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When comparing the QoL scores of the epilepsy without meningioma and the meningioma with epilepsy group, subscale and summary scores were consistently, but not significantly, worse in the epilepsy without meningioma group. On the SF-36, QoL was reduced in the epilepsy without meningioma group for all summary and subscale scores, but only the difference in mental health subscale was significant. The differences in summary scores were statistically and clinically non-significant.

A shortened version of the FACT-BR was used to compare quality of life in the meningioma with epilepsy and epilepsy without meningioma groups. All subscale and summary scores were lower in the epilepsy without meningioma group compared to the meningioma with epilepsy group, but none of these differences were statistically significant. Of the four subscales, emotional wellbeing had the biggest difference in score.

The total AEP scores in the epilepsy without meningioma group were larger than the total scores observed in the meningioma with epilepsy group and similarly to the above, these differences were not statistically or clinically significant. When interpreting the individual item scores, the majority of item means had higher scores in the epilepsy without meningioma group, but there was no statistically significant differences in individual item score.

These findings suggest that patients with meningioma and epilepsy have QoL that is equivalent patients with epilepsy but no meningioma. This is despite the severity of epilepsy being mild in the epilepsy without meningioma group. If QoL was more impaired in the meningioma with epilepsy group, this should have been reflected on the FACT-BR scores. Instead this measure also demonstrated that QoL is slightly impaired in the epilepsy without meningioma group.

Both groups differ significantly in terms of epilepsy severity and it may be hypothesised that differences in QoL should have significantly impaired QoL in the control group. One explanation for this not being shown, could be a lack of sensitivity to milder differences in epilepsy severity, particularly on the SF-36 and FACT-BR, both of which are not epilepsy specific measures. This explanation is supported by another study using the SF-36 in an

129 epilepsy population. It was found that when comparing patients with and without seizures, patients that experienced at least one seizure a month had significantly impaired scores271. In the present study, less than 20% of patients in the epilepsy without meningioma group experienced 6 or more seizures in 6 months.

On the AEP, seizure frequency alone cannot explain the insignificant findings. Instead the mild severity of epilepsy in the control group and an overall lack of adverse drug reactions could have explained this.

The effect of the meningioma could be reducing the difference in QoL. In other words, assuming that epilepsy severity is important in determining QoL differences in these groups, the difference in QoL due to epilepsy severity in the epilepsy without meningioma group could be reduced by the effect of meningioma in the meningioma with epilepsy group. The findings from the regression analysis help to interpret the above findings. Increased seizure frequency, increased number of AEDs and the use of levetiracetam were found to significantly predict impaired QoL scores in the univariate analysis for all QoL measures. However in the multiple regression analysis only levetiracetam remained significant and this was only shown on FACT-G and AEP. The role of levetiracetam in predicting impaired QoL could be explained by its association with increased epilepsy severity260. Grouped epilepsy variables in a multiple regression analysis significantly add to the amount of accounted variance on the FACT-BR and the AEP, but this is not the case for the SF-36 confirming that this measure is not particularly sensitive at detecting differences in QoL due to epilepsy. When considering meningioma related variables in the QoL of the meningioma with epilepsy and epilepsy without meningioma groups, two variables were significant in the univariate analysis: cognitive/emotional symptoms in PCS and cranial nerve symptoms on FACT-G and AEP. In the univariate analysis, these factors were the least significant identified predictors of their respective questionnaire. In the multiple regression analysis, only cognitive/emotional symptoms were predictive. Furthermore, this variable only became predictive after the epilepsy block of variables were entered into the regression model, indicating that the presence of cognitive/emotional symptoms is only significant in the context of epilepsy related factors in this model. Furthermore, the addition of the meningioma block of variables was insignificant for all models. This regression model could

130 be criticised for only containing two meningioma related variables, but these were the only variables that significantly predicted any dependent variable. All other variables were found to be poor predictors. Epilepsy related variables were more powerful in predicting the dependent variable as individual and grouped independent variables in the multiple regression analyses.

Overall, demographics and comorbidities were more consistent and superior in predicting impaired QoL than epilepsy or meningioma variables. Unemployment was consistently a predictive factor of impaired Qol in both the univariate and multiple regression analysis. Increased numbers of comorbidities, depression, diabetes mellitus and stroke were also found to be influential in the multiple regression. Number of comorbidities and unemployment have been shown in previous studies to impair QoL188.

In the multiple regression analysis of the meningioma patients, depression was found to be predictive in the univariate but not the multiple regression analysis. In the multiple regression analyses of the epilepsy populations in this study, depression has a more significant role. This cannot be attributed to epilepsy related variables, such as AED use, as the correlation between them is not strong. Depression is significantly correlated with unemployment and the number of comorbidities in this sample, a finding similar in the meningioma regression analysis.

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