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Mohammed W. Rahman, Niti U. Trivedi, Peter B. Bach, and Aaron P. Mitchell

Characteristics The proportion of oncologists who received any payments within the year increased from 65.1% in 2014 to 68.7% in 2017, and the proportion who received >$10,000 within the year increased from 7.0% to 10.2% ( Table 2 ). In comparison, in 2014, 44

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Rachel F. Dear, Kevin McGeechan, Megan B. Barnet, Alexandra L. Barratt, and Martin H.N. Tattersall

were extracted from ClinicalTrials.gov . Of these, 500 did not meet inclusion criteria, most because they did not use a drug intervention (80%; 400/500). Trials may have been excluded for more than one reason ( Figure 1 ). Characteristics of the 215

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Ning Ning, Jingsheng Yan, Xian-Jin Xie, and David E. Gerber

following characteristics: year, disease under study, phase and type (interventional/noninterventional), and sponsor type (institutional/industrial). Institutional trials included investigator-initiated trials with a local study chair or a study chair at

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Ashwin Shinde, Richard Li, Arya Amini, Yi-Jen Chen, Mihaela Cristea, Wenge Wang, Mark Wakabyashi, Ernest Han, Catheryn Yashar, Kevin Albuquerque, Sushil Beriwal, and Scott Glaser

backward selection of variables at a significance level of P <.10. An alpha threshold of 0.05 was chosen for statistical significance. Statistical analyses were performed using SPSS Statistics, version 24.0 (IBM Corp). Results Patient Characteristics A

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Ami M. Vyas, Hilary Aroke, and Stephen Kogut

explained portion of the gap is the sum of the differences between HR-positive and HR-negative women in terms of observed characteristics weighted by the pooled regression coefficients. It is calculated by multiplying the differences in the average

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Vinayak Muralidhar, Paul J. Catalano, Gally Reznor, Brandon A. Mahal, Toni K. Choueiri, Christopher J. Sweeney, Neil E. Martin, Clair J. Beard, Yu-Wei Chen, Michelle D. Nezolosky, Karen E. Hoffman, Felix Y. Feng, Quoc-Dien Trinh, and Paul L. Nguyen

, treatment, and survival data in addition to patient-specific demographic characteristics, covering 28% of the US population and 97% of incident cancers. 12 SEER was linked to Medicare administrative data, which contains insurance claims data for patients

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Iman K. Berrahou, Ava Snow, Megan Swanson, and Juno Obedin-Maliver

selected because of their particular relevance to the SGM population with regard to enumeration of protections in nondiscrimination policies across federal and state laws. Analyses were performed to determine whether cancer center characteristics impacted

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Jia-Wei Lv, Yu-Pei Chen, Guan-Qun Zhou, Xu Liu, Ying Guo, Yan-Ping Mao, Jun Ma, and Ying Sun

subsequent publications, and to identify the trends of reporting quality and associated characteristics. Methods Data Source and Study Sample Data were obtained through the Aggregate Analysis of ClinicalTrials.gov (AACT) database, reflecting data

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Ali A. Mokdad, Rebecca M. Minter, Adam C. Yopp, Matthew R. Porembka, Sam C. Wang, Hong Zhu, Mathew M. Augustine, John C. Mansour, Michael A. Choti, and Patricio M. Polanco

between 2006 and 2012 in the National Cancer Database (NCDB). The NCDB collects information from >1,500 Commission on Cancer centers and captures >70% of incident cancer cases in the United States. 11 We abstracted patient characteristics, including age

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Esther N. Pijnappel, Willemieke P.M. Dijksterhuis, Lydia G. van der Geest, Judith de Vos-Geelen, Jan Willem B. de Groot, Marjolein Y.V. Homs, Geert-jan Creemers, Nadia Haj Mohammad, Marc G. Besselink, Hanneke W.M. van Laarhoven, Johanna W. Wilmink, and for the Dutch Pancreatic Cancer Group

representation of the progression-free survival. Data on TTF were only available for patients with complete follow-up (diagnosis in 2015–2016). Statistical Analysis Data in this study were analyzed using SAS 9.4 (SAS Institute Inc). Baseline characteristics