Xiaoyong Wu
University of Louisville
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Oral Oncology | 2017
Cesar Augusto Perez; Xiaoyong Wu; Mark J. Amsbaugh; Rahul Gosain; Wederson M. Claudino; Mehran Yusuf; T. Roberts; Dharamvir Jain; Alfred B. Jenson; Sujita Khanal; Craig I. Silverman; Paul Tennant; Jeffrey M. Bumpous; N.E. Dunlap; Shesh N. Rai; Rebecca Redman
OBJECTIVES To compare the outcomes and toxicity of high-dose cisplatin (HDC) versus weekly cisplatin (WC) definitive chemoradiotherapy (CRT) for patients with human papillomavirus (HPV) related oropharyngeal squamous cell carcinoma (SCCOPx). METHODS All patients with p16 positive SCCOPx treated with definitive CRT with cisplatin between 2010 and 2014 at a single institution were retrospectively reviewed. CTCAE v 4.03 toxicity criteria were used. The Kaplan-Meier method was used to estimate event-free survival (EFS) and the overall survival (OS). RESULTS Of the 55 patients included, 22 were patients treated with HDC at dose of 100mg/m2 on days 1 and 22; and the remaining 33 patients were treated with WC at 40mg/m2. Both cohorts received a median total dose of cisplatin of 200mg/m2. At median follow-up of 31months, there was one local failure and no distant failures in the HDC cohort. In the WC group, there were 6 total failures (2 local, 4 distant). Estimated 2-year EFS was better in HDC cohort as compared to WC (96% vs. 75%; p=0.04). There was no significant difference in 2-year OS (95% vs. 94%; p=0.40). Weight loss, gastric tube dependence at six months, acute renal injury and grade 3 or 4 hematological toxicity were all similar between both groups. CONCLUSIONS HPV-related SCCOPx treated with definitive CRT with either HDC or WC had similar toxicity profile. HDC had better EFS when compared with WC and this seems to be driven by increased distant failure rates, although the OS was similar.
Open Access Medical Statistics | 2018
Shesh N. Rai; Xiaoyong Wu; Deo Kumar Srivastava; John Craycroft; Jayesh P Rai; Sanjay Srivastava; Robert F. James; Maxwell Boakye; Aruni Bhatnagar; Richard N. Baumgartner
php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). Open Access Medical Statistics 2018:8 11–23 Open Access Medical Statistics Dovepress
International Journal of Clinical Biostatistics and Biometrics | 2017
Xiaoyong Wu; Shesh N Rai
Citation: Wu X, Rai SN (2017) A Systematic Approach to Increase Reproducibility in Simulation Studies. Int J Clin Biostat Biom 3:012. doi.org/10.23937/2469-5831/1510012 Received: July 25, 2017: Accepted: October 05, 2017: Published: October 07, 2017 Copyright:
Cancer Research | 2013
Elizabeth C. Riley; Dharamvir Jain; B Kantardzic; Xiaoyong Wu; S.N. Rai
Introduction: There are well described barriers to clinical trial enrollment and participation among varied racial, ethnic and demographic groups. Little is known about clinical trial drop-out rate among these groups. The purpose of this study is to analyze the demographic and clinical characteristics of patients who originally signed consent and enrolled in the Bubble Study but then withdrew at a later date. The Bubble Study is a non- blinded, prospective observational cohort study designed to assess the adherence rate of adjuvant endocrine therapy among women with early stage breast cancer. Materials and Methods: From August 2012 to May of 2013, 75 women were enrolled into the Bubble Study. Demographic data (age, race and insurance status) and treatment factors (stage, surgery type, and therapy duration) were collected. Descriptive statistics (such as mean, median, standard deviation, minimum and maximum for continuous measures and frequency and percentage for discrete measures) were produced for the entire cohort and the subjects of cohort. Frequencies were compared using a Chi-square test (Fisher9s exact test when expected cell frequencies are small). Continuous measures were compared using a two-sample t test or Wilcoxon rank sum test for normally or non-normally outcome measures, respectively (Matthews and Farewell, 2007). In addition, linear and logistic regression analyses were used to explore association with different factors. Results were declared significant at significance level of 5% and all analyses are performed using SAS (2003, 2005). Results: At the time of analysis, 75 patients enrolled into the Bubble Study. Table 1 summarizes the demographic, social economic, therapeutic factors such as race, age, stage, surgery type, insurance and therapy durations and their relevant frequency and percentage are presented. The p-values are shown based on the chi square test. Blacks represented 28% of the total enrollment. Private insurance represented the majority (61.3%) of those enrolled and Medicare, Medicaid and Uninsured followed in that order (24.3%, 13% and 1.3% respectively.) In regards to race and insurance status, there was no significant difference between the enrolled group and the withdrawal group although there was a trend toward Blacks and Medicare with higher rate of withdrawal. Stage, surgery type or age did not predict for withdrawal. The most common reasons reported for withdrawal were financial and/or insurance reasons (22%), inconvenience of pharmacy pick up (13%) and preference for the prior system (9%). Conclusions: Demographic characteristics that traditionally predict for underrepresentation in clinical trial enrollment did not predict for withdrawal from the Bubble Study. Although small, this data set suggests disparities in clinical trial participation are largely due to enrollment rather than withdrawal. Larger analysis is needed to confirm these findings. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P1-09-19.
Journal of Clinical Oncology | 2016
Cesar Augusto Perez; Xiaoyong Wu; Mark J. Amsbaugh; Wederson M. Claudino; Mehran Yusuf; T. Roberts; Jorge Arturo Rios-Perez; Dharamvir Jain; Alfred B. Jenson; Sujita Khanal; Craig I. Silverman; Paul Tennant; N.E. Dunlap; Shesh N. Rai; Rebecca Redman
Biometrics & Biostatistics International Journal | 2015
Deo Kumar Srivastava; Melissa M. Hudson; Leslie L. Robison; Xiaoyong Wu; Shesh N. Rai
Journal of Clinical Oncology | 2017
Kamila Izabela Cisak; Amitoj Gill; Erin Faber; Rebecca Redman; N.E. Dunlap; Shesh N. Rai; Xiaoyong Wu; Cesar Augusto Perez
Journal of Clinical Oncology | 2017
Srividya Srinivasamaharaj; Dhruv Chaudhary; Xiaoyong Wu; Shesh N. Rai; Mary Ann Sanders; Rebecca Redman
Journal of Clinical Oncology | 2017
Rebecca Redman; Callie Linden; Cesar Augusto Perez; N.E. Dunlap; C.L. Silverman; Paul Tennant; Jeffrey M. Bumpous; Mary Gregg; Xiaoyong Wu; Shesh N. Rai
International Journal of Radiation Oncology Biology Physics | 2016
B. Cavanaugh; Carlos A. Perez; N.E. Dunlap; C.L. Silverman; Z. Khan; Liz Wilson; K. Potts; Paul Tennant; Jeffrey M. Bumpous; Xiaoyong Wu; S.N. Rai; Rebecca Redman