Multiple sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system. The progression and severity of MS varies by individual, but it is generally a disabling disease. Although medications have been developed to slow the disease progression and help manage symptoms, MS research has yet to result in a cure. Early diagnosis and treatment of the disease have been shown to be effective at slowing the development of disabilities. However, early MS diagnosis is difficult because symptoms are intermittent and shared with other diseases. Thus most previous works have focused on uncovering the risk factors associated with MS and predicting the progression of disease after a diagnosis rather than disease prediction. This paper investigates the use of data available in electronic medical records (EMRs) to create a risk prediction model; thereby helping clinicians perform the difficult task of diagnosing an MS patient. Our results demonstrate that even given a limited time window of patient data, one can achieve reasonable classification with an area under the receiver operating characteristic curve of 0.724. By restricting our features to common EMR components, the developed models also generalize to other healthcare systems.
Other autoimmune disorders and specific cancers have been proposed as potential comorbidities to MS. In a paper that summarized the environmental features researched in etiological research on MS @cite_9 , Lauer noted that inflammatory bowel disease (IBD), ulcerative colitis, and Type 1 diabetes have the strongest correlations to MS amongst the various autoimmune disorders. The paper also referenced potential associations with Hodgkin's, oral, and colon cancers with the caveat that there was insufficient evidence to support these connections.
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As discussed in Part I of this review, the geographic distribution of multiple sclerosis (MS) and the change in risk among migrants provide compelling evidence for the existence of strong environmental determinants of MS, where “environmental” is broadly defined to include differences in diet and other behaviors. As we did for infections, we focus here primarily on those factors that may contribute to explain the geographic variations in MS prevalence and the change in risk among migrants. Among these, sunlight exposure emerges as being the most likely candidate. Because the effects of sun exposure may be mediated by vitamin D, we also examine the evidence linking vitamin D intake or status to MS risk. Furthermore, we review the evidence on cigarette smoking, which cannot explain the geographic variations in MS risk, but may contribute to the recently reported increases in the female male ratio in MS incidence. Other proposed risk factors for MS are mentioned only briefly; although we recognize that some of these might be genuine, evidence is usually sparse and unpersuasive. Ann Neurol 2007 Multiple sclerosis (MS) represents a spectrum of demyelination that depends on disease duration and clinical categorization. Most patients present with the relapsing–remitting form of the disease. The earliest clinical presentation of relapsing–remitting MS (RRMS) is the clinically isolated syndrome (CIS). Predicting which CIS patients are at high risk for MS is complicated by the disparity between clinical attacks and the extent of axon pathology. However, recent interferon-beta (IFN-β) trials have demonstrated a delay in time to the second demyelinating event with early treatment, and early treatment could also slow the progression from RRMS to secondary-progressive MS (SPMS). Clinical findings in combination with brain MRI and CSF analysis can be used in CIS patients to evaluate their risk for clinically definite MS (CDMS). Application of the McDonald criteria also allows an earlier MS diagnosis by using new MRI lesions to define dissemination in time. Early immunomodulatory therapy for selected CIS patients may eventually prevent future axon pathology and progression of disability in this lifelong disease. The etiology of multiple sclerosis is, at present, not definitely known, but genetic and environmental factors play a role in its causation. Environmental causes have a predominant impact. Epidemiologic research has contributed considerably to the identification of external risk factors in this multifactorial setting, but methodological constraints still play a major part. Viral and other microbial agents have drawn much attention, although none of them is a necessary condition for the disease. This is true also for the Epstein–Barr virus, for which most data, including prospective data, supports a role in the majority of multiple sclerosis patients. In parallel, the hypothesis is still attractive in that it is not the virus per se, but rather more the age when it infects the human being that is the crucial matter. Other risk factors, such as tobacco smoking and vitamin D deficiency, which have immunomodulating properties, may also play some role, although the latter is not compatible with all data of the... Using multivariate analyses, individual risk of clinically definite multiple sclerosis (C DMS) after monosymptomatic optic neuritis (MO N) was quantified in a prospective study with clinical MO N onset during 1990 -95 in Stockholm, Sweden. During a mean follow-up time of 3.8 years, the presence of MS-like brain magnetic resonance imaging (MRI) lesions and oligoclonal immunoglobulin (Ig) G bands in cerebrospinal fluid (CSF) were strong prognostic markers of C DMS, with relative hazard ratios of 4.68 95 confidence interval (CI) 2.21 -9.91 and 5.39 (95 C I 1.56 -18.61), respectively. Age and season of clinical onset were also significant predictors, with relative hazard ratios of 1.76 (95 C I 1.02 -3.04) and 2.21 (95 C I 1.13 -3.98), respectively. Based on the above two strong predicto rs, individual probability of C DMS development after MO N was calculated in a three-quarter sample drawn from a cohort, with completion of follow-up at three years. The highest probability, 0.66 (95 C I 0.48 -0.80), wa...