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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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Kan Wu, Xu Liu, Zhihong Liu, Yiping Lu, Xianding Wang, and Xiang Li

nonmetastatic ACC using a large population-based database. In addition, we sought to identify a subset of patients with ACC who may be more likely to benefit from adjuvant radiation based on their tumor characteristics. Patients and Methods Study

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Christopher P. Chung, Carolyn Behrendt, Louise Wong, Sarah Flores, and Joanne E. Mortimer

classified according to the IIQ-7 score as major (33–99), moderate (5–29), or no impact (0). Statistical Analyses For this exploratory study, statistical significance ( P <.05) was unadjusted for multiple hypothesis testing. Demographic characteristics (age

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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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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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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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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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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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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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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