Little Evidence for Usefulness of Biomarkers for Predicting Successful Dose Reduction or Discontinuation of a Biologic Agent in Rheumatoid Arthritis: A Systematic Review
SourceArthritis & Rheumatology, 69, 2, (2017), pp. 301-308
Article / Letter to editor
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Arthritis & Rheumatology
SubjectRadboudumc 5: Inflammatory diseases RIHS: Radboud Institute for Health Sciences
OBJECTIVE: To systematically review studies addressing prediction of successful dose reduction or discontinuation of a biologic agent in rheumatoid arthritis (RA). METHODS: PubMed, Embase, and Cochrane Library databases were searched for studies that examined the predictive value of biomarkers for successful dose reduction or discontinuation of a biologic agent in RA. Two reviewers independently selected studies, and extracted data and assessed the risk of bias. A biomarker was classified as a "potential predictor" if the univariate association was either strong (odds ratio or hazard ratio >2.0 or <0.5) or statistically significant. For biomarkers that were studied multiple times, qualitative best-evidence synthesis was performed separately for the prediction of successful dose reduction and discontinuation. Biomarkers that were defined in >/=75% of the studies as potential predictors were regarded as "predictor" for the purposes of our study. RESULTS: Of 3,029 nonduplicate articles initially searched, 16 articles regarding 15 cohorts were included in the present study. Overall, 17 biomarkers were studied multiple times for the prediction of successful dose reduction, and 33 for the prediction of successful discontinuation of a biologic agent. Three predictors were identified: higher adalimumab trough level for successful dose reduction and lower Sharp/van der Heijde erosion score and shorter symptom duration at the start of a biologic agent for successful discontinuation. CONCLUSION: The predictive value of a wide variety of biomarkers for successful dose reduction or discontinuation of biologic treatment in RA has been investigated. We identified only 3 biomarkers as predictors, in just 2 studies. The strength of the evidence is limited by the low quality of the included studies and the likelihood of reporting bias and multiple testing.
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