Multiple sclerosis, the measurement of disability and access to clinical trial data

Background: Inferences about long-term effects of therapies in multiple sclerosis (MS) have been based on surrogate markers studied in short-term trials. Nevertheless, MS trials have been getting steadily shorter despite the lack of a consensus definition for the most important clinical outcome - unremitting progression of disability. Methods: We have examined widely used surrogate markers of disability progression in MS within a unique database of individual patient data from the placebo arms of 31 randomised clinical trials. Findings: Definitions of treatment failure used in secondary progressive MS trials include much change unrelated to the target of unremitting disability. In relapsing-remitting MS, disability progression by treatment failure definitions was no more likely than similarly defined improvement for these disability surrogates. Existing definitions of disease progression in relapsing-remitting trials encompass random variation, measurement error and remitting relapses and appear not to measure unremitting disability. Interpretation: Clinical surrogates of unremitting disability used in relapsing -remitting trials cannot be validated. Trials have been too short and/or degrees of disability change too small to evaluate unremitting disability outcomes. Important implications for trial design and reinterpretation of existing trial results have emerged long after regulatory approval and widespread use of therapies in MS, highlighting the necessity of having primary trial data in the public domain

Average Run Length and Mean Delay for Changepoint Detection: Robust Estimates for Threshold Alarms

Online Monitoring is a rapidly expanding field in different areas such as quality control, finance and navigation. The automated detection of so-called changepoints is playing a prominent role in all these fields, be it the detection of sudden shifts of the mean of a continuously monitored quantity, the variance of stock quotes or the change of some characteristic features indicating the malfunctioning of one of the detectors used for navigation (the ``faulty sensor problem''). A prominent example for the application of advanced statistical methods for the detection of changepoints in biomedical time series is the multi-process Kalman filter used by Smith and West [Smith 1983] to monitor renal transplants. However, despite the fact that the algorithm could be tuned in such a way that the computer could predict dangerous situations on the average one day before the human experts it has nevertheless become superfluous as soon as new diagnosic tools became available. Many of the automated monitoring systems which are widely used in practice are based on simple threshold alarms. Some upper and lower limits are chosen at the beginning of the monitoring session and an alarm is triggered whenever the measured values exceed the upper limit or fall below the lower limit. This is e.g. common practice for the monitoring of patients during surgery, where such thresholds are chosen for heart rate, blood pressure etc. by the anaesthesist. The fate of the multi-process Kalman filter for monitoring renal transplants teaches two lessons: first, there is considerable power in statistical methods to improve conventional biomedical monitoring techniques. Second, if the statistical model and the methods are too refined they may never be used in practice. We shall suggest a stochastic model for changepoints which we have found to have the capacity to be very useful in practice, i.e. which is sufficiently complex to cover the important features of a changepoint system but simple enough to be understandable and adaptible. We focus our attention on the properties of the threshold alarm for different values of the parameters of the threshold alarm and the model. This will give us practically relevant estimates for this important class of alarm systems and moreover a benchmark for the evaluation of competing alternative algorithms. Note that virtually every algorithm designed to detect changepoints is based on a threshold alarm, the only difference being that the threshold alarm is not fed with the original data but by a transformation thereof, usually called ``residuum'' [Basseville 1993]. As a general measure for quality, we look on the one hand at the mean delay time $\tau$ between a changepoint and its detection and on the other hand at the mean waiting time for a false alarm, the so-called average run length ARL

Treating Systematic Errors in Multiple Sclerosis Data

Multiple sclerosis (MS) is characterized by high variability between patients and, more importantly here, within an individual over time. This makes categorization and prognosis difficult. Moreover, it is unclear to what degree this intra-individual variation reflects the long-term course of irreversible disability and what is attributable to short-term processes such as relapses, to interrater variability and to measurement error. Any investigation and prediction of the medium or long term evolution of irreversible disability in individual patients is therefore confronted with the problem of systematic error in addition to random fluctuations. The approach described in this article aims to assist in detecting relapses in disease curves and in identifying the underlying disease course. To this end neurological knowledge was transformed into simple rules which were then implemented into computer algorithms for pre-editing disease curves. Based on simulations it is shown that pre-editing time series of disability measured with the Expanded Disability Status Scale (EDSS) can lead to more robust and less biased estimates for important disease characteristics, such as baseline EDSS and time to reach certain EDSS levels or sustained progression

Chromosomal in situ suppression hybridization of human gonosomes and autosomes and its use in clinical cytogenetics

DNA libraries from sorted human gonosomes were used selectively to stain the X and Y chromosomes in normal and aberrant cultured human cells by chromosomal in situ suppression (CISS-) hybridization. The entire X chromosome was stained in metaphase spreads. Interphase chromosome domains of both the active and inactive X were clearly delineated. CISS-hybridization of the Y chromosome resulted in the specific decoration of the euchromatic part (Ypter-q11), whereas the heterochromatic part (Yq12) remained unlabeled. The stained part of the Y chromosome formed a compact domain in interphase nuclei. This approach was applied to amniotic fluid cells containing a ring chromosome of unknown origin (47,XY; +r). The ring chromosome was not stained by library probes from the gonosomes, thereby suggesting its autosomal origin. The sensitivity of CISS-hybridization was demonstrated by the detection of small translocations and fragments in human lymphocyte metaphase spreads after irradiation with 60Co-gamma-rays. Lymphocyte cultures from two XX-males were investigated by CISS-hybridization with Y-library probes. In both cases, metaphase spreads demonstrated a translocation of Yp-material to the short arm of an X chromosome. The translocated Y-material could also be demonstrated directly in interphase nuclei. CISS-hybridization of autosomes 7 and 13 was used for prenatal diagnosis in a case with a known balanced translocation t(7;13) in the father. The same translocation was observed in amniotic fluid cells from the fetus. Specific staining of the chromosomes involved in such translocations will be particularly important, in the future, in cases that cannot be solved reliably by conventional chromosome banding alone

Evaluating Microarray-based Classifiers: An Overview

For the last eight years, microarray-based class prediction has been the subject of numerous publications in medicine, bioinformatics and statistics journals. However, in many articles, the assessment of classification accuracy is carried out using suboptimal procedures and is not paid much attention. In this paper, we carefully review various statistical aspects of classifier evaluation and validation from a practical point of view. The main topics addressed are accuracy measures, error rate estimation procedures, variable selection, choice of classifiers and validation strategy

Quasi-ballistic transport in HgTe quantum-well nanostructures

The transport properties of micrometer scale structures fabricated from high-mobility HgTe quantum-wells have been investigated. A special photoresist and Ti masks were used, which allow for the fabrication of devices with characteristic dimensions down to 0.45 $\mu$m. Evidence that the transport properties are dominated by ballistic effects in these structures is presented. Monte Carlo simulations of semi-classical electron trajectories show good agreement with the experiment.Comment: 3 pages, 3 figures; minor revisions: replaced "inelastic mean free path" with "transport mean free path"; corrected typing errors; restructered most paragraphs for easier reading; accepted for publication in AP

Prognosis of the individual course of disease - steps in developing a decision support tool for Multiple Sclerosis

<p>Abstract</p> <p>Background</p> <p>Multiple sclerosis is a chronic disease of uncertain aetiology. Variations in its disease course make it difficult to impossible to accurately determine the prognosis of individual patients. The Sylvia Lawry Centre for Multiple Sclerosis Research (SLCMSR) developed an "online analytical processing (OLAP)" tool that takes advantage of extant clinical trials data and allows one to model the near term future course of this chronic disease for an individual patient.</p> <p>Results</p> <p>For a given patient the most similar patients of the SLCMSR database are intelligently selected by a model-based matching algorithm integrated into an OLAP-tool to enable real time, web-based statistical analyses. The underlying database (last update April 2005) contains 1,059 patients derived from 30 placebo arms of controlled clinical trials. Demographic information on the entire database and the portion selected for comparison are displayed. The result of the statistical comparison is provided as a display of the course of Expanded Disability Status Scale (EDSS) for individuals in the database with regions of probable progression over time, along with their mean relapse rate. Kaplan-Meier curves for time to sustained progression in the EDSS and time to requirement of constant assistance to walk (EDSS 6) are also displayed. The software-application OLAP anticipates the input MS patient's course on the basis of baseline values and the known course of disease for similar patients who have been followed in clinical trials.</p> <p>Conclusion</p> <p>This simulation could be useful for physicians, researchers and other professionals who counsel patients on therapeutic options. The application can be modified for studying the natural history of other chronic diseases, if and when similar datasets on which the OLAP operates exist.</p

Ambiguities of arrival-time distributions in quantum theory

We consider the definition that might be given to the time at which a particle arrives at a given place, both in standard quantum theory and also in Bohmian mechanics. We discuss an ambiguity that arises in the standard theory in three, but not in one, spatial dimension.Comment: LaTex, 12 pages, no figure