Search PubMed⌕ Search

PubMed · 1345740

Issues in multiple sclerosis. A focused disease oriented research program.

Abstract

This report presents a brief overview of our own focused disease oriented research program, and rationale, to find the etiopathogenesis of multiple sclerosis (MS). Our hypothesis-driven research proposes that MS is caused by a persistent virus located at the edge of active plaques. Further, we propose that the immune system has eradicated the virus from inactive plaques or that the putative virus has become latent. In 1988 polymerase chain reaction (PCR) was reported and it has turned out to be the most sensitive and specific method to detect viral nucleic acid sequences in body fluids and tissues. This technique may be a breakthrough to test the MS viral hypothesis. Our search is further enhanced by the availability of a large collection (from MS Neurospecimen Bank) of cryopreserved MS brains and other neurological diseases suitable for PCR. An enigma is the specificity of the elevation of intrathecal IgG synthesis (rate and oligoclonal bands) that is found in over 99% of clinically definite MS cases. Our 2 dimensional electrophoresis of cerebrospinal fluid (CSF) IgG shows it to be temporally and clonally stable, evidence that intrathecal IgG synthesis is not non-specific. Intrathecal IgG synthesis is a marker of IgG synthesizing plasma cells in the central nervous system (CNS) and especially in active plaques. Another issue is the inclusion in all clinical trials of our objective quantitative examination of neurologic function (instrumented tests of functions which patients want improved) as well as CSF examination before and after the trial to determine the effect of the putative treatment on the polyphasic CNS inflammation.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

W W Tourtellotte. 1992. Issues in multiple sclerosis. A focused disease oriented research program.. https://pubmed.ncbi.nlm.nih.gov/1345740/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

On the exact interval estimation for the difference in paired areas under the ROC curves.

An important measure for comparison of accuracy between two diagnostic procedures is the difference in paired areas under the receiver operating characteristic (ROC) curves. Non-parametric and maximum likelihood methods have been proposed for interval estimation for the difference in paired areas under ROC curves. However, these two methods are asymptotic procedures and their performance in finite sample sizes has not been thoroughly investigated. We propose to use the concept of generalized pivotal quantities (GPQs) to construct an exact confidence interval for the difference in paired areas under ROC curves. A simulation study is conducted to empirically investigate the probability coverage and expected length of the three methods for various combinations of sample sizes, values of the area under the ROC curve and correlations. Simulation results demonstrate that the exact confidence interval based on the concept of GPQs provides not only sufficient probability coverage but also reasonable expected length. Numerical examples using published data sets illustrate the proposed method.

Clinical Trials as Topic↗

An efficient test for the analysis of dichotomized variables when the reliability is known.

A difference in an outcome variable between the treatment groups in a trial does not necessarily mean that there is a difference in the number of patients who experience relevant improvement on that variable. When the relevant improvement corresponds with an outcome or change in outcome that exceeds a certain threshold, the outcome variable can be dichotomized. A responder is a patient whose outcome exceeds the threshold. Comparisons can be made between the number of responders in the two treatment groups using logistic regression, or some other method to evaluate binary outcomes. An important disadvantage of this approach is the loss of power. In general, it is more efficient to test the difference between the mean values. We developed a statistical test that compares response rates for a dichotomized variable. It requires that an estimate of the reliability of the outcome variable is available. Simulations showed that the test was valid and robust over a wide range of distributions and sample sizes. The power was greater than the power of a chi(2) test, which would enable substantial reduction in the sample size.

Clinical Trials as Topic↗

Sample size determination for logistic regression revisited.

There is no consensus on the approach to compute the power and sample size with logistic regression. Some authors use the likelihood ratio test; some use the test on proportions; some suggest various approximations to handle the multivariate case. We advocate the use of the Wald test since the Z-score is routinely used for statistical significance testing of regression coefficients. The null-variance formula became popular from early studies, which contradicts modern software, which utilizes the method of maximum likelihood estimation (MLE), when the variance of the MLE is estimated at the MLE, not at the null. We derive general Wald-based power and sample size formulas for logistic regression and then apply them to binary exposure and confounder to obtain a closed-form expression. These formulas are applied to minimize the total sample size in a case-control study to achieve a given power by optimizing the ratio of controls to cases. Approximately, the optimal number of controls to cases is equal to the square root of the alternative odds ratio. Our sample size and power calculations can be carried out online at www.dartmouth.edu/ approximately eugened.

Clinical Trials as Topic↗