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Published on: December 9, 2015
Prevalence, Predictors, and Prognostic Benefits of Remission Achievement in Patients With Systemic Lupus
Ziyi Yang1, Cheng Cheng1, Ziqian Wang1
1Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, National Clinical Research Center for Dermatologic and Immunologic Diseases, Ministry of Science and Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China.
Objective:
To systematically review and evaluate the prevalence, potential predictors, and prognostic benefits of remission achievement in patients with systemic lupus erythematosus (SLE).
Methods:
Studies reporting on the prevalence, predictors, and prognostic benefits of remission in adult patients with SLE were searched and selected from PubMed and Embase databases. Studies were reviewed for relevance and quality. Two reviewers independently assessed the studies and extracted data.
Results:
Data from 41 studies including 17,270 patients were included and analyzed. Although no consensus has been achieved on the definition of remission, clinical disease activity, serologic activity, duration, and treatment are agreed to be critical components of defining remission status. In most studies published in the recent 5 years, 42.4-88% of patients achieved and maintained the remission status for 1 year, and 21.1-70% did so for at least 5 years. Factors associated with remission included older age at diagnosis, lower baseline disease activity, and absence of major organ involvement, while positive serologic results were shown to be negatively associated with remission. Remission (especially prolonged remission) when achieved, demonstrated an association with lower accrual of damage and better quality of life among patients with SLE.
Conclusion:
Remission is an achievable and desirable target for SLE patients and proven to be associated with prognostic benefits. Further development and assessment of a clear remission definition, a risk stratification model, as well as a full algorithm with frequency of monitoring time points for treatment adjustment and drug withdrawal are required.
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