Disease modifying therapy have changed the natural evolution of multiple sclerosis (MS), with efficacy demonstrated in randomized clinical trials. Standard-of-care effectiveness is needed to complement clinical trial data and highlight outcomes in real-world practice, but comparing prospective patients with historical cohorts likely introduces biases. To address these potential biases, assigning a patient with a score that expresses his/her disease prognosis before starting a therapy may make it possible to evaluate the unbiased ability of the therapy to modify disease natural history. Thus, we aimed at analyzing the effectiveness of intramuscular interferon-β1a (im IFN-β1a) matching by BREMSO score (Bayesian Risk Estimate for Multiple Sclerosis at Onset) a prospective real-world cohort of treated patients with a historical cohort of untreated patients.

A method to compare prospective and historical cohorts to evaluate drug effects. Application to the analysis of early treatment effectiveness of intramuscular interferon-β1a in multiple sclerosis patients

Patti, Francesco;
2020-01-01

Abstract

Disease modifying therapy have changed the natural evolution of multiple sclerosis (MS), with efficacy demonstrated in randomized clinical trials. Standard-of-care effectiveness is needed to complement clinical trial data and highlight outcomes in real-world practice, but comparing prospective patients with historical cohorts likely introduces biases. To address these potential biases, assigning a patient with a score that expresses his/her disease prognosis before starting a therapy may make it possible to evaluate the unbiased ability of the therapy to modify disease natural history. Thus, we aimed at analyzing the effectiveness of intramuscular interferon-β1a (im IFN-β1a) matching by BREMSO score (Bayesian Risk Estimate for Multiple Sclerosis at Onset) a prospective real-world cohort of treated patients with a historical cohort of untreated patients.
2020
BREMSO; Bayesian analysis; Beta-interferon; Multiple sclerosis; Prognosis natural history
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/381250
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