Predictors of preoperative MRI for breast cancer: differences by data source
Year: 2015
Type: article
Study design: Observational Study
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.
DOI: 10.2217/cer.15.1
Authors: Elizabeth T Loggers, Hongyuan Gao, Laura S Gold, Larry Kessler, Ruth Etzioni, Diana SM Buist, ADVICE Investigators
Language: English
Topic: MRI in cancer diagnosis
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: G2087751801, SURVEILLANCE EPIDEMIOLOGY &END RESULTS PROGRAM, SURVEILLANCE, EPIDEMIOLOGY, AND END RESULTS (SEER) PROGRAM., Comparative effectiveness of breast imaging strategies in community practice, G8550955980, Advancing Risk-based Breast Cancer Screening and Surveillance in Community Practice
OpenAlex ID: W1856603163