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精神科患者服用抗精神病药物时 TD 发生率的风险评估和预测:回顾性数据分析。

Risk assessment and prediction of TD incidence in psychiatric patients taking concomitant antipsychotics: a retrospective data analysis.

机构信息

Analysis Group, Inc., 111 Huntington Avenue, Boston, MA, 02199, USA.

Teva Pharmaceuticals, 41 Moores Rd, Malvern, PA, 19355, USA.

出版信息

BMC Neurol. 2019 Jul 20;19(1):174. doi: 10.1186/s12883-019-1385-4.

Abstract

BACKGROUND

Tardive dyskinesia (TD) is a serious, often irreversible movement disorder caused by prolonged exposure to antipsychotics; identifying patients at risk for TD is critical to preventing it. Predictive models for the occurrence of TD can improve patient monitoring and inform implementation of counteractive interventions. This study aims to identify risk factors associated with TD and to develop a model using a retrospective data analysis to predict the incidence of TD among patients taking antipsychotic medications.

METHODS

Adult patients with schizophrenia, major depressive disorder, or bipolar disorder taking oral antipsychotics were identified in a Medicaid claims database (covering six US states from 1997 to 2016) and divided into cohorts based on whether they developed TD within 1 year after the first observed claim for antipsychotics. Patient characteristics between cohorts were compared, and univariate Cox analyses were used to identify potential TD risk factors. A cross-validated version of the least absolute shrinkage and selection operator regression method was used to develop a parsimonious multivariable Cox proportional hazards model to predict diagnosis of TD.

RESULTS

A total of 189,415 eligible patients were identified. Potential TD risk factors were identified based on the cohort analysis within a sample of 151,280 patients with at least 1 year of continuous eligibility. The prediction model had a clinically meaningful concordance of 70% and was well calibrated (P = 0.32 for Hosmer-Lemeshow goodness-of-fit test). Age (hazard ratio [HR] = 1.04, P < 0.001), diagnosis of schizophrenia (HR = 1.99, P < 0.001), antipsychotic dosage (up to 100 mg/day chlorpromazine equivalent; HR = 1.65, P < 0.01), and comorbid bipolar and related disorders (HR = 1.39, P < 0.01) were significantly associated with an increased risk of TD. Other potential risk factors included history of extrapyramidal symptoms (HR = 1.35), other movement disorders (parkinsonism, HR = 1.43; bradykinesia, HR = 1.44; tremors, HR = 2.12, and myoclonus, HR = 2.33), and diabetes (HR = 1.13). A modest reduction in the risk of TD was associated with the use of second-generation antipsychotics (HR = 0.85) versus first-generation drugs.

CONCLUSIONS

This study identified factors associated with development of TD among patients taking antipsychotics. The prediction model described herein can enable physicians to better monitor patients at high risk for TD and recommend appropriate treatment plans to help maintain quality of life.

摘要

背景

迟发性运动障碍(TD)是一种严重的、通常不可逆转的运动障碍,由长期接触抗精神病药物引起;识别出有发生 TD 风险的患者对于预防 TD 至关重要。用于预测 TD 发生的预测模型可以改善患者监测并为实施对抗性干预措施提供信息。本研究旨在确定与 TD 相关的风险因素,并使用回顾性数据分析来开发一种预测接受抗精神病药物治疗的患者发生 TD 的模型。

方法

从 1997 年至 2016 年覆盖美国六个州的医疗补助索赔数据库中确定了正在服用口服抗精神病药物的精神分裂症、重度抑郁症或双相情感障碍的成年患者,并根据他们在首次服用抗精神病药物后 1 年内是否出现 TD 分为两组。比较两组患者的特征,并用单变量 Cox 分析来确定潜在的 TD 风险因素。使用交叉验证的最小绝对收缩和选择算子回归方法开发了一个简约的多变量 Cox 比例风险模型来预测 TD 的诊断。

结果

共确定了 189415 名符合条件的患者。在至少有 1 年连续合格的 151280 名患者的样本中,根据队列分析确定了潜在的 TD 风险因素。预测模型的临床一致性为 70%,校准良好(霍斯默-莱梅肖拟合优度检验 P=0.32)。年龄(危险比[HR] =1.04,P<0.001)、精神分裂症诊断(HR =1.99,P<0.001)、抗精神病药物剂量(最大 100 毫克/天氯丙嗪当量;HR =1.65,P<0.01)和共患双相和相关障碍(HR =1.39,P<0.01)与 TD 风险增加显著相关。其他潜在的风险因素包括锥体外系症状史(HR =1.35)、其他运动障碍(帕金森病,HR =1.43;运动迟缓,HR =1.44;震颤,HR =2.12,肌阵挛,HR =2.33)和糖尿病(HR =1.13)。与第一代药物相比,第二代抗精神病药物(HR =0.85)的使用与 TD 风险降低有关。

结论

本研究确定了接受抗精神病药物治疗的患者发生 TD 的相关因素。本文描述的预测模型可以帮助医生更好地监测有发生 TD 风险的患者,并推荐适当的治疗方案,以维持生活质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a91/6642740/e27ba54d1a18/12883_2019_1385_Fig1_HTML.jpg

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