240 (46.0%) were HER2-low, 142 (27.2%) HER2+, 46 (8.8%) HER2 IHC 0, and 94 (18.0%) had unknown/incomplete HER2 results. Among the HER2-low patients, 198 (82.5%) were HR+, 40 (16.7%) were HR-, and 2 (0.8%) were unknown. The tumor characteristics and
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Alexandre Hikiji Watanabe, Connor Willis, Melissa Pavilack-Kirker, Clara Lam, Leah Park, Sandhya Mehta, Jackie Kwong, Anindit Chhibber, Hillevi Bauer, Sabrina Ilham, Diana Brixner, and David Stenehjem
Claire de Oliveira, Joyce Cheng, Kelvin Chan, Craig C. Earle, Murray Krahn, and Nicole Mittmann
and identified patient and system characteristics associated with high system costs after cancer treatment. The most common trajectory consisted of patients who were low-cost in the year before cancer treatment and remained low-cost after completing
Sevinj E. Rahimzade, Jamil A. Aliyev, Elkhan E. Kazimov, Leylakhanum A. Melikova, Konul S. Mardanova, Turkan E. Mansurova, and Elchin B. Mansurov
gynecological anamnesis characteristics in Azerbaijani women with BC and investigation of the prognostic significance of the relationship with the stage (S) of BC and biological subtypes (BS). Materials: 570 randomly selected women with BC were included in the
Nirmala K. Manjappachar, John A. Cuenca, Claudia M. Ramírez, Mike Hernandez, Peyton Martin, Maria P. Reyes, Alba J. Heatter, Cristina Gutierrez, Nisha Rathi, Charles L. Sprung, Kristen J. Price, and Joseph L. Nates
bias. We also excluded all postsurgical patients. Data Sources and Measurements Demographic and clinical information such as age, sex, comorbidities, Charlson comorbidity index (CCI), and characteristics of cancer, such as cancer diagnosis
Yao Zhu, Yu Wei, Hao Zeng, Yonghong Li, Chi-Fai Ng, Fangjian Zhou, Caiyun He, Guangxi Sun, Yuchao Ni, Peter K.F. Chiu, Jeremy Y.C. Teoh, Beihe Wang, Jian Pan, Fangning Wan, Bo Dai, Xiaojian Qin, Guowen Lin, Hualei Gan, Junlong Wu, and Dingwei Ye
), but detailed clinical characteristics were not available for patients from the commercial laboratory. Patients from the laboratory were offered germline sequencing, according to the genetic testing recommendations in the NCCN Clinical Practice
Benjamin R. Roman, Snehal G. Patel, Marilene B. Wang, Anna M. Pou, F. Christopher Holsinger, David Myssiorek, David Goldenberg, Samuel Swisher-McClure, Alexander Lin, Jatin P. Shah, and Judy A. Shea
-level factors related to the decision to use surveillance imaging are not well understood. Several studies have found that physician demographic and practice characteristics correlate with surveillance testing use in breast and colon cancers. 7 , 10 , 11
Benjamin L. Franc, Timothy P. Copeland, Robert Thombley, Miran Park, Ben Marafino, Mitzi L. Dean, W. John Boscardin, Hope S. Rugo, David Seidenwurm, Bhupinder Sharma, Stephen R. Johnston, and R. Adams Dudley
included in the study when the claim included an indication of breast cancer (ICD-9 codes 174.0–174.9). Patient characteristics examined included age group, whether RT was received, whether hormonal therapy was received, payer class, and MSA. Patients
Jessica S.W. Borgers, Richard P. Tobin, Robert J. Torphy, Victoria M. Vorwald, Robert J. Van Gulick, Carol M. Amato, Dasha T. Cogswell, Tugs-Saikhan Chimed, Kasey L. Couts, Adrie Van Bokhoven, Christopher D. Raeburn, Karl D. Lewis, Joshua Wisell, Martin D. McCarter, Rao R. Mushtaq, and William A. Robinson
stage IV disease without AGMs were identified. Patients without a valid research consent, incomplete medical records, or inadequate follow-up information were excluded. The following patient and tumor characteristics were collected from electronic
Ali Mokdad, Travis Browning, John C. Mansour, Hao Zhu, Amit G. Singal, and Adam C. Yopp
on characteristic radiographic imaging on dynamic contrasted-enhanced CT or MRI. Most of these diagnostic imaging studies are ordered by primary care physicians, who are at the beginning of the cancer care continuum and must not only discern an
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
Cancer Staging Manual 26 based on pelvic MRI and CT imaging. Figure 1. (A) Patient flow and (B) the timeline for the longitudinal analysis in this study. Patients were grouped based on CEA level and recurrent status. The clinical characteristics
