Abstract
As more biologics are approved, there is increasing interest in comparative effectiveness research (CER). Health insurance claims databases have encounter data but seldom contain clinical outcomes. recently published algorithm assessed the clinical effectiveness of RA biologics using VA claims data and validated against the DAS28ESR[1] had a sensitivity, 72% (95% CI = 67- 77%) and specificity, 91% (95% CI = 89- 93%). The accompanying editorial [2] commented, A claims-based effectiveness algorithm with acceptable performance characteristics across different data settings will be a powerful and desired tool for CER of RA. Such an algorithm will enable large-scale, population-based studies comparing the effectiveness of different DMARD regimens. Such studies will facilitate head-to-head comparisons, supplementing typical randomized controlled trials and prospective registries that usually include disease activity...Whether the algorithm will have a similar performance in other claims databases therefore needs to be further examined. We performed an independent analysis to evaluate the algorithm's positive predictive value (PPV) in a commercial claims data source compared to a clinical gold standard.
Highlights
As more biologics are approved, there is increasing interest in comparative effectiveness research (CER)
Data came from a previous comparative effectiveness study linking outpatient medical records from multiple US institutions and physician practices to commercial claims data from OptumInsight (Eden Prairie, MN, USA) [3] that evaluated the effectiveness of etanercept (ETN), adalimumab (ADA), and infliximab (INF) in biologic naïve adult rheumatoid arthritis (RA) patients persistent on their initial biologic for at least 1 year from 2006 to 2008
Sensitivity, specificity, and negative predictive value could not be determined, because patients switching biologic agents were excluded from the original study
Summary
As more biologics are approved, there is increasing interest in comparative effectiveness research (CER). In an editorial in the same issue, Kim and Solomon [2] commented the following: ‘a claims-based effectiveness algorithm with acceptable performance characteristics across different data settings will be a powerful and desired tool for CER of RA. Such an algorithm will enable large-scale, population-based studies comparing the effectiveness of different DMARD [disease-modifying antirheumatic drug] regimens. Such studies will facilitate head-to-head comparisons, supplementing typical randomized controlled trials and prospective registries that usually include disease activity. We performed an independent analysis to evaluate the algorithm’s positive predictive value (PPV) in a commercial claims data source compared with a clinical gold standard
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