Quality of life measures in epilepsy
How well can they detect change over time?
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Abstract
Objective: To evaluate the ability of health-related quality of life (HRQOL) measures to detect change over time in persons with epilepsy.
Background: The application of HRQOL measures in clinical trials has been limited by a dearth of information regarding their abilities to measure change over time (i.e., their responsiveness). To calculate responsiveness, one must categorize subjects as “changed” or “unchanged” by a priori criteria.
Methods: The authors analyzed data collected at baseline and at 28-week follow-up from an antiepileptic drug trial. Two different criteria for classifying subjects as changed or unchanged—one based on seizure frequency (where changed = attainment of seizure freedom) and one based on self-reported overall condition (where changed = improvement in overall condition)—were used. We compared responsiveness indices for two generic (Short Form [SF]-36 and SF-12) and two epilepsy-targeted (Quality of Life in Epilepsy [QOLIE]-89 and QOLIE-31) HRQOL measures. Two scoring procedures for the SF-36, one based on classic test theory and the other on item response theory (IRT), were compared.
Results: Effect sizes of the most responsive HRQOL measures were medium to large. The shorter epilepsy-targeted measure had similar responsiveness indices to those of the longer measure. Epilepsy-targeted measures were consistently more responsive than generic measures under the overall condition criterion, but for the seizure freedom criterion, IRT scoring of the SF-36 yielded responsiveness indices comparable to those of the epilepsy-targeted measures.
Conclusion: Epilepsy-targeted health-related quality of life measures may be preferable to generic ones in longitudinal studies. Selection of a shorter epilepsy-targeted measure does not compromise responsiveness. Item response theory scoring should be applied to epilepsy-targeted HRQOL measures.
Within the field of epilepsy, there is increasing recognition that traditional measures, such as seizure counts, do not capture a broad range of outcomes that may be relevant in evaluating the clinical impact of the growing number of medical and surgical interventions now available.1-3 A number of health-related quality of life (HRQOL) measures for epilepsy have been developed over the last several years.4-9 These measures enable assessment of patients’ perception of the impact of their disease on their social, mental, and physical health. Despite the desirability of assessing epilepsy outcomes more broadly, a recent literature review revealed only four antiepileptic drug (AED) randomized trials for epilepsy that included a comprehensive measure of HRQOL.10
Although a percentage reduction of seizure frequency has often been the primary measure of efficacy in epilepsy treatment studies, there is a growing debate about the impact partial reduction in seizure occurrence may have on HRQOL—particularly when baseline seizure occurrence is relatively high. There is also ongoing discussion about whether endpoints for both efficacy and effectiveness should be re-evaluated and tailored more meaningfully to particular investigations. For example, “percentage responder,” where “responder” is defined as a patient undergoing a clinically meaningful improvement, has been proposed as a more optimal measure of efficacy for certain AEDs. However, reliability may have been a problem with this measure.11 Others speculate that a 50% reduction in seizure frequency, a common endpoint to assess AED efficacy,12-16 may not reflect a clinically meaningful improvement in certain contexts. Some have suggested that at least a 75% reduction as well as the percentage of subjects attaining seizure freedom be reported in AED therapeutic trials.2,12
Generic and disease-targeted HRQOL measures are now available for many populations, including epilepsy, and their comparative performance in specific populations is still being actively explored.10 Generic instruments, such as the Short Form (SF)-36, have the advantage of broad applicability across diagnoses. Such applicability enables comparisons across conditions that may be useful in health policy context, for example, resource allocation decisions. However, generic HRQOL measures may lack specificity and be unable to assess the unique difficulties encountered by patients with a specific condition.17-18
HRQOL measurement could further elucidate the relationship between reductions in seizure frequency and functioning and well-being. One potential barrier to the use of HRQOL measures in clinical trials is the dearth of information regarding the responsiveness of existing measures to changes in clinical status.18-20 Responsiveness is a measure of the degree to which an instrument is capable of detecting change over time with alterations in disease state or in response to treatment and an indicator of longitudinal validity.21
To address these issues, we analyzed data collected for a randomized controlled trial of an AED. Criteria for determining change were defined a priori, and several responsiveness indices were calculated to evaluate both generic and epilepsy-targeted HRQOL measures. The impact on responsiveness of alternative scoring methods that were available for the generic measure was also assessed.
Methods.
Sample.
Data were gathered from a national, multicenter randomized controlled trial of vigabatrin add-on therapy. All enrollees were taking phenytoin or carbamazepine monotherapy at study entry. Of the 192 subjects who were randomized, 142 completed the study, including follow-up questionnaires and interviews at a 28-week follow-up. Mean age of the 142 subjects was 38.2 years (range 18.8 to 66.8 years), and 48% were men. Over 85% of the subjects were white, 12.2% were African American, and 1.4% were Asian American. Predominant seizure types represented included 51.6% with complex partial seizures, 26.2% with tonic clonic seizures, and 21.7% with both complex partial and tonic-clonic seizures. Seizure etiology was unknown in 51.7% and related to trauma in 17% of the patients. Mean seizure frequency at baseline was 3.6 seizures per month. Subsets of these 142 subjects that met different criteria for “changed” and “unchanged” were included in the analyses presented here.
Criteria for change.
We evaluated two primary criteria for positive change. The most stringent criterion for classifying a subset of subjects as changed based on changes in seizure frequency was achieving seizure freedom—that is, a 100% reduction in complex partial and tonic-clonic seizure frequency from the 12 weeks before baseline to the 12-week interval before the 28-week follow-up. Participants were classified as unchanged if they had less than a 50% change in seizure frequency. (Fewer than 10% of subjects in the analysis group had a 50% or more increase in seizure frequency; thus, there were not enough people in the subgroups to evaluate responsiveness based on negative change.)
We used a two-category or greater improvement in patients’ self-ratings of their overall condition as another criterion of positive change. Subjects were asked at baseline and again at the 28-week follow-up to categorize their overall quality of life at that time (Appendix). Participants who had no change in this rating were classified as unchanged for this criterion.
HRQOL measures.
Two generic and two epilepsy-targeted measures were evaluated (table 1).
Summary of health-related quality of life (HRQOL) measures
Generic measures.
The SF-36 consists of 36 items that measure eight dimensions of health: physical functioning, social functioning, role limitations due to physical problems, role limitations due to emotional problems, emotional well-being, energy/fatigue, general health perceptions, and pain.22-23 These scales can be summarized into two underlying dimensions: physical and mental health summary scores. The SF-12 is a 12-item subset of the SF-36 that provides accurate estimates of the SF-36 mental and physical health composite summary scores.24
In addition to the SF-36 scoring method adduced by Ware and colleagues,24 the 36 items contained in the SF-36 were estimated using the RAND-36 Health Status Inventory (HSI) scoring procedure, which is based on item response theory (IRT).25 Rather than assume that each item in a scale contributes equal information and adding items together, IRT scoring models estimate the association between a respondent’s underlying level on a characteristic and the probability of a particular item response.26 Consequently, IRT models can yield more accurate estimates of latent traits than do classic test theory scoring methods.25,26 The RAND-36 HSI includes a mental health composite, a physical health composite, and a global health composite.22
Epilepsy-targeted measures.
Quality of Life in Epilepsy (QOLIE)-89 is an epilepsy-targeted measure that includes the SF-36 as a generic core.6 Four domain scores (epilepsy-targeted, mental health, physical health, and cognitive distress) and an overall QOLIE-89 score have been derived. Previously reported analyses of the QOLIE-89 provide support for its reliability and construct validity.8 A short form of the measure, the QOLIE-31, yields an overall score.7,9 Construction of the QOLIE-31 was based on expert consensus regarding dimensions of HRQOL issues covered in the QOLIE-89 thought to be the most important for people with epilepsy, including seizure worry, emotional well-being, energy/fatigue, medication effects, work–driving–social limitations, and cognitive distress.
Data collection.
HRQOL measures, self-ratings of overall condition, and seizure data used in these analyses were collected at baseline and at a 28-week follow-up. Seizure frequency data for classifying subjects as changed or unchanged were determined based on the 12-week interval before randomization into the clinical trial (baseline) and the 12-week interval before the 28-week follow-up after baseline. HRQOL data were returned directly to UCLA investigators; seizure and other clinical data were returned to investigators at Hoechst Marion Roussel and subsequently transferred to UCLA investigators. Participating institutional review boards approved all procedures for recruitment and interactions with subjects.
Analyses.
Responsiveness indices included effect size, standardized response mean, Guyatt responsiveness statistic, and F statistics comparing change scores between the changed and unchanged groups.27 All indices were calculated for each of the HRQOL measures with the two primary external change criteria discussed above: a 100% reduction in seizure frequency and a two-category or greater improvement in patients’ self-ratings of their overall condition. Cohen’s effect size criteria of “small,” “medium,” and “large” were applied to observed effect sizes for each change criterion and each HRQOL measure.28 The median rank of each HRQOL measure across responsiveness indices was determined. These rankings provide comparative assessments of the degree of responsiveness of each measure.
Results.
Classification of subjects by external criteria.
Of the 142 subjects, 22 (15%) became seizure free and were thus classified as changed according to that criterion. Sixty-one (43%) had less than a 50% increase or decrease in seizure frequency and composed the unchanged group. For the patients’ self-ratings of their overall condition, 27 (21%) of the 142 subjects had ratings that were at least two categories better at follow-up compared with baseline. Fifty-one (40%) had no change in their global rating and comprised the unchanged group for this criterion.
Comparisons of responsiveness (tables 2 and 3⇓).
The QOLIE-31 yielded responsiveness indices comparable to the QOLIE-89, despite having one-third the number of items. Effect sizes for the overall QOLIE-31 score were 0.70 for the criterion of 100% reduction in seizure frequency and 0.74 for the overall condition criterion, corresponding to a medium-to-large effect.28 Effect sizes for the overall QOLIE-89 score for these criteria were 0.68 and 0.63. For the QOLIE-89 epilepsy-targeted domain, corresponding effect sizes were 0.66 and 0.80. Using the seizure freedom criterion, the QOLIE-89 physical health composite had a higher effect size than the QOLIE-89 mental health composite (0.65 versus 0.57). For the QOLIE-89, effect sizes were medium and large for all domains and summary scores except for cognitive distress, where effect sizes were small.
Health-related quality of life (HRQOL) responsiveness indices for change in seizure frequency criterion
Health-related quality of life (HRQOL) responsiveness indices for subjects with two-point or greater improvement in overall condition rating from baseline to follow-up
In general, both epilepsy-targeted measures had larger responsiveness indices than the SF-36 and SF-12. However, the responsiveness indices of the RAND-36 HSI mental health and global health composites were comparable to those of the epilepsy-targeted measures for the criterion of change in seizure frequency. The traditional scoring of the SF-36 revealed less sensitivity to change, with effect sizes for the mental health summary score of 0.58 and only 0.38 for the physical health summary score. SF-12 responsiveness indices were even smaller than those of the SF-36.
In general, other responsiveness indices (standardized response mean, Guyatt statistic, and F-ratio) yielded similar findings for generic versus epilepsy-targeted measures. p Values associated with F-statistics were all significant except for those of the SF-12 composites for the change in patients’ self-ratings of their overall condition, and for the SF-36 physical health composite for the change in seizure frequency criterion.
Discussion.
Some previous studies1,29,30 have found disease-targeted HRQOL instruments to be more responsive than generic instruments. In this AED trial, the disease-targeted instruments (QOLIE-89 and QOLIE-31) were more responsive than the generic SF-36 and the SF-12, but we found the RAND-36 HSI’s responsiveness comparable to the disease-targeted instruments for one of the two change criteria. Epilepsy-targeted measures were more responsive than the SF-36 and the SF-12 using the seizure freedom criterion and patients’ ratings of overall condition as criteria for change. The higher responsiveness of epilepsy-targeted HRQOL instruments was consistent across different methods of assessing responsiveness.
Among epilepsy-targeted measures, the responsiveness indices were highest for the QOLIE-89 epilepsy-targeted domain and lowest for cognitive distress. We found that the QOLIE-31, which contains items judged as targeting issues relevant to people with epilepsy, was as responsive as the QOLIE-89 in this sample. Because the QOLIE-31 is shorter and therefore less burdensome to complete, our data suggest that using the shorter QOLIE-31 may be an acceptable trade-off to the longer QOLIE-89 for studies where respondent burden is at a premium and no HRQOL comparisons to other populations (which can be conducted using the SF-36 core measure contained within the QOLIE-89) are desired or planned.
Our findings also suggest that the method for scoring HRQOL measures can influence an instrument’s validity. To date, comparisons of alternative scoring methods has been limited, even for commonly used generic measures like the SF-36. We found that the RAND-36 HSI IRT scoring method yielded responsiveness indices that were better than the SF-36 scoring procedure for one external change criterion. In another example, a study of 194 MS patients revealed that the SF-36 mental health summary score was only slightly lower in MS patients compared with the general population (0.20 standard deviations), but the RAND-36 HSI mental health composite was almost one SD lower.31 The RAND-36 HSI mental health composite score also correlated more strongly with the Expanded Disability Status Scale than did the SF-36 mental health composite score in that study. Future application of the IRT method for scoring other HRQOL measures—including the epilepsy-targeted QOLIE-89 and QOLIE-31 measures used here—is warranted to see if responsiveness is improved using this approach.
Although responsiveness is a quality of the measurement instrument, how one chooses to define changed and unchanged is a key determinant of responsiveness. Additional analyses of this data set using more liberal criteria for changed, such as a 50% or greater reduction in seizure frequency, yielded lower responsiveness indices than the more stringent criterion of achievement of complete seizure freedom, as reported here.32 To incorporate HRQOL measures into clinical trials as a primary outcome requires calculations of sample size or power. Some definition of the “minimally clinically important change” has to be designated by the researcher. We chose the achievement of seizure freedom as one criterion for change in our analysis. Our global self-rated overall condition criterion specified a two-category improvement. For example, a patient who reported having “moderately severe impairment” at baseline had to improve to “mild impairment” after initiation of the AED to be classified as changed.
For a “significant” improvement in HRQOL to occur in samples like this, seizure freedom may be imperative. Other studies have suggested that the HRQOL may actually decrease over time among epilepsy surgery patients who have less than a 90% reduction in seizure frequency postoperatively.33 Although a 50% reduction in seizures has become a traditional endpoint for add-on AED therapy,2 this is a somewhat arbitrary goal. The findings presented here do not answer these questions, but support that further investigation is warranted. A study of the Spanish version of the QOLIE-31 utilized a group of postsurgical epilepsy patients to serve as the changed population and a nonsurgical group with stable global self-ratings as the unchanged population. These investigators found a large effect size for the overall QOLIE-31 using this criterion.34 Explicitly defining what constitutes a minimally clinically important change in epilepsy presents another challenge to the use of HRQOL measures in clinical trials.
Adding HRQOL outcome assessment to AED drug trials ideally can enable the evaluation of the overall impact of the treatment by providing a summary indicator of the direct effects of the treatment on HRQOL and the treatment’s indirect effects on HRQOL through changes in seizure frequency. Such data could assist clinical decision-making about the optimal agent for a patient from among the many new therapies available, and could delineate potential health benefits relative to cost, if evaluated relative to existing, older agents. Reliable and valid measures of HRQOL are needed to answer these questions in a rigorous way.
Appendix
We would like you to think about the present time. Please rate your overall condition as it is now, at this time. This rating should encompass factors such as social activities, performance at work or school, seizures, alertness, and functional capacity, that is, your overall quality of life.
□ no impairment
□ very mild impairment
□ mild impairment
□ moderate impairment
□ moderately severe impairment
□ severe impairment
□ extremely severe impairment
Acknowledgments
Acknowledgment
The authors are grateful to Thomas Belin, PhD, and Gang Li, PhD, of the Health Services Research Center of the UCLA Neuropsychiatric Institute for their advice on parts of the analyses. They appreciate comments on a draft of the manuscript from Donald Patrick, PhD, MSPH. They also thank Mary Cifaldi, RPh, MSHA; Joe Tooley, PharmD, MPH; Ann Tanner, RPharm, MPH; Lawrence E. Dollar Jr, MS, RPharm; Carolyn Wilkerson, PharmD; and Timothy T. Clark, PharmD, MBA, for their help.
Footnotes
-
Views presented are those of the authors and do not necessarily reflect those of the University of California, Hoechst Marion Roussel, Inc., or the Robert Wood Johnson Foundation.
-
Support for these analyses was provided by The Robert Wood Johnson Foundation Clinical Scholars Program; Hoechst Marion Roussel, Inc. provided funding for the primary data collection.
- Received August 30, 1999.
- Accepted January 19, 2000.
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