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Abstract Number: 1698

Predictors of Discontinuation of Biologics in 2,281 US Patients with Rheumatoid Arthritis

Sofia Ramiro1, Frederick Wolfe2, David J. Harrison3, George Joseph3, David H. Collier3, Désirée van der Heijde4, Robert Landewé5 and Kaleb Michaud6, 1Clinical Immunology & Rheumatology, Academic Medical Center, University of Amsterdam, The Netherlands and Hospital Garcia de Orta, Almada, Portugal, 2National Data Bank for Rheumatic Diseases, Wichita, KS, 3Amgen Inc., Thousand Oaks, CA, 4Rheumatology, Leiden University Medical Center, Leiden, Netherlands, 5Clinical Immunology & Rheumatology, Academic Medical Center, University of Amsterdam and Atrium Medical Center, Heerlen, Netherlands, 6Rheumatology, National Data Bank for Rheumatic Diseases & University of Nebraska Medical Center, Omaha, NE

Meeting: 2012 ACR/ARHP Annual Meeting

Keywords: biologic response modifiers, outcome measures and rheumatoid arthritis (RA)

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Session Information

Session Title: Rheumatoid Arthritis Treatment - Small Molecules, Biologics and Gene Therapy: Safety II

Session Type: Abstract Submissions (ACR)

Background/Purpose: Identifying predictors of discontinuation of biologic treatment for Rheumatoid Arthritis (RA) has clinical and research importance given the chronicity of RA and high costs and potential side effects of these agents. Our aim was to identify predictors of biologic discontinuation in patients with RA.

Methods: We studied patients with RA starting their first biologic while participating in an ongoing US longitudinal cohort study (1998 -2011). Patients provided all medication use, demographics, and clinical status via semiannual questionnaires. Discontinuation was analyzed through Cox multivariable regression models with baseline predictors adjusted by the biologic drug class patients were on (anti-TNF vs other) and a variable reflecting the onset after Jan 1, 2005, when more biologic treatment options became available. Three pre-specified prediction models were developed, a “research” model, with all significant variables, a “clinical” model, reflecting variables more commonly used in clinical practice and one restricted to patients that started a biologic after Jan 1, 2005. Forward selection was performed until the best-fit model was obtained, taking confounding effects into account.

Results: A total of 2,281 RA patients initiated their first biologic; 1,100 (48%) discontinued. Age, smoking status and comorbidity index were positive baseline predictors of discontinuation (Table). Methotrexate use and higher SF-36 PCS and MCS scores were associated with less risk of discontinuation. In the “clinical” model, patient global assessment was positively associated with discontinuation. The discontinuation among patients starting biologics after 2005 was associated with a higher patient global assessment and inversely predicted by BMI.

Conclusion: Worse overall health strongly predicted biologic discontinuation in RA. Co-medication with methotrexate independently contributed to a lower biologic discontinuation. A higher number of comorbidities and a smoking status were also predictive of biologic discontinuation. The predictors of discontinuation might guide the clinician when starting a biologic therapy.  While these are important factors leading to discontinuation, their impact is lessened when there are more biologic therapies to choose from.

Table. Hazard ratios (95% CI) of baseline predictors of biologic discontinuation in RA

 

Research model

 

 Clinical model

 

≥2005 model

 

Age (years)

1.01 (1.00; 1.01)

1.01 (1.00; 1.01)

**

BMI (kg/m2)

§

§

0.97 (0.94; 0.99)

Patient global (0-10)

**

1.05 (1.03; 1.08)

1.13(1.06; 1.20)

Comorbidity index (0-9)

1.08 (1.04; 1.13)

1.11 (1.06; 1.15)

**

Smoking

1.21 (1.01; 1.45)

1.23 (1.03; 1.47)

§

MTX

0.83 (0.73; 0.94)

0.84 (0.74; 0.95)

§

SF-36 MCS (0-100)

0.99 (0.98; 0.99)

¥

**

SF-36 PCS (0-100)

0.99 (0.98; 0.99)

¥

§

Adjusted for biologic drug class (anti-TNF vs other) and onset≥2005

§ Not included in the multivariable model (not significant in the univariable model) **Not selected during multivariable regression analysis (p≥0.05)

¥ Not included in this short “clinical” model (to present a model with variables more used in clinical practice)


Disclosure:

S. Ramiro,
None;

F. Wolfe,
None;

D. J. Harrison,

Amgen,

1,

Amgen,

3;

G. Joseph,

Amgen Inc.,

1,

Amgen Inc.,

3;

D. H. Collier,

Amgen Inc.,

1,

Amgen Inc.,

3;

D. van der Heijde,

Abbott, Amgen, AstraZeneca, BMS, Centocor, Chugai, Eli-Lilly, GSK, Merck, Novartis, Otsuka, Pfizer Inc., Roche, Sanofi-Aventis, Schering-Plough, UCB, Wyeth,

5,

Imaging Rheumatology,

4;

R. Landewé,

Rheumatology Consultancy BV ,

4,

Abbott, Amgen, AstraZeneca, BMS, Centocor, GSK, Merck, Novartis, Pfizer, Roche, Schering-Plough, UCB, Wyeth,

5;

K. Michaud,
None.

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