Eli Lilly and Company, Lilly Research Centre, Erl Wood Manor, Sunninghill Road, Windlesham, Surrey, GU20 6PH, UK.
Psychiatry Res. 2010 Apr 30;176(2-3):109-13. doi: 10.1016/j.psychres.2009.05.004. Epub 2010 Feb 24.
To assess baseline predictors and consequences of antipsychotic adherence during the long-term treatment of schizophrenia outpatients, data were taken from the 3-year, prospective, observational, European Schizophrenia Outpatients Health Outcomes (SOHO) study, in which outpatients starting or changing antipsychotics were assessed every 6 months. Physician-rated adherence was dichotomized as adherence/non-adherence. Regression models tested for predictors of adherence during follow-up, and associations between adherence and outcome measures. Of the 6731 patients analysed, 71.2% were adherent and 28.8% were non-adherent over 3 years. The strongest predictor of adherence was adherence in the month before baseline assessment. Other baseline predictors of adherence included initial treatment for schizophrenia and greater social activities. Baseline predictors of non-adherence were alcohol dependence and substance abuse in the previous month, hospitalization in the previous 6 months, independent housing and the presence of hostility. Non-adherence was significantly associated with an increased risk of relapse, hospitalization and suicide attempts. In conclusion, non-adherence is common but can partly be predicted. This may allow strategies to improve adherence to be targeted to high-risk patients. Also, reversal of some risk factors may improve adherence. Non-adherence is associated with a range of poorer long-term outcomes, with clinical and economic implications.
为了评估精神分裂症门诊患者长期治疗过程中抗精神病药物依从性的基线预测因素和后果,我们从为期 3 年的前瞻性、观察性欧洲精神分裂症门诊患者健康结局(SOHO)研究中获取数据,该研究对开始或改变抗精神病药物治疗的门诊患者每 6 个月进行一次评估。医生评估的依从性分为依从和不依从。回归模型检验了随访期间依从性的预测因素,以及依从性与结局测量之间的关联。在分析的 6731 名患者中,71.2%的患者在 3 年内依从,28.8%的患者不依从。依从性最强的预测因素是基线评估前一个月的依从性。依从性的其他基线预测因素包括精神分裂症的初始治疗和更多的社会活动。不依从的基线预测因素包括前一个月的酒精依赖和物质滥用、前 6 个月的住院治疗、独立住房和存在敌意。不依从与更高的复发、住院和自杀企图风险显著相关。总之,不依从很常见,但部分可以预测。这可能允许将提高依从性的策略针对高风险患者。此外,一些风险因素的逆转可能会提高依从性。不依从与一系列较差的长期结局相关,具有临床和经济意义。