13 research outputs found

    Patient and provider factors associated with the noninitiation of tamoxifen for young women at high-risk for the development of breast cancer

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    We sought to identify factors associated with disparities in tamoxifen utilization among young patients at high- risk for developing breast cancer. We identified 67 premenopausal, high- risk women age 35- 45, without surgical prophylaxis, who did not initiate tamoxifen. Factors associated with noninitiation were examined. About 37% of patients had no documented provider- based discussion regarding initiation. Type of high- risk diagnosis was the only factor associated with a provider- based discussion (P = .03). For patients offered tamoxifen, primary reasons for noninitiation were perceived minimal benefit (66.7%), fertility concerns (16.7%), and concerns about side effects (7.1%). Implementation of comprehensive educational strategies regarding the benefits of tamoxifen should be facilitated to improve initiation among young high- risk patients.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154627/1/tbj13528_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154627/2/tbj13528.pd

    Patient and provider factors associated with the noninitiation of tamoxifen for young women at high-risk for the development of breast cancer

    Full text link
    We sought to identify factors associated with disparities in tamoxifen utilization among young patients at high- risk for developing breast cancer. We identified 67 premenopausal, high- risk women age 35- 45, without surgical prophylaxis, who did not initiate tamoxifen. Factors associated with noninitiation were examined. About 37% of patients had no documented provider- based discussion regarding initiation. Type of high- risk diagnosis was the only factor associated with a provider- based discussion (P = .03). For patients offered tamoxifen, primary reasons for noninitiation were perceived minimal benefit (66.7%), fertility concerns (16.7%), and concerns about side effects (7.1%). Implementation of comprehensive educational strategies regarding the benefits of tamoxifen should be facilitated to improve initiation among young high- risk patients.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154627/1/tbj13528_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154627/2/tbj13528.pd

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    The Role of Mesothelin as a Diagnostic and Therapeutic Target in Pancreatic Ductal Adenocarcinoma: A Comprehensive Review

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    On Cartan matrices with two parameters (Cohomology theory of finite groups and related topics)

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    A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34%) of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments and medicinal chemistry programs. The data for all of these assays are presented and analyzed to show how outstanding leads for many indications can be selected. These results reveal the immense potential for translating the dispersed expertise in biological assays involving human pathogens into drug discovery starting points, by providing open access to new families of molecules, and emphasize how a small additional investment made to help acquire and distribute compounds, and sharing the data, can catalyze drug discovery for dozens of different indications. Another lesson is that when multiple screens from different groups are run on the same library, results can be integrated quickly to select the most valuable starting points for subsequent medicinal chemistry efforts

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

    No full text

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

    No full text
    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press
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