Impact of gene-expression profiling in patients with early breast cancer when applied outside the guideline directed indication area

Purpose In Dutch guidelines, gene expression profiles (GEP) are indicated in estrogen receptor positive early breast cancer patients in whom benefit of chemotherapy (CT) is uncertain based on traditional prognostic factors alone. Aim of the present study is to assess the use and impact of GEP on administration of adjuvant CT in breast cancer patients who have according to national guidelines a clear indication to either use or withhold adjuvant chemotherapy (clinical high or low risk). Methods Clinical low- and high-risk patients, according to Dutch breast cancer guidelines, diagnosed between 2011 and 2014 were selected from the Netherlands Cancer Registry. Influence of GEP use and GEP test result on CT administration was assessed with logistic regression. Results Overall, 26,425 patients were identified; 4.8% of patients with clinical low risk (444/9354), 7.5% of the patients with a clinical high risk (1281/17,071) received a GEP. GEP use was associated with significantly increased odds of CT administration in clinical low-risk patients (OR = 2.12 95% CI: 1.44–3.11). In clinical high-risk patients, GEP use was associated with a decreased frequency of CT administration (OR = 0.55, 95% CI: 0.48–0.63). Adherence to the GEP result was higher in clinical high-risk patients with a discordant GEP result as compared to clinical low-risk patients with a discordant GEP result: 71.7% vs. 52.2%, respectively. Conclusion GEP is frequently used outside the indicated area and significantly influenced the administration of adjuvant CT, although adherence to the test result was limited

Using a gene expression signature when controversy exists regarding the indication for adjuvant systemic treatment reduces the proportion of patients receiving adjuvant chemotherapy : a nationwide study

PURPOSE: The Dutch national guideline advises use of gene-expression signatures, such as the 70-gene signature (70-GS), in case of ambivalence regarding the benefit of adjuvant chemotherapy (CT). In this nationwide study, the impact of 70-GS use on the administration of CT in early breast cancer patients with a dubious indication for CT is assessed. METHODS: Patients within a national guideline directed indication area for 70-GS use who were surgically treated between November 2011 and April 2013 were selected from the Netherlands Cancer Registry database. The effect of 70-GS use on the administration of CT was evaluated in guideline- and age-delineated subgroups addressing potential effect of bias by linear mixed-effect modeling and instrumental variable (IV) analyses. RESULTS: A total of 2,043 patients within the indicated area for 70-GS use were included, of whom 298 received a 70-GS. Without use of the 70-GS, 45% of patients received CT. The 70-GS use was associated with a 9.5% decrease in CT administration (95% confidence interval (CI): -15.7 to -3.3%) in linear mixed-effect model analyses and IV analyses showed similar results (-9.9%; 95% CI: -19.3 to -0.4). CONCLUSION: In patients in whom the Dutch national guidelines suggest the use of a gene-expression profile, 70-GS use is associated with a 10% decrease in the administration of adjuvant CT.Genet Med 18 7, 720-726.Genetics in Medicine (2016); 18 7, 720-726. doi:10.1038/gim.2015.152

Accuracy of the online prognostication tools PREDICT and Adjuvant! for early-stage breast cancer patients younger than 50 years

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) meandifference: −1.1% (95%CI: −3.2%–0.9%; P = 0.28). PREDICT tended to underestimate all-cause mortality in good prognosis subgroups (range meandifference: −2.9% to −4.8%), overestimated all-cause mortality in poor prognosis subgroups (range meandifference: 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 meandifference: 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