Dataset Information

Amelioration of sexual adverse effects in the early breast cancer patient.

ABSTRACT: As the number of breast cancer survivors increases, the long term consequences of breast cancer treatment are gaining attention. Sexual dysfunction is a common complaint amongst breast cancer survivors, and there are few evidence based recommendations and even fewer well designed clinical trials to establish what treatments are safe or effective in this patient population.We conducted a PubMed search for articles published between 1995-2009 containing the terms breast cancer, sexual dysfunction, libido, vaginal dryness, testosterone, and vaginal estrogen. We initially reviewed articles focusing exclusively on sexual issues in breast cancer patients. Given the paucity of clinical trials addressing sexual issues in breast cancer patients, we also included studies evaluating both hormone and non-hormone based interventions for sexual dysfunction in post-menopausal women in general.Among breast cancer survivors, vaginal dryness and loss of libido represent some of the most challenging long term side effects of breast cancer treatment. In the general post-menopausal population, topical preparations of estrogens and testosterone both appear to improve sexual function; however there are conflicting reports about the efficacy and safety of these interventions in women with a history of breast cancer, and further research is warranted.

SUBMITTER: Melisko ME

PROVIDER: S-EPMC2921487 | biostudies-other | 2010 Sep

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Amelioration of sexual adverse effects in the early breast cancer patient.

Melisko Michelle E ME Goldman Mindy M Rugo Hope S HS

Journal of cancer survivorship : research and practice 20100704 3

<h4>Background</h4>As the number of breast cancer survivors increases, the long term consequences of breast cancer treatment are gaining attention. Sexual dysfunction is a common complaint amongst breast cancer survivors, and there are few evidence based recommendations and even fewer well designed clinical trials to establish what treatments are safe or effective in this patient population.<h4>Design</h4>We conducted a PubMed search for articles published between 1995-2009 containing the terms ...[more]

PMID: 20602189

Similar Datasets

Project description:BackgroundBiomarkers are a key component of precision medicine. However, full clinical integration of biomarkers has been met with challenges, partly attributed to analytical difficulties. It has been shown that biomarker reproducibility is susceptible to data preprocessing approaches. Here, we systematically evaluated machine-learning ensembles of preprocessing methods as a general strategy to improve biomarker performance for prediction of survival from early breast cancer.ResultsWe risk stratified breast cancer patients into either low-risk or high-risk groups based on four published hypoxia signatures (Buffa, Winter, Hu, and Sorensen), using 24 different preprocessing approaches for microarray normalization. The 24 binary risk profiles determined for each hypoxia signature were combined using a random forest to evaluate the efficacy of a preprocessing ensemble classifier. We demonstrate that the best way of merging preprocessing methods varies from signature to signature, and that there is likely no 'best' preprocessing pipeline that is universal across datasets, highlighting the need to evaluate ensembles of preprocessing algorithms. Further, we developed novel signatures for each preprocessing method and the risk classifications from each were incorporated in a meta-random forest model. Interestingly, the classification of these biomarkers and its ensemble show striking consistency, demonstrating that similar intrinsic biological information are being faithfully represented. As such, these classification patterns further confirm that there is a subset of patients whose prognosis is consistently challenging to predict.ConclusionsPerformance of different prognostic signatures varies with pre-processing method. A simple classifier by unanimous voting of classifications is a reliable way of improving on single preprocessing methods. Future signatures will likely require integration of intrinsic and extrinsic clinico-pathological variables to better predict disease-related outcomes.

Dataset Information

Amelioration of sexual adverse effects in the early breast cancer patient.

Publications

Amelioration of sexual adverse effects in the early breast cancer patient.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets