title: Predictors of preoperative MRI for breast cancer: differences by data source.
abstract: OBJECTIVE
  Investigate how the results of predictive models of preoperative MRI for breast cancer change based on available data.
  
  
  METHODS
  A total of 1919 insured women aged ≥18 with stage 0-III breast cancer diagnosed 2002-2009. Four models were compared using nested multivariable logistic, backwards stepwise regression; model fit was assessed via area under the curve (AUC), R2.
  
  
  RESULTS
  MRI recipients (n = 245) were more recently diagnosed, younger, less comorbid, with higher stage disease. Significant variables included: Model 1/Claims (AUC = 0.76, R2= 0.10): year, age, location, income; Model 2/Cancer Registry (AUC = 0.78, R2= 0.12): stage, breast density, imaging indication; Model 3/Medical Record (AUC = 0.80, R2= 0.13): radiologic recommendations; Model 4/Risk Factor Survey (AUC = 0.81, R2= 0.14): procedure count.
  
  
  CONCLUSIONS
  Clinical variables accounted for little of the observed variability compared with claims data.
authors.affiliation: Fred Hutchinson Cancer Research Center, Clinical Research Division, 1100 Fairview Ave, D5-380, Seattle, WA 98109, USA.
authors.forename: Elizabeth T
authors.initials: ET
authors.lastname: Loggers
authors.affiliation: Group Health Research Institute, Seattle, WA, USA.
authors.forename: Hongyuan
authors.initials: H
authors.lastname: Gao
authors.affiliation: School of Pharmacy, University of Washington, Seattle, WA, USA.
authors.forename: Laura S
authors.initials: LS
authors.lastname: Gold
authors.affiliation: Department of Health Services, School of Public Health, University of Washington, Seattle, WA, USA.|Fred Hutchinson Cancer Research Center, Public Health Sciences Division, Seattle, WA, USA.
authors.forename: Larry
authors.initials: L
authors.lastname: Kessler
authors.affiliation: Department of Health Services, School of Public Health, University of Washington, Seattle, WA, USA.|Fred Hutchinson Cancer Research Center, Public Health Sciences Division, Seattle, WA, USA.
authors.forename: Ruth
authors.initials: R
authors.lastname: Etzioni
authors.affiliation: Group Health Research Institute, Seattle, WA, USA.|Department of Health Services, School of Public Health, University of Washington, Seattle, WA, USA.|Fred Hutchinson Cancer Research Center, Public Health Sciences Division, Seattle, WA, USA.
authors.forename: Diana Sm
authors.initials: DS
authors.lastname: Buist
keywords: MRI; breast cancer; chart abstraction; claims/utilization data; predictive variables; risk factor data; survey data