Research Proposal
Background: Antipsychotics are the mainstem for treating schizophrenia and other mental disorders. While use of antipsychotic treatment is essential for favorable outcomes in terms of acute efficacy and relapse prevention, the use of antipsychotics can cause various unpleasant side effects such as sedation, extrapyramidal symptoms, hyperprolactinemia, metabolic and cardiovascular disturbances, and anticholinergic side effects (1). These side effects are associated with a lower quality of life and poorer adherence in patients (2). It is known that patients acquire tolerance to some side effects in clinical practice whereas other side effects may get more severe over time. However, it is unclear when side effects occur and disappear.
Objective: We aim to systematically assess the occurrence, onset, duration and severity of side effects associated with antipsychotic treatment.
Study Design: This study is an Individual-Patient-Data (IPD) meta-analysis of clinical trials to evaluate the occurrence, onset, duration and severity of side effects associated with antipsychotic treatment.
Participants: Participants in clinical trials of antipsychotic drug monotherapy irrespective of diagnosis, age, gender, and ethnicity.
Main Outcome Measures: The occurrence, onset, duration, and severity of side effects associated with antipsychotic treatment
Statistical Analysis: The median time to onset and the duration of side effects will be calculated from synthesized data by IPD meta analysis.
Antipsychotics are the mainstem for the treatment of schizophrenia and used for the treatment of other psychiatric diseases. While the use of antipsychotic therapy is essential for favorable outcomes in terms of acute efficacy and relapse prevention, the use of antipsychotics can cause various unpleasant side effects such as sedation, extrapyramidal symptoms, hyperprolactinemia, metabolic and cardiovascular disturbances, and anticholinergic side effects (1). The impacts of side effects vary widely, ranging from very unpleasant in daily life (e.g., sedation, akathisia, weight gain, and constipation) to life-threatening (e.g., neuroleptic malignant syndrome, pneumonia, thromboembolism, and sudden cardiac death). Given these side effects are associated with a lower quality of life and poorer adherence in patients (2), proper management of side effects is important for a long-term treatment. However, the timeline of side effects has not been systematically studied. Knowing for example when side effects occur and disappear not only allows clinicians to optimize treatment with antipsychotics, but also helps patients monitor and manage their side effects. Therefore, this study aims to systematically assess the occurrence, onset, duration, and severity of side effects associated with antipsychotic treatment.
The purpose of this project is to systematically assess temporal trajectories (the occurrence, onset, duration, and severity) of side effects associated with antipsychotic treatment and factors that could influence them.
Primary objective:
Evaluate temporal trajectories of antipsychotic-associated side-effects, e.g., time of onset, duration, temporal changes in severity, and time of disappearance.
Secondly objectives:
Evaluate factors (e.g., type of antipsychotic, dosage) that could influence temporal trajectories of antipsychotic-associated side-effects.
We will consider prospective trials investigating the antipsychotic treatment in monotherapy without further restrictions, such as in terms of randomization, blinding, or follow-up duration. Any antipsychotic drug (ATC codes of N05., except lithium N05AN01) or placebo will be eligible. All participants in eligible studies will be included, irrespective of underlying diagnosis (e.g., schizophrenia, schizoaffective disorder, bipolar disorder, and children with disruptive behavior disorder), stage and severity of illness (e.g., acute, chronic), age (e.g., children, adolescent, and adults), gender, ethnicity, and comorbidities.
We will investigate temporal trajectories of antipsychotic-associated side-effects (e.g., time of onset, duration, changes in their severity, and time of disappearance).
We will consider 1) adverse events, such as extrapyramidal symptoms, akathisia, sedation, weight gain, prolactin elevation, QTc prolongation, and anticholinergic side-effects (e.g., constipation, blurred vision) We will use the Medical Dictionary for Regulatory Activities Terminology (MedDRA)(3) for the classification of adverse events. We will also consider 2) rating scale measures (e.g., Drug Induced Extra Pyramidal Symptoms Scale, Simpson-Angus Extrapyramidal Rating Scale, UKU side effect rating scale, Visual Analog Scale, Barnes Akathisia Rating Scale), and 3) biological measures (e.g., body weight, corrected QT interval on ECG, blood pressure, prolactin, blood glucose)
The use of antipsychotics will be the independent variable.
The independent variable allows us to investigate the relationship between antipsychotic use and the onset, duration, and severity of the side effects of antipsychotics.
We will consider factors with a potential influence on the temporal trajectories of antipsychotic-associated side-effects, such as specific antipsychotics, dosage of antipsychotics, administration route of antipsychotics, age, gender, ethnicity, diagnosis, life-time antipsychotic exposure (when not available, duration of illness will be used as a proxy in participants with schizophrenia), comorbid disorders, family history, smoking, baseline BMI, measures of psychopathology, and concomitant medications, etc.
First, we will conduct descriptive analysis on time to onset and duration of side effects, and then with statistical models that take temporal trajectories into account, such as the Kaplan-Meier method for binary adverse event data and Mixed-Models-of-Repeated-Measurements (MMRM) for rating-scale outcomes and biological measures. The effect size measures will be the time to onset and the time to resolution for binary adverse events and the change from baseline for rating-scale-outcomes or biological measures.
We consider occurrence and duration of somatic side effects of antipsychotics rather independent of the underlying psychiatric disease (e.g., schizophrenia or bipolar disorder) and therefore, we include a priori studies in different disorders. However, we expect variability in the effects due to differences in participant, intervention, and study characteristics. Therefore, we will explore sources of heterogeneity by subgroup and meta-regression analyses on potentially important effect modifiers such as age, sex, diagnosis (to investigate our assumption above), previous antipsychotic exposure, type, application and dose of antipsychotic, trial duration, RCT (Randomized control trial) and not RCT, … (see list of “Other Variables of Interest” above).
Variables which emerge as having a substantial effect on occurrence and duration of side effects will be included in the statistical model by introducing interactions.
We will handle missing outcome and covariate data following Little et al.(4) and impute it, when scientifically sound, by multiple imputations.
Effect size measures and covariates of different studies will be synthesized with meta-analysis.
I-squared and Tau-squared will be used to measure heterogeneity.
To estimate publication bias, we will use funnel plot and Egger’s test. In addition to examining the risk of small-trial/publication bias with funnel plots, we will investigate the potential risk of bias due to selection of reported results within the risk of bias assessment and the potential risk of bias due to selective non-reporting of results with the ROB-MEN(5) tool within the CINeMA assessment.
The standardized Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach will be used to examine the strength of evidence.
Antipsychotics are the mainstem for the treatment of schizophrenia and other mental disorder. While use of antipsychotics is essential for favorable outcomes in terms of acute efficacy and relapse prevention, it can cause various unpleasant side effects (1). These side effects are associated with a lower quality of life and poorer adherence in patients (2). It is known that patients acquire tolerance to some side effects in clinical practice whereas others may get more severe over time. However, the temporal trajectories of side effects are yet unclear. Therefore, we will investigate temporal trajectories (e.g., onset, duration) of side effects associated with antipsychotic treatment.
Start of project: The study will start immediately after the data is available.
The actual state of the project: it is planned to finish data extraction and to start data analysis by 11/2022. The manuscript will be made and submitted in six months (6/2023). The publication is planned for the following six months(12/2023).
The results of this work will be a significant advancement in optimizing antipsychotic treatment for psychiatric disease, which in turn will reduce the burden for patients with schizophrenia and their caregivers, as well as medical costs in the long term. We will make the results available in several publications in scientific journals (e.g., JAMA Psychiatry, Lancet Psychiatry). Moreover, it is expected that the results will be included in local and international treatment guidelines.
1. Huhn M, Nikolakopoulou A, Schneider-Thoma J, Krause M, Samara M, Peter N, et al. Comparative efficacy and tolerability of 32 oral antipsychotics for the acute treatment of adults with multi-episode schizophrenia: a systematic review and network meta-analysis. Lancet. 2019; 394(10202): 939-51.
2. Dibonaventura M, Gabriel S, Dupclay L, Gupta S, Kim E. A patient perspective of the impact of medication side effects on adherence: results of a cross-sectional nationwide survey of patients with schizophrenia. BMC Psychiatry. 2012; 12(1): 20.
3. International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH). Medical Dictionary for Regulatory Activities Terminology (MedDRA). www.meddra.org.
4. Little RJ, D'Agostino R, Cohen ML, Dickersin K, Emerson SS, Farrar JT, et al. The Prevention and Treatment of Missing Data in Clinical Trials. New England Journal of Medicine. 2012; 367(14): 1355-60.
5. Chiocchia V, Nikolakopoulou A, Higgins JPT, Page MJ, Papakonstantinou T, Cipriani A, et al. ROB-MEN: a tool to assess risk of bias due to missing evidence in network meta-analysis. BMC Medicine. 2021; 19(1).
