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- Fragoulis, George E., et al.
(author)
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2022 EULAR recommendations for screening and prophylaxis of chronic and opportunistic infections in adults with autoimmune inflammatory rheumatic diseases
- 2023
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In: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 82:6, s. 742-753
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Journal article (peer-reviewed)abstract
- Objectives: To develop EULAR recommendations for screening and prophylaxis of chronic and opportunistic infections in patients with autoimmune inflammatory rheumatic diseases (AIIRD). Methods: An international Task Force (TF) (22 members/15 countries) formulated recommendations, supported by systematic literature review findings. Level of evidence and grade of recommendation were assigned for each recommendation. Level of agreement was provided anonymously by each TF member. Results: Four overarching principles (OAP) and eight recommendations were developed. The OAPs highlight the need for infections to be discussed with patients and with other medical specialties, in accordance with national regulations. In addition to biologic/targeted synthetic disease-modifying antirheumatic drugs (DMARDs) for which screening for latent tuberculosis (TB) should be performed, screening could be considered also before conventional synthetic DMARDs, glucocorticoids and immunosuppressants. Interferon gamma release assay should be preferred over tuberculin skin test, where available. Hepatitis B (HBV) antiviral treatment should be guided by HBV status defined prior to starting antirheumatic drugs. All patients positive for hepatitis-C-RNA should be referred for antiviral treatment. Also, patients who are non-immune to varicella zoster virus should be informed about the availability of postexposure prophylaxis should they have contact with this pathogen. Prophylaxis against Pneumocystis jirovecii seems to be beneficial in patients treated with daily doses >15-30 mg of prednisolone or equivalent for >2-4 weeks. Conclusions: These recommendations provide guidance on the screening and prevention of chronic and opportunistic infections. Their adoption in clinical practice is recommended to standardise and optimise care to reduce the burden of opportunistic infections in people living with AIIRD.
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| 2. |
- Mongin, Denis, et al.
(author)
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Imputing missing data of function and disease activity in rheumatoid arthritis registers : What is the best technique?
- 2019
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In: RMD Open. - : BMJ. - 2056-5933. ; 5:2
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Journal article (peer-reviewed)abstract
- Objective To compare several methods of missing data imputation for function (Health Assessment Questionnaire) and for disease activity (Disease Activity Score-28 and Clinical Disease Activity Index) in rheumatoid arthritis (RA) patients. Methods One thousand RA patients from observational cohort studies with complete data for function and disease activity at baseline, 6, 12 and 24 months were selected to conduct a simulation study. Values were deleted at random or following a predicted attrition bias. Three types of imputation were performed: (1) methods imputing forward in time (last observation carried forward; linear forward extrapolation); (2) methods considering data both forward and backward in time (nearest available observation - NAO; linear extrapolation; polynomial extrapolation); and (3) methods using multi-individual models (linear mixed effects cubic regression - LME3; multiple imputation by chained equation - MICE). The performance of each estimation method was assessed using the difference between the mean outcome value, the remission and low disease activity rates after imputation of the missing values and the true value. Results When imputing missing baseline values, all methods underestimated equally the true value, but LME3 and MICE correctly estimated remission and low disease activity rates. When imputing missing follow-up values at 6, 12, or 24 months, NAO provided the least biassed estimate of the mean disease activity and corresponding remission rate. These results were not affected by the presence of attrition bias. Conclusion When imputing function and disease activity in large registers of active RA patients, researchers can consider the use of a simple method such as NAO for missing follow-up data, and the use of mixed-effects regression or multiple imputation for baseline data.
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