate from therapy was low (13%). These results demonstrate the positive and potentially enduring impact of psychological therapy on a range of meaningful outcomes for clients with psychosis. The follow-up assessments were conducted on only a sub-set, which may not generalize to the full sample. Nevertheless this study is the largest of its kind in psychosis, and has important implications for the practice of CBTp in clinical services.