Correspondence to: Daniel B. Kopans, M.D., F.A.C.R., Massachusetts General Hospital, Harvard Medical School, Department of Radiology, Wang Ambulatory Care Center, Suite 240, 15 Parkman St., Boston, MA 02114 (e-mail: kopans.daniel{at}mgh.harvard.edu).
Studies such as the recent one by Beam et al. (1) that purport to evaluate the reading skills of radiologists interpreting screening mammograms only point out the pitfalls and complexities of these analyses. The only true test of a radiologists skill in interpreting screening mammograms would be to perform a study that accurately reflected the screening setting. Because this would involve the readers interpreting the same tens of thousands of mammograms, an accurate study is not feasible. Unfortunately, the study design used by the authors introduces a number of important and undocumented biases that make the conclusions highly suspect. Although the authors suggest that the initial cases were chosen by "random sampling," the ultimate case distribution was highly selected. There were 64 (43%) cancers among 148 women. As the authors acknowledge, this is far more cancers than a single radiologist would ever expect to see in a year let alone among a group of 148 women. This is almost 100 times more cancers than would be seen in a group of 1000 women undergoing screening. The only instructions that the radiologists were given were that the cases "did not have the mixture of mammograms expected from a typical screening population." This "slight understatement" of course could be interpreted in many ways. The authors should have queried the radiologists to determine what they thought was the prior probability of cancer in the group because this would influence how each interpreted the studies. I suspect that few radiologists expected that almost half the women had cancer.
An important question that is not answered is the mix of cancers that were included. Other studies have included a large number of cancers that are borderline in appearance, and I suspect that the same was true for this study. This will also skew the results. An experienced radiologist would be more likely than a less experienced reader to (correctly) dismiss a circumscribed lesion as "probably benign" because these lesions have such a low probability of cancer in "real life." The number of borderline lesions was likely high in this study, which could easily explain the results. Furthermore, the authors should have interviewed the readers to try to understand why they missed a lesion. Was it because they did not see it, or was it because they correctly dismissed the very low probability findings? The only conclusion of this paper that is probably legitimate (although not demonstrated by this study) is that "health policy recommendations aimed at improving the quality of interpretation that considers only radiologist volume will likely be misleading."
NOTES
Editors note: Beam et al. declined our invitation to respond.
REFERENCE
1 Beam CA, Conant EF, Sickles EA. Association of volume and volume-independent factors with accuracy in screening mammogram interpretation. J Natl Cancer Inst 2003;95:28290.
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