Antipsychotic-Induced Parkinsonism: A Risk Assessment Scale and Personalised Diagnosis Algorithm - N. A. Shnayder; E. E. Vaiman; R. F. Nasyrova (Ministry of Health of the Russian Federation, Federal State Budgetary Institution «Scientific Centre for Expert Evaluation of Medicinal Products», 2022)
INTRODUCTION. Antipsychotic-induced parkinsonism (AIP) is an extrapyramidal adverse drug reaction (ADR) associated with antipsychotics (APs). Despite its classification as a non-serious ADR, AIP significantly decreases the quality of life in patients with schizophrenia spectrum disorders, which makes early diagnosis and timely management of AIP an urgent issue.AIM. This study aimed to develop a risk assessment scale and a personalised diagnostic algorithm for AIP as the most common and clinically significant neurological ADR in patients with schizophrenia spectrum disorders.MATERIALS AND METHODS. The authors analysed modifiable and non-modifiable risk factors for AIP, as well as rating scales, questionnaires, and laboratory testing methods to diagnose the condition. The analysis was based on full-text publications in Russian or in English sourced from the eLIBRARY.RU, PubMed, Springer, ClinicalKey, and Google Scholar databases. As a preliminary step, the authors compared the effectiveness of validated AIP risk assessment scales, including the Simpson-Angus Scale (SAS), the Extrapyramidal Symptom Rating Scale (ESRS), the Unified Parkinson's Disease Rating Scale (UPDRS), the Hoehn and Yahr scale (H&Y Scale), the Webster Rating Scale, and the Mindham Rating Scale. Comparisons were made regarding the duration of testing, the degree of reliability in assessing clinical manifestations of AIP, and the ability to assess risk factors (predictors) of AIP and the rate of AIP development. The results obtained formed the basis for developing an AIP riskometer and a diagnostic algorithm.RESULTS. The authors developed an original risk assessment scale for diagnosing and predicting AIP. Directions for personalised patient management were determined for patients at high and medium risk of AIP. This article presents an algorithm for diagnosing AIP in patients with schizophrenia spectrum disorders in two variants based on pro-reactive (predictive) or reactive pharmacogenetic testing. According to the study results, pro-reactive pharmacogenetic testing can help determine the risk of AIP in a patient before primary therapy.CONCLUSIONS. The risk assessment scale and the personalised diagnostic algorithm developed by the authors may be useful for practising neurologists, psychiatrists, and clinical pharmacologists. The development and clinical implementation of novel tools for risk assessment, prevention, and diagnosis of AIP-the most common AP-associated neurological ADR-can improve the quality of treatment and preventive care for patients with schizophrenia spectrum disorders.