967 resultados para breast screening


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The potential value of baseline health-related quality-of-life (HRQOL) and clinical factors in predicting prognosis was examined using data from an international randomised phase III trial which compared doxorubicin and paclitaxel with doxorubicin and cylophosphamide as first line chemotherapy in 275 women with metastatic breast cancer. The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 and the related breast module (QLQ-BR23) were used to assess baseline HRQOL data. The Cox proportional-hazards regression model was used for both univariate and multivariate analyses of survival. In the univariate analyses, performance status (P<0.001) and number of sites involved (P=0.001) were the most important clinical prognostic factors. The HRQOL variables at baseline most strongly associated with longer survival were better appetite, physical and role functioning, as well as less fatigue (P<0.001). The final multivariate model retained performance status (P<0.001) and appetite loss (P=0.005) as the variables best predicting survival. Substantial loss of appetite was the only independent HRQOL factor predicting poor survival and was strongly correlated (/r/>0.5) with fatigue, role and physical functioning. In addition to known clinical factors, appetite loss appears to be a significant prognostic factor for survival in women with metastatic breast cancer. However, the mechanism underlying this association remains to be precisely defined in future studies.

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BACKGROUND: The impact of aromatase inhibitors (AIs) on non-cancer-related outcomes, which are known to be affected by oestrogens, has become increasingly important in postmenopausal women with hormone-dependent breast cancer. So far, data related to the effect of AIs on lipid profile in postmenopausal women is scarce. This study, as a companion substudy of an EORTC phase II trial (10951), evaluated the impact of exemestane, a steroidal aromatase inactivator, on the lipid profile of postmenopausal metastatic breast cancer (MBC) patients. PATIENTS AND METHODS: The EORTC trial 10951 randomised 122 postmenopausal breast cancer patients to exemestane (E) 25 mg (n = 62) or tamoxifen (T) 20 mg (n = 60) once daily as a first-line treatment in the metastatic setting. Exemestane showed promising results in all the primary efficacy end points of the trial (response rate, clinical benefit rate and response duration), and it was well tolerated with low incidence of serious toxicity. As a secondary end point of this phase II trial, serum triglycerides (TRG), high-density lipoprotein cholesterol (HDL), total cholesterol (TC), lipoprotein a (Lip a), and apolipoproteins (Apo) B and A1 were measured at baseline and while on therapy (at 8, 24 and 48 weeks) to assess the impact of exemestane and tamoxifen on serum lipid profiles. Of the 122 randomised patients, those who had baseline and at least one other lipid assessment are included in the present analysis. The patients who received concomitant drugs that could affect lipid profile are included only if these drugs were administered throughout the study treatment. Increase or decrease in lipid parameters within 20% of baseline were considered as non-significant and thus unchanged. RESULTS: Seventy-two patients (36 in both arms) were included in the statistical analysis. The majority of patients had abnormal TC and normal TRG, HDL, Apo A1, Apo B and Lip a levels at baseline. Neither exemestane nor tamoxifen had adverse effects on TC, HDL, Apo A1, Apo B or Lip a levels at 8, 24 and 48 weeks of treatment. Exemestane and tamoxifen had opposite effects on TRG levels: exemestane lowered while tamoxifen increased TRG levels over time. There were too few patients with normal baseline TC and abnormal TRG, HDL, Apo A1, Apo B and Lip a levels to allow for assessment of E's impact on these subsets. The atherogenic risk determined by Apo A1:Apo B and TC:HDL ratios remained unchanged throughout the treatment period in both the E and T arms. CONCLUSIONS: Overall, exemestane has no detrimental effect on cholesterol levels and the atherogenic indices, which are well-known risk factors for coronary artery disease. In addition, it has a beneficial effect on TRG levels. These data, coupled with E's excellent efficacy and tolerability, support further exploration of its potential in the metastatic, adjuvant and chemopreventive setting.

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Although the management of breast cancer has improved over the past few decades, it remains an important challenge for the clinician. Cytotoxic chemotherapy and hormonotherapy, when given in the adjuvant setting, have a definitive though modest impact on the outcome of early-stage breast cancer. In metastatic disease, these therapies help to provide substantial palliation of symptoms but have a limited impact on survival. The discovery of vinorelbine and the taxanes, paclitaxel and docetaxel, certainly represented the most encouraging clinical development of the 1980s in breast cancer therapy. Several other new cytotoxic agents have been recognised for their potential in the treatment of this disorder. Many of them are only in a very early phase of their clinical development and it remains to be proven that they will have a major role in daily practice in the near future.

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PURPOSE: Overall survival (OS) can be observed only after prolonged follow-up, and any potential effect of first-line therapies on OS may be confounded by the effects of subsequent therapy. We investigated whether tumor response, disease control, progression-free survival (PFS), or time to progression (TTP) could be considered a valid surrogate for OS to assess the benefits of first-line therapies for patients with metastatic breast cancer. PATIENTS AND METHODS: Individual patient data were collected on 3,953 patients in 11 randomized trials that compared an anthracycline (alone or in combination) with a taxane (alone or in combination with an anthracycline). Surrogacy was assessed through the correlation between the end points as well as through the correlation between the treatment effects on the end points. RESULTS: Tumor response (survival odds ratio [OR], 6.2; 95% CI, 5.3 to 7.0) and disease control (survival OR, 5.5; 95% CI, 4.8 to 6.3) were strongly associated with OS. PFS (rank correlation coefficient, 0.688; 95% CI, 0.686 to 0.690) and TTP (rank correlation coefficient, 0.682; 95% CI, 0.680 to 0.684) were moderately associated with OS. Response log ORs were strongly correlated with PFS log hazard ratios (linear coefficient [rho], 0.96; 95% CI, 0.73 to 1.19). Response and disease control log ORs and PFS and TTP log hazard ratios were poorly correlated with log hazard ratios for OS, but the confidence limits of rho were too wide to be informative. CONCLUSION: No end point could be demonstrated as a good surrogate for OS in these trials. Tumor response may be an acceptable surrogate for PFS.

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Optimising chemotherapy dose density and dose intensity are strategies aimed at improving outcomes in adjuvant therapy for patients with breast cancer. There are, in theory, at least five models allowing the delivery of a higher overall drug dose intensity. These are reviewed in this article and vary according to three main variables: the dose per course, the interval between doses and the total cumulative dose. Cyclophosphamide, anthracyclines and taxanes are among the most active agents for the treatment of breast cancer and, as such, they have been or are currently the focus of prospective, randomised clinical trials testing some of these dose-intensity models in the adjuvant setting. The results of recent trials suggest that anthracyclines, but not cyclophosphamide, are associated with better outcomes if used at higher doses per course and at higher cumulative doses. However, care has to be taken with premenopausal women where an increased dose of anthracycline per course but a reduced cumulative dose appears to produce a worse outcome. Moreover, decreasing the interval between doses, for anthracyclines and cyclophosphamide, does not seem to provide, so far, additional benefits for women with locally advanced breast cancer. This approach is not feasible with docetaxel, since an increase in dose density induces unwanted side-effects. These results represent our current state of knowledge, but clinical trials are being performed to evaluate further the effect of dose intensity, dose density and cumulative dose of key therapeutic agents on patient outcomes.

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The past few years have witnessed an exponential increase in studies trying to identify molecular markers in patients with breast tumours that might predict for the success or failure of hormonal therapy or chemotherapy. HER2, a tyrosine kinase membrane receptor of the epidermal growth factor receptor family, has been the most widely studied marker in this respect. This paper attempts to critically review to what extent HER2 may improve 'treatment individualisation' for the breast cancer patient. Copyright (C) 2000.

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PURPOSE: Taxanes (paclitaxel or docetaxel) have been sequenced or combined with anthracyclines (doxorubicin or epirubicin) for the first-line treatment of advanced breast cancer. This meta-analysis uses data from all relevant trials to detect any advantages of taxanes in terms of tumor response, progression-free survival (PFS), and survival. PATIENTS AND METHODS: Individual patient data were collected on eight randomized combination trials comparing anthracyclines + taxanes (+ cyclophosphamide in one trial) with anthracyclines + cyclophosphamide (+ fluorouracil in four trials), and on three single-agent trials comparing taxanes with anthracyclines. Combination trials included 3,034 patients; single-agent trials included 919 patients. RESULTS: Median follow-up of living patients was 43 months, median survival was 19.3 months, and median PFS was 7.1 months. In single-agent trials, response rates were similar in the taxanes (38%) and in the anthracyclines (33%) arms (P = .08). The hazard ratios for taxanes compared with anthracyclines were 1.19 (95% CI, 1.04 to 1.36; P = .011) for PFS and 1.01 (95% CI, 0.88 to 1.16; P = .90) for survival. In combination trials, response rates were 57% (10% complete) in taxane-based combinations and 46% (6% complete) in control arms (P < .001). The hazard ratios for taxane-based combinations compared with control arms were 0.92 (95% CI, 0.85 to 0.99; P = .031) for PFS and 0.95 (95% CI, 0.88 to 1.03; P = .24) for survival. CONCLUSION: Taxanes were significantly worse than single-agent anthracyclines in terms of PFS, but not in terms of response rates or survival. Taxane-based combinations were significantly better than anthracycline-based combinations in terms of response rates and PFS, but not in terms of survival.

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info:eu-repo/semantics/published

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SCOPUS: ar.j

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SCOPUS: ar.j

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To compare the incidence and timing of bone fractures in postmenopausal women treated with 5 years of adjuvant tamoxifen or letrozole for endocrine-responsive early breast cancer in the Breast International Group (BIG) 1-98 trial.

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According to EUSOMA position paper 'The requirements of a specialist breast unit', each breast unit should have a core team made up of health professionals who have undergone specialist training in breast cancer. In this paper, on behalf of EUSOMA, authors have identified the standards of training in breast cancer, to harmonise and foster breast care training in Europe. The aim of this paper is to contribute to the increase in the level of care in a breast unit, as the input of qualified health professionals increases the quality of breast cancer patient care.

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The recognition that early breast cancer is a spectrum of diseases each requiring a specific systemic therapy guided the 13th St Gallen International Breast Cancer Consensus Conference [1]. The meeting assembled 3600 participants from nearly 90 countries worldwide. Educational content has been centred on the primary and multidisciplinary treatment approach of early breast cancer. The meeting culminated on the final day, with the St Gallen Breast Cancer Treatment Consensus, established by 40-50 of the world's most experienced opinion leaders in the field of breast cancer treatment. The major issue that arose during the consensus conference was the increasing gap between what is theoretically feasible in patient risk stratification, in treatment, and in daily practice management. We need to find new paths to access innovations to clinical research and daily practice. To ensure that continued innovation meets the needs of patients, the therapeutic alliance between patients and academic-led research should to be extended to include relevant pharmaceutical companies and drug regulators with a unique effort to bring innovation into clinical practice. We need to bring together major players from the world of breast cancer research to map out a coordinated strategy on an international scale, to address the disease fragmentation, to share financial resources, and to integrate scientific data. The final goal will be to improve access to an affordable, best standard of care for all patients in each country.

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As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p < 0.02) and achieved AUC=0.85 +/- 0.01. The DF-P surpassed the other classifiers in terms of pAUC (p < 0.01) and reached pAUC=0.38 +/- 0.02. For the mass data set, DF-A outperformed both the ANN and the LDA (p < 0.04) and achieved AUC=0.94 +/- 0.01. Although for this data set there were no statistically significant differences among the classifiers' pAUC values (pAUC=0.57 +/- 0.07 to 0.67 +/- 0.05, p > 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p < 0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets.