Linked Life Data

9449936

Source:http://linkedlifedata.com/resource/pubmed/id/9449936

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
1998-2-23
pubmed:abstractText
This paper is concerned with the design and analysis of mammography reading studies. In particular we consider studies aimed at evaluating interventions to improve the accuracy with which mammograms are read. A simple randomized design is suggested in which a relatively large group of readers read sets of mammograms before and after an intervention phase. We propose solutions to three difficult statistical issues that arise in the context of such studies: (i) the choice of primary outcome measure; (ii) the data analysis technique to be employed; and (iii) the methodology for calculating sample sizes for readers and images to be read. First, we argue in favor of using sensitivity and specificity as the primary outcome measures rather than receiver operating characteristic (ROC) curves in mammography studies, although the latter are considered state of the art for many types of radiology reading studies. We argue that sensitivity and specificity are more clinically relevant and conceptually more straightforward than ROC curves. Second, we suggest a bivariate approach to data analysis for evaluating intervention effects on sensitivity and specificity. This accommodates the correlations inherent between these measures and allows for estimation of joint effects on them. Finally we propose a method for power calculations that uses computer simulation techniques. Simple formulas for sample size calculations are not available in part because variability in accuracy amongst readers and variation in difficulty among images introduce complexity into power calculations. The simulation method that we propose accommodates such complexity and is easy to implement. The methodology was motivated by a study funded by the Department of Defense to evaluate the potential efficacy of an educational intervention. In the context of this study we illustrate the steps involved in power calculations and apply the data analytic techniques to the sort of data expected to result from this study. Though the proposed methods were motivated by this particular study, the statistical considerations are relevant more broadly in mammography and indeed in other types of radiologic imaging studies. Standards for the conduct of radiologic reading studies are not yet well developed, as they are for randomized clinical trials and for case-control studies. We hope that the discussion in this paper will add to the dialogue necessary for development of such standards.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0895-4356
pubmed:author
pubmed:issnType
Print
pubmed:volume
50
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1327-38
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1997
pubmed:articleTitle
Design of a study to improve accuracy in reading mammograms.
pubmed:affiliation
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98104, USA.
pubmed:publicationType
Journal Article, Clinical Trial, Comparative Study, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S., Randomized Controlled Trial