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PurposeMINDACT demonstrated that 46% of patients with early breast cancer at high clinical but low genomic risk on the basis of MammaPrint may safely avoid adjuvant chemotherapy. A second random assignment (R-C) compared docetaxel-capecitabine with an anthracycline-based regimen.Patients and methodsR-C randomly assigned patients 1:1 between standard anthracycline-based regimens, with or without taxanes (control) and experimental docetaxel 75 mg/m2 intravenously plus oral capecitabine 825 mg/m2 two times per day for 14 days (DC) every 3 weeks for 6 cycles. The primary end point was disease-free survival (DFS). Secondary end points included overall survival and safety.ResultsOf 2,832 patients, 1,301 (45%) were randomly assigned, and 97% complied with R-C assignment. In the control arm, 29.6% only received taxanes (0.5% of N0 patients). DFS events (n = 148) were much less than required (n = 422) as a result of a lower-than-expected accrual and event rate. At 5 years of median follow-up, DFS was not different between DC (n = 652) and control (n = 649; 90.7% [95% CI, 88% to 92.8%] v 88.8% [95% CI, 85.9% to 91.1%]; hazard ratio [HR], 0.83 [95% CI, 0.60 to 1.15]; P = .26). Overall survival (HR, 0.91 [95% CI, 0.54 to 1.53]) and DFS in the clinical high and genomic high-risk subgroup (86.1% v 88.1%; HR, 0.83 [95% CI, 0.58 to 1.21]) were similar in both arms. DC led to more grade 1 neuropathy (27.1% v 11.2%) and more grade 2 hand/foot syndrome (28.5% v 3.3%) and diarrhea (13.7% v 5.8%). Serious cardiac events occurred in 9 patients (control, n = 4; DC, n = 5). Fifty-three patients developed second cancers (control, n = 32; DC, n = 21; leukemia: 2 v 1). Five treatment-related deaths occurred (control, 2 [0.3%]; DC, 3 [0.5%]).ConclusionAlthough underpowered, this second randomization in MINDACT did not show any improvement in outcome or safety with the use of DC compared with anthracycline-based chemotherapy.

PurposeAccording to the Institute of Medicine, high-quality cancer care should include effective communication between clinicians and patients about the risks and benefits, expected response, and impact on quality of life of a recommended therapy. In the delivery of oncology care, the barriers to and facilitators of communication about potential long-term and late effects, post-treatment expectations, and transition to survivorship care have not been fully defined.Patients and methodsWe collected qualitative data through semistructured interviews with medical oncologists and focus groups with breast cancer survivors and applied the Theoretical Domains Framework to systematically analyze and identify the factors that may influence oncologists' communication with patients with breast cancer about the long-term and late effects of adjuvant therapy.ResultsEight key informant interviews with medical oncologists and two focus groups with breast cancer survivors provided data. Both oncologists and patients perceived information on long-term effects as valuable in terms of improved clinical communication but had concerns about the feasibility of inclusion before treatment. They described the current approaches to communication of therapy risks as a brief laundry list that emphasized acute adverse effects and minimized more long-term issues. We describe the barriers to communication about potential long-term effects from the perspectives of both groups.ConclusionThis study provides insight into oncologists' communication with patients with breast cancer regarding the potential long-term and late effects of adjuvant chemotherapy and about setting realistic expectations for life after treatment. Opportunities to improve oncologists' communication about the potential toxicities of therapy, particularly regarding long-term and late effects, should be examined further.

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]