The positive predictive value for diagnosis of breast cancer full-field digital mammography versus film-screen mammography in the diagnostic mammographic population.

RATIONALE AND

OBJECTIVES

Diagnostic mammography is performed on women with clinical symptoms that suggest breast cancer or women for whom further mammographic evaluation has been requested because of an abnormal screening mammography. We assessed whether the use of full-field digital mammography would improve the positive predictive value (PPV) for the diagnosis of breast cancer in a diagnostic population compared with film-screen mammography.

MATERIALS AND

METHODS

From January 2002 to December 2003, 11,621 patients underwent diagnostic mammography at the University of North Carolina Hospital, Chapel Hill. Among these 11,621 patients, 1400 lesions in 1121 patients underwent biopsy. We included the biopsy-performed lesions, so PPV3 was used for comparison of PPVs between film-screen mammography and full-field digital mammography. Six breast radiologists interpreted the images using the Breast Imaging Reporting and Data System of the American College of Radiology. PPV3s were compared between film-screen and full-field digital mammography in the entire study cohort and in specified subgroups according to different radiologists, breast density, and lesion type on mammography. The chi(2) and Fisher's exact tests were used for comparison of PPV3s between two modalities of mammography with the Bonferroni procedure for subgroup analysis.

RESULTS

In the entire study cohort, PPV3s of full-field digital mammography and film-screen mammography were similar (difference in PPV3,-0.007; 95% confidence interval, -0.081 to 0.068; P = .8602). In predefined subgroups, there was no difference in PPV3 by the radiologist, breast density, or lesion type between two modalities of mammography (P > .005).

CONCLUSION

There is no improvement in PPV for the diagnosis of breast cancer with full-field digital mammography compared with film-screen mammography in a large diagnostic population.