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Comorbidities, Rather Than Older Age, Are Strongly Associated With Higher Utilization of Healthcare in Colorectal Cancer Survivors

Melissa S.Y. Thong, Daniel Boakye, Lina Jansen, Uwe M. Martens, Jenny Chang-Claude, Michael Hoffmeister, Hermann Brenner, and Volker Arndt

of demographic and clinical characteristics by CCIS were tested for statistical significance using either an analysis of variance for continuous variables or a chi-square test for categorical variables. We used multivariable linear regression to

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Trends in Annual Surveillance Mammography Participation Among Breast Cancer Survivors From 2004 to 2016

Kathryn P. Lowry, Katherine A. Callaway, Janie M. Lee, Fang Zhang, Dennis Ross-Degnan, J. Frank Wharam, Karla Kerlikowske, Karen J. Wernli, Allison W. Kurian, Louise M. Henderson, and Natasha K. Stout

enrollment. Results Cohort Selection and Characteristics Of 27,456,015 women enrolled from 2004 to 2016, we identified 141,672 aged 40 to 64 years with evidence of a personal breast cancer history meeting our inclusion/exclusion criteria

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Long-Term Patterns of Oral Anticancer Agent Adoption, Duration, and Switching in Patients With CML

Matthew P. Banegas, Donna R. Rivera, Maureen C. O’Keeffe-Rosetti, Nikki M. Carroll, Pamala A. Pawloski, David C. Tabano, Mara M. Epstein, Kai Yeung, Mark C. Hornbrook, Christine Lu, and Debra P. Ritzwoller

standards. 22 VTR data were obtained via chart review by trained abstractors and included data associated with health service use and clinical, treatment, and tumor characteristics. The VDW pharmacy files provided data on national drug code

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“Standard Care” in Cancer Clinical Trials: An Analysis of Care Provided to Women in the Control Arms of Breast Cancer Clinical Trials

Rachel F. Dear, Kevin McGeechan, Megan B. Barnet, Alexandra L. Barratt, and Martin H.N. Tattersall

were extracted from ClinicalTrials.gov . Of these, 500 did not meet inclusion criteria, most because they did not use a drug intervention (80%; 400/500). Trials may have been excluded for more than one reason ( Figure 1 ). Characteristics of the 215

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Body Mass Index and Weight Change in Patients With HER2-Positive Early Breast Cancer: Exploratory Analysis of the ALTTO BIG 2-06 Trial

Samuel Martel, Matteo Lambertini, Dominique Agbor-Tarh, Noam F. Ponde, Andrea Gombos, Vicki Paterson, Florentine Hilbers, Larissa Korde, Anna Manukyants, Amylou Dueck, Christian Maurer, Martine Piccart, Alvaro Moreno-Aspitia, Christine Desmedt, Serena Di Cosimo, and Evandro de Azambuja

original ALTTO trial. 10 Statistical Considerations Patient baseline characteristics were compared with respect to BMI category (underweight, normal weight, overweight, obese) using the chi-square test. Weight change was calculated as a percentage (by

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Clinical Utility of 18F-FDG PET/CT in Staging Localized Breast Cancer Before Initiating Preoperative Systemic Therapy

Heidi Ko, Yaser Baghdadi, Charito Love, and Joseph A. Sparano

for categorical variables. Association Between Clinical Characteristics and Upstaging Frequencies Associations between clinical characteristics and upstaging frequencies were assessed using the Fisher exact test for categorical variables and the

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Frailty in Patients With Newly Diagnosed Diffuse Large B-Cell Lymphoma Receiving Curative-Intent Therapy: A Population-Based Study

Abi Vijenthira, Lee Mozessohn, Chenthila Nagamuthu, Ning Liu, Danielle Blunt, Shabbir Alibhai, Anca Prica, and Matthew C. Cheung

frequency and percentages where appropriate. The Student t test was used to compare baseline characteristics, frailty scores, and chemoimmunotherapy cycles received between frail and nonfrail patients. The chi-square test was used to compare categorical

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A US Registry–Based Assessment of Use and Impact of Chemotherapy in Stage I HER2-Positive Breast Cancer

Benjamin M. Parsons, Dipesh Uprety, Angela L. Smith, Andrew J. Borgert, and Leah L. Dietrich

potential associations between sociodemographic, stage, estrogen receptor (ER)/progesterone receptor (PR) status, and tumor and treatment characteristics using Pearson chi-square or Fisher exact tests. Survival analysis using Kaplan-Meier curves Figure 1

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Guideline Discordance and Patient Cost Responsibility in Medicare Beneficiaries With Metastatic Breast Cancer

Courtney P. Williams, Andres Azuero, Kelly M. Kenzik, Maria Pisu, Ryan D. Nipp, Smita Bhatia, and Gabrielle B. Rocque

years. 4 , 5 Covariates Patient demographic and clinical characteristics were compared and used for model adjustment, including age at index diagnosis, race (white, black, other) type of MBC (de novo vs treated, secondary metastatic disease), HR status

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Cost Implications and Complications of Overtreatment of Low-Risk Prostate Cancer in the United States

Ayal A. Aizer, Xiangmei Gu, Ming-Hui Chen, Toni K. Choueiri, Neil E. Martin, Jason A. Efstathiou, Andrew S. Hyatt, Powell L. Graham, Quoc-Dien Trinh, Jim C. Hu, and Paul L. Nguyen

cancer and a short life expectancy in the United States. Subjects/Patients and Methods Patient Characteristics and Study Design A population-based study was conducted of patients with low-risk prostate cancer identified by the SEER