( Table 3 ). Nearly half (46%) had Medicaid or other public insurance, and 54% lived in a low-income zip code (median income ≤200% FPL). Nearly half of caregivers were college graduates (46%). Table 2. AYA Caregiver Characteristics Table
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Jennifer W. Mack, Erin R. Currie, Vincent Martello, Jordan Gittzus, Asisa Isack, Lauren Fisher, Lisa C. Lindley, Stephanie Gilbertson-White, Eric Roeland, and Marie Bakitas
U-Syn Ha, Jin Bong Choi, Jung Im Shim, Minjoo Kang, Eunjung Park, Shinhee Kang, Jooyeon Park, Jangmi Yang, Insun Choi, Jeonghoon Ahn, Cheol Kwak, Chang Wook Jeong, Choung Soo Kim, Seok-Soo Byun, Seong Il Seo, Hyun Moo Lee, Seung-Ju Lee, Seung Hwan Lee, Byung Ha Chung, and Ji Youl Lee
physical activity. Because placement in the PADT group was strongly associated with patient characteristics, we used PSM analysis to balance covariates between the groups. We stratified by age and summary cancer stages to account for the clinical
Zhong Ye, Chun Wang, Limin Guo, Juan P. Palazzo, Zhixing Han, Yinzhi Lai, Jing Jiang, James A. Posey, Atrayee Basu Mallick, Bingshan Li, Li Jiang, and Hushan Yang
characteristic (ROC) curves and calculating the area under the curve (AUC). The prediction power was also estimated using Concordance-index (C-index), which works as an extension of AUC to the case of censored survival data. Patients with CRC were divided into
Tara M. Mackay, Anouk E.J. Latenstein, Mirjam A.G. Sprangers, Lydia G. van der Geest, Geert-Jan Creemers, Susan van Dieren, Jan-Willem B. de Groot, Bas Groot Koerkamp, Ignace H. de Hingh, Marjolein Y.V. Homs, Evelien J.M. de Jong, I. Quintus Molenaar, Gijs A. Patijn, Lonneke V. van de Poll-Franse, Hjalmar C. van Santvoort, Judith de Vos-Geelen, Johanna W. Wilmink, Casper H. van Eijck, Marc G. Besselink, Hanneke W.M. van Laarhoven, and for the Dutch Pancreatic Cancer Group
treatment characteristics, such as date of diagnosis, age at diagnosis, sex, body mass index, comorbidities, ECOG performance status, pathologic diagnosis, tumor location, tumor stage (according to AJCC, 7th edition), tumor size, tumor differentiation grade
Marsha Reyngold, Joyce Niland, Anna ter Veer, Dana Milne, Tanios Bekaii-Saab, Steven J. Cohen, Lily Lai, Deborah Schrag, John M. Skibber, William Small Jr, Martin Weiser, Neal Wilkinson, and Karyn A. Goodman
Demographic characteristics potentially associated with receipt of RT chosen for analysis included age at diagnosis, gender, racial/ethnic background, type of insurance (private, Medicare, Medicaid), household income, NCCN Member Institution, distance to the
Lindsay J. Collin, Ming Yan, Renjian Jiang, Keerthi Gogineni, Preeti Subhedar, Kevin C. Ward, Jeffrey M. Switchenko, Joseph Lipscomb, Jasmine Miller-Kleinhenz, Mylin A. Torres, Jolinta Lin, and Lauren E. McCullough
cancer outcomes. 10 – 13 Nonadherence to guidelines could arise from multiple factors, including structural racism, barriers to access, tumor and patient characteristics, or clinician and patient preferences. 11 Therefore, nonadherence to clinical
Davinia S.E. Seah, Ines Vaz Luis, Erin Macrae, Jessica Sohl, Georgia Litsas, Eric P. Winer, Nancy U. Lin, and Harold J. Burstein
subtypes. 14 Decisions about treatment are increasingly being tailored to individual patient characteristics, such as tumor subtype. This clinical classification identifies targets with established data on treatment efficacy; hormonal therapies for HR
Eva Battaglini, David Goldstein, Peter Grimison, Susan McCullough, Phil Mendoza-Jones, and Susanna B. Park
were calculated for demographic and clinical characteristics. For the comparison of respondents reporting current CIPN symptoms to those without symptoms, t tests were used for continuous variables and chi-square tests were used for categorical
James Sun, Brittany J. Mathias, Christine Laronga, Weihong Sun, Jun-Min Zhou, William J. Fulp, John V. Kiluk, and M. Catherine Lee
%) had additional nodal disease. Table 1. Demographic and Clinicopathologic Characteristics In terms of adjuvant therapy, 176 (53%) of 329 patients received RT, 245 (75%) received chemotherapy, and 272 (83%) received endocrine therapy ( Table 1 ). Records
Owen Tan, Deborah J. Schofield, and Rupendra Shrestha
Patient Characteristics Hospital and ED Costs Hospital treatment costs were estimated using Australian Refined Diagnosis Related Groups (AR-DRGs) and episode of care LoS. Cost estimates were obtained from the National Hospital Cost Data Collection
