背景:抗癫痫治疗的药物不良反应(ADR)会恶化生活质量,减少依从性,并可能导致治疗中断和不受控制的癫痫发作。
目的:本研究的目的是建立哥伦比亚成年癫痫患者抗癫痫治疗ADR的预后模型。
方法:本病例对照研究纳入成年癫痫患者,将其分为两组:一组抗癫痫治疗不良反应(病例),由癫痫学家进行的全面评估确定,和另一组无不良反应(对照)。分析变量以确定两组之间的统计学差异,然后选择变量以使用逻辑回归构建预后模型。Bonferroni方法用于多重比较。
结果:研究了3154例癫痫患者。150名(42%)患者有ADR,204名(57%)患者没有ADR。总共报告了362种ADR,其中三分之一是一般症状,最常见于老一代抗癫痫药物(58%)。女性性别,耐药癫痫,LEV,CZP是危险因素,由于肿瘤病因的存在,没有癫痫发作的触发因素,VPA被确定为保护因素。使用先前报道的抗癫痫治疗ADR的危险因素和该人群研究中可用的其他变量来构建预后模型。在多变量分析中,以前使用过的抗癫痫药物的数量(1、2或≥3),TPM,CZP,LEV,PHT,女性是ADR的预测因子。校正后的p值是通过Bonferroni方法估算的;然而,通过这种调整,并非所有变量都达到了统计学意义。
结论:在来自哥伦比亚的成年癫痫患者中,我们发现以前使用过的抗癫痫药物的数量,TPM,CZP,LEV,PHT,女性是抗癫痫治疗ADR的预测因素。
Adverse drug reactions (ADRs) to antiseizure therapy can worsen the quality of life, reduce adherence, and potentially lead to treatment discontinuation and uncontrolled seizures.
The aim of the study was to develop a prognostic model for ADRs to antiseizure therapy in adult patients with epilepsy from Colombia.
This
case-control study included adult patients with epilepsy, who were separated into two groups: one group with ADRs to antiseizure therapy (cases), as determined by a complete evaluation conducted by an epileptologist, and another group without ADRs (controls). Variables were analyzed to identify statistical differences between the two groups and were then selected to construct a prognostic model using logistic regression. The Bonferroni method was applied for multiple comparisons.
Three hundred fifty-four patients with epilepsy were studied. One hundred and fifty (42%) patients had ADRs and 204 (57%) patients did not have ADs. A total of 362 ADRs were reported, with a third of them being general symptoms and most frequently occurring with older-generation antiseizure drugs (58%). Female sex, drug-resistant epilepsy, LEV, and CZP were risk factors, whereras the presence of tumoral etiology, absence of seizure triggers, and VPA were identified as protective factors. A prognostic model was constructed using previously reported risk factors for ADRs to antiseizure therapy and other variables available in this population study. In the multivariable analysis, the number of previously used antiseizure drugs (1, 2, or ≥3), TPM, CZP, LEV, PHT, and female sex were predictors of ADRs. The corrected p-values were estimated by the Bonferroni method; however, not all the variables achieved statistical significance with this adjustment.
In adult patients with epilepsy from Colombia, we found that the number of previously used antiseizure drugs, TPM, CZP, LEV, PHT, and female sex were predictive factors for ADRs to antiseizure therapy.