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      Creating scenarios of the impact of copd and their relationship to copd assessment test (CAT™) scores

      research-article
      1 , , 2 , 3
      BMC Pulmonary Medicine
      BioMed Central

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          Abstract

          Background

          The COPD Assessment Test (CAT™) is a new short health status measure for routine use. New questionnaires require reference points so that users can understand the scores; descriptive scenarios are one way of doing this. A novel method of creating scenarios is described.

          Methods

          A Bland and Altman plot showed a consistent relationship between CAT scores and scores obtained with the St George's Respiratory Questionnaire for COPD (SGRQ-C) permitting a direct mapping process between CAT and SGRQ items. The severity associated with each CAT item was calculated using a probabilistic model and expressed in logits (log odds of a patient of given severity affirming that item 50% of the time). Severity estimates for SGRQ-C items in logits were also available, allowing direct comparisons with CAT items. CAT scores were categorised into Low, Medium, High and Very High Impact. SGRQ items of corresponding severity were used to create scenarios associated with each category.

          Results

          Each CAT category was associated with a scenario comprising 12 to 16 SGRQ-C items. A severity 'ladder' associating CAT scores with exemplar health status effects was also created. Items associated with 'Low' and 'Medium' Impact appeared to be subjectively quite severe in terms of their effect on daily life.

          Conclusions

          These scenarios provide users of the CAT with a good sense of the health impact associated with different scores. More generally they provide a surprising insight into the severity of the effects of COPD, even in patients with apparently mild-moderate health status impact.

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          Most cited references7

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          Statistical methods for assessing agreement between two methods of clinical measurement.

          In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
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            St. George's Respiratory Questionnaire: MCID.

            The SGRQ is a disease-specific measure of health status for use in COPD. A number of methods have been used for estimating its minimum clinically important difference (MCID). These include both expert and patient preference-based estimates. Anchor-based methods have also been used. The calculated MCID from those studies was consistently around 4 units, regardless of assessment method. By contrast, the MCID calculated using distribution-based methods varied across studies and permitted no consistent estimate. All measurements of clinical significance contain sample and measurement error. They also require value judgements, if not about the calculation of the MCID itself then about the anchors used to estimate it. Under these circumstances, greater weight should be placed upon the overall body of evidence for an MCID, rather than one single method. For that reason, estimates of MCID should be used as indicative values. Methods of analysing clinical trial results should reflect this, and use appropriate statistical tests for comparison with the MCID. Treatments for COPD that produced an improvement in SGRQ of the order of 4 units in clinical trials have subsequently found wide acceptance once in clinical practice, so it seems reasonable to expect any new treatment proposed for COPD to produce an advantage over placebo that is not significantly inferior to a 4-unit difference.
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              Interpreting thresholds for a clinically significant change in health status in asthma and COPD.

              Health status (or Health-Related Quality of Life) measurement is an established method for assessing the overall efficacy of treatments for asthma and chronic obstructive pulmonary disease (COPD). Such measurements can indicate the potential clinical significance of a treatment's effect. This paper is concerned with methods of estimating the threshold of clinical significance for three widely used health status questionnaires for asthma and COPD: the Asthma Quality of Life Questionnaire, Chronic Respiratory Questionnaire and St George's Respiratory Questionnaire. It discusses the methodology used to obtain such estimates and shows that the estimates appear to be fairly reliable; ie. for a given questionnaire, similar estimates may be obtained in different studies. These empirically derived thresholds are all mean estimates with confidence intervals around them. The presence of these confidence intervals affects the way in which the thresholds may be used to draw inferences concerning the clinical relevance of clinical trial results. A new system of judging the magnitude of clinically significant results is proposed. Finally, an attempt is made to translate these thresholds into scenarios that illustrate what a clinically significant change with treatment may mean to an individual patient.
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                Author and article information

                Journal
                BMC Pulm Med
                BMC Pulmonary Medicine
                BioMed Central
                1471-2466
                2011
                11 August 2011
                : 11
                : 42
                Affiliations
                [1 ]Division of Clinical Science, St. George's University of London, London, UK
                [2 ]Global Health Outcomes, GlaxoSmithKline, London, UK
                [3 ]Center for Health Outcomes Research, United Biosource Corporation, Bethesda, MD, USA
                Article
                1471-2466-11-42
                10.1186/1471-2466-11-42
                3199910
                21835018
                01cd7290-34ca-48f2-bdd3-565ab661a59f
                Copyright ©2011 Jones et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 18 February 2011
                : 11 August 2011
                Categories
                Research Article

                Respiratory medicine
                Respiratory medicine

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