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Siew Tzuh Tang, Jen-Shi Chen, Fur-Hsing Wen, Wen-Chi Chou, John Wen-Cheng Chang, Chia-Hsun Hsieh, and Chen Hsiu Chen

eAppendix 4 ). Data Collection Participants’ characteristics were assessed at baseline (before random assignment). Data on outcome measures (LST preferences, QoL, anxiety symptoms, and depressive symptoms) and time-varying covariates were collected at

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Mohammad Abu Zaid, Paul C. Dinh Jr, Patrick O. Monahan, Chunkit Fung, Omar El-Charif, Darren R. Feldman, Robert J. Hamilton, David J. Vaughn, Clair J. Beard, Ryan Cook, Sandra Althouse, Shirin Ardeshir-Rouhani-Fard, Howard D. Sesso, Robert Huddart, Taisei Mushiroda, Michiaki Kubo, M. Eileen Dolan, Lawrence H. Einhorn, Sophie D. Fossa, Lois B. Travis, and for the Platinum Study Group

Platinum Study ( P =.30), and other clinical and sociodemographic characteristics ( supplemental eTable 1 , available with this article at JNCCN.org ). Data on the prevalence of metabolic syndrome and its risk factors in this cohort have been previously

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Christopher J. Magnani, Kevin Li, Tina Seto, Kathryn M. McDonald, Douglas W. Blayney, James D. Brooks, and Tina Hernandez-Boussard

. Characteristics of Patients Eligible for Screening In the OptumLabs 1% sample, we identified 93,334 prepolicy and 110,067 postpolicy patients. Patient counts for the control and exposure groups were equivalent for the OptumLabs analysis because patient records

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Thomas L. Sutton, Marina Affi Koprowski, Jeffrey A. Gold, Benjamin Liu, Alison Grossblatt-Wait, Caroline Macuiba, Andrea Lehman, Susan Hedlund, Flavio G. Rocha, Jonathan R. Brody, and Brett C. Sheppard

Clinicopathologic characteristics were tabulated and evaluated with Fischer’s exact test and Student t testing, as appropriate. Odds of being offered electronic distress screening, which required an active Portal, were analyzed via univariable and multivariable

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Taymeyah Al-Toubah, Eleonora Pelle, Tiffany Valone, Mintallah Haider, and Jonathan R. Strosberg

correlations and chi-square analyses. Results Patient Characteristics Supplemental eTable 1 presents patient demographics (available with this article at JNCCN.org ), and Table 1 presents tumor characteristics. A total of 462 patients met

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Richard Li, Ashwin Shinde, Marwan Fakih, Stephen Sentovich, Kurt Melstrom, Rebecca Nelson, Scott Glaser, Yi-Jen Chen, Karyn Goodman, and Arya Amini

in the final matched cohort. All statistical analyses were performed using SPSS Statistics, version 23 (IBM Corp.). Results Patient Cohort Characteristics A total of 3,729 patients with a median follow-up of 41.1 months who met the inclusion criteria

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Zhiyuan Zheng, Ahmedin Jemal, Reginald Tucker-Seeley, Matthew P. Banegas, Xuesong Han, Ashish Rai, Jingxuan Zhao, and K. Robin Yabroff

sample of the civilian noninstitutionalized US population. Because deidentified NHIS data are publicly available, this study was exempt from Institutional Review Board review. The survey collects information on demographic characteristics, access to and

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Andrew G. Robinson, Xuejiao Wei, William J. Mackillop, Yingwei Peng, and Christopher M. Booth

( Figure 1 ). Table 1 shows the characteristics of these 8,005 patients; notably, only 39% (n=3,146) had previously received radical-intent surgery or radiation-therapy. The advanced age (75% were >70 years) and sex distribution (73% were male) were

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Andrea Cercek, Karyn A. Goodman, Carla Hajj, Emily Weisberger, Neil H. Segal, Diane L. Reidy-Lagunes, Zsofia K. Stadler, Abraham J. Wu, Martin R. Weiser, Philip B. Paty, Jose G. Guillem, Garrett M. Nash, Larissa K. Temple, Julio Garcia-Aguilar, and Leonard B. Saltz

measured. 15 Pathologic complete response (pathCR) was defined as the complete disappearance of all tumor cells. Results Patient Characteristics Of approximately 300 patients with rectal cancer treated between 2007 and 2012 at MSKCC and its

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Mandy R. Sakamoto, Megan Eguchi, Christine M. Azelby, Jennifer R. Diamond, Christine M. Fisher, Virginia F. Borges, Cathy J. Bradley, and Peter Kabos

Characteristics We used SEER data on patient age, year of diagnosis, race/ethnicity, marital status, poverty rate at the census tract, education level, practice setting, census tract rural-urban commuting area codes, geographic region, and tumor stage ( Table 1