Literature DB >> 28026205

Preoperative Breast MRI: Surgeons' Patient Selection Patterns and Potential Bias in Outcomes Analyses.

Jiyon Lee1, Elaine Tanaka2, Peter R Eby3, Shouhao Zhou4, Wei Wei4, Christine Eppelheimer5, Vilert A Loving6.   

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.
MATERIALS AND 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.
CONCLUSION: 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.

Entities:  

Keywords:  breast MRI; breast cancer; breast surgeons; preoperative MRI; preoperative breast MRI

Mesh:

Year:  2016        PMID: 28026205     DOI: 10.2214/AJR.16.17038

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  6 in total

1.  Major Factors Driving Expert Opinion on Preoperative Breast MRI Do Not Predict Additional Disease.

Authors:  Lars J Grimm
Journal:  Radiol Imaging Cancer       Date:  2020-07-10

2.  The Impact of Preoperative Breast Magnetic Resonance Imaging on Surgical Management in Symptomatic Patients With Invasive Lobular Carcinoma.

Authors:  Brian M Moloney; Peter F McAnena; Éanna J Ryan; Ellen O Beirn; Ronan M Waldron; AnnaMarie O Connell; Sinead Walsh; Rachel Ennis; Catherine Glynn; Aoife J Lowery; Peter A McCarthy; Michael J Kerin
Journal:  Breast Cancer (Auckl)       Date:  2020-08-14

Review 3.  Imaging in Locoregional Management of Breast Cancer.

Authors:  Christiane K Kuhl; Constance Lehman; Isabelle Bedrosian
Journal:  J Clin Oncol       Date:  2020-05-22       Impact factor: 44.544

4.  Utilization of breast MRI and breast MRI-guided biopsy in clinical practice: results of a survey in Québec and France.

Authors:  Benoît Mesurolle; Simon Sun; Michelle Zhang
Journal:  Insights Imaging       Date:  2020-07-01

5.  Magnetic resonance imaging before breast cancer surgery: results of an observational multicenter international prospective analysis (MIPA).

Authors:  Francesco Sardanelli; Rubina M Trimboli; Nehmat Houssami; Fiona J Gilbert; Thomas H Helbich; Marina Álvarez Benito; Corinne Balleyguier; Massimo Bazzocchi; Peter Bult; Massimo Calabrese; Julia Camps Herrero; Francesco Cartia; Enrico Cassano; Paola Clauser; Andrea Cozzi; Danúbia A de Andrade; Marcos F de Lima Docema; Catherine Depretto; Valeria Dominelli; Gábor Forrai; Rossano Girometti; Steven E Harms; Sarah Hilborne; Raffaele Ienzi; Marc B I Lobbes; Claudio Losio; Ritse M Mann; Stefania Montemezzi; Inge-Marie Obdeijn; Umit A Ozcan; Federica Pediconi; Katja Pinker; Heike Preibsch; José L Raya Povedano; Daniela Sacchetto; Gianfranco P Scaperrotta; Simone Schiaffino; Margrethe Schlooz; Botond K Szabó; Donna B Taylor; Özden S Ulus; Mireille Van Goethem; Jeroen Veltman; Stefanie Weigel; Evelyn Wenkel; Chiara Zuiani; Giovanni Di Leo
Journal:  Eur Radiol       Date:  2021-10-13       Impact factor: 5.315

6.  Perioperative magnetic resonance imaging in breast cancer care: Distinct adoption trajectories among physician patient-sharing networks.

Authors:  Xiao Xu; Pamela R Soulos; Jeph Herrin; Shi-Yi Wang; Craig Evan Pollack; Brigid K Killelea; Howard P Forman; Cary P Gross
Journal:  PLoS One       Date:  2022-03-15       Impact factor: 3.240

  6 in total

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