Session Information
Session Type: Abstract Submissions (ACR)
Background/Purpose: Indirect costs are part of the medical and financial burden of SLE. These costs are easy to undervalue because a significant portion of this economic loss results from lost productivity in the workforce (Clarke A, et al. Am J Manag Care, 2001; 7(16):S496-S501.). This effect is magnified by the population typically affected by SLE, young women, who may suffer disabilities that affect the most productive years of life (Panopalis P, et al. Arthritis & Rheumatism, 2008; 59(12):1788-1795.). We attempted to identify both demographic and disease variables that may serve as predictors of this loss in work-related activities.
Methods: The medical resource use questionnaire was distributed to SLE patients in the Hopkins Lupus Cohort that covered the last 3 months before the baseline visit and then at the following two quarterly clinic visits. 199 SLE patients (89% female, 58% Caucasian, 31% African-American, 11% other ethnicities, mean age at baseline 44±11 years) were included in the analysis. Exclusion criteria were diagnosis with lupus less than 6 months ago, age younger than 18 or older than 75, pregnant at baseline, and active HIV patients. Those who were unemployed were also excluded.
Results: The mean number of missed work days over 6 months was 2.6 days (range 0 to 39). Predictors of missed work days are shown in Table 1. The two significant predictors were low family income (p=0.019) and a history of missed work days in the 3 months before the study year (p<0.0001). A multivariate linear regression model for number of missed work days was then constructed (Table 2). In the multivariate model, disease activity (mean SLEDAI) was not associated with the number of missed work days. Renal activity (urine protein/cr ratio) had a borderline association. Family income was not predictive.
Table 1. Predictors of missed work days (any vs none) – univariate analysis.
|
|
|
Number (%) missed work days during followup |
P-value |
|
Age at baseline (years) |
≤ 40 (n=86) > 40 (n=113) |
36 (41.9) 44 (38.9) |
0.68 |
|
Gender |
Female (n=177) Male (n=22) |
71 (40.1) 9 (40.9) |
0.94 |
|
Ethnicity
|
African-American (n=61) Caucasian (n=115) |
29 (47.5) 42 (36.5) |
0.16 |
|
Family income ($)
|
≤ 50K (n=75) > 50K (n=124) |
38 (50.7) 42 (33.9) |
0.019 |
|
Education (years)
|
< 12 (n=7) ≥ 12 (n=192) |
4 (57.1) 76 (39.6) |
0.44 |
|
Use of prednisone at baseline
|
No (n=126) Yes (n=73) |
46 (36.5) 34 (46.6) |
0.16 |
|
PGA1at baseline
|
≤1 (n=176) >1 (n=23) |
67 (38.1) 13 (56.5) |
0.090 |
|
Mean PGA over year
|
≤1 (n=170) >1 (n=29) |
65 (38.2) 15 (51.7) |
0.17 |
|
SLEDAI at baseline
|
≤2 (n=154) >2 (n=45) |
59 (38.3) 21 (46.7) |
0.31 |
|
Mean SLEDAI over year
|
≤2 (n=140) >2 (n=59) |
54 (38.6) 26 (44.1) |
0.47 |
|
Anti-dsDNA at baseline
|
Negative (n=148) Positive (n=49) |
58 (39.2) 21 (42.9) |
0.65 |
|
C3 or C4 at baseline
|
Low (n=40) Normal (n=156) |
15 (37.5) 63 (40.4) |
0.74 |
|
Increased ESR at baseline
|
No (n=117) Yes (n=74) |
46 (39.3) 31 (41.9) |
0.72 |
|
Urine Pr:Cr ratio at baseline |
≤0.5 (n=178) >0.5 (n=12) |
70 (39.3) 7 (58.3) |
0.23 |
|
Diabetes
|
No (n=187) Yes (n=12) |
72 (38.5) 8 (66.7) |
0.070 |
|
BMI at baseline
|
≤30 (n=143) >30 (n=55) |
52 (36.4) 27 (49.1) |
0.10 |
|
Vitamin D
|
<32 (n=57) ≥32 (n=137) |
26 (45.6) 52 (38.0) |
0.32 |
|
Baseline history of missed work days |
No (n=108) Yes (n=75) |
22 (20.4) 52 (69.3) |
<0.0001 |
1PGA: Physician’s global assessment (0-3 scale)
Table 2. Multivariate Linear Regression Model
|
|
Effect on number of missed work days |
P-value |
|
Age at baseline (per 10 years) |
0.03±0.04 |
0.39 |
|
Ethnicity (African-American) |
0.19±0.91 |
0.83 |
|
Family income (>50K) |
0.29±0.85 |
0.73 |
|
Mean SLEDAI (per unit) |
0.05±0.20 |
0.79 |
|
Urine Pr:Cr ratio at baseline (per unit) |
1.23±0.66 |
0.063 |
|
Diabetes |
2.81±1.88 |
0.13 |
|
Vitamin D at baseline |
-0.04±0.03 |
0.19 |
|
Number of missed work days at baseline |
0.67±0.11 |
<0.0001 |
Conclusion: This study found that disease activity (either by physician’s global assessment or SLEDAI) is not predictive of missed work days. However, renal lupus had a borderline association. Demographic factors (sex, ethnicity, income) were not significant in the multivariate model. The most important factor remains a pattern of past history of missed work days.
Disclosure:
J. Xu,
None;
H. Fang,
None;
M. Petri,
HGS,
5,
GlaxoSmithKline,
5,
Medimmune,
5,
UCB,
5,
Anthera,
5,
Pfizer Inc,
5,
TEVA,
5.
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