Early predictors of non-response to interferon in multiple sclerosis
Jazyk angličtina Země Dánsko Médium print-electronic
Typ dokumentu časopisecké články, randomizované kontrolované studie, práce podpořená grantem
- MeSH
- dospělí MeSH
- dvojitá slepá metoda MeSH
- imunologické faktory terapeutické užití MeSH
- interferon beta terapeutické užití MeSH
- interpretace obrazu počítačem MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- prognóza MeSH
- relabující-remitující roztroušená skleróza farmakoterapie patologie MeSH
- ROC křivka MeSH
- senzitivita a specificita MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- randomizované kontrolované studie MeSH
- Názvy látek
- imunologické faktory MeSH
- interferon beta MeSH
OBJECTIVE: To identify early clinical and MRI predictors of non-response to interferon (IFN) treatment in multiple sclerosis (MS). METHODS: In 172 patients with relapsing-remitting MS treated with IFNβ, we evaluated prediction of future treatment non-response. Candidate predictors comprised disability and its sustained progression, relapse score (combining frequency and severity of relapses), brain volume change, brain parenchymal fraction, number of new T2 lesions, and T2 and T1 lesion volume within the initial year of treatment. Treatment non-response was evaluated as confirmed disability progression or overall average annual relapse score exceeding 1 over the following 5 years. Logistic regression model was adjusted for patient age, gender, disease duration and changes in treatment. RESULTS: Ninety patients (52%) reached the status of IFN non-responders in years 2-6. Patients with ≥1 new T2 lesion and relapse score ≥2 (odds ratio ≥5.7) or those with ≥3 new T2 lesions regardless of the relapse score (odds ratio = 3) were in a significantly higher risk of future treatment non-response. CONCLUSIONS: In patients with MS treated with IFNβ for 1 year, number of new T2 lesions and annualized relapse score predict individual risk of treatment non-response over the following 5 years.
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