Lesion load reproducibility and statistical sensitivity of clinical trials in multiple sclerosis.
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Biomedical subjects
Publications and source records attributed to J Petkau.
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The primary clinical outcome measure for evaluating multiple sclerosis in clinical trials has been Kurtzke's expanded disability status scale (EDSS). New therapies appear to favourably impact the course of multiple sclerosis and render continued use of placebo control groups more difficult. Consequently, future trials are likely to compare active treatment groups which will most probably require increased sample sizes in order to detect therapeutic efficacy. Because more responsive outcome measures will be needed for active arm comparison studies, the National Multiple Sclerosis Society's Advisory Committee on Clinical Trials of New Agents in Multiple Sclerosis appointed a Task Force that was charged with developing improved clinical outcome measures. This Task Force acquired contemporary clinical trial and historical multiple sclerosis data for meta-analyses of primary and secondary outcome assessments to provide a basis for recommending a new outcome measure. A composite measure encompassing the major clinical dimensions of arm, leg and cognitive function was identified and termed the multiple sclerosis functional composite (MSFC). The MSFC consists of three objective quantitative tests of neurological function which are easy to administer. Change in this MSFC over the first year of observation predicted subsequent change in the EDSS, suggesting that the MSFC is more sensitive to change than the EDSS. This paper provides details concerning the development and testing of the MSFC.
This article will discuss basic concepts and simple but commonly used methods of statistical analysis which are relevant to the evaluation of the results of randomized controlled clinical trials in multiple sclerosis. The focus throughout will be on an expository discussion to facilitate understanding of the logic, objectives and implementation of these methods. The context for most of the discussion is that of a two-armed clinical trial, involving a placebo and an active treatment arm. Clinical trials are carried out to allow conclusions concerning the efficacy and effectiveness of therapies, so the discussion will focus on aspects of inferential statistics. Simple methods for continuous and count responses, as well some specifically developed for use with categorical and time-to-event data are discussed. A very brief discussion of some of the more sophisticated methods that are often essential for a comprehensive analysis of the data collected in a clinical trial is also provided.
Although increases in inhalable particle (PM10) concentrations have been associated with acute reductions in the level of lung function and increased symptom reporting in children, including children with asthma, it is not clear whether these effects occur largely in asthmatic children, or even whether asthmatic children are more likely to experience these effects than children without asthma. To address these points, the following subgroups of children were selected from a survey population of all 2,200 elementary school children (6 to 13 yr of age) in a pulp mill community on the west coast of Vancouver Island: (1) all children with physician-diagnosed asthma (n = 75 participated), (2) all children with an exercise-induced fall in FEV1 without diagnosed asthma (n = 57), (3) all children with airway obstruction (FEV1/FVC < 0.76) without either of the above (n = 18), and (4) control children without any of the above (n = 56). The children were followed for as long as 18 mo with twice daily measurements of peak expiratory flow (PEF) and daily symptom diary recording. Maximum daily PM10 concentration was 159 microm/m3 (median, 22.1), but only 8 d (1.2%) had concentrations above 100 microg/m3. In an analysis that accounted for time-varying covariates, and serially correlated and missing data, for the entire sample of children, increases in PM10 were associated with reductions in PEF and increased reporting of cough, phlegm production, and sore throat. For the subgroup of children with diagnosed asthma, PEF in the time period with the highest PM10 concentrations fell by an estimated 0.55 L/min (95% CI, 0.06 to 1.05) for a 10 microg/m3 PM10 increase above the mean daily PM10 concentration of 27.3 microg/m3 and the odds of reported cough increased by 8% (95% CI, 0 to 16%); no consistent effects were observed in the other groups of children. It is concluded that children experience reductions in PEF and increased symptoms after increases in relatively low ambient PM10 concentrations, and that children with diagnosed asthma are more susceptible to these effects than are other children.
This article provides recommendations from the National Multiple Sclerosis Society's Clinical Outcomes Assessment Task Force. The Task Force was appointed in 1994 and charged with recommendending improved approaches for clinical outcomes assessment in future controlled clinical trials. The recommendations herein follow extensive deliberation and data analysis during 2.5 years. General principles and desirable measurement attributes were used to assess alternative measurement techniques and clinical scales. On the basis of the analysis of existing multiple sclerosis (MS) data sets, a new measurement approach is proposed. The approach is based on quantitative functional composites that consist of simple quantitative measures from the major clinical dimensions of MS combined into a single score. Quantitative functional composites are likely to provide improved precision and sensitivity in future MS clinical trials. Studies necessary to further refine quantitative functional composites as useful MS clinical trial outcomes are delineated.
A basic feature of many clinical trials is the collection of longitudinal data on individual patients. Analysis of such data is often based on summaries over time. This allows use of standards methods to assess treatment effects but sacrifices information on patterns over time as well as potential greater efficiency of analysis. The purpose of this paper is to illustrate the utility of the generalized estimating equations (GEE) approach to the analysis of longitudinal binary, count, and continuous responses for the frequent magnetic resonance imaging (MRI) substudy of the 3-year pivotal trial of interferon beta-1 b in relapsing-remitting multiple sclerosis.
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This article represents initial deliberation of an international task force appointed by the US National Multiple Sclerosis Society to develop recommendations for optimal clinical assessment tools for multiple sclerosis clinical trials. Presented within this article are the key issues identified by the task force during its initial year of deliberation. These include the precise purpose for a clinical assessment tool, the clinical dimensions to be measured in a multidimensional outcome measure, desirable attributes of an optimal clinical outcome measure, the complexities of multidimensional outcome measures, the relative merits of categorical clinical ratings and quantitative functional assessments, and a number of other important design issues that relate to the use of a multidimensional outcome measure. An action plan for analysis of existing data is summarized, as are the plans for more detailed recommendations from the task force.