Evaluation of the cost-effectiveness of services for Schizophrenia in the UK across the entire care pathway in a single whole-disease model

Importance The existing economic models for schizophrenia often have 3 limitations; namely, they do not cover nonpharmacologic interventions, they report inconsistent conclusions for antipsychotics, and they have poor methodologic quality. Objectives To develop a whole-disease model for schizophrenia and use it to inform resource allocation decisions across the entire care pathway for schizophrenia in the UK. Design, Setting, and Participants This decision analytical model used a whole-disease model to simulate the entire disease and treatment pathway among a simulated cohort of 200 000 individuals at clinical high risk of psychoses or with a diagnosis of psychosis or schizophrenia being treated in primary, secondary, and tertiary care in the UK. Data were collected March 2016 to December 2018 and analyzed December 2018 to April 2019. Exposures The whole-disease model used discrete event simulation; its structure and input data were informed by published literature and expert opinion. Analyses were conducted from the perspective of the National Health Service and Personal Social Services over a lifetime horizon. Key interventions assessed included cognitive behavioral therapy, antipsychotic medication, family intervention, inpatient care, and crisis resolution and home treatment team. Main Outcomes and Measures Life-time costs and quality-adjusted life-years. Results In the simulated cohort of 200 000 individuals (mean [SD] age, 23.5 [5.1] years; 120 800 [60.4%] men), 66 400 (33.2%) were not at risk of psychosis, 69 800 (34.9%) were at clinical high risk of psychosis, and 63 800 (31.9%) had psychosis. The results of the whole-disease model suggest the following interventions are likely to be cost-effective at a willingness-to-pay threshold of £20 000 ($25 552) per quality-adjusted life-year: practice as usual plus cognitive behavioral therapy for individuals at clinical high risk of psychosis (probability vs practice as usual alone, 0.96); a mix of hospital admission and crisis resolution and home treatment team for individuals with acute psychosis (probability vs hospital admission alone, 0.99); amisulpride (probability vs all other antipsychotics, 0.39), risperidone (probability vs all other antipsychotics, 0.30), or olanzapine (probability vs all other antipsychotics, 0.17) combined with family intervention for individuals with first-episode psychosis (probability vs family intervention or medication alone, 0.58); and clozapine for individuals with treatment-resistant schizophrenia (probability vs other medications, 0.81). Conclusions and Relevance The results of this study suggest that the current schizophrenia service configuration is not optimal. Cost savings and/or additional quality-adjusted life-years may be gained by replacing current interventions with more cost-effective interventions

Extracting antipsychotic polypharmacy data from electronic health records: developing and evaluating a novel process

Background Antipsychotic prescription information is commonly derived from structured fields in clinical health records. However, utilising diverse and comprehensive sources of information is especially important when investigating less frequent patterns of medication prescribing such as antipsychotic polypharmacy (APP). This study describes and evaluates a novel method of extracting APP data from both structured and free-text fields in electronic health records (EHRs), and its use for research purposes. Methods Using anonymised EHRs, we identified a cohort of patients with serious mental illness (SMI) who were treated in South London and Maudsley NHS Foundation Trust mental health care services between 1 January and 30 June 2012. Information about antipsychotic co-prescribing was extracted using a combination of natural language processing and a bespoke algorithm. The validity of the data derived through this process was assessed against a manually coded gold standard to establish precision and recall. Lastly, we estimated the prevalence and patterns of antipsychotic polypharmacy. Results Individual instances of antipsychotic prescribing were detected with high precision (0.94 to 0.97) and moderate recall (0.57-0.77). We detected baseline APP (two or more antipsychotics prescribed in any 6-week window) with 0.92 precision and 0.74 recall and long-term APP (antipsychotic co-prescribing for 6 months) with 0.94 precision and 0.60 recall. Of the 7,201 SMI patients receiving active care during the observation period, 338 (4.7 %; 95 % CI 4.2-5.2) were identified as receiving long-term APP. Two second generation antipsychotics (64.8 %); and first -second generation antipsychotics were most commonly co-prescribed (32.5 %). Conclusions These results suggest that this is a potentially practical tool for identifying polypharmacy from mental health EHRs on a large scale. Furthermore, extracted data can be used to allow researchers to characterize patterns of polypharmacy over time including different drug combinations, trends in polypharmacy prescribing, predictors of polypharmacy prescribing and the impact of polypharmacy on patient outcomes

Cost and health impacts of adherence to the National Institute for Health and Care Excellence schizophrenia guideline recommendations

Background Discrepancies between the National Institute for Health and Care Excellence (NICE) schizophrenia guideline recommendations and current clinical practice in the UK have been reported. Aims We aim to assess whether it is cost-effective to improve adherence to the NICE schizophrenia guideline recommendations, compared with current practice. Method A previously developed whole-disease model for schizophrenia, using the discrete event simulation method, was adapted to assess the cost and health impacts of adherence to the NICE recommendations. Three scenarios to improve adherence to the clinical guidelines were modelled: universal provision of cognitive–behavioural therapy for patients at clinical high risk of psychosis, universal provision of family intervention for patients with first-episode psychosis and prompt provision of clozapine for patients with treatment-resistant schizophrenia. The primary outcomes were lifetime costs and quality-adjusted life-years gained. Results The results suggest full adherence to the guideline recommendations would decrease cost and improve quality-adjusted life-years. Based on the NICE willingness-to-pay threshold of £20 000–£30 000 per quality-adjusted life-year gained, prompt provision of clozapine for patients with treatment-resistant schizophrenia results in the greatest net monetary benefit, followed by universal provision of cognitive–behavioural therapy for patients at clinical high risk of psychosis, and universal provision of family intervention for patients with first-episode psychosis. Conclusions Our results suggest that adherence to guideline recommendations would decrease cost and improve quality-adjusted life-years. Greater investment is needed to improve guideline adherence and therefore improve patient quality of life and realise potential cost savings

A systematic review of economic models across the entire schizophrenia pathway

Background Schizophrenia is associated with a high economic burden. Economic models can help to inform resource allocation decisions to maximise benefits to patients. Objectives This systematic review aims to assess the availability, quality and consistency of conclusions of health economic models evaluating the cost effectiveness of interventions for schizophrenia. Methods An electronic search was performed on multiple databases (MEDLINE, EMBASE, PsycINFO, Cochrane database of systematic reviews, NHS Economic Evaluation Database and Health Technology Assessment database) to identify economic models of interventions for schizophrenia published between 2005 and 2020. Two independent reviewers selected studies for inclusion. Study quality was assessed using the National Institute for Health and Care Excellence (NICE) checklist and the Cooper hierarchy. Model characteristics and conclusions were descriptively summarised. Results Seventy-three models met inclusion criteria. Seventy-eight percent of existing models assessed antipsychotics; however, due to inconsistent conclusions reported by different studies, no antipsychotic can be considered clearly cost effective compared with the others. A very limited number of models suggest that the following non-pharmacological interventions might be cost effective: psychosocial interventions, stratified tests, employment intervention and intensive intervention to improve liaison between primary and secondary care. The quality of included models is generally low due to use of a short time horizon, omission of adverse events of interventions, poor data quality and potential conflicts of interest. Conclusions This review highlights a lack of models for non-pharmacological interventions, and limitations of the existing models, including low quality and inconsistency in conclusions. Recommendations on future modelling approaches for schizophrenia are provided

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

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. 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. 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 %). 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

Peripheral immune markers and antipsychotic non-response in psychosis

Background Peripheral immune markers have previously been linked to a poor response to antipsychotic medication and more severe negative symptoms at the onset of psychosis. The present study investigated the association of blood cytokines and complement markers with the presence of antipsychotic non-response and symptom severity in patients with psychosis. Methods This cross-sectional study recruited 94 patients with schizophrenia and other psychoses, of whom 47 were defined as antipsychotic responders and 47 as antipsychotic non-responders. In all subjects we measured plasma levels of cytokines (IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α, and IFN-γ), complement markers (C1-inhibitor, C3, C4, C3a, C3b, Bb, factor D, C5a, terminal complement complex) and high sensitivity C-reactive protein (hsCRP). Symptom severity was recorded using the Positive and Negative Syndrome scale for Schizophrenia (PANSS). Binary logistic regression tested each immune marker as predictor of response status while covarying for relevant socio-demographic variables. Correlation analyses tested the association between immune markers and the severity of symptoms. Results Interleukin (IL)-8 significantly predicted antipsychotic non-response (OR=24.70, 95% CI, 1.35–453.23, p = 0.03). Other immune markers were not associated with antipsychotic response. IL-6, IL-8, IL-10 and TNF-α significantly positively correlated with negative psychotic symptoms. Conclusions Higher levels of IL-8 are associated with a poor response to antipsychotic treatment. Increased cytokines levels are specifically associated with more severe negative symptoms in patients with schizophrenia and other psychoses

Gene set enrichment analysis of pathophysiological pathways highlights oxidative stress in psychosis.

Polygenic risk prediction remains an important aim of genetic association studies. Currently, the predictive power of schizophrenia polygenic risk scores (PRSs) is not large enough to allow highly accurate discrimination between cases and controls and thus is not adequate for clinical integration. Since PRSs are rarely used to reveal biological functions or to validate candidate pathways, to fill this gap, we investigated whether their predictive ability could be improved by building genome-wide (GW-PRSs) and pathway-specific PRSs, using distance- or expression quantitative trait loci (eQTLs)- based mapping between genetic variants and genes. We focused on five pathways (glutamate, oxidative stress, GABA/interneurons, neuroimmune/neuroinflammation and myelin) which belong to a critical hub of schizophrenia pathophysiology, centred on redox dysregulation/oxidative stress. Analyses were first performed in the Lausanne Treatment and Early Intervention in Psychosis Program (TIPP) study (n = 340, cases/controls: 208/132), a sample of first-episode of psychosis patients and matched controls, and then validated in an independent study, the epidemiological and longitudinal intervention program of First-Episode Psychosis in Cantabria (PAFIP) (n = 352, 224/128). Our results highlighted two main findings. First, GW-PRSs for schizophrenia were significantly associated with early psychosis status. Second, oxidative stress was the only significantly associated pathway that showed an enrichment in both the TIPP (p = 0.03) and PAFIP samples (p = 0.002), and exclusively when gene-variant linking was done using eQTLs. The results suggest that the predictive accuracy of polygenic risk scores could be improved with the inclusion of information from functional annotations, and through a focus on specific pathways, emphasizing the need to build and study functionally informed risk scores

Effect of age on the relative efficacy of clozapine in schizophrenia.

OBJECTIVE Early treatment of schizophrenia improves outcomes. Clozapine appears to have unique benefit when other antipsychotic medication has failed. This systematic review and meta-analysis aims to assess clozapine's superiority over alternative antipsychotic medication and examine whether earlier use is associated with additional benefit. METHOD Systematic retrieval of blinded, randomized controlled trials comparing clozapine with alternative antipsychotics in adults with schizophrenia. The effect of mean age on relative clozapine response was examined using random effects meta-regression, and multiple linear regression on available patient data. RESULTS 276 studies were retrieved. Thirty-four studies were included in the meta-analysis. Clozapine was significantly more effective than alternative antipsychotics in reducing psychotic symptoms and increasing response. However, meta-regression failed to show a more significant effect in younger patients (age on effect size (total psychotic symptoms) 0.00, p =0.79 CI -0.03 - 0.03). Individual patient data was available for 2 studies, the larger of which showed a significant interaction between younger age and superiority of clozapine. CONCLUSION The results support clozapine's superiority over other antipsychotics. A convincing effect of age on this effect was not demonstrated, although this was suggested in one study. In view of the age of many of the included studies, and changes in reporting practice over time, new clozapine RCTs, which include age of illness onset as well as age at trial time, would be welcome in order to provide meta-analysable data for future use