Epilepsia, 48(8):1438–1446, 2007 Blackwell Publishing, Inc. C 2007 International League Against Epilepsy
Multivariate Neuropsychological Prediction of Seizure Lateralization in Temporal Epilepsy Surgical Cases Therese A. Keary, Thomas W. Frazier, Robyn M. Busch, Cynthia S. Kubu, and Mary Iampietro Cleveland Clinic, Department of Psychiatry and Psychology, Section of Neuropsychology, Cleveland, Ohio, U.S.A.
Summary: Purpose: Neuropsychological assessment can be of assistance in determining seizure lateralization in cases where EEG and MRI findings do not provide clear lateralizing data. While several studies have examined the lateralizing value of individual neuropsychological measures, clinicians are still in need of a statistically sound method that permits the incorporation of multiple neuropsychological variables to predict seizure lateralization in the individual patient. Method: The present study investigated the lateralizing value of several commonly used neuropsychological measures in a large sample of patients (n = 217) who eventually underwent surgical resection to treat their epilepsy. Side of surgery was used to operationally define seizure lateralization. A comparison of the relative utility of a multivariate versus univariate approach to
predict seizure lateralization was conducted in temporal epilepsy cases. Results: The results provide evidence for the incremental validity of neuropsychological measures, other than memory and IQ tests, in the prediction of seizure lateralization in patients with medically intractable epilepsy. These data indicate that a multivariate approach increases the accuracy of prediction of seizure lateralization for temporal lobe epilepsy cases. Conclusion: This study supports the use of a multivariate approach using neuropsychological measures to predict seizure lateralization in temporal epilepsy surgical candidates. Regression formulas are provided to enhance the clinical utility of these findings. Key Words: Epilepsy—Lateralization— Neuropsychology.
Neuropsychologists are frequently consulted to assist in determining candidacy for epilepsy surgery. Historically, neuropsychological evaluations contribute two critical components to the process: (1) prediction of the lateralization and localization of seizure onset, and (2) assessment of the risk of cognitive changes following surgery (Chelune et al., 1991; Sawrie et al., 1998; Jones-Gotman et al., 2000). Neuropsychological evaluations can inform and influence the decision to perform surgery and, if surgery is warranted, the potential site and extent of surgery. The clinical utility of preoperative neuropsychological data in predicting cognitive changes following surgery at the individual patient level has been well established (Chelune and Najm, 2001; Stroup et al., 2003). However, corresponding data regarding the clinical utility of neuropsychological test scores in predicting seizure lateralization and localization in individual patients are lacking. The goal of this study was to examine the validity of neuropsychological measures in predicting seizure lateralization using a multivariate methodology and to generate regression equa-
tions that can be readily adapted for everyday clinical use with individual patients. Much of the previous research has focused on distinguishing left versus right temporal lobe epilepsy (TLE) patients on the basis of modality specific memory scores. For example, Sawrie et al. (2001) examined the lateralization utility of verbal retention, as operationalized by the Logical Memory percent (LM%) retention score from the revised Wechsler Memory Scale (WMS-R; Wechsler, 1987b) in a mixed group of right and left TLE patients. Their results showed that LM% retention may provide important lateralization information in patients who are difficult to lateralize via magnetic resonance imaging (MRI). A more popular approach to the study of lateralization appears to be the use of discrepancy scores on memory measures, including the Memory Assessment Scales (MAS; Williams, 1991) Verbal-Visual Memory discrepancy (Loring et al., 2000); the WMSR Verbal-Visual Memory Index discrepancy (Kneebone et al., 1997); the Wechsler Memory Scale—Third Edition (WMS-III; Wechsler, 1997b) Auditory-Visual Delayed Index difference (Wilde et al., 2001); and the Recognition Memory Test (RMT; Warrington, 1984) Words-Faces discrepancy (Naugle et al., 1994; Kneebone et al., 1997). In general, the results of these studies demonstrate that memory deficits are indicative of temporal lobe
Accepted January 31, 2007. Address correspondence and reprint requests to Therese A. Keary, Department of Psychology, B.S., Kent State University, P.O. Box 5190, Kent, OH 44242, USA. E-mail:
[email protected] doi: 10.1111/j.1528-1167.2007.01098.x
1438
NP PREDICTION OF SEIZURE LATERALIZATION dysfunction and, more specifically, that verbal memory deficits frequently indicate left temporal dysfunction while visual memory deficits typically reflect right temporal dysfunction. Unfortunately, most of these early studies did not provide clinicians with a practical method for determining lateralization of seizure focus at the individual patient level. The lateralizing value of neuropsychological measures other than memory tests has also been investigated. Akanuma and colleagues (2003) reported that the Wechsler Adult Intelligence Scale—Revised (WAIS-R; Wechsler, 1987a) Verbal IQ (VIQ) Index Score had significant lateralizing value for identifying patients with left TLE. However, VIQ accurately lateralized only 57.6% of the patients in the study, improving prediction only slightly above chance. Schefft et al. (1997) assessed the diagnostic utility of the Boston Naming Test (BNT; Kaplan et al., 1983) and Visual Naming Test (VNT) of the Multilingual Aphasia Examination, second edition (Benton and Hamsher, 1989) in lateralizing an epileptogenic region of left temporal origin. Results indicated that the BNT was diagnostically more sensitive than the VNT in identifying left TLE (77.5% vs. 17.5%, respectively). Busch et al. (2005) further examined the utility of the BNT in predicting side of surgery in patients with TLE. Their results demonstrated not only that the BNT raw score was a significant predictor of side of surgery, but that it also provided incremental validity over presurgical intellectual and delayed memory scores. Busch et al. (2005) further noted that the relationship between BNT and side of surgery was moderated by Wechsler Adult Intelligence Scale, Third Edition (WMS-III) (Wechsler, 1997a) FullScale IQ (FSIQ), age of seizure onset, and duration of epilepsy. Using BNT raw score, age of seizure onset, and duration of epilepsy, Busch et al. (2005) were able to correctly predict seizure lateralization in 69.5% of their sample of patients with TLE. Only one known study has utilized multiple predictors to identify seizure lateralization. Kim et al. (2004) evaluated the lateralizing value of three combined indices (intelligence, memory, and handedness). They found that multiple predictors considered in combination demonstrated significantly higher lateralization sensitivity (i.e., proportion of patients correctly identified into left and right surgical groups) than the individual predictors considered in isolation. Thus, combining multiple predictors appears to be an effective means of improving the lateralizing value of neuropsychological measures. However, Kim et al. (2004) did not provide a clinically useful means by which multiple predictors could be combined to lateralize the epileptogenic focus at the individual classification level. Consequently, clinicians are still in need of a statistically sound method that permits incorporation of multiple neuropsychological variables to predict seizure laterality in the individual patient.
1439
The present study investigated the lateralizing value of several commonly used neuropsychological measures in a large set of patients who eventually underwent surgical resection to treat their epilepsy. Side of surgery was used to operationally define seizure lateralization. The study examined the predictive validity of neuropsychological measures in lateralizing seizure focus in patients with TLE. Based upon the vast literature documenting memory deficits in TLE (Delaney et al., 1980; Hermann et al., 1987; Loring et al., 1988; Rausch et al., 1991; Sass et al., 1992a; Sass et al., 1992b; Breier et al., 1993; Miller et al., 1993; Rausch and Babb, 1993; Saling et al., 1993), we examined the incremental validity of other neuropsychological measures over and above memory indices in predicting seizure lateralization. We hypothesized that language and IQ measures would provide incremental validity over memory measures (see Busch et al., 2005) and completed a multivariate analysis to examine this hypothesis. The role of several potential moderating variables in predicting seizure lateralization was also examined, including age of seizure onset, duration of epilepsy, and overall intellectual ability. Regression formulas were developed to assist clinicians in determining seizure lateralization in individual patients. METHOD Participants The data from this retrospective study were obtained from an IRB-approved Epilepsy Patient Registry consisting of neuropsychological data collected as part of the participants’ standard clinical management. Table 1 summarizes participants’ demographic characteristics, seizure variables, and neuropsychological test scores. Participants in this study were 217 surgical patients (97 males, 120 females; 206 white; 11 nonwhite) with medically intractable epilepsy who completed a comprehensive neuropsychological evaluation as part of their presurgical investigations for the treatment of their epilepsy. Participants ranged in age from 18 to 65 years (M = 36.06; SD = 10.96) and in education from 6 to 20 years (M = 13.00; SD = 2.27). The mean age of seizure onset for this group was 15.65 years (SD = 11.48) and the mean duration of epilepsy was 20.51 years (SD = 13.52). There were no significant differences between right and left TLE groups with regard to race, sex, age, education, age at seizure onset, duration of epilepsy, or WAIS-III Full Scale IQ (FSIQ). All patients in this study were right-handed, as determined by a handedness score of eight or greater on a standard handedness questionnaire (Annett, 1970). All participants underwent a comprehensive presurgical assessment that included video-EEG monitoring, MRI studies, PET and other molecular imaging, and a comprehensive neuropsychological evaluation. Surgical decision making varies substantially depending upon individual patient characteristics and presentation. Nevertheless, Epilepsia, Vol. 48, No. 8, 2007
1440
T. A. KEARY ET AL. TABLE 1. Demographic, seizure, and neuropsychological data for study patients (n = 217) Total
N Sex Male Female Race White Nonwhite
Age Education Age at Seizure Onset Duration of Epilepsy FSIQ ADMI VDMI VCI POI WMI PSI TMT-A TMT-B WCST-Cat WCST-SF WCST-PE RFFT-ER FAS-Tot RFFT- Tot BNT WRAT-III Reading GPegs-d GPegs-nd FTT-d FTT-nd
217 97 (45%) 120 (55%)
Right
Left
116
χ 2 (df ), p
101
55 (47%) 61 (53%)
43 (43%) 58 (57%)
0.346 (1), 0.557
206 (95%) 11 (5%) Mean (SD)
111 (96%) 5 (4%) Mean (SD)
95 (94%) 6 (6%) Mean (SD)
0.30, (1), 0.585 T or χ 2 (df), p
36.05 (10.96) 13.00 (2.27) 15.65 (11.48) 20.51 (13.52) 91.22 (13.56) 89.66 (15.73) 87.98 (16.65) 90.10 (13.37) 95.05 (15.23) 88.81 (15.86) 91.93 (14.03) 31.55 (12.44) 88.11 (59.96) 4.44 (2.00) 1.02 (1.40) 90.69 (21.71) 56.14 (10.37) 28.02 (11.81) 42.26 (9.85) 47.27 (7.96) 92.01 (12.45) 78.23 (20.04) 84.89 (23.75) 45.80 (6.89) 41.22 (6.33)
36.93 (10.94) 13.03 (2.27) 16.60 (11.38) 20.64 (14.20) 90.50 (14.35) 91.85 (16.56) 86.26 (17.08) 90.96 (13.78) 93.48 (15.82) 91.42 (15.32) 90.71 (13.62) 32.59 (13.09) 94.13 (64.46) 4.10 (2.23) 1.02 (1.52) 89.46 (22.07) 55.96 (10.56) 27.80 (11.49) 42.76 (10.10) 48.90 (7.45) 91.01 (12.56) 78.97 (20.32) 86.90 (24.53) 45.38 (7.30) 41.13 (7.18)
35.04 (10.95) 12.98 (2.29) 14.56 (11.54) 20.37 (12.76) 92.03 (12.63) 87.15 (14.40) 89.96 (15.99) 89.12 (12.87) 96.90 (14.39) 93.90 (14.06) 93.34 (14.43) 30.36 (11.59) 81.20 (53.83) 4.84 (1.61) 1.03 (1.26) 92.14 (21.31) 56.35 (10.20) 28.29 (12.26) 41.68 (9.58) 45.42 (8.16) 93.13 (12.29) 77.37 (19.80) 82.79 (22.75) 46.28 (6.38) 41.31 (5.21)
1.27 (215), 0.206 0.147 (215), 0.883 1.310 (215), 0.192 0.147 (215), 0.883 −0.831 (213.99), 0.407 2.218 (215), 0.028 −1.640 (215), 0.102 1.010 (215), 0.313 −1.656 (215), 0.099 −1.231 (212), 0.220 −1.380 (215), 0.169 1.320 (215), 0.188 1.590 (215), 0.133 −2.774 (202.42), 0.006 −0.069 (209), 0.945 −0.896 (209), 0.371 −0.273 (208), 0.785 −0.298 (211), 0.766 0.792 (208), 0.429 3.278 (213), 0.001 −1.234 (208), 0.218 0.584 (215), 0.560 1.270 (214), 0.206 −0.959 (214), 0.339 −0.207 (214) 0.836
Note. Levene’s test for equality of variances was examined. In each case where the variances are not equal, the appropriate t, (df), and p value are reported instead. Age, Education, Age at Seizure Onset, and Duration of Epilepsy are reported in years.
patients are typically judged to be good surgical candidates for temporal lobectomy if they have demonstrated poor response to multiple antiepileptic medications, show a clear unilateral seizure focus on EEG, and demonstrate evidence of MRI or PET abnormalities within the ipsilateral temporal lobe. Patients without a clear epileptogenic focus or an identifiable lesion on MRI often undergo invasive investigations, such as subdural grid placement and/or depth electrode evaluation to further delineate the epileptogenic zone. The majority of patients did not undergo Wada testing and none of the participants had previous neurosurgical intervention. Seizure lateralization was classified according to the side of surgery. Approximately 90% of patients had favorable postsurgery outcomes (e.g., 2 or fewer seizures at their postoperative follow-up, approximately 6 months following surgery). The fact that approximately 90% of patients had favorable postsurgery outcome suggests that side of surgery represented a good proxy for seizure lateralization. All 217 patients were suspected to have a unilateral seizure focus (left hemisphere = 116; right hemisphere = 101) with discharges localized in the temporal lobe.
Epilepsia, Vol. 48, No. 8, 2007
Measures Participants completed a comprehensive neuropsychological battery that included: Full Scale IQ (FSIQ), Verbal Comprehension Index (VCI), Perceptual Organization Index (POI), Working Memory Index (WMI), and Processing Speed Index (PSI) from the WAIS-III (Wechsler, 1997a); the Auditory Delayed Memory Index (ADMI) and Visual Delayed Memory Index (VDMI) from the WMS-III (Wechsler, 1997b); the times to complete the Trail Making Test Parts A and B (TMT-A and TMT-B; Army Individual Test Battery, 1944); the number of categories completed (WCST-Cat), number of set failures (WCST-SF), and perseverative errors (Standard Scores, WCST-PE) on the Wisconsin Card Sort Test (WCST; Heaton et al., 1981); the corrected total designs t-score (RFTT-Tot) and error ratio t-score (RFFT-ER) of the Ruff Figural Fluency Test (Ruff, 1988); the total words generated for the Controlled Oral Word Association (FAS-Tot; Benton and Hamsher, 1989); the total raw score of the Boston Naming Test (BNT; Kaplan et al., 1983); the standard score from the Reading subtest of the Wide Range Achievement Test, Third Edition (WRAT-III Reading; Wilkinson, 1993); the time
NP PREDICTION OF SEIZURE LATERALIZATION TABLE 2. Point-biserial correlations between neuropsychological measures and side of surgery Memory (WMS-III) ADMI VDMI Intelligence VCI POI Attention/working-memory WMI PSI TMT-A Executive functioning TMT-B WCST-Cat WCST-SF WCST-PE RFTT-ER Fluency FAS-Tot RFFT-Tot Language BNT WRAT-III Reading Motor GPegs-d GPegs-nd FTT-d FTT-nd
0.131 −0.150∗ 0.111 0.091 −0.069 0.112 0.089 0.084 0.094 −0.090 0.076 −0.108 ∗∗ 0.185 0.005 0.062 0.019 0.038 0.021 −0.055 0.152 ∗∗∗ −0.219 0.085 0.051 −0.040 −0.086 0.065 0.014
Note: Averages of absolute values of correlations appear in bolded italics. ∗ ∗∗ ∗∗∗ p < 0.05, p < 0.01, p < 0.001.
to complete the Grooved Pegboard Test (Kløve, 1963) for both dominant (Gpegs-d) and nondominant hands (Gpegs-nd); and the average number of taps on the Finger Tapping Test (Reitan and Wolfson, 1993) for both dominant (FTT-d) and nondominant hands (FTT-nd). Such measures represent well-accepted elements of a presurgical epilepsy neuropsychological evaluation (JonesGotman et al., 1993). The scores listed above were grouped on a theoretical basis according to major cognitive domains: memory (ADMI and VDMI), intelligence (VCI and POI), attention/working memory/processing speed (WMI, PSI, and TMT-A), executive functioning (TMT-B, WCST-Cat, WCST-SF, WCST-PE, and RFFT-ER), fluency (FAS-Tot and RFFT-Tot), language (BNT and WRAT-III), and motor functioning (GPegs-d, GPegs-nd, FTT-d, FTT-nd). Analytic Strategy The relationship between neuropsychological measures, grouped by hypothetical domain, and side of surgery was examined using point-biserial correlations (see Table 2). For each domain, the average absolute value of the correlations was reported because some of the correlations were positive and some were negative, followed by individual measure correlations. Individual correlations were coded such that positive correlations indicated that better performance on the measure was associated with left-sided surgery. For example, the positive correlation
1441
between Visual Delayed Memory on the WMS-III and side of surgery indicates that higher Visual Delayed Memory scores were associated with left-sided surgery. Inspection of Table 2 reveals that, for temporal cases, memory and language scores tended to produce the largest average correlations; however, the average correlation for language measures was largely driven by the BNT. All of the correlations tended to be low-to-moderate in magnitude for the temporal cases (ranging from 0.014 to −0.219). The only correlations that were significant were WCST-Cat (r = 0.185, p = 0.007), BNT (r = −0.219, p = 0.001); and ADMI (r = −0.150, p = 0.028). The correlation for VDMI approached marginal significance (r = 0.111, p = 0.100), as did the correlation for POI (r = 0.112, p = 0.099). In order to identify which neuropsychological domains contributed significant incremental variance to the prediction of seizure lateralization, a series of hierarchical logistic regressions were computed with memory as the independent variable in step one and other neuropsychological test scores grouped by domain entered in step two. The neuropsychological measures that made the largest contribution to memory, as indexed by Beta coefficients and Wald statistics, were then included in step one, along with memory variables, in a new hierarchical logistic regression analysis. Only the variables in each domain that contributed significant unique variance were retained in subsequent analyses. In subsequent analyses, all of the remaining variables were entered in step 2 to determine whether any of these variables contributed further incremental validity. This process continued iteratively until the neuropsychological variables no longer contributed significant incremental variance to the variables retained in step one of the logistic regression analyses. For each of these regression analyses, individual neuropsychological variables were grouped by domain with individual predictors entered as a group. Composite domain scores were not used since these scores may obscure specific relations between predictors and the goal of these analyses was to compute simple regression equations based upon commonly used measures that clinicians could easily implement.
Moderators To examine whether prediction of side of surgery was influenced by moderating variables, two separate analyses were conducted. First, a hierarchical logistic regression was computed with each of the neuropsychological measures retained in the previous analyses entered in step 1 along with the moderating variables (age of seizure onset, duration of epilepsy, and FSIQ). Then, in step 2, the interactions between the moderators and neuropsychological measures were entered. This analysis examined whether any of the moderators influenced prediction of seizure Epilepsia, Vol. 48, No. 8, 2007
1442
T. A. KEARY ET AL.
lateralization when neuropsychological measures are considered in a multivariate fashion. Second, a similar set of hierarchical logistic regressions was computed to those described above; however, these regressions were computed separately for each of the neuropsychological measures that demonstrated significant predictive ability in the incremental validity analyses. In these analyses, the individual neuropsychological predictor was entered in step 1 along with the three moderating variables. In step 2, the interactions between the individual neuropsychological predictor and the three moderating variables were entered. This analysis examined whether the moderating variables influence prediction of seizure lateralization when neuropsychological variables are considered in a univariate fashion. Both of these analyses follow the basic procedures for testing moderation outlined by Baron and Kenny (1986). RESULTS Table 3 presents the results for the series of hierarchical regressions computed for temporal epilepsy cases. Results of the first analysis indicated that the language domain contributed the most unique variance (R2 = 0.120, Block χ 2 = 21.56, p < 0.001) over and above memory scores (Step 1 R2 = 0.101, Block χ 2 = 17.12, p < 0.001). In the next regression analysis the memory (ADMI and VDMI) and language (BNT and WRAT-III Reading) variables were entered in step 1 and the remaining neuropsychological variables entered in step 2. The WCST-Cat measure provided the most substantial incremental validity (R2 = 0.039, Block χ 2 = 7.32, p = 0.007). In the final analysis, with the memory and language variables and WCST-Cat entered in step 1 and the remaining neuropsychological variables entered in step 2, none of the
TABLE 3. Incremental validity in temporal cases
Regression #1 Step 1: Memory Step 2: IQ Attention/Working Memory Executive Functioning Fluency ∗ Language Motor Regression #2 Step 1: Memory & Language Step 2: Executive Functioning ∗ WCST-Cat IQ POI Regression #3 Step 1: Memory, Language & WCST-Cat Step 2: POI ∗
R2 / R2
Block χ 2
0.101 0.032 0.014 0.070 0.100 0.120 0.031
17.12 5.68 2.37 12.03 1.76 21.56 5.35
