Система дистанційної освіти та її захист

BACKGROUND: It is currently unknown whether early immunomodulatory treatment in relapsing-remitting MS (RRMS) can delay the transition to secondary progression (SP). OBJECTIVE: To compare the time interval from onset to SP in patients with RRMS between a contemporary cohort, treated with first generation disease modifying drugs (DMDs), and a historical control cohort. METHODS: We included a cohort of contemporary RRMS patients treated with DMDs, obtained from the Swedish National MS Registry (disease onset between 1995-2004, n = 730) and a historical population-based incidence cohort (onset 1950-64, n = 186). We retrospectively analyzed the difference in time to SP, termed the "period effect" within a 12-year survival analysis, using Kaplan-Meier and Cox regression analysis. RESULTS: We found that the "period" affected the entire severity spectrum. After adjusting for onset features, which were weaker in the contemporary material, as well as the therapy initiation time, the DMD-treated patients still exhibited a longer time to SP than the controls (hazard ratios: men, 0.32; women, 0.53). CONCLUSION: Our results showed there was a longer time to SP in the contemporary subjects given DMD. Our analyses suggested that this effect was not solely driven by the inclusion of benign cases, and it was at least partly due to the long-term immunomodulating therapy given

Cost of managing an episode of relapse in multiple sclerosis in the United States

BACKGROUND: The purpose of this study was to determine the direct medical US cost of managing multiple sclerosis relapses. METHODS: Direct data analysis and cost modeling were employed to derive typical resource use profiles and costs in 2002 US dollars, from the perspective of a third-party payer responsible for comprehensive health-care. The location and scope of health care services provided over a 90-day period were used to define three levels of relapse management. Hospitalization and resulting subsequent care was defined as high intensity management. A medium level of intervention was defined as either use of the emergency room, an observational unit, or administration of acute treatments, such as intravenous methylprednisolone in an outpatient or home setting. The lowest intensity of care comprised physician office visits and symptom-related medications. Data were obtained from many sources including all payer inpatient, ambulatory and emergency room databases from several states, fee schedules, government reports, and literature. All charges were adjusted using cost-to-charge ratios. RESULTS: Average cost per person for high management level was $12,870, based on analysis of 4,634 hospital cases (mean age 48 years, 73$1,847 and mild episode $243. CONCLUSIONS: Management strategies leading to a reduction in the frequency and severity of a relapse, less reliance on inpatient care, or increased access to steroid infusions in the home, would have a substantial impact on the economic consequences of managing relapses

Prediction of acute multiple sclerosis relapses by transcription levels of peripheral blood cells

<p>Abstract</p> <p>Background</p> <p>The ability to predict the spatial frequency of relapses in multiple sclerosis (MS) would enable physicians to decide when to intervene more aggressively and to plan clinical trials more accurately.</p> <p>Methods</p> <p>In the current study our objective was to determine if subsets of genes can predict the time to the next acute relapse in patients with MS. Data-mining and predictive modeling tools were utilized to analyze a gene-expression dataset of 94 non-treated patients; 62 patients with definite MS and 32 patients with clinically isolated syndrome (CIS). The dataset included the expression levels of 10,594 genes and annotated sequences corresponding to 22,215 gene-transcripts that appear in the microarray.</p> <p>Results</p> <p>We designed a two stage predictor. The first stage predictor was based on the expression level of 10 genes, and predicted the time to next relapse with a resolution of 500 days (error rate 0.079, p < 0.001). If the predicted relapse was to occur in less than 500 days, a second stage predictor based on an additional different set of 9 genes was used to give a more accurate estimation of the time till the next relapse (in resolution of 50 days). The error rate of the second stage predictor was 2.3 fold lower than the error rate of random predictions (error rate = 0.35, p < 0.001). The predictors were further evaluated and found effective both for untreated MS patients and for MS patients that subsequently received immunomodulatory treatments after the initial testing (the error rate of the first level predictor was < 0.18 with p < 0.001 for all the patient groups).</p> <p>Conclusion</p> <p>We conclude that gene expression analysis is a valuable tool that can be used in clinical practice to predict future MS disease activity. Similar approach can be also useful for dealing with other autoimmune diseases that characterized by relapsing-remitting nature.</p