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Abstract Number: 2570

Lymphoma Risk in Systemic Lupus: Effects of Disease Activity Versus Treatment

Sasha Bernatsky1, Ann E. Clarke2, Karen H. Costenbader3, Murray B. Urowitz4, Dafna D. Gladman5, Paul R. Fortin6, Michelle Petri7, Susan Manzi8, D.A. Isenberg9, Anisur Rahman10, Daniel Wallace11, Caroline Gordon12, Christine Peschken13, Mary Anne Dooley14, E.M. Ginzler15, Cynthia Aranow16, Steven M. Edworthy17, Ola Nived18, Søren Jacobsen19, Guillermo Ruiz-Irastorza20, Edward H. Yelin21, Susan G. Barr22, Irene Blanco23, Candace H. Feldman24 and R. Ramsey-Goldman25, 1Clinical Epidemiology, Systemic Lupus International Collaborating Clinics, Montreal, QC, Canada, 2Division of Clinical Epidemiology, Research Institute of the McGill University Health Centre, Montreal, QC, Canada, 3Rheumatology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 4Division of Rheumatology, Toronto Western Hospital and University of Toronto,, Toronto, ON, Canada, 5Division of Rheumatology, Toronto Western Hospital and University of Toronto, Toronto, ON, Canada, 6University of Laval, Quebec, QC, 7Johns Hopkins University School of Medicine, Baltimore, MD, 8Division of Rheumatology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 9Centre for Rheumatology Research, University College London, London, United Kingdom, 10Centre for Rheumatology Research,Rayne Institute, 4th Floor, University College London, London, United Kingdom, 11Cedars-Sinai/UCLA, Los Angeles, CA, 12School of Immunity and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom, 13Medicine & Community Health Sciences, University of Manitoba, Winnipeg, MB, Canada, 14University of North Carolina at Chapel Hill, Chapel Hill, NC, 15Rheumatology, SUNY-Downstate Medical Center, Brooklyn, NY, 16Feinstein Institute for Medical Research, Manhasset, NY, 17The University of Calgary, Calgary, AB, Canada, 18Department of Clinical Science, Lund University, Rheumatology, Lund, Sweden, 19Department of Rheumatology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark, 20Autoimmune Diseases Research Unit, Department of Internal Medicine, BioCruces Health Research Institute, Hospital Universitario Cruces, University of the Basque Country, Barakaldo, Spain, 21Medicine, UC San Francisco, San Francisco, CA, 22University of Calgary, University of Calgary, Calgary, AB, Canada, 23Rheumatology, Albert Einstein College of Medicine, Bronx, NY, 24Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 25Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL

Meeting: 2012 ACR/ARHP Annual Meeting

Keywords: Malignancy and systemic lupus erythematosus (SLE)

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Session Information

Title: ACR/REF Edmond L. Dubois, MD Memorial Lectureship: Hydroxychloroquine Reduces Thrombosis in Systemic Lupus Erythematosus, Particularly in Antiphospholipid Positive Patients

Session Type: Abstract Submissions (ACR)

Background/Purpose: In systemic lupus (SLE), concern exists about immunosuppressive drugs and lymphoma risk,  Yet, the relative influence of disease activity vs treatment, is unknown. Our objective was to determine, in SLE, the relative importance of disease activity vs drugs.  

Methods:  We performed case-cohort analyses within a multi-site SLE cohort. Cancers were ascertained by cancer registry linkage. Adjusted hazard ratios (HRs) for lymphoma were generated in multivariate regression models, for time-dependent exposures to immunomodulators (cyclophosphamide, azathioprine, methotrextate, mycophenolate, anti-malarials, glucocorticoids) demographics, calendar year, Sjogren’s syndrome, SLE duration, and disease activity(mean adjusted SLEDAI-2k). Partially adjusted models were also performed, using only covariates whose HR confidence interval excluded the null value. Sensitivity analyses were performed, lagging cyclophosphamide exposures by 5 years. We used average mean SLE disease activity scores over time, and medications were treated both categorically (ever/never) and as cumulative doses.

Results: We studied 64 lymphomas (61 non-Hodgkin’s, 3 Hodgkin’s) and 4,739 cancer-free controls. As is seen in the general population, lymphoma risk in SLE was higher in males versus females, and increased with age. Lymphoma cases occurred a mean of 13.1 years (standard deviation 9.8, median 12.3) after SLE diagnosis. Univariate analyses suggested a decreased lymphoma risk within the highest tertile of disease activity (relative to those with the lowest activity) but in fully adjusted models (using all variables listed above), the confidence interval widened to include the null value. Sensitivity analyses, lagging cyclophosphamide exposures, showed similar results to that portrayed in the table below. In a partially adjusted model (retaining age and highest tertile of disease activity), the HR suggested a two-fold lymphoma risk after cyclophosphamide. Despite a trend towards greater cyclophosphamide use in cases versus cancer-free controls, in fully adjusted models, no drug exposure was estimated to be an independent risk factor. Still, due to correlation, it remains difficult to differentiate the effects of medications from disease activity.

 Conclusion: We did not definitively demonstrate an increased risk for any medications, despite a trend to greater cyclophosphamide use in the lymphoma cases. If anything, we noted a protective effect for very high SLE disease activity. Further work will focus on genetic profiles that might interact with medication exposures to influence lymphoma risk in SLE.

Results of the univariate and multivariate models to assess the hazard ratio (HR) of exposures on lymphoma development in patients with SLE

Variable

Univariate HR (95% CI)*

Partially adjusted model (95% CI)

Multivarate HR (95% CI)

Outside North America

1.04 (0.53, 2.05)

–

1.06 (0.45, 2.50)

Calendar year

1.01 (0.98, 1.05)

–

0.98 (0.94, 1.02)

Male

2.47 (1.24, 4.92)

–

2.21 (1.05, 4.66)

Age

1.05 (1.03, 1.07)

1.04 (1.03, 1.06)

1.05 (1.03, 1.07)

White race/ethnicity

0.97 (0.55, 1.71)

–

0.86 (0.46, 1.59)

Sjogren’s syndrome

1.29 (0.66, 2.54)

–

1.21 (0.53, 2.78)

Glucocorticosteroids (GC) ever

1.39 (0.75, 2.56)

–

1.03 (0.40, 2.64)

Cumulative GC**> 3.5 gm

1.27 (0.75, 2.17)

–

1.59 (0.69, 3.67)

Cyclophosphamide (CY) ever

1.73 (0.90, 3.33)

1.99 (1.00, 3.96)

1.95 (0.61, 6.22)

Cumulative CY > 6 gm

1.51 (0.63, 3.62)

–

0.79 (0.18, 3.54)

Azathioprine (AZA) ever

0.82 (0.45, 1.52)

–

1.28 (0.53, 3.07)

Cumulative AZA > 36.5 gm

0.49 (0.19, 1.25)

–

0.46 (0.14, 1.54)

Methotrexate ever used

0.99 (0.45, 2.16)

–

0.79 (0.30, 2.05)

Mycophenolate ever used

1.38 (0.58, 3.29)

–

1.74 (0.70 4.34)

Antimalarials ever used

1.47 (0.80, 2.69)

–

1.39 (0.69, 2.78)

Disease activity (2nd tertile)***

1.00 (0.55, 1.82)

–

1.10(0.56, 2.14)

Disease activity (3rd tertile)

0.43 (0.22, 0.84)

0.49 (0.27, 0.90)

0.52 (0.24, 1.12)

*CI=confidence interval**Systemic glucocorticosteroids, considered in prednisone equivalent doses.***Mean adjusted SLE Disease Activity-2K (SLEDAI-2k)


Disclosure:

S. Bernatsky,

National Institutes of Health, Canadian Institutes of Health Research,

2;

A. E. Clarke,
None;

K. H. Costenbader,
None;

M. B. Urowitz,
None;

D. D. Gladman,
None;

P. R. Fortin,
None;

M. Petri,
None;

S. Manzi,
None;

D. A. Isenberg,
None;

A. Rahman,
None;

D. Wallace,
None;

C. Gordon,
None;

C. Peschken,
None;

M. A. Dooley,
None;

E. M. Ginzler,
None;

C. Aranow,
None;

S. M. Edworthy,
None;

O. Nived,
None;

S. Jacobsen,
None;

G. Ruiz-Irastorza,
None;

E. H. Yelin,
None;

S. G. Barr,
None;

I. Blanco,
None;

C. H. Feldman,
None;

R. Ramsey-Goldman,
None.

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