anecdotally described, 5 , 6 but in light of the increasing rate of publication in these types of studies, we seek to describe the characteristics of a systematic sampling of NI studies in oncology from an updated search of recent published oncology trials
Search Results
Alyson Haslam, Jennifer Gill, and Vinay Prasad
Catherine Lockhart, Cara McDermott, James Marshall, Aaron Mendelsohn, Pamala Pawloski, and Jeffrey Brown
. 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
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
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
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
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
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
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
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
characteristics were described using means with standard deviations or medians with interquartile ranges (IQRs) for continuous variables, and absolute numbers with percentages for categorical variables. Chi-square tests were used to analyze differences between
Camilla Zimmermann, Ashley Pope, Breffni Hannon, Monika K. Krzyzanowska, Gary Rodin, Madeline Li, Doris Howell, Jennifer J. Knox, Natasha B. Leighl, Srikala Sridhar, Amit M. Oza, Rebecca Prince, Stephanie Lheureux, Aaron R. Hansen, Anne Rydall, Brittany Chow, Leonie Herx, Christopher M. Booth, Deborah Dudgeon, Neesha Dhani, Geoffrey Liu, Philippe L. Bedard, Jean Mathews, Nadia Swami, and Lisa W. Le
PROs, age, sex, tumor site, and baseline ESAS-r Distress score. The target sample size was 100, based on our feasibility criteria for this 1-year study. We compared patient characteristics and PROs at baseline for screen-positive versus screen
