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Psychosomatic Medicine 61:876-882 (1999)
© 1999 American Psychosomatic Society


ORIGINAL ARTICLE

Daily Psychosocial Stressors Interfere With the Dynamics of Urine Neopterin in a Patient With Systemic Lupus Erythematosus: An Integrative Single-Case Study

Christian Schubert, MD, Astrid Lampe, MD, Gerhard Rumpold, MS, Dietmar Fuchs, PhD, Paul König, MD, Emil Chamson, BA and Gerhard Schüssler, MD

From the Departments of Medical Psychology and Psychotherapy (C.S., A.L., G.R., E.C., G.S.) and Internal Medicine (P.K.), University Hospital Innsbruck, and Institute of Medical Chemistry and Biochemistry (D.F.), University Innsbruck, Innsbruck, Austria.

Address reprint requests to: Christian Schubert, MD, Department of Medical Psychology and Psychotherapy, University Hospital Innsbruck, Sonnenburgstrasse 9, A-6020 Innsbruck, Austria. Email: Christian.Schubert{at}uibk.ac.at


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
OBJECTIVE: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by flare-ups, the causes of which are not known. In accordance with new concepts in stress research, this study investigated whether daily psychosocial stressors interfere with immunological processes in SLE. Because such processes are unique to each individual, single-case design using time-series analysis (Box and Jenkins) was applied.

METHODS: A 40-year-old woman with SLE (last flare-up September 1995) was interviewed initially to determine major life events and difficulties (using the Life Events and Difficulties Schedule) in the previous 2 years. She was then observed for 63 days. Urine neopterin, an immunological parameter demonstrated to parallel disease activity in SLE patients, was measured in daily overnight urine. Daily incidents were identified weekly by the Incidents and Hassles Inventory and independently rated. Intervening factors, including infections, medication, and lifestyle, were controlled.

RESULTS: Retrospectively, data obtained from the Life Events and Difficulties Schedule indicated that major life events and difficulties had preceded the patient’s last flare-up in 1995. Although there were no clinical signs of SLE during this prospective study of 63 days, cross-correlational analyses revealed that "moderately" stressful incidents associated with higher levels of emotional irritation (lag 0: +0.271, p < .05) predicted an increase in urine neopterin the following day (lag 1: +0.441, p < .05). Moreover, a 7-day cyclicity in neopterin levels that corresponded to the weekly examinations and interviews was found.

CONCLUSIONS: This study showed a causal relationship between psychosocial stressors and urine neopterin concentrations that may be related to SLE disease activity. Furthermore, the workability of an integrative approach using single-case design and time-series analysis in psychoneuroimmunology was demonstrated for the first time.

Key Words: psychoneuroimmunology • stress • single-case design • time-series analysis • systemic lupus erythematosus • neopterin

Abbreviations: EWL = Eigenschaftswörterliste ("list ofadjectives"); HAWIE-R = Hamburg-Wechsler-Intelligenz-Test fürErwachsere; SLAM = Systemic Lupus Activity Measure; SLE =systemic lupus erythematosus; ARIMA = auto regressive integratedmoving average.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
SLE is a chronic autoimmune disease of unknown etiology affecting the skin, joints, kidneys, heart, and nervous and hematopoietic systems. The clinical course is highly variable and characterized by periods of flare-ups and remission (1). Among the many different kinds of triggers, such as excessive exposure to sunlight, psychosocial stress has also been discussed as being capable of provoking disease exacerbations (2). In retrospective studies, patients with SLE have often reported stressful life events preceding acute episodes of lupus activity (35). Prospectively, however, only one study has dealt with the impact of daily psychosocial stressors on SLE activity as indicated by laboratory measurements (6). In that study, which was performed on 21 SLE patients, analysis over nine time points at 6-week intervals resulted in only weak correlations between the psychosocial, hematological, and serological variables under study. These weak correlations were attributed by the authors to enormous differences among individual patients. These differences might be explained not only by the immune system’s interindividual susceptibility to stress but also by the varying temporal relationships between stress and immune responses.

According to new concepts in stress research, differences among individuals no longer need be considered a nuisance and need not be obscured by averaging (7, 8). New stress concepts are based on the reconceptualization of health and disease that has occurred in the last decade (9, 10). According to this view, stress-mediated disease results from a perturbation of dynamic functions that is represented by changes in form, frequency, and amplitude of any variable that behaves rhythmically (7). These dynamic processes are unique. A variable’s dynamics consist of characteristic longitudinal patterns of interdependent time points (11). This same uniqueness holds true for the complex interaction of many variables over time. When we average individual dynamics or interactions in groups, these unique structures are extinguished or denaturalized. Therefore, to analyze the dynamic interdependencies between psychosocial, emotional, and physiological factors, it is necessary to consider individuals on a single basis.

This new perspective in stress research is in line with the present investigation, the aim of which was to gather evidence, using a single-case design, about the temporal relationship between daily psychosocial stress and immunological functioning in SLE (12). To investigate the dynamic interactions among psychosocial, emotional, and physiological variables in a patient with SLE, time-series analysis as proposed by Box and Jenkins (11) was applied. This method requires at least 50 to 100 equidistant (in this study, daily) measurements for statistical description of the internal structure of a variable’s series. To guarantee the validity of the data, it was of utmost importance to interfere as little as possible in the patient’s normal routine. Daily overnight urine samples were thus collected by the patient herself, and urine neopterin concentrations were then measured as the indicator of immune system activity. Large amounts of neopterin are released by macrophages during T-cell-dependent activation (13) and show a circadian rhythm peaking in the early morning (14). In several studies comparing nonspecific as well as specific SLE parameters, SLE activity was found to be paralleled by fluctuating neopterin concentrations in serum and urine. Similarly, neopterin concentrations have been identified as one of the best single indicators for the serial determination of SLE activity (1518). Daily psychosocial incidents and hassles were identified in this study in weekly semistructured interviews, allowing a wide variety of patient responses (19). Furthermore, various lifestyle variables that can intervene with cross-correlations between stressors and immune functions were identified (20).


    METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Study Design
One month before the patient began collecting urine, she was interviewed (A.L.) to determine stressful life events and chronic difficulties during the preceding 2 years. The day before the start of the study, the patient was examined thoroughly, both medically (P.K.) and psychologically (G.S.).

The patient was then observed daily for 63 days, from December 13, 1996, to February 13, 1997. Late each afternoon, the patient answered questions about her emotional state, daily lifestyle, SLE, and unrelated symptoms. Beginning at 8 PM each evening, the patient collected her urine for the next 12 hours and froze it at a temperature of -20°C. These urine samples were brought to the laboratory weekly in a cold box and kept frozen at -70°C until further analysis. Each week, the patient was examined by a senior internist (P.K.) to control for any clinical symptoms of disease activity and was interviewed by a trained psychotherapist (A.L.) to identify the past week’s stressful incidents and hassles. At the end of the study, these incidents were assessed by independent raters. The interviewer as well as the independent raters were blind to the physiological data.

Because this study was designed to gather evidence about biopsychosocial interactions over time, the following inclusion criteria were necessary: disease remission, no use of steroidal antiphlogistics or immunosuppressants, no psychiatric disease (based on the third revised edition of the Diagnostic and Statistical Manual of Mental Disorders) or attention and memory deficits (HAWIE-R), and no renal dysfunction.

The patient gave informed consent to participate, and the protocol was approved by the hospital’s internal review board.

Patient
The patient is a 40-year-old white woman who was diagnosed with chronic discoid lupus erythematosus in 1979. In 1991, she developed erythema, photosensitivity, and arthralgia (small joints) and exhibited decreased complement C3. According to American Rheumatism Association criteria, she was thus diagnosed with SLE. In addition, the patient had proteinuria (102 mg/dl). A kidney biopsy for histological examination was refused by the patient. Tests for antinuclear anti–double-stranded DNA antibodies were negative. The patient was then treated with steroid bolus therapy and a daily maintenance dose of 10 mg of methylprednisolone for 1 year. After this treatment, neither proteinuria nor pathological urine sediment could be detected. The patient’s last flare-up occurred in September 1995.

The patient is married and has a 21-year-old son who left home in November 1995. She is a hair dresser but has been on disability pension since December 1995 because of her illness. She is a moderately heavy smoker (30 cigarettes per day). In May 1993, the patient had a hysterectomy.

MEDICAL EXAMINATION
Systemic Lupus Activity Measure.
The SLAM (21) is used to assess SLE activity by measuring 24 clinical manifestations and 8 laboratory parameters. Immune function parameters are not included. The weekly medical examination using the SLAM required approximately 30 minutes.

PSYCHOLOGICAL EXAMINATION
Assessment of life events, chronic difficulties, and incidents.
According to Brown and Harris (22), incidents occur at a discrete point in time and introduce changes that require an adaptive response. Events are incidents that introduce changes above a certain agreed level of seriousness. Severe events introduce what most people in equivalent biographical circumstances would see as even more serious and upsetting changes. Difficulties are ongoing problems that last at least 4 weeks and may or may not be made up of events and/or incidents. The following two interviews were used to assess these variables.

Life Event and Difficulties Schedule.
Life events and chronic difficulties were assessed for the period 2 years preceding the interview. This was necessary 1) to investigate retrospectively whether highly stressful life events and chronic difficulties might be capable of provoking severe disease exacerbations and 2) to have more information about patient’s psychosocial background when rating the daily incidents. Contextual threat rating of major life events (1 = marked, 2 = moderate, 3 = some, 4 = little/no) and chronic difficulties (1 = high marked, 2 = low marked, 3 = high moderate, 4 = low moderate, 5 = mild, 6 = very mild, 7 = no longer a difficulty) were scored by an independent panel of blind raters as previously described (22).

Incidents and Hassles Inventory.
In the semistructured Incidents and Hassles Inventory (G.W. Brown and T.O. Harris, 1996, unpublished), comprising 39 items, the proband is asked about incidents and hassles that occurred during the previous week. Additionally, at the end of the interview, daily notes made by the proband are included. The duration of incidents and the emotional response to them is documented. Afterward, an independent panel of blind raters assesses each incident according to its severity on a three-point scale (1 = marked, 2 = moderate, 3 = some). The length of the weekly interview was approximately 60 minutes.

3-skalen Version der Eigenschafswörterliste.
The 3-scale-EWL ("list of adjectives"; Ref. 23) is a paper-and-pencil test used to measure the proband’s emotional state (mood, mental energy levels, irritation) using 28 adjectives. Emotional state is assessed using a four-point system. Use of the 3-scale-EWL in longitudinal designs is recommended. The proband needs about 5 minutes to complete the test.

Assessment of daily lifestyle factors and subjective estimation of SLE activity.
The patient records daily cigarette use, alcohol and coffee consumption, drug use, and sleep. Using visual analog scales, the proband rates the degree of physical activity, joint pain, weakness, fatigue, and overall disease activity. Moreover, the proband indicates body temperature and whether any symptoms unrelated to SLE are present. The proband needs about 5 minutes for these questions.

Biochemical Analysis
Daily urine neopterin levels were determined by high-performance liquid chromatography (model LC 550, Varian Associates, Palo Alto, CA) as previously described (24). To avoid interassay variability, all 63 urine aliquots were measured in one single run within 3 months after all urine samples had been collected and stored at -70°C. For each of three independent determinations, a new aliquot was used. Urine neopterin levels are expressed as the micromolar concentration of neopterin per molar concentration of creatinine to compensate for variations in urine density (15, 16, 24).

Statistical Analysis
Statistical analyses were conducted using SPSS-Trends (25). In this study, the time-series were cross-correlated both at zero lag (ie, concurrent correlation) and at higher lags (until ±7) to determine whether one variable significantly preceded and hence predicted the other during the following days. Statistically significant cross-correlations reached the p < .05 criterion.

Time-series values are generated successively, and each value tends to (auto)correlate with the preceding value. Therefore, according to Box and Jenkins (11), each time-series is a function of two main factors, internal serial dependencies, such as autoregression and moving average components, and the independent, standard distributed residuals. Because of serial dependencies, cross-correlational analysis between two time-series may lead to false-positive or false-negative correlations. Therefore, adjusted cross-correlational analysis using only time-series residuals was applied in this study (26). Residuals that are free of serial dependencies were generated by ARIMA modeling. The residuals’ serial independency was controlled for using the Durbin-Watson statistical method, ranging from 0 to 4. A value near 2 indicates nonautocorrelation (27). Because modeling can overadjust and thus cancel out true covariance, unadjusted cross-correlations with premodeled series were also calculated for comparison.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
At the beginning of the study, the patient was asked retrospectively about the occurrence of major life events and chronic difficulties during the preceding 2 years. As shown in Figure 1, several severe events and chronic difficulties (patient’s depression, patient’s chronic low back pain, patient’s court case for disability pension, family’s financial problems) preceded the patient’s last SLE flare-up in September 1995 by a few months. After the flare-up, only one event (son leaves home) and one chronic difficulty (nephew’s chronic cough) occurred.



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Fig. 1. Major life events and chronic difficulties during the 2 years preceding the study and their temporal relationship to the patient’s last flare-up in September 1995. Events and difficulties are indicated by serially numbered capital letters (E1 = patient’s orthopedic surgery, E2 = uncle’s operation, E3 = sister’s divorce, E4 = son leaves home, D1 = patient’s depression, D2 = patient’s chronic low back pain, D3 = patient’s court case for disability pension, D4 = family’s financial problems, D5 = nephew’s chronic cough). Additionally, they are characterized by time of occurrence (dotted line) and severity ratings. For example, the patient’s orthopedic surgery (E1) occurred in April 1995 and was rated as moderate (2) on short-term contextual threat and little (4) on long-term contextual threat. Another example is the patient’s depression (D1), which began with a "high moderate" contextual threat (3) in January 1995, did not change in severity, and ended in February 1995 after 4 to 5 weeks.

 
To determine whether similar results under prospective conditions would occur, the patient collected her overnight urine daily for 63 days, from December 13, 1996, to February 13, 1997. Figure 2 shows the time-series of urine neopterin during this study. The mean neopterin value was 199 ± 46 µmol/mol creatinine (range, 123–370 µmol/mol).



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Fig. 2. Urine neopterin time-series covering a period of 63 days. Both the raw neopterin data (black line) as well as the fit from the ARIMA model representing the series’ internal structure (gray line) are plotted. The 300-µmol urine neopterin level, which has been determined to be a significant predictor of SLE activity, is indicated by the dotted line. The data represent the mean of three independent determinations.

 
The internal serial dependency of the urine neopterin time-series in this patient is best represented by a first-order autoregressive process as well as a 7-day seasonality. This corresponds to a (1,0,0)(1,0,0)7 ARIMA model. As shown in Figure 2, the 7-day seasonality is particularly prominent in the first 4 weeks of the study. Here, neopterin levels peaked every Saturday, 1 day after the patient’s weekly examination and interview on Friday. Additionally, notable positive deviations from the internal serial dependency are evident both at the beginning (day 2) and in the zig-zag configuration in the middle of the series (days 21–26). On days 2 and 24, the values exceeded 300 µmol neopterin/mol creatinine.

During the 63 days, 59 incidents were identified using recorded interviews. Of these, 11 (19%) were independently rated as having "some" severity, and 8 (14%) were rated as having "moderate" severity. None were rated as having "marked" severity. This study proceeded on the basis of a threshold model, assuming that only incidents of a certain severity are able to interfere with the course of urine neopterin. Therefore, only the eight incidents rated as moderate are listed chronologically in Table 1. Additionally, short descriptions of all moderate incidents are given. Days featuring a moderate incident were coded as "1," and the rest were coded as "0." The resulting time-series of moderate incidents is described by a (1,0,0) ARIMA model.


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Table 1. Short Descriptions of Eight Incidents Rated as Moderately Stressful
 
Next, the temporal relationship between moderate incidents and the course of urine neopterin was examined statistically. The residuals of both the urine neopterin time-series and the time-series of moderate incidents were used for adjusted cross-correlational analysis and are plotted in Figure 3. Whereas adjusted (Durbin-Watson = 2.02) cross-correlations were slightly below significance (lag 1: +0.248, NS), unadjusted cross-correlations, including the covariances due to serial dependencies, revealed that the occurrence of a moderate incident significantly predicted an increase in urine neopterin the following day, approximately 24–48 hours later (lag 1: +0.300, p < .05).



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Fig. 3. Residuals free of serial dependencies from both the urine neopterin model and the stress model. Both residuals from the neopterin model (gray line) and residuals from the stress model (black line) are plotted. Stress peaks are labeled according to the day on which the moderate incident occurred. Those associated with an increase in neopterin 1 day later are indicated in bold.

 
When we look more closely at Figure 3, however, four of the eight incidents (start of the study, day 1; argument with sister, day 20; son’s departure, day 25; filthy student club, day 44) were followed by increases in urine neopterin 1 day later. When cross-correlated in a separate time-series, again coding days with an incident as "1" and days without an incident as "0," resulting in a (1,0,0) ARIMA model, these four incidents had a significant impact on the urine neopterin course with and without adjustment of the series (lag 1: +0.441(1.95)/+0.389, p < .05) (this notation means adjusted cross-correlation coefficient(Durbin-Watson value)/unadjusted cross-correlation coefficient). These incidents were also found to be significantly cross-correlated with higher emotional irritation levels according to the EWL (lag 0: +0.271(1.98)/+0.291, p < .05). In contrast, the remaining four moderate incidents, which were not followed by neopterin increases (forgotten house key, day 8; argument with husband and son, day 11; trouble with computer, day 21; skidding car, day 50), did not influence the course of urine neopterin significantly, either at lag 1 (-0.102(1.96)/+0.021, NS) or at any other lags. They were, however, significantly associated with higher mental energy levels (lag 0: +0.35(1.95)/+0.336, p < .05).

Cross-correlational analyses including all variables measured in this study revealed no other significant one-lagged correlation with urine neopterin. Alcohol had a suppressive effect on urine neopterin (lag 0: -0.407(1.17)/-0.269, p < .05).

As to the clinical features during the study period, weekly examinations revealed no evidence of increased SLE activity according to SLAM criteria. From days 28 to 36, the patient had an elevated temperature (37.2–37.7°) without evidence of infection. During the last 11 days (days 53–63), the patient reported having a cold accompanied by an elevated temperature. This was confirmed by the weekly medical examinations (data not shown).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
This study is the first to apply a single-case design and time-series analysis as proposed by Box and Jenkins (11) in modern psychoneuroimmunology. More than 30 years ago, Solomon and Moos (28) suggested that a causal relationship might exist between psychological distress, immunological dysfunction, and the disease process of rheumatoid arthritis. The present investigation, which made use of both a retrospective and a prospective approach, supports this suggestion in another autoimmune disease. In an SLE patient, it was found that moderately stressful incidents predicted an increase of urine neopterin approximately 24 to 48 hours later. Although our SLE patient did not exhibit signs of a clinical worsening of her disease, the results suggest that the neopterin increases were nonetheless indicators of immune deviations and may thus be related to SLE activity. Lim et al. (15), comparing nonspecific as well as specific SLE parameters, found that urine neopterin levels exceeding 300 µmol/mol creatinine were significant predictors of SLE disease activity. Indeed, these levels were exceeded twice in our SLE patient in connection with moderate stressors.

The current investigation also provided evidence about the specificity of stressors. Four of the eight moderate incidents, start of the study, argument with sister, son’s departure, and filthy student’s club were followed by substantial urine neopterin increases 1 day later. In contrast, forgotten house key, argument with husband and son, trouble with computer, and skidding car (Table 1) were not associated with neopterin increases. We believe that this discrepancy was due to the fact that those incidents that triggered urine neopterin increases were characterized by emotional irritation and high interpersonal stress, whereas the others were characterized by mental activity and lower interpersonal stress. To illustrate the varying meaning of interpersonal stress to the patient, we can look more closely at 1) argument with sister and 2) argument with husband and son, both of which deal with conflicts between the patient and persons close to her. The argument with her sister lasted considerably longer: In the interviews, the patient said that the argument with her husband and son had ceased to be a problem for her as early as half an hour after its occurrence. The argument with her sister, however, was not settled until the next day and remained on the patient’s mind for several days. In regard to content, the argument with her sister was clearly more significant: Whereas the argument with her husband and son was an everyday argument in an otherwise good-functioning marriage and loving relationship with her son, the argument with her sister was an argument with biographically significant content within the framework of the patient’s tense relationship with her sister, a problem that had been an issue for years.

When looking at the 7-day cyclicity of urine neopterin in the first 4 weeks of the study, one might conclude that our patient also experienced interpersonal stress due to the weekly interviews and examinations each Friday (Figure 2). The increase in neopterin levels was likely due to anticipation of these visits; the decrease, in turn, probably resulted from the relief that followed such visits. This phenomenon became weaker from week to week. This was confirmed by the patient’s own statements in the interviews. In this patient, interpersonally meaningful stressors have also been associated with both the onset of chronic discoid lupus erythematosus, which occurred while she was on her honeymoon, 8 months after her father’s death, and her last SLE flare-up in September 1995 (Figure 1). This, again, is in agreement with previous results demonstrating retrospectively that particularly significant crises in interpersonal relations (eg, death, divorce, feared loss of loved one) precede the onset of SLE or SLE exacerbations (35).

The results of the current investigation contrast with the findings of Wekking et al. (6), who concluded that no clear relationship exists between laboratory data and subjective ratings of physical and psychosocial status in SLE patients. Unfortunately, the authors investigated their topic’s dynamic aspects by static means, making their conclusions questionable: They determined both daily stress parameters and laboratory data at large 6-week intervals, averaged the longitudinal data of 21 probands, and neglected the data’s serial dependency. Although the approach of the current investigation may be more valid, it can certainly be refined in future studies. As a posteriori analysis of Figure 3 revealed, the interview process, the identification of incidents, and severity ratings should be improved to achieve a higher differentiation of psychosocial stressors.

As to the clinical relevance for the patient of this study, our results emphasize the importance of recognizing and controlling for psychosocial stressors with a special focus on stress in interpersonal relationships. For example, if our patient should experience a highly stressful major life event, closer monitoring of the disease course (eg, weekly urine neopterin determinations) would be recommended so that pharmaceutic as well as psychotherapeutic intervention could be made as soon as possible. This might prevent severe SLE exacerbations and therefore significantly decrease the risk of serious complications.

Nevertheless, particularly in light of the heterogeneity of SLE, a generalization of the results and conclusions of this study can only occur after numerous other single cases have been investigated. We may then be able to draw conclusions about possible systematic patterns, which may then form the basis for cohort studies. In this sense, the single-case design proposed in this study demonstrated the feasibility of collecting data on life elements, which, until now, have been neglected in biomedical research. It seems possible to gather data about the dynamics and interaction of biological as well as psychosocial variables. This approach is in line with new concepts in stress research (7, 8). Furthermore, the unique design of this study, based on consecutive weekly interviews while preserving the patient’s normal routine, allowed closer access to the meaning of stress under natural conditions on both the biochemical and psychosocial levels. This type of integrative single-case research is therefore also in accordance with George Engel’s biopsychosocial model (29, 30).


    ACKNOWLEDGMENTS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
This study was supported in part by Grant 6990 from the National Bank of Austria. Additionally, funding was provided by Janssen-Cilag.

We thank the patient of this study for her participation. We also thank Gerhard Lücke for his valuable help. Finally, we thank Tirril Harris and George Brown for both their training in conducting and rating the Life Event and Difficulty Schedule and the Incidents and Hassles Inventory and their contributions to this article.

Received for publication July 21, 1998.

Revision received May 13, 1999.


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 

  1. Mohan C, Datta SK. Lupus: key pathogenic mechanisms and contributing factors. Clin Immunol Immunopathol 1995; 77: 209–20.[Medline]
  2. Weiner H. Social and psychobiological factors in autoimmune disease. In: Ader R, Felten D, Cohen N, editors. Psychoneuroimmunology. San Diego (CA): Academic Press; 1991. p. 955–1011.
  3. McClary AR, Meyer E, Weitzman EL. Observations on the role of the mechanism of depression in some patients with disseminated lupus erythematosus. Psychosom Med 1955; 4: 311–21.
  4. Otto R, Mackay IR. Psycho-social and emotional disturbance in systemic lupus erythematosus. Med J Aust 1967; 9: 488–93.
  5. Hall RCW, Stickney SK, Gardner ER. Psychiatric symptoms in patients with systemic lupus erythematosus. Psychosomatics 1981; 22: 15–24.[Abstract/Free Full Text]
  6. Wekking EM, Vingerhoets AJJM, van Dam AP, Nossent JC, Swaak AJJG. Daily stressors and systemic lupus erythematosus: a longitudinal analysis—first findings. Psychother Psychosom 1991; 55: 108–13.[Medline]
  7. Weiner H. New concepts about the organism and its perturbation by stressful experience. In: Perturbing the organism: the biology of stressful experience. Chicago: University of Chicago Press; 1994. p. 246–84.
  8. Lazarus RS. Issues of causality. Emotion and Adaptation. Oxford, UK: Oxford University Press; 1991. p. 203–11.
  9. Garfinkel A. A mathematics for physiology. Am J Physiol 1983; 245: 455–66.
  10. Glass L, Mackay MC. From clocks to chaos: the rhythms of life. Princeton (NJ): Princeton University Press; 1988.
  11. Box GEP, Jenkins GM. Time-series analysis: forecasting and control. San Francisco: Holden-Day; 1976.
  12. Schubert C. Psychoneuroimmunologische Forschung in Kontext Biochemischer Erkenntnisfortschritte und ihre para dijmatischen Greuzen. Zschr Psychosom Med 1998; 44: 1–20.
  13. Fuchs D, Weiss G, Wachter H. Neopterin, biochemistry and clinical use as a marker for cellular immune reactions. Int Arch Allergy Immunol 1993; 101: 1–6.[Medline]
  14. Auzéby A, Bogdan A, Krosi Z, Touitou Y. Time-dependence of urinary neopterin, a marker of cellular immune activity. Clin Chem 1988; 34: 1866–7.[Abstract/Free Full Text]
  15. Lim KL, Jones AC, Brown NS, Powell RJ. Urine neopterin as a parameter of disease activity in patients with systemic lupus erythematosus: comparisons with serum sIL-2R and antibodies to dsDNA, erythrocyte sedimentation rate, and plasma C3, C4, and C3 degradation products. Ann Rheum Dis 1993; 52: 429–35.[Abstract/Free Full Text]
  16. Lim KL, Muir K, Powell RJ. Urine neopterin: a new parameter for serial monitoring of disease activity in patients with systemic lupus erythematosus. Ann Rheum Dis 1994; 53: 743–8.[Abstract/Free Full Text]
  17. Leohiron J, Thuvasethakul P, Sumethkul V, Pholcharoen T, Boonpucknavig V. Urinary neopterin in patients with systemic lupus erythematosus. Clin Chem 1991; 37: 47–50.[Abstract/Free Full Text]
  18. Samsonov MY, Tilz GP, Egorova O, Reibnegger G, Balabanova RM, Nassonov EL, Nassonova VA, Wachter H, Fuchs D. Serum soluble markers of immune activation and disease activity in systemic lupus erythematosus. Lupus 1995; 4: 29–32.[Abstract/Free Full Text]
  19. McGuire WJ. A contextualist theory of knowledge: its implications for innovation and reform in psychological research. In: Berkowitz L, editor. Advances in experimental social psychology. New York: Academic Press; 1983. p. 1–47.
  20. Kiecolt-Glaser JK, Glaser R. Methodological issues in behavioral immunology research with humans. Brain Behav Immun 1988; 2: 67–78.[Medline]
  21. American Rheumatism Association Glossary Committee. Dictionary of the rheumatic diseases. Vol 1. New York: Contact Associates; 1982.
  22. Brown GW, Harris TO. Life events and illness. New York: Guilford Press; 1989.
  23. Becker P. Skalen für Verlaufsstudien der emotionalen Befindlichkeit. Zschr exp angew Psychol 1988; 3: 345–69.
  24. Wachter H, Fuchs D, Hausen A, Reibnegger G, Werner ER. Neopterin as marker for activation of cellular immunity: immunologic basis and clinical application. Adv Clin Chem 1989; 27: 81–141.[Medline]
  25. SPSS Institute. SPSS/PC+ Trends. Chicago: SPSS Institute; 1994.
  26. Jenkins GM, Watts DW. Spectral analysis and its applications. San Francisco: Holden-Day; 1969.
  27. Durbin J, Watson GS. Testing for serial correlation in least square regression. Biometrica 1951; 38: 115–78.
  28. Solomon GF, Moos RH. The relationship of personality to the presence of rheumatoid factor in asymptomatic relatives of patients with rheumatoid arthritis. Psychosom Med 1965; 27: 350–60.[Abstract/Free Full Text]
  29. Engel GL. The need for a new medical model: a challenge for biomedicine. Science 1977; 196: 129–36.[Abstract/Free Full Text]
  30. von Uexküll T, Wesiack W. In: von Uexküll T, Adler R, editors. Psychosomatic medicine. Baltimore: Urban and Schwarzenberg; 1997. p. 13–52.



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