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Treatment Patterns and Survival Outcomes in Patients With Breast Cancer on Medicaid, Pre- and Post-Expansion

Siran M. Koroukian, Weichuan Dong, Jeffrey M. Albert, Uriel Kim, Kirsten Eom, Johnie Rose, Cynthia Owusu, Kristine M. Zanotti, Gregory Cooper, and Jennifer Tsui

a score test. 31 If the proportional hazard assumption was found to be violated for a given covariate, we used a stratified Cox model—in this case, by receipt of standard treatment. Table 1. Patient Characteristics of Study Population

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Effective Translation of Research to Practice: Hospital-Based Rehabilitation Program Improves Health-Related Physical Fitness and Quality of Life of Cancer Survivors

Amy A. Kirkham, Riggs J. Klika, Tara Ballard, Paul Downey, and Kristin L. Campbell

with a goniometer and with the sit and reach test following standardized instructions, 15 respectively. Statistics Baseline characteristics were compared between the total group that enrolled in the program and the group of participants with a

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Prevalent Pseudoprogression and Pseudoresidue in Patients With Rectal Cancer Treated With Neoadjuvant Immune Checkpoint Inhibitors

Yumo Xie, Jinxin Lin, Ning Zhang, Xiaolin Wang, Puning Wang, Shaoyong Peng, Juan Li, Yuanhui Wu, Yaoyi Huang, Zhuokai Zhuang, Dingcheng Shen, Mingxuan Zhu, Xiaoxia Liu, Guangjian Liu, Xiaochun Meng, Meijin Huang, Huichuan Yu, and Yanxin Luo

study to evaluate the response pattern of nICIs compared with conventional neoadjuvant chemoradiotherapy (nCRT) in patients with MSI-H/dMMR rectal cancer and explored the underlying pathologic characteristics. Based on these findings, we proposed a

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SOURCE-PANC: A Prediction Model for Patients With Metastatic Pancreatic Ductal Adenocarcinoma Based on Nationwide Population-Based Data

Héctor G. van den Boorn, Willemieke P.M. Dijksterhuis, Lydia G.M. van der Geest, Judith de Vos-Geelen, Marc G. Besselink, Johanna W. Wilmink, Martijn G.H. van Oijen, and Hanneke W.M. van Laarhoven

treatment of metastatic disease. Tools that can accurately predict survival while taking individual characteristics and treatments into account can be helpful for clinicians and patients when making treatment decisions. Within the past decade, the

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Nationwide Trends and Determinants of Germline BRCA1/2 Testing in Patients With Breast and Ovarian Cancer

Kelsey S. Lau-Min, Anne Marie McCarthy, Katherine L. Nathanson, and Susan M. Domchek

other high-penetrance cancer susceptibility genes for a subset of patients with breast cancer (eg, based on tumor characteristics, age at diagnosis, ancestry, and family history) and all patients diagnosed with ovarian cancer. 2 Despite these

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Association Between Urologist Characteristics and Radiation Oncologist Consultation for Patients With Locoregional Prostate Cancer

Ruben G.W. Quek, Kevin C. Ward, Viraj A. Master, Chun Chieh Lin, Kenneth M. Portier, Katherine S. Virgo, and Joseph Lipscomb

patients’ treatment decisions. 7 , 8 Multiple studies have indicated that physician characteristics are important determinants of referral patterns. 9 – 13 This study examined urologists’ characteristics as determinants of radiation oncologist

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Machine Learning–Based Early Warning Systems for Acute Care Utilization During Systemic Therapy for Cancer

Robert C. Grant, Jiang Chen He, Ferhana Khan, Ning Liu, Sho Podolsky, Yosuf Kaliwal, Melanie Powis, Faiyaz Notta, Kelvin K.W. Chan, Marzyeh Ghassemi, Steven Gallinger, and Monika K. Krzyzanowska

. We also considered a soft-voting ensemble model of the 5 models. We selected the best model based on the area under the receiver operating characteristic curve (AUROC) in the tuning cohort. We also developed a simple baseline model that used the

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Contribution of Geographic Location to Disparities in Ovarian Cancer Treatment

Carolina Villanueva, Jenny Chang, Scott M. Bartell, Argyrios Ziogas, Robert Bristow, and Verónica M. Vieira

-adherent. Chemotherapy must have been delivered subsequent to surgery, with the exception of stages IIIC–IV, in which it could have been received before or after surgery. 19 , 28 – 33 Several important patient characteristics were included as predictors: age at diagnosis

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Variation in Integrated Head and Neck Cancer Care: Impact of Patient and Hospital Characteristics

Lydia F.J. van Overveld, Robert P. Takes, Jozé C.C. Braspenning, Robert J. Baatenburg de Jong, Jan P. de Boer, John J.A. Brouns, Rolf J. Bun, Eric A. Dik, Boukje A.C. van Dijk, Robert J.J. van Es, Frank J.P. Hoebers, Barry Kolenaar, Arvid Kropveld, Ton P.M. Langeveld, Hendrik P. Verschuur, Jan G.A.M. de Visscher, Stijn van Weert, Max J.H. Witjes, Ludi E. Smeele, Matthias A.W. Merkx, and Rosella P.M.G. Hermens

obtain insight into the quality of currently delivered HNC care in the Netherlands and some of the influencing characteristics to test the value of the QI set as an instrument for monitoring and improving clinical performance for this quality registration

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Reaching Populations to Address Disparities in Cancer Care Delivery: Results From a Six-Site Initiative

Noël Arring, Christopher R. Friese, Bidisha Ghosh, Marita Titler, Heidi Hamann, Sanja Percac-Lima, Adrian Sandra Dobs, Michelle J. Naughton, Pooja Mishra, Melissa A. Simon, Bingxin Chen, Electra D. Paskett, Robert J. Ploutz-Snyder, Martha Quinn, and Debra L. Barton

evaluates the representativeness of the population that participates in an intervention/program by assessing the number, characteristics, and proportions of those who participated. 23 The purpose of this publication is to report the collective results of