Everolimus (EVE) and exemestane (EXE) in patients with advanced breast cancer aged 65 65 years: New lessons for clinical practice from the EVA study

BACKGROUND: The present analysis focuses on real-world data of Everolimus-Exemestane in advanced HR+ve, HER2-ve elderly breast cancer patients (aged 65 years) included in the EVA study, with unique findings in those aged 70 years. METHODS: Data are collected from clinical records and analysed according to age cut-off (< 65 years; 65 - 69 years and {greater than or equal to} 70 years). Relationship of analyzed variables with response were tested by mean of a Mantel-Haenszel chi square test. Time to event analysis was described by Kaplan Meier approach and association with baseline characteristics was analysed by stratified log-rank test and proportional hazard model. RESULTS: From July 2013 to December 2015, the EVA study enrolled overall 404 pts. 154 patients out of 404 (38,1%) were aged {greater than or equal to} 65 years, of whom 87 were {greater than or equal to} 70 years. Median duration of EVE treatment was 28.5 weeks (95% CI 19.0 - 33.8) in patients aged 65-69 years and 24,4 weeks (95% CI 19,2 - 33,2) in those aged {greater than or equal to} 70 years. Fewer patients aged 65 years received the highest EVE Dose-Intensity (>7.5 mg/day) in comparison to younger patients (49,6% vs. 66,8%). Grade 3-4 toxicities occurred to 55 patients (35,7%), mainly stomatitis (10,9%), rash (5,8%) and non-infectious pneumonitis (NIP) (3,6%). Some toxicities, such as weight loss and anaemia were peculiarly observed in patients aged {greater than or equal to} 70 years. Five treatment-related deaths were collected (3,2%). CONCLUSIONS: EVE-EXE combination remains one of the potential treatments in HR+ patients also for elderly ones

Pareto-optimal radar waveform design

This study deals with the problem of Pareto-optimal waveform design in the presence of coloured Gaussian noise, under a similarity and an energy constraint. At the design stage, the authors, determine the optimal radar code according the following criterion: constrained maximisation of the detection performance and constrained minimisation of the Cramer-Rao lower bound (CRLB) on the Doppler estimation accuracy. This is tantamount to jointly maximising two quadratic forms under two quadratic constraints, so that the problem can be formulated in terms of a non-convex multi-objective optimisation problem. In order to solve it, the authors resort to the scalarisation technique, which reduces the vectorial problem into a scalar one using a Pareto weight defining the relative importance of the two objective functions. At the analysis stage, the authors assess the performance of the proposed waveform design scheme in terms of detection performance, region of achievable Doppler estimation accuracy and ambiguity function. In particular, the authors analyse the role of the Pareto weight in the optimisation process

Pareto-optimal radar waveform design

This paper deals with the problem of Pareto-optimal waveform design in the presence of colored Gaussian noise, under a similarity and an energy constraint. At the design stage, we determine the optimal radar code according to the following criterion: joint constrained maximization of the detection probability and constrained minimization of the Cramer Rao Lower Bound (CRLB) on the Doppler estimation accuracy. This is tantamount to jointly maximizing two quadratic forms under two quadratic constraints, so that the problem can be formulated in terms of a non-convex multi-objective optimization problem. In order to solve it, we resort to the scalarization technique, which reduces the vectorial problem into a scalar one using a Pareto weight defining the relative importance of the two objective functions. At the analysis stage, we assess the performance of the proposed waveform design scheme in terms of detection performance and region of achievable Doppler estimation accuracy. In particular, we analyze the role of the Pareto weight in the optimization process