Publications by authors named "Viola Tozzi"

Background: Clinical trials comparing the efficacy of ocrelizumab (OCR) with other disease-modifying therapies (DMTs) other than interferon (IFN) β-1a in relapsing multiple sclerosis (RMS) are lacking.

Objectives: To compare the treatment effect of OCR vs six DMTs' (IFN β-1a, glatiramer acetate, fingolimod, dimethyl fumarate, teriflunomide, natalizumab) treatment pathways used in clinical practice by combining clinical trial and real-world data.

Methods: Patient-level data from OPERA trials and open-label extension phase, and from the German NeuroTransData (NTD) MS registry, were used to build 1:1 propensity score-matched (PSM) cohorts controlling for seven baseline covariates, including brain imaging activity.

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Background: Monoclonal antibodies (mAbs) targeting the calcitonin gene-related peptide (CGRP) pathway have shown good efficacy in migraine prophylaxis. However, a subset of patients does not respond to the first mAb treatment and switches among the available mAbs. The goal of this study is to characterize the switching pattern of migraine patients treated with anti-CGRP(-receptor, -R) mAbs, and to describe the headache burden of those who did not switch, switched once, and switched twice.

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Background: ImputAccur is a software tool to measure genotype-imputation accuracy. Imputation of untyped markers is a standard approach in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy for imputed genotypes is fundamental.

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Objective: To implement a dynamic data management and control framework that meets the multiple demands of high data quality, rigorous information technology security, and flexibility to continuously incorporate new methodology for a large disease registry.

Materials And Methods: Guided by relevant sections of the COBIT framework and ISO 27001 standard, we created a data control framework supporting high-quality real-world data (RWD) studies in multiple disease areas. We first mapped and described the entire data journey and identified potential risks for data loss or inconsistencies.

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Background: Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are implemented in imputation software, unfortunately diversely across platforms.

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Prenatal exposure to airborne particles is a potential risk factor for infant neuropsychological development. This issue is usually explored by regression analysis under the implicit assumption that all relevant confounders are accounted for. Our aim is to estimate the causal effect of prenatal exposure to high concentrations of airborne particles with a diameter < 2.

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Genome-wide association studies have led in the past to the discovery of susceptibility genes for many diseases including cancer and inflammatory conditions. However, a number of these studies did not realise their full potential. A first critical step in developing such large-scale studies is the choice of genotyping array with respect to the study goal.

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