Meta-analysis of trials comparing anastrozole and tamoxifen for adjuvant treatment of postmenopausal women with early breast cancer

<p>Abstract</p> <p>Objective</p> <p>It was aimed to review the literature and make a meta-analysis of the trials on both upfront, switching, and sequencing anastrozole in the adjuvant treatment of early breast cancer.</p> <p>Methods</p> <p>The PubMed, ClinicalTrials.gov and Cochrane databases were systematically reviewed for randomized-controlled trials comparing anastrozole with tamoxifen in the adjuvant treatment of early breast cancer.</p> <p>Results</p> <p>The combined hazard rate of 4 trials for event-free survival (EFS) was 0.77 (95%CI: 0.70–0.85) (<it>P </it>< 0.0001) for patients treated with anastrozole compared with tamoxifen. In the second analysis in which only ITA, ABCSG 8, and ARNO 95 trials were included and ATAC (upfront trial) was excluded, combined hazard rate for EFS was 0.64 (95%CI: 0.52–0.79) (<it>P </it>< 0.0001). In the third analysis including hazard rate for recurrence-free survival (excluding non-disease related deaths) of estrogen receptor-positive patients for ATAC trial and hazard rate for EFS of all patients for the rest of the trials, combined hazard rate was 0.73 (95%CI: 0.65–0.81) (<it>P </it>< 0.0001).</p> <p>Conclusion</p> <p>Anastrozole appears to have superior efficacy than tamoxifen in the adjuvant hormonal treatment of early breast cancer. Until further clinical evidence comes up, aromatase inhibitors should be the initial hormonal therapy in postmenopausal early breast cancer patients and switching should only be considered for patients who are currently receiving tamoxifen.</p

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Numerical prediction of thrombus risk in an anatomically dilated left ventricle: the effect of inflow cannula designs

Background: Implantation of a rotary blood pump (RBP) can cause non-physiological flow fields in the left ventricle (LV) which may trigger thrombosis. Different inflow cannula geometry can affect LV flow fields. The aim of this study was to determine the effect of inflow cannula geometry on intraventricular flow under full LV support in a patient specific model. Methods: Computed tomography angiography imaging of the LV was performed on a RBP candidate to develop a patient-specific model. Five inflow cannulae were evaluated, which were modelled on those used clinically or under development. The inflow cannulae are described as a crown like tip, thin walled tubular tip, large filleted tip, trumpet like tip and an inferiorly flared cannula. Placement of the inflow cannula was at the LV apex with the central axis intersecting the centre of the mitral valve. Full support was simulated by prescribing 5 l/min across the mitral valve. Thrombus risk was evaluated by identifying regions of stagnation. Rate of LV washout was assessed using a volume of fluid model. Relative haemolysis index and blood residence time was calculated using an Eulerian approach. Results: The inferiorly flared inflow cannula had the lowest thrombus risk due to low stagnation volumes. All cannulae had similar rates of LV washout and blood residence time. The crown like tip and thin walled tubular tip resulted in relatively higher blood damage indices within the LV. Conclusion: Changes in intraventricular flow due to variances in cannula geometry resulted in different stagnation volumes. Cannula geometry does not appreciably affect LV washout rates and blood residence time. The patient specific, full support computational fluid dynamic model provided a repeatable platform to investigate the effects of inflow cannula geometry on intraventricular flow.Full Tex