scholarly journals Investigating Determinants of Multiple Sclerosis in Longitunal Studies: A Bayesian Approach

2009 ◽  
Vol 2009 ◽  
pp. 1-24 ◽  
Author(s):  
Clelia Di Serio ◽  
Claudia Lamina
Keyword(s):  
Multiple Sclerosis ◽  
Longitudinal Studies ◽  
Bayesian Approach ◽  
Statistical Models ◽  
Time Intervals ◽  
Response Variable ◽  
Smooth Effects ◽  
Nonlinear Smooth ◽  
Modelling Data

Modelling data from Multiple Sclerosis longitudinal studies is a challenging topic since the phenotype of interest is typically ordinal; time intervals between two consecutive measurements are nonconstant and they can vary among individuals. Due to these unobservable sources of heterogeneity statistical models for analysis of Multiple Sclerosis severity evolve as a difficult feature. A few proposals have been provided in the biostatistical literature (Heijtan (1991); Albert, (1994)) to address the issue of investigating Multiple Sclerosis course. In this paper Bayesian P-Splines (Brezger and Lang, (2006); Fahrmeir and Lang (2001)) are indicated as an appropriate tool since they account for nonlinear smooth effects of covariates on the change in Multiple Sclerosis disability. By means of Bayesian P-Spline model we investigate both the randomness affecting Multiple Sclerosis data as well as the ordinal nature of the response variable.

Increasing incidence of multiple sclerosis in women in Northern Finland

2010 ◽  
Vol 17 (2) ◽  
pp. 133-138 ◽  
Author(s):  
O Krökki ◽  
R Bloigu ◽  
M Reunanen ◽  
AM Remes
Keyword(s):  
Multiple Sclerosis ◽  
Geographical Location ◽  
Epidemiological Studies ◽  
The Arctic ◽  
Time Intervals ◽  
The Past ◽  
Mcdonald Criteria ◽  
Epidemiological Features ◽  
High Prevalence ◽  
The Mean

Background: The geographical distribution of multiple sclerosis (MS) means that prevalence rates increase with latitude north or south of the equator. Temporally, a tendency for increased incidences of MS has been observed over the past two decades. Objectives: Since epidemiological studies of MS in areas close to the Arctic Circle are rare, we evaluated the incidence and prevalence of MS in Northern Ostrobothnia by means of a retrospective cohort study covering the period 1992–2007. Methods: Patients with a definite clinical diagnosis of MS based on the Poser criteria and the early McDonald criteria of 2001 were identified in the region of Northern Ostrobothnia (population 386,972) and the incidence was calculated at 1-year time intervals, both overall and by gender. Results: The overall prevalence was 103/100,000 (95% CI, 93–113), with a female/male ratio of 2.17. The mean overall incidence was 6.3/100,000 (95% CI, 5.2–7.2). The incidence shows a tendency to increase over the 16-year period due to a pronounced rise in the female incidence. Conclusions: Our results show a high prevalence of MS in Northern Ostrobothnia and a disproportional increase in the female MS incidence. These recent epidemiological features may be associated with environmental risk factors such as a vitamin D deficit, low life-long UV radiation and the high-latitude geographical location.

Measuring evoked responses in multiple sclerosis

1999 ◽  
Vol 5 (4) ◽  
pp. 263-267 ◽  
Author(s):  
Giancarlo Comi ◽  
Letizia Leocani ◽  
Stefania Medaglini ◽  
Tiziana Locatelli ◽  
Vittorio Martinelli ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Disease Activity ◽  
Longitudinal Studies ◽  
Negative Impact ◽  
Diagnostic Value ◽  
Clinical Findings ◽  
Therapeutic Interventions ◽  
Evoked Responses ◽  
Central Nervous System Damage ◽  
Disease Evolution

Evoked potentials (EPs) have been widely utilised in Multiple Sclerosis (MS) patients to demonstrate the involvement of sensory and motor pathways. Their diagnostic value is based on the ability to reveal clinically silent lesions and to objectivate the central nervous system damage in patients who complain frequently of vague and indefinite disturbances which frequently occurs in the early phases of the disease. The advent of magnetic resonance imaging (MRI) techniques has greatly reduced the clinical utilisation of EPs, which is not fully justifiable, as the information provided by EPs are quite different from those provided by MRI. The abnormalities of evoked responses reflect the global damage of the evoked nervous pathway and are significantly correlated with the clinical findings, while the vast majority of MRI lesions are not associated to symptoms and signs. Transversal and longitudinal studies have demonstrated that EP changes in MS are more strictly related to disability than MRI lesion burden. On the contrary, MRI is more sensitive than EPs in revealing the disease activity. Evoked responses modifications observed in MS are not disease-specific; moreover longitudinal studies showed latency and morphology changes of evoked responses not always related to clinical changes. Such a dissociation can be explained both by technical factors and by subclinical disease activity. To reduce the negative impact of technical aspects, only reproducible parameters of the evoked responses should be used to monitor disease evolution and therapeutic interventions.

A subtraction pipeline for automatic detection of new appearing multiple sclerosis lesions in longitudinal studies

2014 ◽  
Vol 56 (5) ◽  
pp. 363-374 ◽  
Author(s):  
Onur Ganiler ◽  
Arnau Oliver ◽  
Yago Diez ◽  
Jordi Freixenet ◽  
Joan C. Vilanova ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Longitudinal Studies ◽  
Automatic Detection

scholarly journals Randomized two dimensional between patient response surface pathway design with two interventional and one response variable in estimating minimum efficacy dose

2019 ◽  
Vol 6 (3) ◽  
pp. 75
Author(s):  
Stig Larsen ◽  
Trond Holand ◽  
Kjell Bjørnæs ◽  
Espen Glomsrød ◽  
Joachim Kaufmann ◽  
...  
Keyword(s):  
Gastroesophageal Reflux Disease ◽  
Two Dimensional ◽  
Gerd Patient ◽  
Percent Reduction ◽  
Time Intervals ◽  
Patient Response ◽  
Response Variable ◽  
One Dimensional ◽  
The Third ◽  
Common Response

<p class="abstract"><strong>Background:</strong> The aim of this paper is to introduce and evaluate the RSP design with two interventional and one response variable exemplified by estimating minimum efficacy dose (MED) of osteopathic manual therapy (OMT) in treatment of gastroesophageal reflux disease (GERD).</p><p class="abstract"><strong>Methods:</strong> 15 GERD patients, divided in three design-level with three, five and seven patients. The study was performed as a randomized two-dimensional, between-patient RSP designed multicenter study with two interventional– and one response variable. The interventional variables “Number of OMT’s” and “Treatment Interval” with common response variable, formed two independent one-dimensional randomized between-patient RSP studies. The response variable was percent reduction in sum of the five GERD score from baseline. Three GERD patients were allocated on the first design level and given six OMT with five days’ interval. Based on results obtained in the first and second design level, five patients were included to the second design level and seven to the third.</p><p class="abstract"><strong>Results:</strong> The two-dimensional randomized between-patient RSP-design with the combined outcome procedure worked as expected. The percent reduction in GERD score increased with increasing number of OMT’s and time intervals. This increase leveled out after three to five OMT’s and three to four days between treatments. A clinical interaction between the two interventional variables was obtained. The estimated MED of OMT in treatment of GERD was three treatments with two days between treatments.</p><p class="abstract"><strong>Conclusions: </strong>The suggested two-dimensional, randomized between-patient RSP-design worked as expected and estimated MED of OMT in GERD patient sufficiently.</p><em> </em>

Ecological Data Exploration

2019 ◽  
pp. 27-62
Author(s):  
Mohamed Elhadi Rahmani ◽  
Abdelmalek Amine
Keyword(s):  
Remote Sensing ◽  
Data Mining ◽  
Statistical Models ◽  
Earth Science ◽  
Data Exploration ◽  
Statistical Techniques ◽  
Ecological Data ◽  
Response Variable ◽  
Use Of Data ◽  
Sources Of Variation

Computer modeling of ecological systems is the activity of implementing computer solutions to analyze data related to the fields of remote sensing, earth science, biology, and oceans. The ecologists analyze the data to identify the relationships between a response and a set of predictors, using statistical models that do not accurately describe the main sources of variation in the response variable. Knowledge discovery techniques are often more powerful, flexible, and effective for exploratory analysis than statistical techniques. This chapter aims to test the use of data mining in ecology. It will discuss the exploration of ecological data by defining at first data mining, its advantages, and its different types. Then the authors detail the field of bio-inspiration and meta-heuristics. And finally, they give case studies from where they applied these two areas to explore ecological data.

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