The Effects of Antipsychotic Treatment on Metabolic Function: a Systematic Review and Network Meta-Analysis
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The effects of antipsychotic treatment on metabolic function: a systematic review and network meta-analysis Toby Pillinger, Robert McCutcheon, Luke Vano, Katherine Beck, Guy Hindley, Atheeshaan Arumuham, Yuya Mizuno, Sridhar Natesan, Orestis Efthimiou, Andrea Cipriani, Oliver Howes ****PROTOCOL**** Review questions 1. What is the magnitude of metabolic dysregulation (defined as alterations in fasting glucose, total cholesterol, low density lipoprotein (LDL) cholesterol, high density lipoprotein (HDL) cholesterol, and triglyceride levels) and alterations in body weight and body mass index associated with short-term (‘acute’) antipsychotic treatment in individuals with schizophrenia? 2. Does baseline physiology (e.g. body weight) and demographics (e.g. age) of patients predict magnitude of antipsychotic-associated metabolic dysregulation? 3. Are alterations in metabolic parameters over time associated with alterations in degree of psychopathology? 1 Searches We plan to search EMBASE, PsycINFO, and MEDLINE from inception using the following terms: 1 (Acepromazine or Acetophenazine or Amisulpride or Aripiprazole or Asenapine or Benperidol or Blonanserin or Bromperidol or Butaperazine or Carpipramine or Chlorproethazine or Chlorpromazine or Chlorprothixene or Clocapramine or Clopenthixol or Clopentixol or Clothiapine or Clotiapine or Clozapine or Cyamemazine or Cyamepromazine or Dixyrazine or Droperidol or Fluanisone or Flupehenazine or Flupenthixol or Flupentixol or Fluphenazine or Fluspirilen or Fluspirilene or Haloperidol or Iloperidone or Levomepromazine or Levosulpiride or Lithium or Loxapine or Loxapinsuccinate or Lurasidone or Melperone or Mepazine or Mesoridazine or Methotrimeprazine or Molindone or Moperone or Mosapramine or Olanzapine or Oxypertine or Paliperidone or Penfluridol or Perazine or Periciazine or Pericyazine or Perospirone or Perphenazine or Pimozide or Pipamperone or Pipothiazine or Pipotiazine or Prochlorperazine or Promazine or Promethazine or Prothipendyl or Quetiapine or Remoxipiride or Reserpine or Riospirone or Risperdal or Risperidone or Seroquel or Sertindole or Stelazine or Sulpiride or Sultopride or Thiopropazate or Thioproperazine or Thioridazine or Tiospirone or Thiothixene or Tiapride or Tiotixene or Trifluoperazine or Trifluperidol or trifluoperidol or Triflupromazine or trifluperazine or Veralipride or Ziprasidone or Zotepine or Zuclopenthixol).mp. [mp=ti, ab, hw, tn, ot, dm, mf, dv, kw, fx, dq, nm, kf, ox, px, rx, ui, sy, tc, id, tm] 2 2 (Antipsychoti$ or Anti-psychotic$ or Neurolepic$ or Neurolept$).mp. [mp=ti, ab, hw, tn, ot, dm, mf, dv, kw, fx, dq, nm, kf, ox, px, rx, ui, sy, tc, id, tm] 3 schizo$.mp. 4 psychosis.mp. 5 randomized.mp. [mp=ti, ab, hw, tn, ot, dm, mf, dv, kw, fx, dq, nm, kf, ox, px, rx, an, ui, sy, tc, id, tm] 6 'double blind'.mp. [mp=ti, ab, hw, tn, ot, dm, mf, dv, kw, fx, dq, nm, kf, ox, px, rx, an, ui, sy, tc, id, tm] 7 5 and 6 8 3 or 4 9 1 or 2 3 10 7 and 8 and 9 Types of study to be included Double-blind, randomised controlled trials that have been published in the English language. Clinical trials registry data relating to papers identified in the literature review will also be included. Condition or domain being studied Metabolic alterations (glucose, total cholesterol, Low Density Lipoprotein (LDL) cholesterol, High Density Lipoprotein (HDL) cholesterol, and triglyceride levels), body weight, body mass index. Participants/population Patients with schizophrenia and related psychoses defined according to standard operationalised diagnostic criteria (Feighner criteria, Research Diagnostic Criteria, DSM-III, DSM-III-R, DSM-IV, DSM-V, and ICD-10). Intervention(s), exposure(s) Monotherapy with antipsychotic or placebo. We will not employ limits on antipsychotic dose, owing to the lack of clear evidence that antipsychotic treatment dose influences degree of metabolic dysregulation, although we will investigate the potential influence 4 of antipsychotic dose on metabolic change using meta-regression (see ‘Meta- regression Analyses’ section).1 Oral or parenteral administration will be accepted. Comparator(s)/control Monotherapy with antipsychotic or placebo. Context It has long been proposed that some antipsychotic drug treatments cause glucose dysregulation and lipid disturbance thereby contributing to development of the metabolic syndrome in patients with schizophrenia.2 However, the relative degree to which metabolic alterations occur in acute treatment with different antipsychotics remain unclear. Furthermore, baseline predictors of metabolic dysregulation are poorly defined, and the association between metabolic change and change in psychopathology is uncertain. Main outcome(s) For each study, we aim to collect data examining mean and standard deviation of change (i.e. from baseline to study endpoint) in the following outcomes: 1. Glucose (mmol/L) 2. Total cholesterol (mmol/L) 3. Low Density Lipoprotein (LDL) cholesterol (mmol/L) 4. High Density Lipoprotein (HDL) cholesterol (mmol/L) 5. Triglycerides (mmol/L) 6. Body weight (kg) 5 7. Body Mass Index (BMI, kg/m2) All metabolic outcomes will be measured from blood tests taken under fasting conditions. Either plasma or serum samples will be accepted. Data extraction (selection and coding) This systematic review and network meta-analysis will adhere to recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA)3 extension statement for network meta-analysis. Extracted information will include: name of first author, year of publication, antipsychotic used in study, average dose of antipsychotic used, type of symptom scale used, patient characteristics including age, %male, %Caucasian, duration of drug intervention, mean ± standard deviation (SD) change in symptom scores between baseline and study endpoint, mean ± SD metabolic parameter concentrations (glucose, total/LDL/HDL cholesterol/triglycerides) and body weight/body mass index (BMI) at baseline, active drug number, placebo number. If applicable, data may be extracted from related publications that refer to the same study. When data required for meta-analysis is unreported, corresponding authors will be contacted to request additional data. Network meta-analysis requires reasonable homogeneity, and as such we will focus on acute treatment, which we define as 6-weeks duration.4 If 6-week data are not available, the datapoint closest to 6-weeks will be given preference. Again, to maintain homogeneity in the sample, we will exclude paediatric studies (i.e. studies where participant age <18 years). We will not employ limits on antipsychotic dose, owing to the lack of clear evidence that antipsychotic dose influences degree of metabolic 6 dysregulation, although we will investigate the potential influence of antipsychotic dose on metabolic change using meta-regression (see ‘Strategy for Data Synthesis’ section).1 Where multiple doses of a single antipsychotic are reported, to increase statistical power, and again in the absence of clear evidence that antipsychotic dose influences metabolic outcomes, a single weighted mean and standard deviation for each metabolic parameter pertaining to a given multi-arm study will be calculated, using formulae recommended by the Cochrane collaboration:5 Weighted mean of multiple study arms: 푁 ∑푖=1 푛푖푥푖 푥̅ = 푁 ∑푖=1 푛푖 Where, N = number of observations (i.e. number of arms of the study) 푛푖 = sample size of study arm 푥푖 = sample mean of study arm Weighted standard deviation for 2 study arms: 푛 푛 (푛 − 1)푠푑2 + (푛 − 1)푠푑2 + 1 2 (푥2 + 푥2 − 2푥 푥 ) 1 1 2 2 푛 + 푛 1 2 1 2 푠 = √ 1 2 푛1 + 푛2 − 1 Where, 푛1 and 푛2 = sample sizes of study arms 1 and 2 푥1 and 푥2 = means of study arms 1 and 2 푠푑1 and 푠푑2 = standard deviations of study arms 1 and 2 7 As recommended by Cochrane,5 where there are more than 2 study arms to combine standard deviations, the above formula will be applied sequentially (i.e. combining study arm 1 and 2 to create arm ‘1+2’, then combining group ‘1+2’ and group 3 to create group ‘1+2+3’ and so on). Since paliperidone represents the active metabolite of risperidone, data pertaining to these 2 antipsychotics will be merged (i.e. considered as the same intervention). Since we set out to examine mean difference between groups (see ‘Strategy for Data Synthesis’ section), data from certain studies will require conversion from conventional to SI units, which will be performed using standardised conversion factors.6 Clinical trials registry data relating to papers identified in the literature review will be included. 5 researchers (YM/LV/KB/AA/GH) will extract data, all studies will be assessed by a minimum of two researchers. Discrepancies will be decided by TP. Strategy for data synthesis Characteristics of included studies We will describe the study population characteristics across all eligible trials, describing the types of comparisons (i.e. which metabolic parameter is examined), and physiological/demographic variables (including age, gender (%male), ethnicity (%Caucasian), duration of drug intervention, and clinical group (i.e. first episode psychosis, established schizophrenia, treatment resistant schizophrenia, older adults). 8 Pairwise meta-analyses For each pairwise comparison with ≥10 studies we will synthesise data to obtain summary mean differences with accompanying 95% confidence interval using a random effects model. Analyses will be carried out in the statistical programming language R (version 3.5.1)7 using ‘metafor’ (version 2.1-0). Visual inspection of the forest plots will be used