characteristics, disease, and alive status were recorded at the time points during follow-up. Abbreviations: DFS, disease-free survival; IDPCD, institutional database program of colorectal disease; OS, overall survival; PRS, postrecurrence survival
Search Results
Dingcheng Shen, Xiaolin Wang, Heng Wang, Gaopo Xu, Yumo Xie, Zhuokai Zhuang, Ziying Huang, Juan Li, Jinxin Lin, Puning Wang, Meijin Huang, Yanxin Luo, and Huichuan Yu
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
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
Andrew D. Zelenetz
highlighted the second-generation BCL-2 inhibitor venetoclax (ABT-199). Early studies with venetoclax have confirmed its activity and the durability of Figure 2 Ideal Characteristics of Immunoconjugates. responses in patients with relapsed
Daniëlle D. Huijts, Julia T. van Groningen, Onno R. Guicherit, Jan Willem T. Dekker, Leti van Bodegom-Vos, Esther Bastiaannet, Johannes A. Govaert, Michel W. Wouters, and Perla J. Marang-van de Mheen
studies grouped colon and rectal surgeries together 3 , 4 or only examined colon surgery, 5 , 6 whereas patient characteristics, complication risks, and clinical outcomes are clearly different for colon and rectal cancers. 9 Another important
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
Héctor G. van den Boorn, Ameen Abu-Hanna, Nadia Haj Mohammad, Maarten C.C.M. Hulshof, Suzanne S. Gisbertz, Bastiaan R. Klarenbeek, Marije Slingerland, Laurens V. Beerepoot, Tom Rozema, Mirjam A.G. Sprangers, Rob H.A. Verhoeven, Martijn G.H. van Oijen, Koos H. Zwinderman, and Hanneke W.M. van Laarhoven
options. Furthermore, prediction models for the metastatic setting are scarce. We recently developed 2 models to predict survival in patients with metastatic esophageal or gastric cancer based on tumor, patient, and treatment characteristics. 13
Julie Hallet, Laura Davis, Alyson Mahar, Michail Mavros, Kaitlyn Beyfuss, Ying Liu, Calvin H.L. Law, Craig Earle, and Natalie Coburn
characteristics and outcomes. Categorical variables were reported as absolute number and percent, and continuous variables were reported as mean with SD or median with interquartile range (IQR). Comparison testing was undertaken using the chi-square test for
Elliott K. Yee, Natalie G. Coburn, Laura E. Davis, Alyson L. Mahar, Victoria Zuk, Vaibhav Gupta, Ying Liu, Craig C. Earle, and Julie Hallet
baseline characteristics of the cohort and outcomes, stratified by distance category and geographic region of residence. Patients were linked to geographic regions using the PCCF. Choropleth maps of the primary outcomes across each geographic region
Narek Shaverdian, Erin F. Gillespie, Elaine Cha, Soo Young Kim, Stephanie Benvengo, Fumiko Chino, Jung Julie Kang, Yuelin Li, Thomas M. Atkinson, Nancy Lee, Charles M. Washington, Oren Cahlon, and Daniel R. Gomez
. Statistical Analysis All completed surveys were analyzed. There were no additional inclusion or exclusion criteria. A predefined statistical plan was used to minimize inflation of type I error. Patient characteristics and survey responses for office visit
