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Background Mammographic screening has led to a proportional shift toward earlier-stage breast cancers at presentation. We assessed whether the method of detection provides prognostic information above and beyond standard prognostic factors and investigated the accuracy of predicted overall and breast cancer–specific survival by the computer tool Adjuvant! among patients with screen-detected, interval, and nonscreening-related carcinomas. Methods We studied 2592 patients with invasive breast cancer who were treated at the Netherlands Cancer Institute from January 1, 1990, through December 31, 2000. Overall and breast cancer–specific survival probabilities among patients with mammographically screen-detected (n = 958), interval (n = 417), and nonscreening-related (n = 1217) breast carcinomas were compared. Analyses were adjusted for clinicopathologic characteristics and adjuvant systemic therapy. Because of gradual implementation of population-based screening in the Netherlands, analyses were stratified a priori according to two periods of diagnosis. All statistical tests were two-sided. Results Screen detection was associated with reduced mortality (adjusted hazard ratio for all-cause mortality = 0.74, 95% confidence interval = 0.63 to 0.87, P < .001, and adjusted hazard ratio for breast cancer–specific mortality = 0.62, 95% confidence interval = 0.50 to 0.78, P < .001, respectively) compared with nonscreening-related detection. The absolute adjusted reduction in breast cancer–specific mortality was 7% at 10 years. The prognostic value of the method of detection was independent of the period of diagnosis and was similar across tumor size and lymph node status categories, indicating its prognostic value beyond stage migration. Adjuvant! underestimated breast cancer–specific survival in patients with screen-detected (−3.2%) and interval carcinomas (−5.4%). Conclusions Screen detection was found to be independently associated with better prognosis for overall and breast cancer–specific survival and to provide prognostic information beyond stage migration among patients with invasive breast cancer. We propose that the method of detection should be taken into account when estimating individual prognosis. [ABSTRACT FROM PUBLISHER]

Background: Despite trials of mammography and widespread use, optimal screening policy is controversial. Objective: To evaluate U.S. breast cancer screening strategies. Design: 6 models using common data elements. Data Sources: National data on age-specific incidence, competing mortality, mammography characteristics, and treatment effects. Target Population: A contemporary population cohort. Time Horizon: Lifetime. Perspective: Societal. Interventions: 20 screening strategies with varying initiation and cessation ages applied annually or biennially. Outcome Measures: Number of mammograms, reduction in deaths from breast cancer or life-years gained (vs. no screening), false-positive results, unnecessary biopsies, and overdiagnosis. Results of Base-Case Analysis: The 6 models produced consistent rankings of screening strategies. Screening biennially maintained an average of 81% (range across strategies and models, 67% to 99%) of the benefit of annual screening with almost half the number of false-positive results. Screening biennially from ages 50 to 69 years achieved a median 16.5% (range, 15% to 23%) reduction in breast cancer deaths versus no screening. Initiating biennial screening at age 40 years (vs. 50 years) reduced mortality by an additional 3% (range, 1% to 6%), consumed more resources, and yielded more false-positive results. Biennial screening after age 69 years yielded some additional mortality reduction in all models, but overdiagnosis increased most substantially at older ages. Results of Sensitivity Analysis: Varying test sensitivity or treatment patterns did not change conclusions. Limitation: Results do not include morbidity from false-positive results, patient knowledge of earlier diagnosis, or unnecessary treatment. Conclusion: Biennial screening achieves most of the benefit of annual screening with less harm. Decisions about the best strategy depend on program and individual objectives and the weight placed on benefits, harms, and resource considerations. Primary Funding Source: National Cancer Institute. [ABSTRACT FROM AUTHOR]

A reply is presented by Drs. Peter M. Ravdin, Kathleen A. Cronin and Rowan T. Chlebowski to letters to the editor about their article "The decrease in breast-cancer incidence in 2003 in the United States."

An initial analysis of data from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) registries shows that the age-adjusted incidence rate of breast cancer in women in the United States fell sharply (by 6.7%) in 2003, as compared with the rate in 2002. Data from 2004 showed a leveling off relative to the 2003 rate, with little additional decrease. Regression analysis showed that the decrease began in mid-2002 and had begun to level off by mid-2003. A comparison of incidence rates in 2001 with those in 2004 (omitting the years in which the incidence was changing) showed that the decrease in annual age-adjusted incidence was 8.6% (95% confidence interval [CI], 6.8 to 10.4). The decrease was evident only in women who were 50 years of age or older and was more evident in cancers that were estrogen-receptor — positive than in those that were estrogen-receptor — negative. The decrease in breast-cancer incidence seems to be temporally related to the first report of the Women's Health Initiative and the ensuing drop in the use of hormone-replacement therapy among postmenopausal women in the United States. The contributions of other causes to the change in incidence seem less likely to have played a major role but have not been excluded. [ABSTRACT FROM AUTHOR]

Background: Decision aids are tools that help patients make specific and deliberative choices among options. This study was a group randomized controlled trial of a novel decision aid to help patients with breast cancer make adjuvant therapy (AT) decisions. Methods: Fourteen oncology practices (n=58 physicians) were randomized to receive the decision aid or a control pamphlet. Complete data were obtained from 405 patient–oncologist pairs. Eligible patients had stage I–III disease and had completed their primary treatment. The decision aid is a simple to use computer program, titled Adjuvant!, that provides estimates of outcome with and without AT. Graphical representations of outcome are shared with patients. Consultations were audiotaped, patients interviewed, and physicians completed a self-administered survey. Results: In a multivariable model, the 54 patients (13.3%) who took no AT were more likely to have received the decision aid (p=0.02). A differential effect of the Adjuvant! Decision Guide was noted between node negative and positive patients. It was stated by 86.2% of patients that the decision aid was influential when making their treatment decision. Over 95% of patients reported that the Adjuvant Decision Guide was easy to understand and 75% of physicians believed that it helped them understand their patient's treatment preferences and 81.4% reported the information as useful for themselves. Conclusions: This study showed that a decision aid made a difference in the choice of whether or not to take AT. The decision aid allowed patients and physicians to consider the benefits of AT in an easy to understand format. Treatment decisions were more individualized for patients in the intervention than in the control group. The use of the decision aid was acceptable to both patients and physicians. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Objective To identify variables within the patient-oncologist communication pattern that impact overall patient comprehension and satisfaction within the breast cancer adjuvant therapy (AT) setting. Setting and participants Fifty patients were recruited from a number of academic and community-based oncology practices. Fifteen oncologists participated. Main variables Three communication variables were identified: percentage of total utterances spoken by the patient, percentage of total physician utterances that were coded as affective (i.e. emotional), and total number of questions asked by the patient during the consultation. Knowledge and satisfaction were assessed by a variety of outcome measures, including knowledge items and satisfaction as measured by VASs, the satisfaction with decision scale and the decisional conflict scale. Results The level of patient knowledge about breast cancer and satisfaction with the clinical encounter showed a tendency to correlate with the variables measuring aspects of patient-physician communication style. Patients who spoke more or asked more questions tended to be more knowledgeable whilst patients whose physicians used more affective language tended to know less but to be more satisfied with their clinical encounter. Conclusions In order to optimize patients’ degree of comprehension and satisfaction with their breast cancer adjuvant therapy, physicians need to increase their affective participation in clinical encounters whilst encouraging patients to ask questions and to actively participate in the decision-making process. [ABSTRACT FROM AUTHOR]

The article comments on a paper which reports the changes in screening mammography, menopausal hormone therapy, and breast cancer incidence in the Kaiser Permanente Northwest health plan. The authors stress that the researchers have failed to consider on what causes the decline in incidence between 2000 and 2004. A randomized trial is considered not helpful in population studies. The authors also emphasize that the paper is not done at the level of individual patient data.

Importance Online prognostication tools such as PREDICT and Adjuvant! are increasingly used in clinical practice by oncologists to inform patients and guide treatment decisions about adjuvant systemic therapy. However, their validity for young breast cancer patients is debated. Objective To assess first, the prognostic accuracy of PREDICT's and Adjuvant! 10-year all-cause mortality, and second, its breast cancer–specific mortality estimates, in a large cohort of breast cancer patients diagnosed <50 years. Design Hospital-based cohort. Setting General and cancer hospitals. Participants A consecutive series of 2710 patients without a prior history of cancer, diagnosed between 1990 and 2000 with unilateral stage I–III breast cancer aged <50 years. Main outcome measures Calibration and discriminatory accuracy, measured with C-statistics, of estimated 10-year all-cause and breast cancer–specific mortality. Results Overall, PREDICT's calibration for all-cause mortality was good (predicted versus observed) mean difference : −1.1% (95%CI: −3.2%–0.9%; P = 0.28). PREDICT tended to underestimate all-cause mortality in good prognosis subgroups (range mean difference : −2.9% to −4.8%), overestimated all-cause mortality in poor prognosis subgroups (range mean difference : 2.6%–9.4%) and underestimated survival in patients < 35 by −6.6%. Overall, PREDICT overestimated breast cancer–specific mortality by 3.2% (95%CI: 0.8%–5.6%; P = 0.007); and also overestimated it seemingly indiscriminately in numerous subgroups (range mean difference : 3.2%–14.1%). Calibration was poor in the cohort of patients with the lowest and those with the highest mortality probabilities. Discriminatory accuracy was moderate-to-good for all-cause mortality in PREDICT (0.71 [95%CI: 0.68 to 0.73]), and the results were similar for breast cancer–specific mortality. Adjuvant!'s calibration and discriminatory accuracy for both all-cause and breast cancer–specific mortality were in line with PREDICT's findings. Conclusions Although imprecise at the extremes, PREDICT's estimates of 10-year all-cause mortality seem reasonably sound for breast cancer patients <50 years; Adjuvant! findings were similar. Prognostication tools should be used with caution due to the intrinsic variability of their estimates, and because the threshold to discuss adjuvant systemic treatment is low. Thus, seemingly insignificant mortality overestimations or underestimations of a few percentages can significantly impact treatment decision-making. [ABSTRACT FROM AUTHOR]

Abstract: Background: The MINDACT (Microarray In Node-negative and 1–3 node positive Disease may Avoid ChemoTherapy) trial investigates the clinical utility of the 70-gene profile (MammaPrint) for the selection of breast cancer patients for adjuvant chemotherapy (CT) together with standard clinicopathological criteria. We present the results of the pilot phase consisting of first 800 patients included. Methods: MINDACT has enrolled 6600 patients, classified into high or low risk by MammaPrint and clinicopathological risk through Adjuvant! Online. Patients with both clinical (C) and genomic (G) high risks are offered adjuvant CT; those with both C and G low risks do not receive CT; patients with discordant risk are randomised for the decision of adjuvant CT based on C or G risk. CT randomisation of anthracycline-based versus docetaxel/capecitabine and endocrine therapy randomisation between letrozole and tamoxifen→letrozole are offered. Results: During the pilot phase 46% of screened patients were enrolled. Main reasons for non-enrolment were node positivity before trial amendment, sample quality problems and failure to meet logistic settings. Among the 800 patients, 386 (48%) were C-low/G-low, 198 (24.8%) as C-high/G-high, 75 (9.4%) as C-low/G-high and 141 (17.6%) as C-high/G-low. In total 216 (27%) cases were discordant. The difference between patients with C-high (42%) and G-high risk (34%) is 8.25% (95% confidence interval (CI), 4.7–11.8%; P <.0001). Compliance with the treatment decision was high (>92%). Conclusions: The logistically complex MINDACT trial is feasible in a multinational setting. The proportion of discordant patients, the potential reduction in CT by using the genomic signature and compliance to treatment assignment are in accordance with the trial hypotheses. [Copyright &y& Elsevier]