ABSTRACTIn clinical trials, selection of appropriate study endpoints is critical for an accurate and reliable evaluation of safety and effectiveness of a test treatment under investigation. In practice, however, there are usually multiple endpoints available for measurement of disease status and/or therapeutic effect of the test treatment under study. For example, in cancer clinical trials, overall survival, response rate, and/or time to disease progression are usually considered as primary clinical endpoints for evaluation of safety and effectiveness of the test treatment under investigation. Once the study endpoints have been selected, sample size required for achieving a desired power is then determined. It, however, should be noted that different study endpoints may result in different sample sizes. In practice, it is usually not clear which study endpoint can best inform the disease status and measure the treatment effect. Moreover, different study endpoints may not translate one another although they may be highly correlated one another. In this article, we intend to develop an innovative endpoint namely therapeutic index based on a utility function to combine and utilize information collected from all study endpoints. Statistical properties and performances of the proposed therapeutic index are evaluated theoretically. A numerical example concerning a cancer clinical trial is given to illustrate the use of the proposed therapeutic index. 相似文献
Four new diarylheptanoids, (1S, 3R, 5R, 6R)-1, 5-epoxy-3, 6 dihydroxy-1-(4-hydroxy-3, 5-dimethoxyphenyl)-7-(4-hydroxy-3-methoxyphenyl) heptane (1), (1R, 3R, 5S)-1, 5-epoxy-3-acetoxy-1-(4, 5-dihydroxy-3-methoxyphenyl)-7-(3, 4- hydroxyphenyl) heptane (2), (3R, 5S, 6R, 7S)-3, 6-epoxy-7-hydroxyl-1-(4-hydroxyphenyl)-7-(3-methoxy-4-hydroxyphenyl) heptane (3), (E)-3-keto-1-(3-methoxy-4-hydroxyphenyl)-7-(4, 5-dihydroxy-3-methoxyphenyl)-4- heptene (4), were isolated from Rhizoma Zingiberis, and their structures were determined based on HR-ESI-MS and extensive spectroscopic techniques (UV, IR, 1D-NMR and 2D-NMR). Compounds 1–4 exhibited no cytotoxicity against HepG2 cell lines.
1. To investigate Genkwa Flos hepatotoxicity, a cell metabolomics strategy combined with serum pharmacology was performed on human HL-7702 liver cells in this study.
2. Firstly, cell viability and biochemical indicators were determined and the cell morphology was observed to confirm the cell injury and develop a cell hepatotoxicity model. Then, with the help of cell metabolomics based on UPLC-MS, the Genkwa Flos group samples were completely separated from the blank group samples in the score plots and seven upregulated as well as two down-regulated putative biomarkers in the loading plot were identified and confirmed. Besides, two signal molecules and four enzymes involved in biosynthesis pathway of lysophosphatidylcholine and the sphingosine kinase/sphingosine-1-phosphate pathway were determined to investigate the relationship between Genkwa Flos hepatotoxicity and these two classic pathways. Finally, the metabolic pathways related to specific biomarkers and two classic metabolic pathways were analyzed to explain the possible mechanism of Genkwa Flos hepatotoxicity.
3. Based on the results, lipid peroxidation and oxidative stress, phospholipase A2/lysophosphatidylcholine pathway, the disturbance of sphingosine-1-phosphate metabolic profile centered on sphingosine kinase/sphingosine-1-phosphate pathway and fatty acid metabolism might be critical participators in the progression of liver injury induced by Genkwa Flos. 相似文献
PurposeTwitter is an increasingly popular social media platform within the health care community. The objective of this analysis is to characterize the profile of radiation oncology–related tweets and Twitter users over the past 6 years.Methods and MaterialsUsing the web-based social media analytics platform Symplur Signals, we filtered tweets containing at least 1 of the following hashtags or key words: #radonc, #radiationoncology, "rad onc," or "radiation oncology." We evaluated radiation oncology–related Twitter activity between October 2014 and March 2020 for tweet frequency, tweet content, and individuals or groups posting tweets. We identified the most influential Twitter users contributing to radiation oncology–related tweets.ResultsFrom 2014 to 2020, the quarterly volume of radiation oncology–related tweets increased from 5027 to 29,763. Physicians contributed the largest growth in tweet volume. Academic radiation oncologists comprise 60% of the most influential Twitter accounts responsible for radiation oncology–related content. The number of radiation-oncology resident physicians on Twitter increased from 25 to 328 over the past 6 years, and 20% of radiation-oncology residency programs have a Twitter account. Seventy-one percent of radiation oncology–related tweets generated direct communication via mentions, and 59% of tweets contain links to external sources, including scientific articles.ConclusionsThe number of physicians contributing radiation oncology–related Twitter content has increased significantly in recent years. Academic radiation oncologists are the primary influencers of radiation oncology–related Twitter activity. Twitter is used by radiation oncologists to both professionally network and discuss findings related to the field. There remains the opportunity for radiation oncologists to broaden their audience on Twitter to encompass a more diverse community, including patients. 相似文献