And less frequently are you warned that these cancer tests could actually kill you!
Again as Women's Health Month continues throughout March, remember the ground breaking work of Dr. John Gofman who proved that mammogram causes cancer.
Computer-Aided Detection Hinders Mammography
Author: Allison Gandey
April 6, 2007 — A study shows that computer-aided detection reduces the accuracy of mammography by increasing false-positive results and boosting recall and biopsy rates. Published in the April 5 issue of The New England Journal of Medicine, the work by Joshua J. Fenton, MD, MPH, from the University of California, Davis, in Sacramento, California, and colleagues, already is sparking reaction. In an accompanying editorial, Ferris M. Hall, MD, from the Beth Israel Deaconess Medical Center in Boston, Massachusetts, calls the findings "a substantial hit to this technology." Dr. Hall writes that the study will surprise and disappoint most mammographers.
Initially developed to assist radiologists, computer-aided detection analyzes digitized mammograms and identifies suspicious areas for review by the radiologist. Promising studies led to its approval by the US Food and Drug Administration (FDA) in 1998, and Medicare and many insurance companies now reimburse for its use. Within 3 years of FDA approval, 10% of mammography facilities in the United States adopted the technology and more have done so since. Dr. Fenton told Medscape that his colleagues estimate that number to be about 25% to 30% of facilities today.
"It's not clear just how popular computer-aided detection is," Dr. Fenton said during an interview. "It's still considered a big-ticket item and is seen as a large capital investment in mammography — a not very lucrative area."
Still, Dr. Hall points out that the work is the "most comprehensive analysis of computer-aided detection in breast screening to date." The study involved more than 429,000 mammograms and 2351 cases of cancer that were detected at 43 facilities of the Breast Cancer Surveillance Consortium. During 4 years of observation, 7 of 43 facilities implemented computer-aided detection allowing for a comparison of the performance at these facilities and their individual radiologists before and after the use of computer-aided detection. The facilities that did not implement the technology served as controls.
Not Only Failed to Increase Cancer Detection, but Was Harmful
The investigators found that the use of computer-aided detection not only failed to significantly increase the cancer-detection rate but also was harmful because of the increased number of false-positive results leading to significantly more call-backs and biopsies. These downstream costs, which also may include payments to surgeons and pathologists, account for perhaps one third of the total cost of breast-screening programs, the researchers propose.
"Our study suggests that this technology may not offer a benefit in the way people would have hoped," Dr. Fenton told Medscape. The investigators explain that approximately 157 women would be recalled and 15 women would undergo biopsy to detect 1 additional case of cancer, possibly a ductal carcinoma in situ. After accounting for the additional fees for the use of computer-aided detection and the costs of diagnostic evaluations after recalls resulting from the use of the technology, the group calculates that system-wide use could increase the annual national costs of screening mammography by approximately 18%.
"One possible flaw in the study was the failure to assess the time it takes to adjust to computer-aided detection," Dr. Hall writes in the editorial. "Mammographers initially exposed to computer-aided detection may be unduly influenced by the 3 to 4 marks the software places on each mammogram, with the necessity to ignore the 1000 to 2000 false positive marks for every true positive mark. The adjustment to computer-aided detection has been estimated to take weeks to years."
The researchers also found that computer-aided detection was disproportionately associated with the detection of ductal carcinoma in situ. Dr. Hall notes this is not surprising because computer-aided detection is relatively more sensitive in detecting microcalcifications than in detecting masses. "The relationship of ductal carcinoma in situ to invasive breast cancer remains unclear: all invasive breast cancers probably arise from an in situ monoclonal cancer," Dr. Hall writes, "but many of these lesions may never progress to invasive cancer during a woman's lifetime."
Dr. Hall argues that it took 2 to 3 decades of controversy before it was proved that screening mammography saves lives. "What is the future of breast imaging? I find it hard to believe that we will continue to use mammography to screen up to one quarter of the adult population of the world annually. Mammography is an inherently poor, 2-dimensional projectional method being used to diagnose small, 3-dimensional cancers."
Dr. Hall recommends larger, controlled studies of computer-aided detection that assess not only cancer diagnosis but also the gold standard of mortality. "But," the editorialist notes, "such studies will be expensive, controversial, indeterminate, or quickly passé owing to the emergence of new technology."
N Engl J Med. 2007;356:1399-1409, 1464-1466.
According to the current study by Fenton and colleagues, computer-aided detection of mammography was approved by the FDA in 1998 to improve mammogram interpretation. This method was initially shown to improve the number of diagnosed cases of breast cancer by 10% to 15%, but the false-positive rates resulting in breast biopsies and the sensitivity, specificity, and positive predictive value for this method of interpretation have not been examined in large trials. Moreover, because this method is more sensitive for detecting microcalcifications than for detecting breast masses, the authors postulated that it may disproportionately increase detection of carcinoma in situ rather than invasive breast cancer, which may not translate to reduction in breast cancer mortality.
This is a large descriptive study performed at 43 US radiology facilities in 3 states. Sites that had adopted vs those that had not adopted computer-aided detection for mammography interpretation were compared, before and after adoption of the system, to identify sensitivities, specificities, and positive predictive values, as well as false-positive rates and resulting breast biopsies.
Participating centers were Breast Cancer Surveillance Consortium facilities that enrolled women older than 40 years for mammography.
Of 43 participating facilities, 7 implemented computer-aided detection during the study period.
Included were bilateral mammograms designated by radiologists as obtained for "routine screening" in women with no history of breast cancer.
Mammographic data included assessments of the Breast Imaging Reporting and Data System (BI-RADS) with recommendations for further evaluation.
BI-RADS assessments were coded from 1 (negative) to 5 (abnormality highly suggestive of breast cancer).
BI-RADS scores of 0, 4, and 5 were considered positive, and scores of 1 and 2 were considered negative.
A score of 3 was considered positive only if the radiologist recommended immediate evaluation.
Sensitivity was defined as the percentage of screening mammograms that were positive among patients who received a diagnosis of breast cancer within 1 year of screening.
Specificity was defined as the percentage of screening mammograms that were negative among patients who did not receive a diagnosis of breast cancer within 1 year of screening.
Positive predictive value was defined as the probability of a breast cancer diagnosis within 1 year after a positive screening mammogram.
Overall accuracy was defined as the true-positive rate (sensitivity) against the false-positive rate (1 - specificity) using the area under the receiver operating characteristic curve.
In the 43 facilities, there were 159 radiologists who interpreted mammograms of which 77% responded to the study.
Mammographic data were available for 222,135 women for a total of 429,345 mammograms.
The 7 facilities that implemented computer-aided detection were staffed by 38 radiologists and used it for a total of 124 facility-months, during which 31,186 (7% of total) mammograms were interpreted, including 156 for women who received a diagnosis of breast cancer within 1 year.
Overall, 31% of women were aged 40 to 59 years and 41% were aged 50 to 59 years, breast density was "scattered fibroglandular tissue" in 43% and "heterogeneously dense" in 39%, and time since most recent mammogram was 9 to 15 months in 45% of women.
Women at the facilities that did not implement computer-aided detection were older, had denser breasts, and were less likely to have undergone mammography within the past 9 to 20 months vs those screened at the 7 facilities with computer-aided detection.
Diagnostic specificity decreased from 90.2% before implementation to 87.2% after implementation (P < .001).
The positive predictive value decreased from 4.1% to 3.2% (P = .01) after implementation of computer-aided detection, and the rate of biopsies increased by 19.7% (P < .001).
There was a nonsignificant increase in sensitivity from 80.4% to 84.0% after implementation (P = .32).
The change in cancer detection rate was not significant (from 4.15 - 4.20 cases per 1000 screening mammograms).
Use of computer-aided detection was significantly associated with lower overall accuracy (area under the receiver operating characteristic curve, 0.871 vs 0.919; P = .005).
In this study, approximately 157 additional women would be recalled and 15 women would undergo biopsy owing to the use of computer-aided detection to detect 1 additional case of cancer, probably a ductal carcinoma in situ.
Pearls for Practice -
Use of computer-aided detection of mammography is associated with reduced specificity and positive predictive value and no improvement in sensitivity for breast cancer detection.
Use of computer-aided detection of mammography is associated with lower overall accuracy and higher false-positive rates, resulting in unnecessary breast biopsies.
Target Audience: This article is intended for primary care clinicians, gynecologists, radiologists, oncologists, and other specialists who care for women.
Goal: The goal of this activity is to provide medical news to primary care clinicians and other healthcare professionals in order to enhance patient care.