Predictors of preoperative MRI for breast cancer: differences by data source. (May 2015)

• Record Type: Journal Article
• Authors: Loggers, Elizabeth T; Gao, Hongyuan; Gold, Laura S; Kessler, Larry; Etzioni, Ruth; Buist, Diana SM
• Is Part Of: Journal of comparative effectiveness research. Volume 4:Number 3(2015)
• Page Start: 215
• Page End: 226
• Publication Date: 2015-05
• Subjects: breast cancer -- chart abstraction -- claims/utilization data -- MRI -- predictive variables -- risk factor data -- survey data; Medical care -- Research -- Periodicals; Medical care -- Research -- Evaluation -- Periodicals; Medical care -- Decision making -- Periodicals; Evidence-based medicine -- Periodicals; Medicine, Comparative -- Periodicals; 362.1072
• DOI: 10.2217/cer.15.1
• Languages: English
• ISSNs: 2042-6305

Abstract

Aim: Investigate how the results of predictive models of preoperative MRI for breast cancer change based on available data.Materials & 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), R 2 .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, R 2 = 0.10): year, age, location, income; Model 2/Cancer Registry (AUC = 0.78, R 2 = 0.12): stage, breast density, imaging indication; Model 3/Medical Record (AUC = 0.80, R 2 = 0.13): radiologic recommendations; Model 4/Risk Factor Survey (AUC = 0.81, R 2 = 0.14): procedure count.Conclusion: Clinical variables accounted for little of the observed variability compared with claims data.