title: An individual person data meta-analysis of preoperative magnetic resonance imaging and breast cancer recurrence.
abstract: OBJECTIVE
  There is little consensus regarding preoperative magnetic resonance imaging (MRI) in breast cancer (BC). We examined the association between preoperative MRI and local recurrence (LR) as primary outcome, as well as distant recurrence (DR), in patients with BC.
  
  
  METHODS
  An individual person data (IPD) meta-analysis, based on preoperative MRI studies that met predefined eligibility criteria, was performed. Survival analysis (Cox proportional hazards modeling) was used to investigate time to recurrence and to estimate the hazard ratio (HR) for MRI. We modeled the univariable association between LR (or DR) and MRI, and covariates, and fitted multivariable models to estimate adjusted HRs. Sensitivity analysis was based on women who had breast conservation with radiotherapy.
  
  
  RESULTS
  Four eligible studies contributed IPD on 3,180 affected breasts in 3,169 subjects (median age, 56.2 years). Eight-year LR-free survival did not differ between the MRI (97%) and no-MRI (95%) goups (P = .87), and the multivariable model showed no significant effect of MRI on LR-free survival: HR for MRI (versus no-MRI) was 0.88 (95% CI, 0.52 to 1.51; P = .65); age, margin status, and tumor grade were associated with LR-free survival (all P < .05). HR for MRI was 0.96 (95% CI, 0.52 to 1.77; P = .90) in sensitivity analysis. Eight-year DR-free survival did not differ between the MRI (89%) and no-MRI (93%) groups (P = .37), and the multivariable model showed no significant effect of MRI on DR-free survival: HR for MRI (v no-MRI) was 1.18 (95% CI, 0.76 to 2.27; P = .48) or 1.31 (95% CI, 0.76 to 2.27; P = .34) in sensitivity analysis.
  
  
  CONCLUSIONS
  Preoperative MRI for staging the cancerous breast does not reduce the risk of LR or DR.
authors.affiliation: Nehmat Houssami, Robin Turner, Petra Macaskill, the Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia; Lindsay W. Turnbull, Centre for Magnetic Resonance Investigations, Hull York Medical School in association with University of Hull, Hull, United Kingdom; David R. McCready, Princess Margaret Cancer Centre, University of Toronto, Toronto, Ontario, Canada; Todd M. Tuttle, University of Minnesota, Minneapolis, MN; Neha Vapiwala and Lawrence J. Solin, University of Pennsylvania School of Medicine; Lawrence J. Solin, Albert Einstein Medical Center, Philadelphia, PA.
authors.forename: Nehmat
authors.initials: N
authors.lastname: Houssami
authors.forename: Robin
authors.initials: R
authors.lastname: Turner
authors.forename: Petra
authors.initials: P
authors.lastname: Macaskill
authors.forename: Lindsay W
authors.initials: LW
authors.lastname: Turnbull
authors.forename: David R
authors.initials: DR
authors.lastname: McCready
authors.forename: Todd M
authors.initials: TM
authors.lastname: Tuttle
authors.forename: Neha
authors.initials: N
authors.lastname: Vapiwala
authors.forename: Lawrence J
authors.initials: LJ
authors.lastname: Solin
mesh_terms: D001943:Breast Neoplasms / Q000401:mortality / Q000556:secondary* / Q000628:therapy*; D018572:Disease-Free Survival; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008279:Magnetic Resonance Imaging; D008408:Mastectomy / Q000009:adverse effects / Q000401:mortality; D008875:Middle Aged; D015999:Multivariate Analysis; D060787:Neoplasm Grading; D009364:Neoplasm Recurrence, Local / Q000401:mortality / Q000517:prevention & control*; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D011300:Preoperative Care; D016016:Proportional Hazards Models; D018714:Radiotherapy, Adjuvant; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome