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Response to light therapy in seasonal affective disorder: personality disorders and temperament as predictors of outcome
JOURNAL
ELSEVIER
Journal of Affective Disorders 41 ( 1996) 101- 110
OF
A.FFEClTIVE DISORDERS
Research report
Response to light therapy in seasonal affective disorder: personality disorders and temperament as predictors of outcome Ted Reichborn-Kjennerud Department
of Psychiatry,
*, Odd Lingjaxde
Unicersity of Oslo, Gaustad Hospital, P.O. Box 33, Gaustad, N-0320 Oslo, Norway
Received
16 April 1996; revised 8 July 1996; accepted 8 July 1996
-~~ Abstract Outcome after 6 days of morning light therapy in subjects fulfilling criteria for winter seasonal affective disorder (SAD) was examined. Responders had significantly fewer previous episodes of SAD, Patients with a diagnosis of any DSM-III-R, axis II personality disorder, were significantly less likely to respond to light therapy than patients without axis II pathology. Poor treatment outcome was also significantly associated with: one or more personality disorders in cluster C, avoidant personality disorder, high number of positive criteria for self-defeating personality disorder and high score on the harm avoidance scale of the Tridimensional Personality Questionnaire. Temperament accounted for 25% of the variance in treatment outcome.
1. Introduction Bright artificial light has been shown to be an effective treatment for winter seasonal affective disorder (SAD), a syndrome characterized by recurring seasonal changes in mood, sleep pattern, social activity, appetite and energy (Rosenthal et al., 1984). The pathophysiology of the disorder and the mechanisms of action of light therapy are still not well understood. Various hypotheses have been proposed, suggesting disturbances in, e.g., circadian rhythms and neurotransmitter systems (see Rosenthal and Wehr, 1992). In a review of data from 14 research centers, Terman et al. (1989) found a response rate (> 50%
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reduction in depression scale score> of 66% to 1 week of morning light therapy in patients with SAD. Although subsequent studies have confirmed the efficacy of phototherapy (Oren and Rosenthal, 19921, there has been some controversy regarding the placebo effect in this form of treatment (Brown, 1990). Recently, however, two well-designed studies have clearly demonstrated the superiority of bright light over placebo (Eastman et al., 1996; Terman and Terman, 1996). Several attempts have been made to determine the characteristics of patients who respond to light treatment (Stinson and Thompson, 1990; Avery et al., 1991; Nagayama et al., 1991; Terman et al., 1992; Oren et al., 1992; Meesters et al., 1993; Krluchi et al., 1993; Lam, 1994). The results, however, have been inconsistent. Variables found to be positively correlated with favorable response to phototherapy in
0 1996 Elsevier Science B.V. All rights reserved.
one or more of these studies include: severity of atypical vegetative symptoms, hypersomnia, hyperphagia, carbohydrate craving, high intake of sweets late in the day, young age, diurnal variation of depressive symptoms and suicidality. Severity of pretreatment typical depressive symptoms, measured as score on the Hamilton Depression Rating Scale (HAM-D) (Hamilton, 1967), has been found to be both negatively (Stinson and Thompson, 1990; Terman et al., 1992) and positively correlated with outcome (Oren et al.. 1992; Meesters et al., 1993). To our knowledge, no systematic study of the relationship between personality and response to phototherapy in SAD has been published. However, in a short report, Lilie et al. (1990) concluded that in a sample of patients with SAD. subjects without axis II psychopathology were more likely to be bright light responders and to fully remit in summer. Personality traits and disorders have been found to influence response to somatic treatments in patients with non-seasonal major depressive disorder (MDD; Ilardi and Craighead, 1995). Temperament, as defined by Cloninger (I 987), with three genetically determined dimensions called ‘novelty seeking’ (NS), ‘harm avoidance’ (HA) and reward dependence (RD), have also been shown to predict outcome of antidepressant treatment for non-seasonal MDD (Joffe et al., 1993; Joyce et al., 1994). The present study was designed to examine DSMIII-R personality disorders (PD) and temperament, as defined by Cloninger, as possible predictors of response to light therapy in patients with SAD. We also evaluated several demographic and clinical variables, some of which have previously been found to be related to outcome of light treatment.
sion. Only patients recruited the first year (n = 33) were included in the part of the study concerning personality disorders and temperament (see below). The subjects were either recruited through the mass media, or referred to our unit by the health care system. They were first screened with the Seasonal Pattern Assessment Questionnaire (SPAQ; Rosenthal et al.. 1984). then interviewed by one of the authors, both experienced psychiatrists, using a semistructured interview, before being included, as previously described (Lingjjaerde et al.. 1993). All patients also fulfilled the DSM-III-R criteria for major depressive disorder, recurrent, seasonal pattern. Patients with psychotic symptoms. severe suicidal ideation. current alcohol or drug abuse, or significant somatic illness were excluded from the study. None of the patients had received antidepressant medication for at least 2 weeks before starting phototherapy. and none had received t’luoxetine, which could have intluenced treatment outcome more than 2 weeks after discontinuation. 2.2. Trerrttnent
2. I. Sul7ject.s
Light treatment was given for 6 consecutive days (Monday to Saturday) for 2 h each morning within the time period 07:OO am. to 1 I:00 a.m. in a specially equipped room in which up to IO patients (usually 5 to 6) could be treated simultaneously. Full-spectrum white light. giving an illuminance of about 1500 lux at eye level, was used. Treatment was offered from the end of November to the beginning of February (Lingjazrde et al., 1993). Our sample also include four patients who received treatment for only I h daily. The clinical characteristics at baseline for these subjects were not significantly different from the rest of the patients. We have, in this and subsequent trials, not found any significant difference in response rates between treatment for I and 2 h (unpublished observation).
The 42 subjects in this sample participated in a treatment study of winter depression at the University of Oslo, Gaustad Hospital. They represent all patients in two consecutive winters (1991/92 and 1992/93) who satisfied the criteria for SAD according to Rosenthal et al. (1984), and who received light therapy as the only treatment for their winter depres-
Before starting therapy (baseline), all patients were rated on the Montgomery Asberg DepLession Rating Scale (MADRS; Montgomery and Asberg. 1979) extended with four items: increased sleep, increased appetite. carbohydrate craving. and fatiguability. All
2. Methods
T. Reichbom-Kjennerud,0. Lingjwde/Joumal of &ffecriceDisorders41 (19961 101-I IO
items were rated on a scale from 0 to 6. Follow-up registrations were done 1, 3, 6, 10 and 14 weeks after beginning of treatment. From SPAQ was derived the Global Seasonality Score (GSS), a measure reflecting the sum of ratings for seasonal variation in 6 areas: sleep length, social activity, mood, weight, appetite and energy level. The 33 patients who were included in the study the first winter, all completed self-report questionnaires to assess DSM-III-R personality disorders and temperament before starting treatment. There were no significant differences between this group and the 9 new inclusions the second year (who did not receive these questionnaires) with regard to age, age at first episode of SAD, number of previous episodes of SAD, depression score at baseline (original MADRS and extended version) or response to treatment. Personality disorders were assessed by the Personality Diagnostic Questionnaire-Revised (PDQ-R), a 152-item, self-administered, true/false questionnaire designed to assess personality disorder diagnosis consistent with the DSM-III-R criteria (Hyler and Rieder, 1987). Compared to structured interviews, this instrument has been shown to have high sensitivity and moderate specificity for most axis II disorders (Hyler et al., 1992), and the reliability of the scores has been found to be similar to those derived from interviews in a 6 months followup study of patients with MDD (Trull and Goodwin, 1993). Temperament was assessed with the Tridimensional Personality Questionnaire (TPQ; Cloninger et al., 1991). 2.4. Statistical analyses SPSS for Windows, release 6.0, was used for statistical analyses. Two methods, commonly used in this type of studies, were employed to examine predictors of response. First, we defined non-responders as patients having a pre- to posttreatment extended MADRS score reduction < 30%, thus using a relative improvement criterion analogous to that used by Terman et al. (1992), and Meesters et al. (1993). Responders were defined as patients showing 2 50% reduction in extended MADRS score in the same period. The two groups were then compared with respect to the relevant variables, using t-tests or Mann-Whitney/Wilcoxon rank-sum
103
tests for continuous variables, and chi square test for categorical variables. In the second approach, outcome as a continuous measure, defined as percentage reduction in extended MADRS score from baseline to the end of the treatment period (1 week after beginning of therapy), was used as dependent variable in bivariate and multivariate linear regressions with possible predictors. Using relative reduction in extended MADRS instead of absolute differences make the results less dependent on baseline scores. By also using outcome as a continuous variable, disadvantages of arbitrary cutting points are avoided. A significance level of P = 0.05was chosen.
3. Results
3. I. Responders
us. non-responders
Table 1 shows data on demographic and clinical variables for the total sample and for the non-responder and responder groups separately. Twentytwo patients (52%) were classified as responders and 8 (19%) as non-responders. The mean reduction in extended MADRS score was 51% for the whole sample, 72% for the responders and 11% for the non-responders. The only statistically significant difference between the groups was that responders reported fewer previous episodes of SAD (P = 0.05, Mann-Whitney/Wilcoxon). Scores on MADRS at baseline were higher for the non-responders, but this difference was not significant (P = 0.09, two-tailed t-test>. Prevalences for DSM-III-R personality disorders, including self-defeating PD, are given in Table 2. None of the patients satisfied criteria for antisocial or narcissistic PD. Sixty-one percent of the sample fulfilled criteria for one or more axis II diagnosis. Disorders in cluster C occurred most frequently (48%). The number of patients with any PD in cluster A, B or C, was significantly higher among the non-responders (P < 0.05, chi-square test) than the responders. Any PD in cluster C also occurred more frequently among the non-responders (P < 0.05, chi-square test). Of the specific disorders, only avoidant PD was significantly more prevalent in the non-responder group (P = 0.001, chi square test).
104 Table 1 Demographic
T. Reichborn-Kjmnenld,
and clinical characteristics
0. Lingjerde
/ Journul
for total sample, non-responders,
of Afccrire
Disorders
and responders
41
f I9961lOI- I IO
to 6 days of light therapy
Total sample (n = 42)
Non-responders (a = 8)
38 (90) 4 (IO) 43.4 + 10.2
7 (87) I(131 45.8 * x.1
’
Responders (rt = 22)
h
Sex,
IL (%) - Female
- Male Age, mean + SD Marital status, n (7~) - Married, cohabiting - Single Lifetime diagnosis MDD. n (%) - Unipolar - Bipolar II
21 (95) I (5) 13.5 * 1 I.‘)
22 (52) 20 (48)
4 (501 4 (50)
I I (SO) 11(SO)
38 (90) 4 (101
8 (100) 0
19 (86) 3(13)
Age at first SAD episode, mean f SD Previous SAD episodes. mean f SD
24.8 + 10.1 15.7 f 8.8
22.4 f 10.0 20.5 f 6.8 L
24.9 + I 1.0 IS.1 5 10.0
GSS, mean k SD
15.6 + 2.8
16.0 k 3.2
15.8 * 2.4
Suicide attempt during SAD, n (%‘c) Suicidal thoughts during SAD, n (%)
5 (12) 37 (88)
Depression scale score, mean + SD MADRS (pretreatment) MADRS (posttreatment) Extended MADRS (pretreatment) Extended MADRS (posttreatment)
18.2 9.5 28.5 14.4
Atypical symptoms score (pretreatment), mean + SD Hypersomnia Hyperphagia Carbohydrate Fatiguability
5.7 1.4 6.7 9.5
2.5 2.2 2.7 2.9
f + f +
f + + +
2 (9) 13 (SO)
5.3 5. I 7.8 1.4
11.1 +4.4
1.8 1.6 1.5 1.2
2.6 2.4 2.6 3.5
i + i f
2.1 1.8 1.7 1.1
17.1 3.5 27.8 8.0
* * * *
5.7 3.8 6.8 5.1
10.1 + 3.8 2.6 2.5 2.8 2.8
+ + + F
I.7 1.4 1.5 1.3
< 30% after 6 days of light therapy. 2 50% after 6 days of light therapy. rank sum test.
Table 3 shows scores on the TPQ subscales. The non-responders had significantly higher scores on the HA scale than the responders (P < 0.001, two-tailed t-test). 3.2. Treatment
21.3 20.1 32.5 28.9
10.3 * 3.9
craving
a Reduction in extended MADRS score h Reduction in extended MADRS score P = 0.05 by Mann-Whitney/Wilcoxon
f i f f
2 (25) 5 (63)
outcome as a continuous
variable
3.2.1. Demographic and clinical variables as predictors of outcome In bivariate regression analyses with treatment outcome (continuous) as dependent variable, we examined the following variables as potential predictors: sex (f or m), age (continuous), marital status
(single or married/cohabiting), lifetime diagnosis MDD (unipolar or bipolar II), age at first episode of SAD (continuous), number of previous episodes of SAD (continuous), GSS (continuous), suicide attempts during previous episodes of SAD (yes or no>, suicidal thoughts during previous episodes of SAD (yes or no), MADRS and extended MADRS at baseline (continuous), hypersomnia, hyperphagia, carbohydrate craving, fatiguability (O-6), total score for all atypical symptoms (continuous) and atypical balance (sum score for the four atypical symptoms in percent of extended MADRS). None of the results were statistically significant. There were trends to-
T. Reichborn-Kjennerud, 0. Lingjcerde / Journal of Affectiur Disorders 41 (1996) IOI- 110 Table 2 Prevalence
of DSM-III-R
personality
disorders
for total sample, non-responders,
Total sample (n = 33) n
and responders a
Responders (n = 18)
8
n
%
n
%
1
6 1
6 11 6 6 33 6
3 4
17 22
1
6
1 3 6 6 8
6 17 33 33 = 44 *
4 5 3 3 8 7
12 15 9 9 24 21
2 1 2 2 5
25 13 13 25 25 63 **
Dependent Obsessive Compulsive
5 7
15 21
0 2
25
Passive Aggressive
3
9
0
6 9 10 16 20
18 27 30 48 61
2 3 4 6 I
A B C A,
to 6 days of light therapy
Non-responders (II = 8)
Paranoid Schizoid Schizotypal Borderline Histrionic Avoidant
Self-defeating Any Cluster Any Cluster Any Cluster Any Cluster B or C
105
I
25 38 50 75 * 88 *
b
2
1 I
*I
a Reduction in extended MADRS score < 30% after 6 days of light therapy. h Reduction in extended MADRS score z 50% after 6 davs . of light . therapy. * P = 0.049, xZ test, * * P = 0.001, x’ test.
wards negative regression on outcome for scores on both MADRS scales ( p = -0.26, P = 0.09). As no variable showed any significant regression with treatment outcome, no multiple regression analyses combining variables was performed. 3.2.2. Personality disorders as predictors of outcome The following variables were used as independent variables in bivariate regression analyses with treatTable 3 Tridimensional non-responders,
personality questionnaire scores for total sample, and responders to 6 days of light therapy Total sample
Novelty seeking Harm avoidance Reward dependence
Nonresponders
Responders
(n = 33) mean f SD
(n = 8) mean f SD
(n= 18) mean + SD
16.5+5.0 19.656.3 17.8 + 4.4
14.5k5.1 25.6k4.0 16.8 + 3.6
17.2 + 5.2 18.2+3.9 * 18.6f3.1
a Reduction in extended MADRS light therapy. b Reduction in extended MADRS lighttherapy. * P < 0.001, two-tailed t-test.
’
’
*
score
< 30% after 6 days of
score
> 50% after 6 days of
ment outcome (continuous) as dependent variable: categorical diagnosis (presence/absence) of any DSM-III-R PD, any PD in each cluster and each specific PD separately, as well as total number of PDs and number of PDs in each of the clusters and dimensional scores (number of positive DSM-III-R criteria) for each PD, each cluster, and all clusters together. As shown in Table 4, the presence of any DSMIII-R PD diagnosis (compared to none) was significantly associated with a negative treatment outcome ( p = - 0.44, P = 0.0 1). This variable explained 17% of the variance in outcome (adjusted r’ = 0.17). Patients without any axis II co-morbidity had a mean
Table 4 Regression coefficients for DSM-III-R personality treatment outcome after 6 days of light therapy
disorders
n = 33
P
P
-0.20 -0.20 - 0.36 -0.44
0.25 0.27 0.04 0.01
Any Any Any Any
cluster cluster cluster PD in
A diagnosis B diagnosis C diagnosis cluster A, B or C
on
response rate of 68%, whereas patients with one or more PD diagnosis had a response rate of 41%. The presence of any cluster C PD also predicted worse outcome ( p = -0.36, P = 0.04, adjusted I’ = 0. I 1), with response rates of 41% compared to 62% for those without a cluster C diagnosis. Avoidant PD was the only specific axis II diagnosis which showed a significant relationship with treatment outcome ( p = -0.46, P = 0.007). Patients with avoidant PD had a mean response rate of only 26%, compared to 59% for those without avoidant PD. This variable alone explained 19% of the variance in outcome (adjusted r’ = 0.19). When number of positive DSM-III-R criteria were considered as dimensional predictors, score for self-defeating PD was the only measure significantly related to outcome (p = - 0.36. P = 0.04). Personality disorder measures were not significantly related to sex, age at first SAD episode, or number of previous winter depressions. MADRS at baseline was significantly related to both total number of positive DSM-III-R criteria in all clusters ( p = 0.36, P = 0.04) and dimensional scores for avoidant PD ( p = 0.50, P = 0.003). Dimensional measures of all personality variables associated with outcome were highly interrelated with regression coefficients ranging from 0.89 (total score in all clusters with total score in cluster C) to 0.53 (avoidant PD with total score in cluster C). 3.2.3. Temperament as predictor of outcome The results of bivariate regression analysis with the TPQ scales on treatment outcome are given in Table 5. Total score on the harm avoidance scale showed a significant negative relationship with the response to light therapy ( p = -0.36, P = 0.04, adjusted Y’ = 0. IO). All HA subscale scores were negatively associated with outcome, but only HAI (anticipatory worry) showed a significant relationship ( p = -0.36, P = 0.04). The lowest regression coefficient was found for RD2 (persistence), a trait which may be inherited separately from the other aspects of reward dependence. Cloninger (1987) postulates the existence of 8 temperament types based on the combination of the three temperament scales. with each measure dichotomized as high or low. We therefore divided the three scales at the means for this sample (NS 17/ 16,
Table 5 Regression coefficients for the tridimensional personality questionnaire scales and subscales on treatment outcome after 6 days of light therapy 33
B
P
Novelty seeking total NS I : (exploratory excitability) NS2: (impulsiveness) NS3: (extra\apance) NS3: (disorderliness)
0.20 0.28 0.0 I 0.33 - 0.06
0.26 0. I I 0.93 0.07 0.72
Harm avoidance total HA I : (anticipatory worry) HA2: (fear of uncertainty) HA3: (shyness with strangers) HA4: ifatiguahility)
- 0.36 ~ 0.36 -0.16 - 0.33 - 0.26
0.01 0.04 0.38 0.06 0. IS
n=
Reward dependence RDI: (sentimentality) RD2: (persistence) RD3: (attachment) RD4: (dependence)
total
0. I I 0.03 0.00 0. IO 0. IS
0.55 0.X6 I .oo 0.60 0.40
HA 16/17, RD 17/16). Patients with high HA had a response rate of 38% compared to 66% for those with low HA. Regression with the dichotomized HA variable explained 19% of the variance in outcome ( p = - 0.46, P = 0.007, adjusted r’ = 0.19). Multiple regression with all three dichotomized variables explained 22% of the variance in outcome (adjusted r’ = 0.22, P = 0.02). Analysis of variance (ANOVA) with the three dichotomized variables showed no significant interactions. There was a weak trend towards a 2-way interaction between HA and RD (P = 0.14). Multiple regression with all 8 temperament types explained 25% of the variance in treatment outcome (adjusted r2 = 0.25, P = 0.04). Temperament was not significantly related to age, age at first SAD episode, or number of previous winter depressions. There was a significant relationship between HA and MADRS at baseline ( /3 = 0.35, P = 0.046) and between RD and sex (fi = 0.35, P = 0.044). Harm Avoidance, total score. was significantly associated with dimensional scores for all PD measures associated with outcome: i.e., number of positive criteria in all clusters ( /3 = 0.54, P = O.OOl), in cluster C (/3 = 0.50, P = 0.003) for avoidant PD
T. Reichborn-Kjennerud,
0. Lingjrrrde/Journal
(p = 0.56,P = 0.001) and for self-defeating P = 0.002).
PD
( p = 0.53,
4. Discussion The only demographic or clinical variable for which there was a significant (P = 0.05) difference between responders and non-responders to light therapy in this sample, was number of previous SAD episodes. Considering the number of variables tested, this relationship is weak, and would not be significant if a Bonferroni correction had been employed. High number of previous episodes has been found to predict poorer response to tricyclic antidepressants (TCA) in patients with non-seasonal MDD (Joyce and Paykel, 1989), but has not been examined as a predictor of response to light treatment in other studies of patients with SAD. In contrast to previous studies of predictors of response to light therapy, we failed to identify any clinical variable at baseline as significantly associated with outcome as a continuous variable. Although the size of our sample (n = 42) is larger than in 4 of the 8 studies referred to in the introduction, our negative results could be the result of low statistical power (type II error). Pretreatment score on the g-item atypical depressive symptom addendum included in the Structured Interview Guide for the Hamilton Depression Inventory, Seasonal Affective Disorder Version (SIGHSAD; Williams et al., 1992), has been found to correlate positively with outcome in four studies (Terman et al., 1992; Nagayama et al., 1991; Oren et al., 1992; Lam, 1994). This measure includes social withdrawal, weight gain, increased appetite, increased eating, carbohydrate craving or eating, hypersomnia, fatiguability, and slump in mood or energy in the evening or afternoon. Our scoring of atypical symptoms included only 4 of these items: appetite increase, carbohydrate craving or eating, hypersomnia, and fatiguability, and can therefore not be directly compared to these studies. Neither of the items by themselves, however, were significantly associated with outcome. We could thus not confirm earlier reports indicating that the presence of hypersomnia (Avery et al., 1991; Oren et al., 1992; Lam, 1994), hyperphagia (Oren et al., 1992; Lam, 1994),
of Affectice Disorders 41 (1996) 101-110
107
or carbohydrate craving (Oren et al., 1992) was associated with a favorable treatment response. Because treatment outcome could be influenced by sample differences in demographic and clinical variables, and treatment methods including duration of therapy and light sources used, it is relevant to comment on these issues. The demographic and clinical characteristics of the subjects in this study, including age, sex distribution, age of first SAD episode, GSS, and atypical vegetative symptoms, are similar to samples of patients with SAD studied previously (Oren and Rosenthal, 1992). Although HAM-D and MADRS cannot be directly compared, the severity of depression in our sample (mean MADRS 18.2, SD 5.7) seems to be within the same range as in the above referred studies (mean HAM-D score: 15-20). In the present study, 52% of the patients showed > 50% reduction in extended MADRS score after 6 days of light treatment with 1500 lux. In another study using the same illumination, ThalCn et al. (1995) found that 53% of the patients showed more than 50% reduction in HAM-D score after 10 days of treatment. These response rates are somewhat lower than found in the review by Terman et al. (1989) where 66% of the patient showed > 50% reduction in HAM-D after receiving 1 week of 2500 lux morning light therapy. Some evidence indicate that increasing illumination can improve the efficacy of light therapy (Lam, 1996), but no clear-cut doseresponse relationship has been found for this type of treatment. Although Terman et al. (1989) found that response to light therapy typically occurs within 3 or 4 days, more recent studies indicate that extending the length of treatment could increase response rates. Bauer et al. (19941, found that significant reduction in HAM-D + seasonal supplement occurred between 2 and 4 weeks of light treatment, and both Labbate et al. (1996) and Lam (1996) have reported significantly better outcome after 2 weeks of phototherapy compared to 1 week. We can therefore not rule out that increasing the illumination or extending the length of treatment beyond 1 week would have influenced our results. In a study where patients with SAD were given the opportunity to determine themselves when to discontinue light therapy, Partonen and Lonnqvist (1995) found that patients with comorbid avoidant
PD chose to use light therapy significantly longer than the rest. This could indicate that these patients respond less well to phototherapy, and therefore require longer treatment duration. This would be in accordance with our findings in the present study. The fact that treatment was given in a specially equipped room in our hospital where up to 10 people were treated simultaneously, makes it possible that group processes could have influenced treatment outcome. We can not rule out that this setting could have affected subjects with personality disorders, especially avoidant PD, differently from the rest of the patients. Personality disorder assessment have been shown to be dependent on both the method used, and the mood state at the time of assessment (Zimmerman, 1994). The fact that MADRS at baseline was significantly associated with total number of positive DSM-III-R criteria for all clusters, and for avoidant PD, indicate that these measures are influenced by the depressive state. In a recent study of patients with SAD. including the patients in this sample (Reichborn-Kjennerud et al., in press). we found that total dimensional score (number of positive DSMIll-R criteria as assessed with PDQ-R) for all clusters together (A, B and C) was significantly lower in the euthymic state than during the depressive episode. Total score for all cluster C disorders, and for avoidant PD was also lower after remission, but this reduction was not statistically significant. Significant reduction in the frequency of cluster C personality disorders has, however, been found in patients with non-seasonal MDD who have recovered from depression (Peselow et al., 1994), and Partonen and Lonnqvist (1995) reported that in patients with SAD, the severity of symptoms of comorbid avoidant PD was reduced simultaneously with the improvement in the severity of the depressive episode by bright light treatment. We also found that score on the HA scale was significantly associated with MADRS at baseline. HA score, but not NS- and RD score, have been shown to be influenced by the depressive state in patients with non-seasonal MDD (Svarakic et al., 1992). In an unpublished study, we found that HA score was significantly lower in patients with SAD after remission of the depressive symptoms. The PD and temperament measures found to be related to
treatment response in the present study thus seem to be state dependent. Whether the same variables measured in a euthymic state would predict outcome in the same way, is a theoretically interesting question that should be addressed in future studies. In clinical settings, however, the choice of treatment strategies are usually made at a time when the patient is in a depressed state, and our study, like most previous studies of this kind (Ilardi and Craighead. 1995; Joffe et al., 1993; Joyce et al., 1994). was therefore carried out at this point in time. Self-report inventories for assessment of PDs have been shown to generate more categorical DSM-III-R axis II diagnoses than structured interviews (Zimmerman, 1994). The prevalence of personality disorders for patients with SAD previously reported by our group (Reichborn-Kjennerud et al.. 1994) were obtained using a structured interview (SIDP-R: Pfohl et al., 1989), when the patients were in a euthymic state. Although we found significant correlations between dimensional scores obtained with PDQ-R and SIDP-R administered to a sample of SAD patients in a non-depressed state (ReichbornKjennerud et al.. in press), the prevalence of categorical PD diagnoses was considerably higher with the use of PDQ-R. For clinical purposes. however. a self-report inventory which is easy to administer and score, has an advantage compared to structured interviews. PDQ-R has previously been shown to be useful in predicting treatment outcome for other axis I disorders (Reich and Green. I99 i 1. and was therefore chosen in this study. The fact that our results with the use of categorical and dimensional measures of PDs are discrepant. is probably due to the small sample size. making all results subject to considerable fluctuations. and thus increasing chances of both type I and type II errors. According to the theory of Cloninger (1987), individual DSM-III-R personality disorders, and personality disorder clusters, reflect underlying temperament as measured by the TPQ. In patients with non-seasonal MDD. HA score has been found to correlate positively with number of positive DSMIII-R criteria in cluster C. and with avoidant and self-defeating PD (Mulder et al.. 1994). The personality disorder and temperament variables found to be related to light therapy response in this study were all significantly interrelated with high positive re-
T. Reichborn-Kjennerud, 0. Lingjmde/.Iournal
gression coefficients, suggesting that they might be different manifestations of a common disposition. In studies on short-term response to antidepressant medication in patients with non-seasonal MDD (Ilardi and Craighead, 19951, the presence of a DSM-III-R axis II disorder was found to be associated with less favorable outcome, and cluster C disorders were associated with poor treatment response in the majority of studies of outpatients. The presence of avoidant and dependent PD were also identified as predictictors of poor treatment response. Joffe et al. (19931, in a study of patients with non-seasonal MDD, found that non-responders to treatment with TCA had significantly higher mean score on the HA scale of the TPQ than responders. In the present study we found that the presence of any DSM-III-R axis II disorder, any cluster C PD, and a diagnosis of avoidant PD, predicted poor response to phototherapy in patients with SAD. We also found that non-responders had significantly higher score on the HA scale. Our results thus indicate that the personality disorder and temperament factors that predict poorer response to antidepressant medication in patients with non-seasonal MDD, also predict poorer response to light treatment in patients with SAD.
Acknowledgements The study was supported by grants from Sommer’s Foundation, Haldis and Josef Andresen’s Legacy, and Gaustad Hospital Research Fund.
References Avery, D.H., Kahn, A., Dager, S.R., Cohen, S., Cox, G.B. and Dunner, D.L. (1991) Morning or evening bright light treatment of winter depression? The significance of hypersomnia. Biol. Psychiatry 29, 117-126. Bauer, M.S., Kurtz, J.W., Rubin, L.B. and Marcus, J.G. (1994) Mood and behavioral effects of four-week light treatment in winter depressives and controls. J. Psychiatr. Res. 28, 135-145. Brown, W.A. (1990) Is light treatment a placebo? Psychopharmacol. Bull. 26, 527-530. Cloninger, CR. (1987) A systematic method for clinical description and classification of personality variance: a proposal. Arch. Gen. Psychiatry 44, 573-588. Cloninger, C.R., Przybeck, T.R. and Svarakic, D.M. (1991) The
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Tridimensional Personality Questionnaire: US normative data. Psychol. Rep. 69, 1047-1057. Eastman, CL, Young, M.A., Fogg, L.F. and Liu, L. (1996) Light therapy for winter depression is more than a placebo. Sot. Light Treatment Biol. Rhythms Abst. 8, 5. Hamilton, M. (1967) Development of a rating scale for primary depressive illness. Br. J. Sot. Clin. Psycho]. 6, 278-296. Hyler, S.E. and Rieder, R.O. (1987) PDQ-R: Personality Diagnostic Questionnare- Revised. New York State Psychiatric Institute, New York, NY. Hyler, S.E., Skodol, A.E.. Oldham, J.M., Kellerman, D.H. and Doidge, N. (1992) Validity of the Personality Diagnostic Questionnaire-Revised: A replication in an outpatient sample. Compr. Psychiatry 33, 73-77. Ilardi, S.S. and Craighead, W.E. (1995) Personality pathology and response to somatic treatments for major depression: a critical review. Depression 2, 200-2 17. Joffe, R.T., Bagby, R.M., Levitt, A.J., Regan, J.J. and Parker, J.D.A. (1993) The Tri-dimensional Personality Questionnaire in major depression. Am. J. Psychiatry 150, 959-960. Joyce, P.R. and Paykel, E.S.(1989) Predictors of drug response in depression. Arch. Gen. Psychiatry 46, 89-99. Joyce, P.R., Mulder, R.T. and Clononger CR. (1994) Temperament predicts clomipramine and desipramine response in major depression. J. Affect. Disord. 30, 35-46. Kriiuchi, K., Wirz-Justice, A. and Craw, P. (1993) High inntake of sweets late in the day predicts a rapid and persistent response to light therapy in winter depression. Psychiatry Res. 46, 107-l 17. Labbate, L.A., Lafer, B., Thibauh, A., Rosenbaum, J.F. and Sachs, G.S. (1996) Influence of phototherapy treatment duration for seasonal affective disorder: outcome at one vs. two weeks. Biol. Psychiatry 38, 747-750. Lam, R.W. (1994) Morning light therapy for winter depression: predictors of response. Acta. Psychiatr. Stand. 89, 97-101. Lam, R.W. (1996) Optimal light treatment for seasonal depression. Paper present ed at the CME course, 8th annual meeting, Sot. Light Treatment Biol. Rhythms, Bethesa, MD. Lilie, J.K., Lahmeyer, H.W., Watel. L.C. and Eastman, C.I. (1990) The relation of personality to clinical outcome in SAD. Sot. Light Treatment Biol. Rhythms Abst. 2, 213. Lingjaerde, 0.. Reichborn-Kjennerud, T., Haggag, A., Glrtner, I., Berg, E.M. and Narud, K. (I 993) Treatment of winter depression in Norway I. Short- and long-term effects of 1500.lux white light for 6 days. Acta Psychiatr. Stand. 88, 292-299. Meesters, Y., Jansen, J.H.C., Lamberts, P.A., Bouhuys, A.L., Beersma, D.G.M. and van den Hoofdakker, R.H. (1993) Morning and evening light treatment of seasonal affective disorder: response, relapse and prediction. J. Affect. Disord. 28, 165-177. Montgomery, S.A. and Asberg, M. (1979) A new depression scale designed to be sensitive to change. Br. J. Psychiatry 134, 382-389. Mulder, R.T., Joyce, P.R. and Cloninger, C.R. (1994) Temperament and early environment influence comorbidity and personality disorders in major depression. Compr. Psychiatry 35, 225-233.
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Nagayama. H.. Sasaki, M., Ichii, S., Handa, K., Okawa, M.. Otha, T., Asano, Y., Sugita. Y.. Yamazaki, J., Kohsaka, M., Kotorii, T.. Maeda. K., Okamoto, N.. Ishizuka, Y., Takahashi, K., Honda. Y. and Takahashi, S. (1991) Atypical depressive symptoms possibly predict responsiveness to phototherapy in seasonal affective disorder. J. Affect. Disord. 23, 185- 189. Oren. D.A., and Rosenthal. N.E. (1992) Seasonal affective disorders. In: Pnykel. E.S. (Ed.), Handbook of Affective Disorders. Churchill-Livingstone. London. pp. 55 l-567. Orcn. D.A.. Jacobsen. F.M., Wehr, T.A., Cameron. C.L. and Rosenthal. N.E. (1992) Predictors of response to phatotherapy in seasonal affective disorder. Compr. Psychiatry 33, I I I-I 14. Partonen, T. and Lonnqvist, J. (1995) The influence of comorbid disorders and of continuation light treatment on remission and recurrence in winter depression. Psychopathology 28. 256-262. Peselow, E.D., Sanfiiipo. M.P.. Fieve, R.D. and Gulbenkian. G. (1994) Personality traits during depression and after recovery. Br. J. Psychiatry 164. 349-354. Pfohl, B.. Blum. N.. Zimmerman, M. and St&, D. (19X9) Structured Interview for DSM-III-R Personality, SIDP-R. Department of Psychiatry, Universty of Iowa. Iowa City. Iowa. IA. Reich. J.H. and Green. 4.1. (199 I ) Effect of personality disorders on outcome of treatment. J. Nerv. Ment. Dis. 179. 74-82. Reichborn-Kjennerud, T.. Lingjaerde, 0. and Dahl, A.A. (1994) Personality disorders in patients with winter depression. Acta Psychiatr. Stand. 90, 4 13-419. Reichborn-Kjennerud, T.. Lingjierde. 0. and Dahl. A.A. (1996) DSM-III-R personality disorders in seasonal affective disorder: change associated with depression. Compr. Psychiatry, in press. Rosenthal. N.E. and Wehr. T.A. (1992) Towards understanding the mechanosms of action of light in seasonal affective disorder. Pharmacopsychiatry 25, 56-60.
of Qjec‘fil,e Disorders
41 (19%)
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Rosenthal. N.E. Sack. D.A., Gillin, C.. Lewy. A.J.. Goodwin, F.K., Davenport, Y., Mueller. P.S.. Newsome, D.A. and Wehr. T.A. (19841 Seasonal affective disorder. A description of the syndrome and preliminary findings with light therapy. Arch. Gen. Psychiatry 4 I, 72-80. Stinson. D. and Thompson, C. (1990) Clinical experience with phototherapy. J. Affect. Disord. 18. 129-135. Svardkic. D.M., Przybeck, T.R. and Cloninger. C.R. (1992) Mood states and personality traits. J. Affect. Disord. 24. 2 17-226. Terman. M. and Terman. J.S. (1996) A multi-year controlled trial of bright light and negative ions. Sot. Light Treatment Biol. Rhythms Abst. 8. I. Terman. M.. Terman, J.S.. Quitkin. F.M.. McCrath. P.J., Stewart. J.W. and Rafferty, B. (1989) Light therapy for seasonal affective disorder. A review of efficacy. Neuropsychopharmacolozy 2. I -2~. Terman, M.. Terman. J.S. and Amird. L. ( 1992)Light-refractor) v’s, light-responsive SAD patients: depression scale predictors. Sac. Light Treatment Biol. Rhythms Ahst. 4. 1X. ThaIen. B.-E., Kjellman, B.F.. Morkrid. L.. Wibom, R. and Wetterberg, L. (I 995) Light treatment in seasonal and nonseasonal depression. Actn. Psychiatr. Stand. 91. 352-360. Trull. T.J. and Goodwin. A.H. (I 993) Relationship between mood changes and the report of personality disorder symptoms. J. Pers. Assess. 61. 99-l I I. Williams, J.B.W.. Link, M.J., Rosenthal. N.E. and Terman. M. (1992) Structured interview guide for the Hamtlton Depression Rating Scale, seasonal affective disorders version (SIGHSAD). New York State Psychiatric Institute. New York. Zimmerman. M. (1994) Diagnosing personnlity dwrders. A trview ot issues and research mcrhods. Arch. Gcn. Psychiatry 5 I. 25 -215.
ELSEVIER
Journal of Affective Disorders 41 ( 1996) 101- 110
OF
A.FFEClTIVE DISORDERS
Research report
Response to light therapy in seasonal affective disorder: personality disorders and temperament as predictors of outcome Ted Reichborn-Kjennerud Department
of Psychiatry,
*, Odd Lingjaxde
Unicersity of Oslo, Gaustad Hospital, P.O. Box 33, Gaustad, N-0320 Oslo, Norway
Received
16 April 1996; revised 8 July 1996; accepted 8 July 1996
-~~ Abstract Outcome after 6 days of morning light therapy in subjects fulfilling criteria for winter seasonal affective disorder (SAD) was examined. Responders had significantly fewer previous episodes of SAD, Patients with a diagnosis of any DSM-III-R, axis II personality disorder, were significantly less likely to respond to light therapy than patients without axis II pathology. Poor treatment outcome was also significantly associated with: one or more personality disorders in cluster C, avoidant personality disorder, high number of positive criteria for self-defeating personality disorder and high score on the harm avoidance scale of the Tridimensional Personality Questionnaire. Temperament accounted for 25% of the variance in treatment outcome.
1. Introduction Bright artificial light has been shown to be an effective treatment for winter seasonal affective disorder (SAD), a syndrome characterized by recurring seasonal changes in mood, sleep pattern, social activity, appetite and energy (Rosenthal et al., 1984). The pathophysiology of the disorder and the mechanisms of action of light therapy are still not well understood. Various hypotheses have been proposed, suggesting disturbances in, e.g., circadian rhythms and neurotransmitter systems (see Rosenthal and Wehr, 1992). In a review of data from 14 research centers, Terman et al. (1989) found a response rate (> 50%
* Corresponding 923-82 1.
author.
Tel.: (47-22)
0165-0327/96/$15.00 Copyright PII SO 165-0327(96)00076-6
923.400;
Fax: (47-22)
reduction in depression scale score> of 66% to 1 week of morning light therapy in patients with SAD. Although subsequent studies have confirmed the efficacy of phototherapy (Oren and Rosenthal, 19921, there has been some controversy regarding the placebo effect in this form of treatment (Brown, 1990). Recently, however, two well-designed studies have clearly demonstrated the superiority of bright light over placebo (Eastman et al., 1996; Terman and Terman, 1996). Several attempts have been made to determine the characteristics of patients who respond to light treatment (Stinson and Thompson, 1990; Avery et al., 1991; Nagayama et al., 1991; Terman et al., 1992; Oren et al., 1992; Meesters et al., 1993; Krluchi et al., 1993; Lam, 1994). The results, however, have been inconsistent. Variables found to be positively correlated with favorable response to phototherapy in
0 1996 Elsevier Science B.V. All rights reserved.
one or more of these studies include: severity of atypical vegetative symptoms, hypersomnia, hyperphagia, carbohydrate craving, high intake of sweets late in the day, young age, diurnal variation of depressive symptoms and suicidality. Severity of pretreatment typical depressive symptoms, measured as score on the Hamilton Depression Rating Scale (HAM-D) (Hamilton, 1967), has been found to be both negatively (Stinson and Thompson, 1990; Terman et al., 1992) and positively correlated with outcome (Oren et al.. 1992; Meesters et al., 1993). To our knowledge, no systematic study of the relationship between personality and response to phototherapy in SAD has been published. However, in a short report, Lilie et al. (1990) concluded that in a sample of patients with SAD. subjects without axis II psychopathology were more likely to be bright light responders and to fully remit in summer. Personality traits and disorders have been found to influence response to somatic treatments in patients with non-seasonal major depressive disorder (MDD; Ilardi and Craighead, 1995). Temperament, as defined by Cloninger (I 987), with three genetically determined dimensions called ‘novelty seeking’ (NS), ‘harm avoidance’ (HA) and reward dependence (RD), have also been shown to predict outcome of antidepressant treatment for non-seasonal MDD (Joffe et al., 1993; Joyce et al., 1994). The present study was designed to examine DSMIII-R personality disorders (PD) and temperament, as defined by Cloninger, as possible predictors of response to light therapy in patients with SAD. We also evaluated several demographic and clinical variables, some of which have previously been found to be related to outcome of light treatment.
sion. Only patients recruited the first year (n = 33) were included in the part of the study concerning personality disorders and temperament (see below). The subjects were either recruited through the mass media, or referred to our unit by the health care system. They were first screened with the Seasonal Pattern Assessment Questionnaire (SPAQ; Rosenthal et al.. 1984). then interviewed by one of the authors, both experienced psychiatrists, using a semistructured interview, before being included, as previously described (Lingjjaerde et al.. 1993). All patients also fulfilled the DSM-III-R criteria for major depressive disorder, recurrent, seasonal pattern. Patients with psychotic symptoms. severe suicidal ideation. current alcohol or drug abuse, or significant somatic illness were excluded from the study. None of the patients had received antidepressant medication for at least 2 weeks before starting phototherapy. and none had received t’luoxetine, which could have intluenced treatment outcome more than 2 weeks after discontinuation. 2.2. Trerrttnent
2. I. Sul7ject.s
Light treatment was given for 6 consecutive days (Monday to Saturday) for 2 h each morning within the time period 07:OO am. to 1 I:00 a.m. in a specially equipped room in which up to IO patients (usually 5 to 6) could be treated simultaneously. Full-spectrum white light. giving an illuminance of about 1500 lux at eye level, was used. Treatment was offered from the end of November to the beginning of February (Lingjazrde et al., 1993). Our sample also include four patients who received treatment for only I h daily. The clinical characteristics at baseline for these subjects were not significantly different from the rest of the patients. We have, in this and subsequent trials, not found any significant difference in response rates between treatment for I and 2 h (unpublished observation).
The 42 subjects in this sample participated in a treatment study of winter depression at the University of Oslo, Gaustad Hospital. They represent all patients in two consecutive winters (1991/92 and 1992/93) who satisfied the criteria for SAD according to Rosenthal et al. (1984), and who received light therapy as the only treatment for their winter depres-
Before starting therapy (baseline), all patients were rated on the Montgomery Asberg DepLession Rating Scale (MADRS; Montgomery and Asberg. 1979) extended with four items: increased sleep, increased appetite. carbohydrate craving. and fatiguability. All
2. Methods
T. Reichbom-Kjennerud,0. Lingjwde/Joumal of &ffecriceDisorders41 (19961 101-I IO
items were rated on a scale from 0 to 6. Follow-up registrations were done 1, 3, 6, 10 and 14 weeks after beginning of treatment. From SPAQ was derived the Global Seasonality Score (GSS), a measure reflecting the sum of ratings for seasonal variation in 6 areas: sleep length, social activity, mood, weight, appetite and energy level. The 33 patients who were included in the study the first winter, all completed self-report questionnaires to assess DSM-III-R personality disorders and temperament before starting treatment. There were no significant differences between this group and the 9 new inclusions the second year (who did not receive these questionnaires) with regard to age, age at first episode of SAD, number of previous episodes of SAD, depression score at baseline (original MADRS and extended version) or response to treatment. Personality disorders were assessed by the Personality Diagnostic Questionnaire-Revised (PDQ-R), a 152-item, self-administered, true/false questionnaire designed to assess personality disorder diagnosis consistent with the DSM-III-R criteria (Hyler and Rieder, 1987). Compared to structured interviews, this instrument has been shown to have high sensitivity and moderate specificity for most axis II disorders (Hyler et al., 1992), and the reliability of the scores has been found to be similar to those derived from interviews in a 6 months followup study of patients with MDD (Trull and Goodwin, 1993). Temperament was assessed with the Tridimensional Personality Questionnaire (TPQ; Cloninger et al., 1991). 2.4. Statistical analyses SPSS for Windows, release 6.0, was used for statistical analyses. Two methods, commonly used in this type of studies, were employed to examine predictors of response. First, we defined non-responders as patients having a pre- to posttreatment extended MADRS score reduction < 30%, thus using a relative improvement criterion analogous to that used by Terman et al. (1992), and Meesters et al. (1993). Responders were defined as patients showing 2 50% reduction in extended MADRS score in the same period. The two groups were then compared with respect to the relevant variables, using t-tests or Mann-Whitney/Wilcoxon rank-sum
103
tests for continuous variables, and chi square test for categorical variables. In the second approach, outcome as a continuous measure, defined as percentage reduction in extended MADRS score from baseline to the end of the treatment period (1 week after beginning of therapy), was used as dependent variable in bivariate and multivariate linear regressions with possible predictors. Using relative reduction in extended MADRS instead of absolute differences make the results less dependent on baseline scores. By also using outcome as a continuous variable, disadvantages of arbitrary cutting points are avoided. A significance level of P = 0.05was chosen.
3. Results
3. I. Responders
us. non-responders
Table 1 shows data on demographic and clinical variables for the total sample and for the non-responder and responder groups separately. Twentytwo patients (52%) were classified as responders and 8 (19%) as non-responders. The mean reduction in extended MADRS score was 51% for the whole sample, 72% for the responders and 11% for the non-responders. The only statistically significant difference between the groups was that responders reported fewer previous episodes of SAD (P = 0.05, Mann-Whitney/Wilcoxon). Scores on MADRS at baseline were higher for the non-responders, but this difference was not significant (P = 0.09, two-tailed t-test>. Prevalences for DSM-III-R personality disorders, including self-defeating PD, are given in Table 2. None of the patients satisfied criteria for antisocial or narcissistic PD. Sixty-one percent of the sample fulfilled criteria for one or more axis II diagnosis. Disorders in cluster C occurred most frequently (48%). The number of patients with any PD in cluster A, B or C, was significantly higher among the non-responders (P < 0.05, chi-square test) than the responders. Any PD in cluster C also occurred more frequently among the non-responders (P < 0.05, chi-square test). Of the specific disorders, only avoidant PD was significantly more prevalent in the non-responder group (P = 0.001, chi square test).
104 Table 1 Demographic
T. Reichborn-Kjmnenld,
and clinical characteristics
0. Lingjerde
/ Journul
for total sample, non-responders,
of Afccrire
Disorders
and responders
41
f I9961lOI- I IO
to 6 days of light therapy
Total sample (n = 42)
Non-responders (a = 8)
38 (90) 4 (IO) 43.4 + 10.2
7 (87) I(131 45.8 * x.1
’
Responders (rt = 22)
h
Sex,
IL (%) - Female
- Male Age, mean + SD Marital status, n (7~) - Married, cohabiting - Single Lifetime diagnosis MDD. n (%) - Unipolar - Bipolar II
21 (95) I (5) 13.5 * 1 I.‘)
22 (52) 20 (48)
4 (501 4 (50)
I I (SO) 11(SO)
38 (90) 4 (101
8 (100) 0
19 (86) 3(13)
Age at first SAD episode, mean f SD Previous SAD episodes. mean f SD
24.8 + 10.1 15.7 f 8.8
22.4 f 10.0 20.5 f 6.8 L
24.9 + I 1.0 IS.1 5 10.0
GSS, mean k SD
15.6 + 2.8
16.0 k 3.2
15.8 * 2.4
Suicide attempt during SAD, n (%‘c) Suicidal thoughts during SAD, n (%)
5 (12) 37 (88)
Depression scale score, mean + SD MADRS (pretreatment) MADRS (posttreatment) Extended MADRS (pretreatment) Extended MADRS (posttreatment)
18.2 9.5 28.5 14.4
Atypical symptoms score (pretreatment), mean + SD Hypersomnia Hyperphagia Carbohydrate Fatiguability
5.7 1.4 6.7 9.5
2.5 2.2 2.7 2.9
f + f +
f + + +
2 (9) 13 (SO)
5.3 5. I 7.8 1.4
11.1 +4.4
1.8 1.6 1.5 1.2
2.6 2.4 2.6 3.5
i + i f
2.1 1.8 1.7 1.1
17.1 3.5 27.8 8.0
* * * *
5.7 3.8 6.8 5.1
10.1 + 3.8 2.6 2.5 2.8 2.8
+ + + F
I.7 1.4 1.5 1.3
< 30% after 6 days of light therapy. 2 50% after 6 days of light therapy. rank sum test.
Table 3 shows scores on the TPQ subscales. The non-responders had significantly higher scores on the HA scale than the responders (P < 0.001, two-tailed t-test). 3.2. Treatment
21.3 20.1 32.5 28.9
10.3 * 3.9
craving
a Reduction in extended MADRS score h Reduction in extended MADRS score P = 0.05 by Mann-Whitney/Wilcoxon
f i f f
2 (25) 5 (63)
outcome as a continuous
variable
3.2.1. Demographic and clinical variables as predictors of outcome In bivariate regression analyses with treatment outcome (continuous) as dependent variable, we examined the following variables as potential predictors: sex (f or m), age (continuous), marital status
(single or married/cohabiting), lifetime diagnosis MDD (unipolar or bipolar II), age at first episode of SAD (continuous), number of previous episodes of SAD (continuous), GSS (continuous), suicide attempts during previous episodes of SAD (yes or no>, suicidal thoughts during previous episodes of SAD (yes or no), MADRS and extended MADRS at baseline (continuous), hypersomnia, hyperphagia, carbohydrate craving, fatiguability (O-6), total score for all atypical symptoms (continuous) and atypical balance (sum score for the four atypical symptoms in percent of extended MADRS). None of the results were statistically significant. There were trends to-
T. Reichborn-Kjennerud, 0. Lingjcerde / Journal of Affectiur Disorders 41 (1996) IOI- 110 Table 2 Prevalence
of DSM-III-R
personality
disorders
for total sample, non-responders,
Total sample (n = 33) n
and responders a
Responders (n = 18)
8
n
%
n
%
1
6 1
6 11 6 6 33 6
3 4
17 22
1
6
1 3 6 6 8
6 17 33 33 = 44 *
4 5 3 3 8 7
12 15 9 9 24 21
2 1 2 2 5
25 13 13 25 25 63 **
Dependent Obsessive Compulsive
5 7
15 21
0 2
25
Passive Aggressive
3
9
0
6 9 10 16 20
18 27 30 48 61
2 3 4 6 I
A B C A,
to 6 days of light therapy
Non-responders (II = 8)
Paranoid Schizoid Schizotypal Borderline Histrionic Avoidant
Self-defeating Any Cluster Any Cluster Any Cluster Any Cluster B or C
105
I
25 38 50 75 * 88 *
b
2
1 I
*I
a Reduction in extended MADRS score < 30% after 6 days of light therapy. h Reduction in extended MADRS score z 50% after 6 davs . of light . therapy. * P = 0.049, xZ test, * * P = 0.001, x’ test.
wards negative regression on outcome for scores on both MADRS scales ( p = -0.26, P = 0.09). As no variable showed any significant regression with treatment outcome, no multiple regression analyses combining variables was performed. 3.2.2. Personality disorders as predictors of outcome The following variables were used as independent variables in bivariate regression analyses with treatTable 3 Tridimensional non-responders,
personality questionnaire scores for total sample, and responders to 6 days of light therapy Total sample
Novelty seeking Harm avoidance Reward dependence
Nonresponders
Responders
(n = 33) mean f SD
(n = 8) mean f SD
(n= 18) mean + SD
16.5+5.0 19.656.3 17.8 + 4.4
14.5k5.1 25.6k4.0 16.8 + 3.6
17.2 + 5.2 18.2+3.9 * 18.6f3.1
a Reduction in extended MADRS light therapy. b Reduction in extended MADRS lighttherapy. * P < 0.001, two-tailed t-test.
’
’
*
score
< 30% after 6 days of
score
> 50% after 6 days of
ment outcome (continuous) as dependent variable: categorical diagnosis (presence/absence) of any DSM-III-R PD, any PD in each cluster and each specific PD separately, as well as total number of PDs and number of PDs in each of the clusters and dimensional scores (number of positive DSM-III-R criteria) for each PD, each cluster, and all clusters together. As shown in Table 4, the presence of any DSMIII-R PD diagnosis (compared to none) was significantly associated with a negative treatment outcome ( p = - 0.44, P = 0.0 1). This variable explained 17% of the variance in outcome (adjusted r’ = 0.17). Patients without any axis II co-morbidity had a mean
Table 4 Regression coefficients for DSM-III-R personality treatment outcome after 6 days of light therapy
disorders
n = 33
P
P
-0.20 -0.20 - 0.36 -0.44
0.25 0.27 0.04 0.01
Any Any Any Any
cluster cluster cluster PD in
A diagnosis B diagnosis C diagnosis cluster A, B or C
on
response rate of 68%, whereas patients with one or more PD diagnosis had a response rate of 41%. The presence of any cluster C PD also predicted worse outcome ( p = -0.36, P = 0.04, adjusted I’ = 0. I 1), with response rates of 41% compared to 62% for those without a cluster C diagnosis. Avoidant PD was the only specific axis II diagnosis which showed a significant relationship with treatment outcome ( p = -0.46, P = 0.007). Patients with avoidant PD had a mean response rate of only 26%, compared to 59% for those without avoidant PD. This variable alone explained 19% of the variance in outcome (adjusted r’ = 0.19). When number of positive DSM-III-R criteria were considered as dimensional predictors, score for self-defeating PD was the only measure significantly related to outcome (p = - 0.36. P = 0.04). Personality disorder measures were not significantly related to sex, age at first SAD episode, or number of previous winter depressions. MADRS at baseline was significantly related to both total number of positive DSM-III-R criteria in all clusters ( p = 0.36, P = 0.04) and dimensional scores for avoidant PD ( p = 0.50, P = 0.003). Dimensional measures of all personality variables associated with outcome were highly interrelated with regression coefficients ranging from 0.89 (total score in all clusters with total score in cluster C) to 0.53 (avoidant PD with total score in cluster C). 3.2.3. Temperament as predictor of outcome The results of bivariate regression analysis with the TPQ scales on treatment outcome are given in Table 5. Total score on the harm avoidance scale showed a significant negative relationship with the response to light therapy ( p = -0.36, P = 0.04, adjusted Y’ = 0. IO). All HA subscale scores were negatively associated with outcome, but only HAI (anticipatory worry) showed a significant relationship ( p = -0.36, P = 0.04). The lowest regression coefficient was found for RD2 (persistence), a trait which may be inherited separately from the other aspects of reward dependence. Cloninger (1987) postulates the existence of 8 temperament types based on the combination of the three temperament scales. with each measure dichotomized as high or low. We therefore divided the three scales at the means for this sample (NS 17/ 16,
Table 5 Regression coefficients for the tridimensional personality questionnaire scales and subscales on treatment outcome after 6 days of light therapy 33
B
P
Novelty seeking total NS I : (exploratory excitability) NS2: (impulsiveness) NS3: (extra\apance) NS3: (disorderliness)
0.20 0.28 0.0 I 0.33 - 0.06
0.26 0. I I 0.93 0.07 0.72
Harm avoidance total HA I : (anticipatory worry) HA2: (fear of uncertainty) HA3: (shyness with strangers) HA4: ifatiguahility)
- 0.36 ~ 0.36 -0.16 - 0.33 - 0.26
0.01 0.04 0.38 0.06 0. IS
n=
Reward dependence RDI: (sentimentality) RD2: (persistence) RD3: (attachment) RD4: (dependence)
total
0. I I 0.03 0.00 0. IO 0. IS
0.55 0.X6 I .oo 0.60 0.40
HA 16/17, RD 17/16). Patients with high HA had a response rate of 38% compared to 66% for those with low HA. Regression with the dichotomized HA variable explained 19% of the variance in outcome ( p = - 0.46, P = 0.007, adjusted r’ = 0.19). Multiple regression with all three dichotomized variables explained 22% of the variance in outcome (adjusted r’ = 0.22, P = 0.02). Analysis of variance (ANOVA) with the three dichotomized variables showed no significant interactions. There was a weak trend towards a 2-way interaction between HA and RD (P = 0.14). Multiple regression with all 8 temperament types explained 25% of the variance in treatment outcome (adjusted r2 = 0.25, P = 0.04). Temperament was not significantly related to age, age at first SAD episode, or number of previous winter depressions. There was a significant relationship between HA and MADRS at baseline ( /3 = 0.35, P = 0.046) and between RD and sex (fi = 0.35, P = 0.044). Harm Avoidance, total score. was significantly associated with dimensional scores for all PD measures associated with outcome: i.e., number of positive criteria in all clusters ( /3 = 0.54, P = O.OOl), in cluster C (/3 = 0.50, P = 0.003) for avoidant PD
T. Reichborn-Kjennerud,
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(p = 0.56,P = 0.001) and for self-defeating P = 0.002).
PD
( p = 0.53,
4. Discussion The only demographic or clinical variable for which there was a significant (P = 0.05) difference between responders and non-responders to light therapy in this sample, was number of previous SAD episodes. Considering the number of variables tested, this relationship is weak, and would not be significant if a Bonferroni correction had been employed. High number of previous episodes has been found to predict poorer response to tricyclic antidepressants (TCA) in patients with non-seasonal MDD (Joyce and Paykel, 1989), but has not been examined as a predictor of response to light treatment in other studies of patients with SAD. In contrast to previous studies of predictors of response to light therapy, we failed to identify any clinical variable at baseline as significantly associated with outcome as a continuous variable. Although the size of our sample (n = 42) is larger than in 4 of the 8 studies referred to in the introduction, our negative results could be the result of low statistical power (type II error). Pretreatment score on the g-item atypical depressive symptom addendum included in the Structured Interview Guide for the Hamilton Depression Inventory, Seasonal Affective Disorder Version (SIGHSAD; Williams et al., 1992), has been found to correlate positively with outcome in four studies (Terman et al., 1992; Nagayama et al., 1991; Oren et al., 1992; Lam, 1994). This measure includes social withdrawal, weight gain, increased appetite, increased eating, carbohydrate craving or eating, hypersomnia, fatiguability, and slump in mood or energy in the evening or afternoon. Our scoring of atypical symptoms included only 4 of these items: appetite increase, carbohydrate craving or eating, hypersomnia, and fatiguability, and can therefore not be directly compared to these studies. Neither of the items by themselves, however, were significantly associated with outcome. We could thus not confirm earlier reports indicating that the presence of hypersomnia (Avery et al., 1991; Oren et al., 1992; Lam, 1994), hyperphagia (Oren et al., 1992; Lam, 1994),
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or carbohydrate craving (Oren et al., 1992) was associated with a favorable treatment response. Because treatment outcome could be influenced by sample differences in demographic and clinical variables, and treatment methods including duration of therapy and light sources used, it is relevant to comment on these issues. The demographic and clinical characteristics of the subjects in this study, including age, sex distribution, age of first SAD episode, GSS, and atypical vegetative symptoms, are similar to samples of patients with SAD studied previously (Oren and Rosenthal, 1992). Although HAM-D and MADRS cannot be directly compared, the severity of depression in our sample (mean MADRS 18.2, SD 5.7) seems to be within the same range as in the above referred studies (mean HAM-D score: 15-20). In the present study, 52% of the patients showed > 50% reduction in extended MADRS score after 6 days of light treatment with 1500 lux. In another study using the same illumination, ThalCn et al. (1995) found that 53% of the patients showed more than 50% reduction in HAM-D score after 10 days of treatment. These response rates are somewhat lower than found in the review by Terman et al. (1989) where 66% of the patient showed > 50% reduction in HAM-D after receiving 1 week of 2500 lux morning light therapy. Some evidence indicate that increasing illumination can improve the efficacy of light therapy (Lam, 1996), but no clear-cut doseresponse relationship has been found for this type of treatment. Although Terman et al. (1989) found that response to light therapy typically occurs within 3 or 4 days, more recent studies indicate that extending the length of treatment could increase response rates. Bauer et al. (19941, found that significant reduction in HAM-D + seasonal supplement occurred between 2 and 4 weeks of light treatment, and both Labbate et al. (1996) and Lam (1996) have reported significantly better outcome after 2 weeks of phototherapy compared to 1 week. We can therefore not rule out that increasing the illumination or extending the length of treatment beyond 1 week would have influenced our results. In a study where patients with SAD were given the opportunity to determine themselves when to discontinue light therapy, Partonen and Lonnqvist (1995) found that patients with comorbid avoidant
PD chose to use light therapy significantly longer than the rest. This could indicate that these patients respond less well to phototherapy, and therefore require longer treatment duration. This would be in accordance with our findings in the present study. The fact that treatment was given in a specially equipped room in our hospital where up to 10 people were treated simultaneously, makes it possible that group processes could have influenced treatment outcome. We can not rule out that this setting could have affected subjects with personality disorders, especially avoidant PD, differently from the rest of the patients. Personality disorder assessment have been shown to be dependent on both the method used, and the mood state at the time of assessment (Zimmerman, 1994). The fact that MADRS at baseline was significantly associated with total number of positive DSM-III-R criteria for all clusters, and for avoidant PD, indicate that these measures are influenced by the depressive state. In a recent study of patients with SAD. including the patients in this sample (Reichborn-Kjennerud et al., in press). we found that total dimensional score (number of positive DSMIll-R criteria as assessed with PDQ-R) for all clusters together (A, B and C) was significantly lower in the euthymic state than during the depressive episode. Total score for all cluster C disorders, and for avoidant PD was also lower after remission, but this reduction was not statistically significant. Significant reduction in the frequency of cluster C personality disorders has, however, been found in patients with non-seasonal MDD who have recovered from depression (Peselow et al., 1994), and Partonen and Lonnqvist (1995) reported that in patients with SAD, the severity of symptoms of comorbid avoidant PD was reduced simultaneously with the improvement in the severity of the depressive episode by bright light treatment. We also found that score on the HA scale was significantly associated with MADRS at baseline. HA score, but not NS- and RD score, have been shown to be influenced by the depressive state in patients with non-seasonal MDD (Svarakic et al., 1992). In an unpublished study, we found that HA score was significantly lower in patients with SAD after remission of the depressive symptoms. The PD and temperament measures found to be related to
treatment response in the present study thus seem to be state dependent. Whether the same variables measured in a euthymic state would predict outcome in the same way, is a theoretically interesting question that should be addressed in future studies. In clinical settings, however, the choice of treatment strategies are usually made at a time when the patient is in a depressed state, and our study, like most previous studies of this kind (Ilardi and Craighead. 1995; Joffe et al., 1993; Joyce et al., 1994). was therefore carried out at this point in time. Self-report inventories for assessment of PDs have been shown to generate more categorical DSM-III-R axis II diagnoses than structured interviews (Zimmerman, 1994). The prevalence of personality disorders for patients with SAD previously reported by our group (Reichborn-Kjennerud et al.. 1994) were obtained using a structured interview (SIDP-R: Pfohl et al., 1989), when the patients were in a euthymic state. Although we found significant correlations between dimensional scores obtained with PDQ-R and SIDP-R administered to a sample of SAD patients in a non-depressed state (ReichbornKjennerud et al.. in press), the prevalence of categorical PD diagnoses was considerably higher with the use of PDQ-R. For clinical purposes. however. a self-report inventory which is easy to administer and score, has an advantage compared to structured interviews. PDQ-R has previously been shown to be useful in predicting treatment outcome for other axis I disorders (Reich and Green. I99 i 1. and was therefore chosen in this study. The fact that our results with the use of categorical and dimensional measures of PDs are discrepant. is probably due to the small sample size. making all results subject to considerable fluctuations. and thus increasing chances of both type I and type II errors. According to the theory of Cloninger (1987), individual DSM-III-R personality disorders, and personality disorder clusters, reflect underlying temperament as measured by the TPQ. In patients with non-seasonal MDD. HA score has been found to correlate positively with number of positive DSMIII-R criteria in cluster C. and with avoidant and self-defeating PD (Mulder et al.. 1994). The personality disorder and temperament variables found to be related to light therapy response in this study were all significantly interrelated with high positive re-
T. Reichborn-Kjennerud, 0. Lingjmde/.Iournal
gression coefficients, suggesting that they might be different manifestations of a common disposition. In studies on short-term response to antidepressant medication in patients with non-seasonal MDD (Ilardi and Craighead, 19951, the presence of a DSM-III-R axis II disorder was found to be associated with less favorable outcome, and cluster C disorders were associated with poor treatment response in the majority of studies of outpatients. The presence of avoidant and dependent PD were also identified as predictictors of poor treatment response. Joffe et al. (19931, in a study of patients with non-seasonal MDD, found that non-responders to treatment with TCA had significantly higher mean score on the HA scale of the TPQ than responders. In the present study we found that the presence of any DSM-III-R axis II disorder, any cluster C PD, and a diagnosis of avoidant PD, predicted poor response to phototherapy in patients with SAD. We also found that non-responders had significantly higher score on the HA scale. Our results thus indicate that the personality disorder and temperament factors that predict poorer response to antidepressant medication in patients with non-seasonal MDD, also predict poorer response to light treatment in patients with SAD.
Acknowledgements The study was supported by grants from Sommer’s Foundation, Haldis and Josef Andresen’s Legacy, and Gaustad Hospital Research Fund.
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