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Predictors of infection in rheumatoid arthritis.
Arthritis Rheum. 2002 Sep; 46(9):2294-300.AR

Abstract

OBJECTIVE

Patients with rheumatoid arthritis (RA) have been shown to have an increased susceptibility to the development of infections. The exact causes of this increased risk are unknown, but may relate to immunologic disturbances associated with the disease or to the immunosuppressive effects of agents used in its treatment. This study was undertaken to identify predictors of serious infections among patients with RA. Identification of such factors is the necessary first step in reducing the excess risk of infection in RA.

METHODS

Members of a population-based incidence cohort of Rochester, Minnesota residents ages >or=18 years, who had been diagnosed with RA between 1955 and 1994, were followed up longitudinally through their complete medical records until January 1, 2000. We examined potential risk factors for the development of all objectively confirmed (by microbiology or radiology) infections and for infections requiring hospitalization. Potential risk factors included RA severity measures (rheumatoid factor positivity, elevated erythrocyte sedimentation rate, extraarticular manifestations of RA, and functional status), comorbidities (diabetes mellitus, alcoholism, and chronic lung disease), and other risk factors for infection (presence of leukopenia, smoking). Predictors were identified using multivariate time-dependent Cox proportional hazards modeling.

RESULTS

The 609 RA patients in the cohort had a total followup time of 7,729.7 person-years (mean 12.7 years per patient). A total of 389 patients (64%) had at least 1 infection with objective confirmation, and 290 (48%) had at least 1 infection requiring hospitalization. Increasing age, presence of extraarticular manifestations of RA, leukopenia, and comorbidities (chronic lung disease, alcoholism, organic brain disease, and diabetes mellitus), as well as use of corticosteroids, were strong predictors of infection (P < 0.004) in both univariate and multivariate analyses. Notably, use of disease-modifying antirheumatic drugs was not associated with increased risk of infection in multivariate analyses, after adjustment for demographic characteristics, comorbidities, and disease-related variables.

CONCLUSION

We identified a number of strong predictors of infections in a population-based cohort of patients with RA. These results can be used to prospectively identify high-risk patients, who may benefit from closer followup and implementation of preventive strategies.

Authors+Show Affiliations

Beaumont Hospital, Dublin, Ireland.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, P.H.S.

Language

eng

PubMed ID

12355476

Citation

Doran, Michele F., et al. "Predictors of Infection in Rheumatoid Arthritis." Arthritis and Rheumatism, vol. 46, no. 9, 2002, pp. 2294-300.
Doran MF, Crowson CS, Pond GR, et al. Predictors of infection in rheumatoid arthritis. Arthritis Rheum. 2002;46(9):2294-300.
Doran, M. F., Crowson, C. S., Pond, G. R., O'Fallon, W. M., & Gabriel, S. E. (2002). Predictors of infection in rheumatoid arthritis. Arthritis and Rheumatism, 46(9), 2294-300.
Doran MF, et al. Predictors of Infection in Rheumatoid Arthritis. Arthritis Rheum. 2002;46(9):2294-300. PubMed PMID: 12355476.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Predictors of infection in rheumatoid arthritis. AU - Doran,Michele F, AU - Crowson,Cynthia S, AU - Pond,Gregory R, AU - O'Fallon,W Michael, AU - Gabriel,Sherine E, PY - 2002/10/2/pubmed PY - 2002/11/26/medline PY - 2002/10/2/entrez SP - 2294 EP - 300 JF - Arthritis and rheumatism JO - Arthritis Rheum VL - 46 IS - 9 N2 - OBJECTIVE: Patients with rheumatoid arthritis (RA) have been shown to have an increased susceptibility to the development of infections. The exact causes of this increased risk are unknown, but may relate to immunologic disturbances associated with the disease or to the immunosuppressive effects of agents used in its treatment. This study was undertaken to identify predictors of serious infections among patients with RA. Identification of such factors is the necessary first step in reducing the excess risk of infection in RA. METHODS: Members of a population-based incidence cohort of Rochester, Minnesota residents ages >or=18 years, who had been diagnosed with RA between 1955 and 1994, were followed up longitudinally through their complete medical records until January 1, 2000. We examined potential risk factors for the development of all objectively confirmed (by microbiology or radiology) infections and for infections requiring hospitalization. Potential risk factors included RA severity measures (rheumatoid factor positivity, elevated erythrocyte sedimentation rate, extraarticular manifestations of RA, and functional status), comorbidities (diabetes mellitus, alcoholism, and chronic lung disease), and other risk factors for infection (presence of leukopenia, smoking). Predictors were identified using multivariate time-dependent Cox proportional hazards modeling. RESULTS: The 609 RA patients in the cohort had a total followup time of 7,729.7 person-years (mean 12.7 years per patient). A total of 389 patients (64%) had at least 1 infection with objective confirmation, and 290 (48%) had at least 1 infection requiring hospitalization. Increasing age, presence of extraarticular manifestations of RA, leukopenia, and comorbidities (chronic lung disease, alcoholism, organic brain disease, and diabetes mellitus), as well as use of corticosteroids, were strong predictors of infection (P < 0.004) in both univariate and multivariate analyses. Notably, use of disease-modifying antirheumatic drugs was not associated with increased risk of infection in multivariate analyses, after adjustment for demographic characteristics, comorbidities, and disease-related variables. CONCLUSION: We identified a number of strong predictors of infections in a population-based cohort of patients with RA. These results can be used to prospectively identify high-risk patients, who may benefit from closer followup and implementation of preventive strategies. SN - 0004-3591 UR - https://www.unboundmedicine.com/medline/citation/12355476/Predictors_of_infection_in_rheumatoid_arthritis_ L2 - https://doi.org/10.1002/art.10529 DB - PRIME DP - Unbound Medicine ER -