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Abstract Number: 938

Hospitalizations in Systemic Lupus Erythematosus: A Longitudinal Study

Hong Fang1, Jie Xu2 and Michelle Petri1, 1Johns Hopkins University School of Medicine, Baltimore, MD, 2Rheumatology, Johns Hopkins University School of Medicine, Baltimore, MD

Meeting: 2012 ACR/ARHP Annual Meeting

Keywords: Systemic lupus erythematosus (SLE)

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Session Information

Title: Epidemiology and Health Services Research: Epidemiology and Outcomes of Rheumatic Disease II

Session Type: Abstract Submissions (ACR)

Background/Purpose: Hospitalizations are one of the major direct costs in SLE.  A review of studies looking at the contributions of different medical components to the economic burden of SLE revealed that hospitalizations may count for 50% of the direct costs in SLE (Panopalis P, et al. Arthritis Rheum 2008; 59:1788–1795.).  Lupus nephritis has been identified as one of the significant factors consistent with increased direct costs (Slawsky KA et al. Arthrit Care Res 2011; 63:1224-1232.).  Identification of predictors of hospitalizations could lead to targeted interventions to reduce costs.

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. 359 patients (91% female, 55% Caucasian, 36% African-American, 9% other ethnicities, mean age at baseline 46±12 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.

Results:

Univariate analysis identified prednisone, disease activity (mean Physician’s global assessment, SLEDAI), and renal lupus as predictors of hospitalization over the next 6 months (Table 1). In the multivariate model for number of hospitalizations, use of prednisone at baseline and mean SLEDAI were associated (Table 2).

We next looked at hospitalizations due to lupus. In a multivariate linear regression model, baseline hospitalizations and mean SLEDAI were predictive.

Table 1. Predictors of hospitalizations (any vs none) – univariate analysis.

 

 

 

Number (%) hospitalization during followup

P-value

Age at baseline (years)

   ≤ 40 (n=134)  

   > 40 (n=225)               

11 (8.2)

28 (12.4)

0.21

Gender

 

   Female (n=327)

   Male (n=32)

35 (10.7)

4 (12.5)

0.77

Ethnicity

 

   African-American (n=131)

   Caucasian (n=197)

19 (14.5)

17 (8.6)

0.096

 

Family income ($)

 

   ≤ 50K (n=165)

   > 50K (n=194)

21 (12.7)

18 (9.3)

0.30

Education (years)

 

   < 12 (n=24)

   ≥ 12 (n=335)

2 (8.3)

37 (11.0)

>0.99

Use of prednisone at baseline

   No (n=224)

   Yes (n=135)

17 (7.6)

22 (16.3)

0.010

PGA1 at baseline

 

   ≤1 (n=310)

   >1 (n=49)

32 (10.3)

7 (14.3)

0.41

Mean PGA over year

   ≤1 (n=304)

   >1 (n=55)

28 (9.2)

11 (20.0)

0.018

SLEDAI at baseline 

 

   ≤2  (n=265)

   >2 (n=94)

23 (8.7)

16 (17.0)

0.026

Mean SLEDAI over year 

   ≤2  (n=242)

   >2 (n=117)

19 (7.9)

20 (17.1)

0.0083

Anti-dsDNA at baseline

   Negative (n=271)

   Positive (n=80)

28 (10.3)

11 (13.8)

0.39

C3 or C4 at baseline

   Low (n=67)

   Normal (n=284)

9 (13.4)

30 (10.6)

0.50

Increased ESR at baseline

   No (n=179)

   Yes (n=167)

15 (8.4)

23 (13.8)

0.11

Urine Pr:Cr ratio at baseline

   ≤0.5 (n=314)

   >0.5 (n=26)

31 (9.9)

6 (23.1)

0.049

Baseline history of hospitalizations

   No (n=327)

   Yes (n=32)

34 (10.4)

5 (15.6)

0.37

1PGA: Physician’s global assessment (0-3 scale)

Table 2.  Multivariate Linear Regression Model.

 

Effect on number of hospitalizations

P-value

Age at baseline (per 10 years)

0.04±0.02

0.061

Ethnicity (African-American)

0.06±0.06

0.25

Education (<12 years)

-0.05±0.10

0.61

Use of prednisone at baseline

0.14±0.06

0.0091

Mean SLEDAI (per unit)

0.03±0.01

0.0086

Urine Pr:Cr ratio at baseline (per unit)

0.01±0.04

0.73

Conclusion: Total hospitalizations are associated with prednisone use and disease activity. Hospitalizations due to SLE were also associated with disease activity captured by SLEDAI. Targeted therapies that reduce SLEDAI would thus be expected to reduce hospitalizations and direct costs.


Disclosure:

H. Fang,
None;

J. Xu,
None;

M. Petri,

HGS,

5,

GlaxoSmithKline,

5,

Medimmune,

5,

UCB,

5,

Anthera,

5,

Pfizer Inc,

5,

TEVA,

5.

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