OBJECTIVE: Disease-modifying therapies, such as fingolimod, interferon (IFN) and glatiramer acetate (GA), have differing effects on relapse rates in patients with multiple sclerosis (MS), but little is known about the real-world differences in relapse rates with these treatments. This retrospective study assessed relapse rates in patients with active MS initiating fingolimod, IFN or GA therapy in a real-world setting. METHODS: Using administrative claims data from the US PharMetrics Plus database, we identified previously treated and untreated patients with MS who initiated fingolimod, IFN or GA treatment between 1 October 2010 and 31 March 2011 and had experienced a relapse in the previous year. A claims-based algorithm was used to identify relapses over the persistence period in patients with 540 days of post-index continuous enrolment. A logistic regression model assessed the probability of having at least one relapse and a generalized linear model estimated differences in annualized relapse rates (ARRs). RESULTS: The study enrolled 525 patients (fingolimod, n = 128; combined IFN/GA cohort, n = 397) of the 31,041 initially identified. Similar findings for fingolimod and IFN/GA were observed for the unadjusted proportion of patients experiencing relapses (31.3% vs. 34.0%, respectively; p = 0.5653) and ARRs (0.50 vs. 0.55, respectively) while persistent to treatment. After adjusting for baseline differences, fingolimod was associated with a 52% reduction in the probability of having a relapse (odds ratio, 0.48; 95% confidence interval [CI], 0.28-0.84; p = 0.0097) and a 50% reduction in ARR (rate ratio, 0.50; 95% CI, 0.34-0.75; p = 0.0006) compared with IFN/GA. LIMITATIONS: Identification of relapses is based on the claims in the database rather than on a clinical assessment. CONCLUSIONS: In a real-world setting, fingolimod was shown to be associated with significantly lower relapse rates than IFN/GA in patients with MS who had a history of relapses.
OBJECTIVE: Disease-modifying therapies, such as fingolimod, interferon (IFN) and glatiramer acetate (GA), have differing effects on relapse rates in patients with multiple sclerosis (MS), but little is known about the real-world differences in relapse rates with these treatments. This retrospective study assessed relapse rates in patients with active MS initiating fingolimod, IFN or GA therapy in a real-world setting. METHODS: Using administrative claims data from the US PharMetrics Plus database, we identified previously treated and untreated patients with MS who initiated fingolimod, IFN or GA treatment between 1 October 2010 and 31 March 2011 and had experienced a relapse in the previous year. A claims-based algorithm was used to identify relapses over the persistence period in patients with 540 days of post-index continuous enrolment. A logistic regression model assessed the probability of having at least one relapse and a generalized linear model estimated differences in annualized relapse rates (ARRs). RESULTS: The study enrolled 525 patients (fingolimod, n = 128; combined IFN/GA cohort, n = 397) of the 31,041 initially identified. Similar findings for fingolimod and IFN/GA were observed for the unadjusted proportion of patients experiencing relapses (31.3% vs. 34.0%, respectively; p = 0.5653) and ARRs (0.50 vs. 0.55, respectively) while persistent to treatment. After adjusting for baseline differences, fingolimod was associated with a 52% reduction in the probability of having a relapse (odds ratio, 0.48; 95% confidence interval [CI], 0.28-0.84; p = 0.0097) and a 50% reduction in ARR (rate ratio, 0.50; 95% CI, 0.34-0.75; p = 0.0006) compared with IFN/GA. LIMITATIONS: Identification of relapses is based on the claims in the database rather than on a clinical assessment. CONCLUSIONS: In a real-world setting, fingolimod was shown to be associated with significantly lower relapse rates than IFN/GA in patients with MS who had a history of relapses.
Authors: Jonathan Alsop; Jennie Medin; Christian Cornelissen; Stefan Viktor Vormfelde; Tjalf Ziemssen Journal: PLoS One Date: 2017-05-05 Impact factor: 3.240
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