. Objective: To evaluate patient characteristics and treatment use patterns in patients treated with GCSFs. This analysis will help inform a large-scale, real-world, observational GCSF comparative effectiveness research (CER) study using the Biologics
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Catherine Lockhart, Cara McDermott, James Marshall, Aaron Mendelsohn, Pamala Pawloski, and Jeffrey Brown
Xiaoqin Yang, Kaushal Desai, Neha Agrawal, Kirti Mirchandani, Sagnik Chatterjee, Eric Sarpong, and Shuvayu Sen
describe the characteristics, treatment patterns, healthcare resource use (HRU) and costs for these patients. Methods: A retrospective study of individuals enrolled in the MarketScan ® Commercial Claims and Encounters claims database from 10
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
Mona H. Cai, Yookyung Christy Choi, Athan Vasilopoulos, Alexander Liede, Sidney S. Lindsey, Leon Raskin, Ethan Truong, Jeremy Fricke, Stephen B. Gruber, and Peter J. Ansell
-Met OE negative (NEG) were less likely to be Asian (14% vs 30%, respectively), more likely to be diagnosed with stage IV disease (57% vs 41%), and more likely to be PD-L1 POS (78% vs 41%). All other observed characteristics were similar between groups
Sumesh Kachroo, Changxia Shao, Kaushal Desai, Jinghua He, Fan Jin, and Shuvayu Sen
Background: This study evaluated the relationship between patients’ clinical and genomic characteristics and high tumor mutational burden (TMB) in the context of small cell lung cancer (SCLC). Methods: This was a retrospective cohort study using
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
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
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
Krupal B. Patel, Amir Alishahi Tabriz, Kea Turner, Brian D. Gonzalez, Laura B. Oswald, Heather S.L. Jim, Oliver T. Nguyen, Young-Rock Hong, Nasrin Aldawoodi, Biwei Cao, Xuefeng Wang, Dana E. Rollison, Edmondo J. Robinson, Cristina Naso, and Philippe E. Spiess
the study period into the same 4 time intervals. Statistical Analyses Patient characteristics were summarized using descriptive statistics, including median and range for continuous measures and proportions and frequencies for categorical
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
