EDITORIAL

Should Screen-detected Breast Cancers Be Managed Differently?

Monika K. Krzyzanowska, Ian F. Tannock

Affiliation of authors: Division of Medical Oncology and Hematology, Princess Margaret Hospital and University of Toronto, Toronto, Canada

Correspondence to: Ian F. Tannock MD, PhD, Division of Medical Oncology and Hematology, Princess Margaret Hospital, 610 University Ave., Toronto, ON M45G 2M9, Canada (e-mail: ian.tannock{at}uhn.on.ca).

In this issue of the Journal, Shen et al. (1) examine the prognostic value of the method of breast cancer detection on cancer-specific survival. They used data from three large North American randomized controlled trials of breast cancer screening to evaluate the prognosis of screen-detected cancers versus cancers in interval and control groups. Across all three trials, screen-detected tumors were associated with longer cancer-specific survival, although the benefit was attenuated after adjustment for known prognostic factors such as stage, tumor size, and axillary lymph node status. This article complements the findings of Joensuu et al. (2), which were based on the Finnish Cancer Registry and which also reported better survival for women with screen-detected tumors, after adjusting for a range of known prognostic factors. Should method of detection be used, therefore, with traditional markers of tumor stage and aggressiveness in estimating prognosis of patients presenting with breast cancer and in selecting optimal treatment for them?

The interpretation of screening trials can be confounded by several types of bias (3,4). Lead-time bias occurs because screening detects asymptomatic tumors that tend to be at an earlier stage than tumors detected by palpating a lump in the breast or because they cause symptoms. As a result, an observed improvement in survival of the screened population can be partially attributed to a shift to earlier stage. In the studies of Shen et al. (1) and Joensuu et al. (2), there is evidence of lead-time bias as demonstrated by the expected stage-shift between screen-detected tumors and those detected by other means. Length bias occurs because screening tends to detect tumors that grow more slowly (4); for example, the initial screen may detect indolent tumors present for a long time, whereas fast-growing tumors may progress to clinical presentation in the interval between screening examinations. In the studies of Shen et al. (1) and Joensuu et al. (2), there appears to be evidence of length bias, manifest by the better prognosis of women with screen-detected tumors after adjusting for cancer stage.

It is important to evaluate critically the validity of the conclusions of the above studies and to place the conclusions in the context of other prognostic studies of breast cancer. The study by Shen et al. (1) is based on large numbers of patients in randomized trials of screening, but these are older studies in which clinical information is incomplete. Thus, in correcting for lead-time bias, the authors were able to adjust cancer-specific survival only for approximate descriptors of disease extent: overall stage, lymph node status (positive or negative, but not for the number of lymph nodes), and tumor size (more than or less than 2 cm, but not the actual tumor diameter). There is substantial heterogeneity of outcome within a given stage of breast cancer (for example, a 2.5-cm lymph node–negative tumor and a 4.5-cm lymph node–positive tumor are both stage II), for tumors of different size, and, most particularly, for the number of involved axillary lymph nodes. Thus, much of the residual effect of better cancer-specific survival for women with screen-detected tumors could still be due to lead-time bias. Shen et al. (1) had no access to other prognostic factors that relate to tumor aggressiveness, including tumor grade, lymphovascular invasion or necrosis, and the expression of estrogen, progesterone, and HER-2 receptors. These factors are routinely taken into account when oncologists estimate prognosis and select whether to give adjuvant therapy (and which type)—for example, using computer programs such as ADJUVANT! (5). Differences in the distribution of these factors between screen-detected and non–screen-detected cancers could account for the difference in outcome described by Shen et al (1).

The study of Joensuu et al. (2) is more provocative than that of Shen et al. (1). Joensuu et al. had access to more detailed data from the Finnish Cancer Registry and adjusted outcome for tumor size, number of involved axillary lymph nodes, tumor grade, hormone receptor content, and use of adjuvant systemic therapy. Moreover, they evaluated retrospectively important known prognostic factors such, as HER-2 status, as well as putative prognostic factors that are not routinely used in estimating prognosis, such as expression of TP53 and MK167, a marker of the rate of tumor cell proliferation. Even after adjusting for all of these factors that might be expected to reflect aggressiveness of tumor growth (and hence length bias due to screening), they found (2) that diagnosis by other than mammographic screening was a statistically significant independent predictor for a higher rate of distant recurrence at 10 years (hazard ratio = 1.90, 95% confidence interval [CI] = 1.15 to 3.11).

An important question relevant to both the above studies is the appropriateness of using primary endpoints of outcome other than overall survival. Biases can occur when assigning the date of recurrence of cancer or in classifying cancer as the cause of death (3). Sticky-diagnosis bias occurs when the cause of death in patients in the screened group is disproportionately ascribed to cancer, thereby falsely decreasing the disease-specific survival in the screened group. Slippery-linkage bias occurs when deaths occurring as a result of screening or of resulting investigation or treatment are falsely misclassified as unrelated, shifting the results in favor of screening. Black et al. (3) have suggested that, as a result of such bias, improvements in cancer-specific survival attributable to mammographic screening might not translate into benefits in overall survival. The endpoint of the study by Shen et al. (1) was cancer-specific survival, and that by Joensuu et al. (2) was distant disease–free survival. Shen et al. (1) had no access to data on overall survival; Joensuu et al. (2) undertook a secondary analysis for impact of method of detection on overall survival and found that women with non–screen-detected cancer had poorer prognosis but with a lower hazard ratio of 1.63 (95% CI = 1.02 to 2.60) than the hazard ratio reported for distant disease–free survival. This result might have been due in part to fewer events (i.e., deaths compared with recurrences) and, therefore, to the reduced power to detect effects on overall survival.

If screen-detected tumors do have a more favorable natural history than tumors with similar known prognostic features not detected by screening, then are we overtreating women with screen-detected tumors? Although adjuvant therapy is rarely life threatening, it has considerable morbidity, and it is important to quantify the risk of recurrence and death so that adjuvant treatment can be selected appropriately. Knowing the method of detection might have added limited prognostic value beyond that offered by well-established prognostic factors, but only in the study of Joensuu et al. (2) was there adequate adjustment for known factors. In a recent evaluation of the ADJUVANT! program (6), known prognostic factors were able to predict overall survival, breast cancer–specific survival, and event-free survival quite accurately in a large cohort of patients diagnosed with breast cancer in British Columbia between 1989 and 1993, with the exception of those patients who were younger than 35 years when diagnosed. Although there was no information provided about method of detection, British Columbia had an active screening program during this period, and it is likely that this cohort included patients who had a mixture of screen-detected and non–screen-detected tumors (7). Although we agree with the conclusion of Shen et al. (1) that clinical trialists should routinely collect information about the method of detection, at present there is insufficient information to suggest that this information should influence the selection of adjuvant therapy for breast cancer.

REFERENCES

(1) Shen Y, Yang Y, Inoue LY, Munsell MF, Miller AB, Berry DA. Role of detection method in predicting breast cancer survival: analysis of randomized screening trials. J Natl Cancer Inst 2005;97:1195–203.[Abstract/Free Full Text]

(2) Joensuu H, Lehtimaki T, Holli K, Elomaa L, Turpeenniemi-Hujanen T, Kataja V, et al. Risk for distant recurrence of breast cancer detected by mammography screening or other methods. JAMA 2004;292:1064–73.[Abstract/Free Full Text]

(3) Black WC, Haggstrom DA, Welch HG. All-cause mortality in randomized trials of cancer screening. J Natl Cancer Inst 2002;94:167–73.[Abstract/Free Full Text]

(4) Brawley OW, Kramer BS. Cancer screening in theory and in practice. J Clin Oncol 2005;23:293–300.[Abstract/Free Full Text]

(5) Ravdin PM, Siminoff LA, Davis GJ, Mercer MB, Hewlett J, Gerson N, et al. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 2001;19:980–91.[Abstract/Free Full Text]

(6) Olivotto IA, Bajdik CD, Ravdin PM, Speers CH, Coldman AJ, Norris BD, et al. Population-based validation of the prognostic model ADJUVANT! for early breast cancer. J Clin Oncol 2005;23:2716–25.[Abstract/Free Full Text]

(7) Olivotto IA, Kan L, d'Yachkova Y, Burhenne LJ, Hayes M, Hislop TG, et al. Ten years of breast screening in the Screening Mammography Program of British Columbia, 1988–97. J Med Screen 2000;7:152–9.[CrossRef][ISI][Medline]



             
Copyright © 2005 Oxford University Press (unless otherwise stated)
Oxford University Press Privacy Policy and Legal Statement