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1.
Ann Oncol ; 28(3): 487-496, 2017 03 01.
Artigo em Inglês | MEDLINE | ID: mdl-27998966

RESUMO

Background: Aromatase inhibitors (AIs) have been associated with cardiovascular disease in adjuvant randomized controlled trials (RCTs) comparing these drugs to tamoxifen. However, it is unclear whether this risk is real or due to cardioprotective effects of tamoxifen. To address this question, we conducted a systematic review and meta-analysis of all RCTs of AIs and tamoxifen in adjuvant and extended adjuvant setting. Patients and methods: We searched PubMed, Embase (OVID), Cochrane CENTRAL, WHO International Clinical Trials Registry Platform, and ClinicalTrials.gov from inception to June 2016 for all RCTs comparing cardiovascular and cerebrovascular safety of AIs to tamoxifen, AIs to placebo or no-treatment, or tamoxifen to placebo or no-treatment in the adjuvant or extended adjuvant setting. Relative risks (RRs) were pooled using DerSimonian and Laird random-effects models with analyses stratified by RCT design. Results: A total of 19 RCTs were included in the meta-analysis (n = 62 345). In the adjuvant setting, AIs were associated with a 19% (RR: 1.19, 95% confidence interval [CI]: 1.07-1.34) increased risk of cardiovascular events compared with tamoxifen. AIs were not associated with an increased risk compared with placebo in the extended-adjuvant setting (RR: 1.01, 95% CI: 0.85-1.20). In the adjuvant setting, tamoxifen was associated with a 33% (RR: 0.67, 95% CI: 0.45-0.98) decreased risk compared with placebo or no-treatment. The results from extended adjuvant RCTs comparing tamoxifen to placebo were inconclusive but suggestive of a small protective effect (RR: 0.91, 95% CI: 0.77-1.07). Conclusions: The increased risk of cardiovascular events with AIs relative to tamoxifen is likely the result of cardioprotective effects of the latter. This new evidence should be considered when assessing the benefits and risks of AIs in the treatment of breast cancer.


Assuntos
Inibidores da Aromatase/efeitos adversos , Neoplasias da Mama/tratamento farmacológico , Cardiotoxicidade/epidemiologia , Tamoxifeno/efeitos adversos , Antineoplásicos Hormonais/efeitos adversos , Antineoplásicos Hormonais/uso terapêutico , Inibidores da Aromatase/uso terapêutico , Neoplasias da Mama/epidemiologia , Neoplasias da Mama/patologia , Cardiotoxicidade/patologia , Feminino , Humanos , Pós-Menopausa/fisiologia , Ensaios Clínicos Controlados Aleatórios como Assunto , Fatores de Risco , Tamoxifeno/uso terapêutico
2.
IEEE J Biomed Health Inform ; 17(1): 19-29, 2013 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-23193313

RESUMO

Public m-health is a new medical service under intensive development, which provides unobtrusive monitoring of peoples health conditions from anywhere at any time to enable detection of deteriorating health conditions before severe discomfort or disability occur. A key challenge in practical implementation of public m-health is the use of shared licensefree spectrum by Body Area Networks (BANs) to report sampled vital signs continuously and in real-time. A cognitive medium access control method called Centralized Body Area Network Access Scheme (CBAS) is proposed in this paper to reduce access delay in a BAN in the presence of coexistent systems. By opportunistic extraction of idle spaces from a pool of orthogonal channels, CBAS dynamically adjusts a BANs channel access pattern according to the current interference environment, and improves the BANs visibility among coexistent networks. Performance of a BAN under CBAS is analyzed by modeling the system as a preemptive-resume priority queue. Numerical and simulation results show that the queuing-delay and throughput of a BAN employing CBAS outperforms those of a BAN that utilizes a single channel statically, as channel access opportunities suffer less fragmentations and interruptions.


Assuntos
Modelos Teóricos , Monitorização Ambulatorial/métodos , Tecnologia de Sensoriamento Remoto/métodos , Telemedicina/métodos , Simulação por Computador , Humanos , Saúde Pública , Processamento de Sinais Assistido por Computador
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