Correspondence to: Alice S. Whittemore, PhD, Department of Health Research and Policy, Redwood Building, Room T204, Stanford University School of Medicine, Stanford, CA 94305-5405 (e-mail: alicesw{at}stanford.edu).
In their article, Taplin et al. (1) used data from enrollees in seven large health care plans to examine differences in screening implementation among women with late-stage and early-stage breast cancer. Late-stage cancers were defined as metastatic cancers or cancers 3 cm or more in size; all other invasive cancers were considered early-stage. The authors found that the odds of having a late-stage cancer were statistically significantly higher among women who had not been screened in the 1- to 3-year period before diagnosis. Women without screening were more likely to be elderly, unmarried, of low annual income, and of low educational level. Taplin et al. (1) concluded that a top priority for screening implementation should be reaching unscreened women, particularly those with these demographic characteristics.
The study design, findings, and concluding public health message were all convincing. Therefore, I was surprised that the accompanying editorial by Baum (2) had a substantially different interpretation of the findings. Baum reminded readers of the three major roadblocks to evaluating the efficacy of mammography screening: 1) lead time bias (an artifactual increase in time from diagnosis to death among screened women because their cancers are detected earlier in their natural history); 2) length bias (an artifactual decrease in breast cancer death rates in screened women because some screen-detected cancers progress too slowly to kill); and 3) class bias (an artifactual decrease in breast cancer death rates in screened women because such women tend to be better educated and to receive better medical care than unscreened women). Baum noted that, because of these biases, most methodologists accept that the only way (Baum's italics) to investigate reliably the benefits of screening is to compare breast cancer mortality in two populations randomly allocated to be screened or to not be screened.
I was confused by these two articles. Should we or should we not invest resources in screening the currently unscreened? Resolution of this issue requires a critical review of the arguments used to support the two opposing viewpoints. Two points seem noteworthy.
First, the three biases cited by Baum (2) are irrelevant to the findings of Taplin et al. (1). As stated by Taplin et al., their goal was to evaluate screening implementation and not screening efficacy. Indeed, the study participants were aged 50 years and older, an age group for which the benefits of screening are generally accepted (thanks to several randomized trials of screening and mortality). The three biases do not invalidate the observed association between absence of screening and late-stage cancers, nor do they invalidate the observed associations between absence of screening and the participants' demographic characteristics.
Second, the study by Taplin et al. (1) is flawed by its use of cancer size as an endpoint for investigation. Translating the findings to public health policy requires a leap of faith from "screening leads to smaller cancers at diagnosis" to "screening reduces mortality." This leap cannot be taken with confidence, as evidenced by the results of the Canadian National Breast Screening Study, a randomized trial of breast cancer mortality in women aged 4049 years (3). The participants were assigned to either the treatment arm (screening with annual mammography, clinical breast evaluation, and instructions on breast self-evaluation) or the control arm (community care after a single breast physical examination and instructions on breast self-examination). Data on the sizes of breast cancers diagnosed during 9 years of follow-up in that study (3, Appendix Table 2), shows that only 47% of the cancers among women in the screened group were greater than 2 cm in diameter, compared with 55% of those among women in the control group (odds ratio = 1.37, two-tailed P = .03). Yet after 1116 years of follow-up, screening had not reduced breast cancer mortality below that of the control group (cumulative mortality risk ratio = 1.06, 95% confidence interval = 0.80 to 1.40).
Thus, we cannot assume that efforts to screen currently unscreened women will lead to lower breast cancer death rates. The study by Taplin et al. (1) would have been more informative had prediagnostic screening practices been compared in breast cancer patients who had and had not died from the disease.
NOTES
Editor's note: Dr. Baum declined to respond.
REFERENCES
(1) Taplin SH, Ichikawa L, Yood MU, Manos MM, Geiger AM, Weinmann S, et al. Reason for late-stage breast cancer: absence of screening or detection, or breakdown in follow-up? J Natl Cancer Inst 2004;96:151827.
(2) Baum M. Breast cancer screening comes full circle. J Natl Cancer Inst 2004;96:14901.
(3) Miller AB, To T, Baines CJ, Wall C. The Canadian National Breast Screening Study-1: breast cancer mortality after 11 to 16 years of follow-up. A randomized screening trial of mammography in women age 40 to 49 years. Ann Intern Med 2002;137:30512.
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