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2954 Tumor Necrosis Factor-Alpha Inhibitor Medications for Inflammatory Conditions and Incidence of Multiple Myeloma

Myeloma: Biology and Pathophysiology, excluding Therapy
Program: Oral and Poster Abstracts
Session: 651. Myeloma: Biology and Pathophysiology, excluding Therapy: Poster II
Sunday, December 6, 2015, 6:00 PM-8:00 PM
Hall A, Level 2 (Orange County Convention Center)

Gregory S. Calip, PharmD, MPH, PhD1,2,3*, Wan-Ju Lee, MS1,2*, Todd A. Lee, PharmD, PhD1,2*, Glen T. Schumock, PharmD, MBA, PhD1,2* and Brian C.-H. Chiu, PhD4

1Center for Pharmacoepidemiology and Pharmacoeconomic Research, University of Illinois at Chicago, Chicago, IL
2Department of Pharmacy Systems, Outcomes and Policy, University of Illinois at Chicago, Chicago, IL
3Population Health, Behavior and Outcomes Program, University of Illinois Cancer Center, Chicago, IL
4Department of Public Health Sciences, The University of Chicago, Chicago, IL

Purpose

Tumor necrosis factor-alpha (TNF-α) is a pleiotropic cytokine that regulates a wide variety of cellular responses including proliferation and differentiation. This potent mediator of inflammation and bone resorption is elevated in plasma of multiple myeloma (MM) patients, and inhibition of TNF-α is hypothesized to enhance the effects of MM treatments. However, the effects of TNF-α inhibitors on incidence of MM have not been fully characterized. Some reports indicate a possible increased risk of hematological malignancies with anti-TNF therapies. The purpose of this study was to examine incidence of MM among adults with inflammatory conditions treated with anti-TNF monoclonal antibodies and TNF fusion protein.

Patients and Methods

We conducted a retrospective cohort study of new users of TNF-α inhibitors from 2009-2013 using the Truven Health MarketScan Database. Patients were required to be 20+ years old and have 12 months of continuous enrollment prior to first TNF-α inhibitor use. Exclusion criteria included presence of the following in the year prior to first TNF-α inhibitor use: any malignancy, HIV+, and hematopoietic stem cell transplant.

We used longitudinal pharmacy claims data to measure continuous use of infliximab, adalimumab, golimumab, certolizumab and etanercept, as well as other immunosuppressive medications. MM cases were identified using a validated algorithm for administrative claims data and ICD-9 diagnosis codes. Data from the year prior to first TNF-α inhibitor use were also used to calculate Charlson comorbidity index scores and document diagnoses of inflammatory conditions, including rheumatoid arthritis, psoriasis, psoriatic arthritis, inflammatory bowel disease (Crohn’s disease, ulcerative colitis) and ankylosing spondylitis. Incidence rates of MM per 100,000 person-years (PY) with 95% confidence intervals (CI) were calculated for the cohort with stratification by gender, age group (20-49, 50-64, 65+ years) and type of TNF-α inhibitor (anti-TNF antibody, TNF fusion protein). Observed rates were compared to MM incidence rates from Surveillance, Epidemiology and End Results Program registries in the same time period and geographic regions. Standardized incidence ratios (SIR) and exact 95% CIs were calculated for those strata using Poisson regression.

Results

Among 114,045 incident users of TNF-α inhibitors, 82,003 (72%) used anti-TNF antibodies and 41,468 (36%) used TNF fusion protein alone or consecutively (after switching) during median follow up of 27 months and 205,635 PY overall. Rheumatoid arthritis (47%), psoriasis (21%) and inflammatory bowel disease (22%) were the most prevalent indications for TNF-α inhibitors, while fewer had psoriatic arthritis (15%) and ankylosing spondylitis (6%). There were 51 patients that developed MM during follow up, for a crude incidence rate (25 per 100,000 PY) that was higher than the expected rate (9 per 100,000 PY, age-standardized). TNF-α inhibitor users that developed MM were older (median: 57 vs. 49 years in non-cases) and had more concurrent treatment with corticosteroids (84% vs. 56%).

The overall age-standardized incidence ratio for MM was SIR=3.2 (95% CI 2.4-4.2), with even higher than expected incidence in younger age groups (20-49 years: SIR=5.5, 95% CI 2.5-10.5; 50-64 years: SIR=8.0, 95% CI 5.1-11.5) but not in older patients (65+ years: SIR=1.8, 95% CI 1.0-3.1). Estimates were slightly higher for anti-TNF antibodies (SIR=3.6, 95% CI 2.6-5.0) vs. TNF fusion protein (SIR=2.8, 95% CI 1.6-4.5) and slightly lower in females (SIR=3.0, 95% CI 2.0-4.3) vs. males (SIR=3.5, 95% CI 2.3-5.2).

Conclusions

In this large sample of patients treated with TNF-α inhibitors, we observed a higher incidence of MM diagnoses than would be expected from a similarly aged population. Other than a causal association between TNF-α inhibitors and increased MM risk, a possible explanation for these findings could be the relationship between the underlying autoimmune, inflammatory conditions and myeloma etiology, particularly with the greater disease severity that would warrant these medications vs. other, non-biologic disease-modifying antirheumatic drugs (DMARDs). Future research on the comparative safety with long-term use of TNF-α inhibitors and other DMARDs that can incorporate clinical information on disease severity is needed to better understand these conditions, their treatment and subsequent MM risk.

Disclosures: No relevant conflicts of interest to declare.

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