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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

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Validating a Patient-Reported Outcomes–Derived Algorithm for Classifying Symptom Complexity Levels Among Patients With Cancer

Linda Watson, Siwei Qi, Andrea DeIure, Eclair Photitai, Lindsi Chmielewski, and Louise Smith

(AUC) of receiver operating characteristic (ROC). Data were exported into SPSS Statistics, version 25 (IBM Corp) for analysis and statistical significance was set a priori at P <.05. Results Sample Characteristics Mean age at diagnosis was 63 years (SD

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External Validation of Risk Factors for Unplanned Hospitalization in Older Adults With Advanced Cancer Receiving Chemotherapy

Mostafa R. Mohamed, Kah Poh Loh, Supriya G. Mohile, Michael Sohn, Tracy Webb, Megan Wells, Sule Yilmaz, Rachael Tylock, Eva Culakova, Allison Magnuson, Can-Lan Sun, James Bearden, Judith O. Hopkins, Bryan A. Faller, and Heidi D. Klepin

hospitalization: (1) demographic variables including age, gender, race, education, and income; (2) clinical characteristics including cancer stage, treatment regimen (standard vs nonstandard), palliative treatment line (first- vs second-line or greater); and (3

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The Impact of Insurance Status on Tumor Characteristics and Treatment Selection in Contemporary Patients With Prostate Cancer

Nicola Fossati, Daniel P. Nguyen, Quoc-Dien Trinh, Jesse Sammon, Akshay Sood, Alessandro Larcher, Giorgio Guazzoni, Francesco Montorsi, Alberto Briganti, Mani Menon, and Firas Abdollah

characteristics, 5 , 6 and none of these examined the interplay between insurance status, cancer characteristics, and treatment selection. This is of utmost importance, because tumor characteristics represent established predictors of cancer prognosis and play a

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Fecal Immunochemical Testing in Patients With Low-Risk Symptoms of Colorectal Cancer: A Diagnostic Accuracy Study

Alex J. Ball, Imran Aziz, Sophie Parker, Ravishankar B. Sargur, Jonathan Aldis, and Matthew Kurien

. Receiver operating characteristics (ROC) are plotted for FIT against CRC diagnosis. Results FIT Returns and Patient Characteristics Between October 1, 2019, and December 31, 2019, a total of 4,219 FIT requests were received from primary care

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High-Cost Patients and Preventable Spending: A Population-Based Study

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

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Clinical Trial Accrual at Initial Course of Therapy for Cancer and Its Impact on Survival

Nicholas G. Zaorsky, Ying Zhang, Vonn Walter, Leila T. Tchelebi, Vernon M. Chinchilli, and Niraj J. Gusani

diagnosed in the United States. The NCDB 7 records demographics, comorbidities, tumor characteristics, and overall survival (OS), and contains information regarding therapies delivered during the first course of treatment (ie, surgery, radiation therapy [RT

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Outcomes and Predictors of 28-Day Mortality in Patients With Hematologic Malignancies and Septic Shock Defined by Sepsis-3 Criteria

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

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Guideline Familiarity Predicts Variation in Self-Reported Use of Routine Surveillance PET/CT by Physicians Who Treat Head and Neck Cancer

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

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Inherited Mutations in Chinese Men With Prostate Cancer

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