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32 results on '"Miao, Xiaopeng"'

4. Selective Inhibition of Na V 1.8 with VX-548 for Acute Pain

Author

Jones, Jim, primary, Correll, Darin J., additional, Lechner, Sandra M., additional, Jazic, Ina, additional, Miao, Xiaopeng, additional, Shaw, David, additional, Simard, Christopher, additional, Osteen, Jeremiah D., additional, Hare, Brian, additional, Beaton, Alina, additional, Bertoch, Todd, additional, Buvanendran, Asokumar, additional, Habib, Ashraf S., additional, Pizzi, Lois J., additional, Pollak, Richard A., additional, Weiner, Scott G., additional, Bozic, Carmen, additional, Negulescu, Paul, additional, and White, Paul F., additional

Published
2023
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5. Reply to Dunning

Author

Gilbert, Peter B., Gabriel, Erin E., Hudgens, Michael G., Miao, Xiaopeng, Li, Xiaoming, Su, Shu-Chih, Parrino, Janie, and Chan, Ivan S. F.

Published
2015

20. An ecological analysis of colorectal cancer incidence and mortality: Differences by sexual orientation

Author

Miao Xiaopeng, Ozonoff Al, and Boehmer Ulrike

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Some have suggested gays and lesbians may carry a greater burden of colorectal cancer. To date, individual sexual orientation data are not available in cancer surveillance registries. This prevents an assessment of differences in colorectal cancer incidence and mortality by sexual orientation, using individual-level data. Methods We use an ecological approach to examine differences in colorectal cancer incidence and mortality by county-level sexual orientation data. From the Surveillance, Epidemiology and End Results (SEER) Program we obtain population-based surveillance data on colorectal cancer incidence and mortality from 1996 to 2004. We use Census 2000 data on same-sex partnered households, a proxy of sexual orientation, to derive county-level sexual orientation data. Using multiple regression models, we examined the county-level association of sexual minority density with colorectal cancer incidence and mortality. Results After controlling for race and SES, we identify a significant positive association between greater density of sexual minority men and women and colorectal cancer incidence. With respect to colorectal cancer mortality, we identify a positive association with density of sexual minority men, but not women. Conclusions In the absence of surveillance data on sexual minority individuals, ecological analyses provide estimates of associations at the aggregate level, thereby providing crucial information for follow-up studies.

Published
2011
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25. Disease Modification in Alzheimer’s Disease: Current Thinking

Author

Liu-Seifert, Hong, Schumi, Jennifer, Miao, Xiaopeng, Tian, Ying, Rabbia, Michael, Andersen, Scott W., Wilson, Steve, Li, Wen, and Entsuah, Richard

Abstract

Alzheimer’s disease (AD) has increasingly been recognized as a huge unmet medical need. Currently, there is no approved drug to cure, prevent, or even slow down the disease. It is imperative to develop disease-modifying treatments for AD to alter the underlying disease progression. This paper reviews the most up-to-date regulatory guidance on how to demonstrate disease modification and provides an overview of available methodologies and applications to clinical trials. The intent is to assist the field with future clinical trials designed to demonstrate disease-modifying effect in AD. The methodologies may be generalizable to broader neurodegenerative diseases.

Published
2024
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26. Predictors of the placebo analgesia response in randomized controlled trials of chronic pain

Author

Vase, Lene, primary, Vollert, Jan, additional, Finnerup, Nanna B., additional, Miao, Xiaopeng, additional, Atkinson, Gary, additional, Marshall, Scott, additional, Nemeth, Robert, additional, Lange, Bernd, additional, Liss, Charlie, additional, Price, Donald D., additional, Maier, Christoph, additional, Jensen, Troels S., additional, and Segerdahl, Märta, additional

Published
2015
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32. Statistical evaluation of surrogate markers in randomized clinical trials

Author

Miao, Xiaopeng

Abstract

In many randomized clinical trials, the primary endpoints are clinical measurements of disease process. It usually requires an extremely long follow-up period and a considerable sample size to assess the treatment effect on such clinical endpoints. Therefore surrogate markers that can predict the treatment effects on the clinical endpoints would be extremely useful in accelerating the drug development process and depicting the mechanisms of drug action. Although candidate surrogate markers are generally proposed based on biological considerations, their validations largely depends on statistical methods. There are two major statistical frameworks of evaluating candidate surrogate markers in a single-trial setting: one is called the statistical surrogate (Prentice, 1989) and the other is referred to as the principal surrogate (Frangakis and Rubin, 2002). Both frameworks define surrogacy based on the treatment effect on the clinical endpoint that is mediated through the surrogate marker. For the evaluation of statistical surrogates, most existing methods are based on parametric regression analyses, which might provide spurious interference in the presence of model misspecification. For the evaluation of principal surrogates, the applications of existing methods are restricted to some simplified contexts (e.g., HIV vaccine trials) or limited types of clinical endpoints (e.g., binary). In this dissertation, we develop two novel approaches for the evaluation of surrogate markers in randomized clinical trials. In the framework of statistical surrogacy, we develop a nonparametic testing procedure based on measure of divergence and random permutation. The proposed method is robust to model misspecification and influential points, and is applicable to a variety of setting. In the framework of principal surrogacy, we propose a multiple imputation approach based on the incorporation of baseline predictors. The proposed approach can accomodate different types of clinical endpoints, and can be used to evaluate principal surrogates in a general setting where most existing methods are not applicable. Extensive simulation studies are conducted to examine the performance of the proposed methods. The usefulness of the method is further illustrated by real examples in clinical trials.

Published
2012

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