Assessing accuracy of mammography in the presence of verification bias and intrareader correlation

Biometrics

Volumn 61, Issue 1, 2005, Pages 259-268

  Zheng, Yingye ^a   Barlow, William E ^a   Cutter, Gary ^b  

^a Fred Hutchinson Cancer Research Center   (United States)

^b UNIVERSITY OF ALABAMA AT BIRMINGHAM   (United States)

Author keywords

Correlated data; Estimating equations; Ordinal regression; Verification bias

Indexed keywords

CORRELATED DATA; DIAGNOSTIC TESTS; DISEASE STATE; ESTIMATING EQUATIONS; MEDICAL DIAGNOSTICS; ORDINAL REGRESSION; PERFORMANCE; RECEIVER OPERATING CHARACTERISTICS ANALYSIS; TEST ACCURACY; VERIFICATION BIAS;

DIAGNOSIS;

ERROR ANALYSIS;

ADULT; BREAST CANCER; CANCER RISK; CANCER SCREENING; COHORT ANALYSIS; DIAGNOSTIC ACCURACY; DIAGNOSTIC PROCEDURE; FEMALE; HUMAN; MAMMOGRAPHY; MATHEMATICAL ANALYSIS; OBSERVATION; PROBABILITY; RADIOLOGIST; RECEIVER OPERATING CHARACTERISTIC; REGRESSION ANALYSIS; REVIEW; RISK FACTOR; STANDARD;

EID: 15044345246     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.2005.031139.x     Document Type: Review

References (20)

1. ACR. (1998). Illustrated Breast Imaging Reporting and Data System (BI-RADS™). Reston, Virginia: American College of Radiology.
2. Alonzo, T. A., Pepe, M. S., and Lumley, T. (2003). Estimating disease prevalence in two-phase studies. Biostatistics 4, 313-326.
3. Ballard-Barbash, R., Taplin, S. H., Yankaskas, B. C., Ernster, V. L., Rosenberg, R. D., and Carney, P. A. (1997). Breast cancer surveillance consortium: A national mammography screening and outcomes database. American Journal of Roentgenology 169, 1001-1008.
4. Begg, C. B. and Greenes, R. A. (1983). Assessment of diagnostic tests when disease verification is subject to selection bias. Biometrics 39, 207-215.
5. Hanley, J. A. (1988). The robustness of the binormal assumptions used in fitting ROC curves. Medical Decision Making 8, 197-203.
6. Holcroft, C. A., Rotnitzky, A., and Robins, J. M. (1997). Efficient estimation of regression parameters from multi-stage studies with validation of outcome and covariates. Journal of Statistical Planning and Inference 65, 349-374.
7. Horvitz, D. and Thompson, D. J. (1951). A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association 47, 663-685.
8. Hosmer, D. W. and Lemeshow, S. (2000). Applied Logistic Regression. New York: John Wiley & Sons.
9. Lipsitz, S. R., Ibrahim, J. G., and Zhao, L. P. (1999). A weighted estimating equation for missing covariate data with properties similar to maximum likelihood. Journal of the American Statistical Association 94, 1147-1160.
10. Little, R. J. A. and Rubin, D. B. (1987). Statistical Analysis with Missing Data. New York: John Wiley & Sons.
11. Metz, C. E. (1986). ROC methodology in radiologic imaging. Investigative Radiology, 720-733.
12. Pepe, M. S. (2003). The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford: Oxford University Press.
13. Pepe, M. S. and Anderson, G. L. (1994). A cautionary note on inference for marginal regression models with longitudinal data and general correlated response data. Communications in Statistics B - Simulation and Computation 23, 939-951.
14. Punglia, R., D'Amico, A., Catalona, W., Roehl, K., and Kuntz, K. (2003). Effect of verification bias on screening for prostate cancer by measurement of prostate-specific antigen. New England Journal of Medicine 349, 335-342.
15. Robins, J. M., Rotnitzky, A., and Zhao, L. P. (1994). Estimation of regression coefficients when some regressors are not always observed. Journal of the American Statistical Association 89, 846-866.
16. Rodenberg, C. and Zhou, X.-H. (2000). ROC curve estimation when covariates affect the verification process. Biometrics 56, 1256-1262.
17. Schisterman, E. and Rotnitzky, A. (2001). Estimation of the mean of a K-sample U-statistic with missing outcomes and auxiliaries. Biometrika 88, 713-725.
18. Swets, J. A. (1986). Form of empirical ROCs in discrimination and diagnostic tasks: Implications for theory and measurement of performance. Psychological Bulletin 99, 181-198.
19. Toledano, A. Y. and Gatsonis, C. (1996). Ordinal regression methodology for ROC curves derived from correlated data. Statistics in Medicine 15, 1807-1826.
20. Tosteson, A. N. and Begg, C. B. (1988). A general regression methodology for ROC curve estimation. Medical Decision Making 8, 204-215.