title: Preoperative Breast MRI: Surgeons' Patient Selection Patterns and Potential Bias in Outcomes Analyses.
abstract: OBJECTIVE
  The purpose of this study is to determine which patient- and tumor-related and clinical variables influence dedicated breast surgeons' and general surgeons' referrals for preoperative breast MRI for patients with newly diagnosed breast cancer.
  
  
  METHODS
  Surgeons who perform breast surgery responded to a survey from June 16, 2014, through August 11, 2014. Participants self-identified as breast or general surgeons and provided professional practice details. They used Likert scores (range, 1-7 with increasing likelihood to order MRI) to weigh numerous patient- and tumor-related and clinical variables. Mean likelihood scores were calculated and compared using a linear mixed model. A p ≤ 0.05 was considered statistically significant.
  
  
  RESULTS
  Two hundred eighty-nine surveys from 154 (53%) breast surgeons and 135 (47%) general surgeons showed an overall likelihood to refer for patients with a BRCA mutation (mean Likert score, 6.17), familial (mean Likert score, 5.33) or personal (mean Likert score, 5.10) breast cancer history, extremely dense breasts (mean Likert score, 5.30), age younger than 40 years (mean Likert score, 5.24), axillary nodal involvement (mean Likert score, 6.22), tumor that is mammographically occult (mean Likert score, 5.62) or fixed to the pectoralis (mean Likert score, 5.49), tumor that is a candidate for neoadjuvant treatment (mean Likert score, 5.38), multifocal or multicentric disease (mean Likert score, 5.22), invasive lobular carcinoma (mean Likert score, 5.20), T3 (mean Likert score, 4.48) or T2 (mean Likert score, 4.41) tumor, triple-negative breast cancer (mean Likert score, 4.66), a patient who is a candidate for mastectomy requesting breast conservation therapy (mean Likert score, 5.27), and radiologists' recommendations (mean Likert score, 5.19). Across all patient ages, breast surgeons referred more often than did general surgeons (mean Likert score, 4.32 vs 3.92; p = 0.03), especially for patients with BRCA mutation (mean Likert score, 6.39 vs 5.93; p = 0.01) and tumors smaller than 1 cm (mean Likert score, 3.84 vs 3.40; p = 0.002). Breast surgeons referred less often than did general surgeons for multifocal or multicentric disease (mean Likert score, 5.02 vs 5.44; p = 0.001). Breast surgeons and general surgeons similarly weighed other variables.
  
  
  CONCLUSIONS
  Preoperative breast MRI referral trended with certain higher risk patient- and tumor-related and clinical variables and were nonuniform between the breast surgeons and general surgeon cohorts. Selection bias could affect outcomes analyses for preoperative breast MRI.
authors.affiliation: 1 Department of Radiology, Breast Imaging Section, NYU Cancer Institute, Breast Imaging Center, New York University School of Medicine, 160 East 34th St, 3rd Fl, New York, NY 10016.
authors.forename: Jiyon
authors.initials: J
authors.lastname: Lee
authors.affiliation: 2 Department of Surgery, University of California, San Diego, La Jolla, CA.
authors.forename: Elaine
authors.initials: E
authors.lastname: Tanaka
authors.affiliation: 3 Department of Radiology, Virginia Mason Medical Center, Seattle, WA.
authors.forename: Peter R
authors.initials: PR
authors.lastname: Eby
authors.affiliation: 4 Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX.
authors.forename: Shouhao
authors.initials: S
authors.lastname: Zhou
authors.affiliation: 4 Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX.
authors.forename: Wei
authors.initials: W
authors.lastname: Wei
authors.affiliation: 5 Department of Radiology, Mount Sinai Beth Israel, New York, NY.
authors.forename: Christine
authors.initials: C
authors.lastname: Eppelheimer
authors.affiliation: 6 Division of Diagnostic Imaging, Banner MD Anderson Cancer Center, Gilbert, AZ.
authors.forename: Vilert A
authors.initials: VA
authors.lastname: Loving
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015982:Bias; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000601:surgery*; D000066491:Clinical Decision-Making; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D008875:Middle Aged; D009518:New York / Q000453:epidemiology; D018579:Patient Selection; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D011300:Preoperative Care / Q000706:statistics & numerical data*; D015995:Prevalence; D011379:Prognosis; D012189:Retrospective Studies; D066231:Surgeons / Q000706:statistics & numerical data*; D055815:Young Adult
keywords: breast MRI; breast cancer; breast surgeons; preoperative MRI; preoperative breast MRI