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1
Department of Radiology, CB 7515, Mason Farm Rd., University of North Carolina
at Chapel Hill, Chapel Hill, NC 27599-7515.
2
Department of Epidemiology, CB 7400, McGavran-Greenberg Hall, University of
North Carolina at Chapel Hill, Chapel Hill, NC 27599-7400.
3
Lineberger Comprehensive Cancer Center, CB 7295, University of North Carolina
at Chapel Hill, Chapel Hill, NC 27599-7295.
Received January 24, 2001;
accepted after revision March 19, 2001.
Supported by grant NCI U01-CA-70040 from the National Cancer Institute.
Abstract
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MATERIALS AND METHODS. Mammography and pathology data are linked in the Carolina Mammography Registry, a population-based registry of screening mammography. Our mammography database is created from prospectively collected data from mammography facilities; the data include information on the woman and the imaging studies. Our pathology database is created from prospectively collected breast pathology data received from pathology sites and the Central Cancer Registry. Women in the registry who were 40 years old and older and who underwent screening mammography between January 1994 and June 1998 were included. "Recall rate" was defined as the percentage of screening studies for which further workup was recommended by the radiologist.
RESULTS. The study included 215,665 screening mammograms. The mean age of the women was 56 years. The recall rates of the average practice ranged from 1.9% to 13.4%. Sensitivity rose from a mean of 65% in the lowest recall rates to 80.2% at the highest level of recall rates. The positive predictive value of screening decreased from 7.2% in the lowest level of recall to 3.3% in the highest. As recall rates increased, sensitivity increased very little beyond a recall rate of 4.8%, and positive predictive value began decreasing significantly at a recall rate of 5.9%.
CONCLUSION. Practices with recall rates between 4.9% and 5.5% achieve the best trade-off of sensitivity and positive predictive value.
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The performance of mammography is often determined by examining accuracy indexes, including sensitivity, specificity, positive predictive value (PPV), and cancer detection rates. Additionally, recall rates are often calculated by mammography practices and are used as a surrogate measure of practice performance. Several studies have been conducted showing how these indexes relate to age, family, personal history of breast cancer, history of biopsy, breast parenchymal density, the number of reviewers, and the number of images [4,5,6,7,8,9,10,11,12]. Although guidelines suggest that setting a recall rate at less than 10% will translate into maximizing the trade-off between sensitivity and PPV [13, 14], no study to date has shown how recall rates affect sensitivity and PPV. We performed this analysis on prospectively collected screening assessment data from a broad representation of mammography facilities in community practice.
The objective of this study was to estimate the association of recall rate with PPV and sensitivity of screening mammography among a wide range of community-based mammography facilities that are linked to a population-based tumor registry for outcome data. Knowledge of how recall rates relate to both sensitivity and PPV, with information of other factors that are independently associated with these rates, should be a useful guide for practices to interpret their own recall rates as surrogate measures of the performance of screening mammography.
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The study group included all screening mammography examinations for women living in North Carolina who underwent screening mammography in any participating facility between January 1994 and June 1998. We identified all standard two-view bilateral mammography examinations in the registry, then selected those that were performed as screening studies and excluded those that were diagnostic studies. Mammography was considered a screening study if the patient was classified as asymptomatic by the radiologist, the examination was bilateral, and the examination was conducted at least 9 months after previous mammography.
The mammography database contains data collected from all patients at the time their mammography is performed, including demographic information, history of breast procedures, reason for visit, hormone use, and family history of breast cancer (defined as a first-degree relative with premenopausal breast cancer). At each visit, the technologist and radiologist record information about the type of examination performed (screening, diagnostic, sonography, or other diagnostic imaging modalities), comparison with previous films, density of breast parenchyma, mammographic impression using the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) [17] and recommendations for type of follow-up study and follow-up time. Recommendations for follow-up care may include additional mammography at specified intervals (immediately, 6 months, or 1 year), additional mammographic images, breast imaging using another modality, biopsy, or surgical consultation. The number of mammograms obtained annually at each facility can be calculated from data in the Carolina Mammography Registry database.
Outcome data from the pathology database include date and type of pathology, method of biopsy, date of biopsy, breast site, number of nodes tested and number positive, estrogen and progesterone receptor status, and tumor grade and stage. All data are reviewed for quality. Detected errors are corrected before the data are entered into the registry. This project has the approval of the internal review board of the Medical School of the University of North Carolina at Chapel Hill and holds a certificate of confidentiality from the United States Public Health Service.
"Recall rate" is defined as the proportion of screening mammography examinations resulting in a recommendation for further workup, including recall for imaging studies and invasive procedures if they were recommended on the basis of the screening mammography findings. Women who were recommended for recall were considered to have a positive screening mammogram. A true-positive study was a positive mammographic examination that showed invasive breast cancer or ductal carcinoma in situ that was diagnosed within 12 months of the screening examination. A true-negative study was a negative mammographic examination that did not show invasive breast cancer or ductal carcinoma in situ diagnosed within 12 months of the examination. A false-negative study was a negative mammographic examination that resulted in a breast cancer diagnosis within 12 months of the study. A false-positive study was a positive mammographic examination that resulted in no diagnosis of cancer within 12 months.
Sensitivity was defined as the proportion of cancers that had positive mammographic findings within 12 months before the cancer diagnosis date, calculated as true-positive / (true-positive + false-negative). The PPV for recall was defined as the proportion of positive mammograms for which cancer was diagnosed within 12 months of the screening, calculated as true-positive / (true-positive + false-positive). Practice volume was calculated as the mean number of screening mammographic examinations performed at the facility per year. For most analyses, a missing response for family history of early breast cancer or personal history of breast cancer was classified as a negative response. The "cancer detection rate" was defined as the number of cancers discovered through mammography per 1000 women screened. Sensitivity, PPV, cancer detection rates, and recall rates were calculated for each practice.
Reduced monotonic regression analysis [18] was used to model PPV and sensitivity rates as functions of the recall rate for each of 31 radiology practices included in the study. Reduced monotonic regression is a nonparametric approach based on the isotonic regression theory. The reduced monotonic regression method simplifies the isotonic fit, identifying cut points from an isotonic regression fit, reflecting locations in the recall rate at which the trend in the dependent variable (sensitivity or PPV) is most manifest. To avoid identifying a cut point between two practices with nearly identical recall rates, practices whose recall rates differed by less than 1% of the range (i.e., by 0.12% in recall rate) were automatically grouped together. For all analyses, the data for each practice are weighted by the number of mammograms interpreted.
Linear regression analysis was performed to examine the association of recall rates with sensitivity and with PPV and to adjust for relevant covariates. In a second linear regression analysis, the recall rates were put into the models according to the groupings that resulted from the reduced monotonic regression.
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In this population, recall rates decreased with increasing age, from 7.3% in women younger than 50 years old to 4.9% in women 70 years old and older. Women with a history of breast cancer were recalled at a greater rate than women whose mammograms were negative for breast cancer: 7.4% and 6.3%, respectively. For women who had a history of breast surgery or breast procedures, the recall rate was 7.2%, compared with 6.3% for women who did not have this history. The recall rate decreased with decreasing breast density, from nearly 7.0% in the extremely dense and heterogeneously dense groups to 2.4% in the almost entirely fat group. Recall rates increased as elapsed time since previous mammogram increased: 5.2% in women having recent previous mammography versus 8.7% in women whose previous mammography was more than 36 months previous or who had no previous mammography.
The largest difference was found between women who reported symptoms at the time of their screening mammogram and those who did not report symptoms: 13.6% for women reporting symptoms, which was twice the 6.1% for women not reporting symptoms. Recall rates were greater in black women than in white and other women. No difference was seen for family history of breast cancer. The characteristics of women giving rise to greater recall rates in this population included black race, age less than 50 years, extremely dense or heterogeneously dense breasts, a history of breast biopsy or surgery, report of a current breast problem, and no previous mammogram or an elapsed time of more than 36 months from the previous mammogram.
The relationship of recall rates to practice volume is seen in Table 2. Recall rates decreased with increasing practice volume: 8.3% in the practices with mean volumes of fewer than 200 mammographic examinations per month compared with 5.6% in practices with mean monthly volumes equal to or greater than 500.
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Recall Rate and Sensitivity
Sensitivity was inversely related to recall rates for age; that is, as age
increased, the recall rate decreased and sensitivity increased. This same
inverse relationship (decrease in recall rate and increase in sensitivity) was
seen for a decrease in breast density, for a personal history of breast
cancer, for a history of breast surgery, and for the presence of breast
symptoms. Mammograms of women with almost entirely fat breasts showed a high
sensitivity (91.9%) and the lowest recall rate (2.4%). Sensitivity was
directly related to time since the last mammogram, increasing with increasing
recall rates as the time increased. Screening mammograms with the shortest
time since the previous mammogram had a recall rate of 5.2% and a sensitivity
of 73%, and screening mammograms with the longest time or with no previous
mammogram had a recall rate of 8.7% and a sensitivity of 80.7%.
With respect to the volume of mammography by practice, we found that sensitivity did not show an association with recall rates. Sensitivity seemed to remain in the mid 70% range, although the recall rate decreased with increasing mean practice volume (Table 2).
Recall Rate and PPV
PPV was inversely related to recall rate for age; that is, as age
increased, the recall rate for age decreased and the PPV increased. This same
pattern was seen for an increase in breast density and an increase in the time
elapsed since previous mammography. For age, the recall rate decreased from
7.3% for the youngest women to 4.9% for the oldest women, and PPV rose from
1.9% to 12.7%. For breast density, as the recall rate rose from 2.4% in the
almost-entirely-fat category to 6.8% in the extremely dense category, the PPV
decreased from 10.8% to 4.1%. PPV was directly related to the recall rate for
history of breast cancer, history of breast procedure, and presence of a
current breast problem. No association of the recall rate with the PPV was
seen for racial group or family history of breast cancer, although the PPV was
greater in women with a family history of breast cancer
(Table 1).
Looking at practice volume, we found an inverse relationship of PPV to recall rate for mean practice volume, with PPV increasing from 4.4% in practices with the lowest volume to 6.4% in practices with the largest volume, and recall rates decreased from 8.3% to 5.6% (Table 2).
Recall Rate and Cancer Detection Rate
The overall cancer detection rate (cancers seen on screening mammograms as
a percentage of the total screened population) was 3.5 per 1000. The cancer
detection rates are displayed in the last column of
Table 1. The largest difference
in recall rate and associated cancer detection was seen for the presence of
symptoms at screening. Recall rates rose from 6.1% in women who did not have
symptoms to 13.6% in symptomatic women, with the associated cancer detection
rate rising from 3.4 to 10.3 per 1000. No association between recall rate and
cancer detection was seen with respect to race, family history of breast
cancer, or breast density.
Recall Rate, Sensitivity, and PPV
The individual data for each practice in the study are displayed in
Table 3. The recall rates for
the 31 practices ranged from 1.9% to 13.4%. These data were fit using an
isotonic regression technique for evaluating the relationship between
practice-specific recall rate and sensitivity. A graphic representation of the
results is presented in Figure
1. The line running through the data points shows the isotonic
regression fit to the data and provides an estimate of how sensitivity
increases with increasing recall rate.
Figure 2 shows the analogous
results for the relationship of PPV as a function of recall rate, where PPV
declines with increasing recall rate. The reduced monotonic regression shows
that the trends for both sensitivity and PPV are statistically significant.
(Reduced monotonic regression models the outcome variable as a constant within
groups defined by cut points.) For sensitivity, a single cut point was
identified at a recall rate of 4.6% (p < 0.0001). A cut point for
the relationship between recall rate and PPV was identified at a recall rate
of 8.8% (p < 0.001). A second suggestive, although statistically
not significant, cut point for PPV (p = 0.13) was obtained at a
recall rate of 5.7%. For practices with recall rates between 1.9 and 4.4%, the
average sensitivity was 65%; for the remaining practices with recall rates
greater than 4.4%, the average sensitivity was 80%
(Table 4). The average PPV was
7.2% for practices with recall rates of 1.9-5.5%, 5.9% for practices with
recall rates of 5.8-8.7%, and 3.3% for practices with recall rates of 8.9% or
greater.
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Linear regression analysis was first performed for recall as a continuous variable controlling for the covariates of age, race, family and personal history of breast cancer, history of breast surgery or biopsy, presence of symptoms, and breast density. The analysis showed that practices with greater recall rates have greater sensitivity (p = 0.003, r2 = 0.64). When the reduced monotonic regression cut point of 4.6% was used for the recall rate, the fit improved to r2 = 0.68. Linear regression analysis likewise showed that PPV decreased as recall rate increased (p = 0.0002), with an overall r2 of 0.56. When the practices are split into groups based on the reduced monotonic regression cut points, the model fit improved to 0.66.
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Comparing our results directly with those in the literature is difficult because of the variation in the definition of recall (often, a definition is lacking). In previous studies, "recall" has been defined on the basis of clinical judgment [29]; need for further workup (including clinical breast examination, sonography, or cytology) [26]; recommendation for further imaging, including repeated mammography, for technical reasons [11]; recommendation for workup for clinical or radiographic suspicion of malignancy [32]; and other factors. Some studies restrict recall to further imaging only; other studies may include recommendations for biopsy. Obviously, the definition affects the recall rate and thereby its relationship with PPV and sensitivity. Our estimates are internally consistent and were based on recall defined as the proportion of screening mammography examinations resulting in a recommendation for further workup, including recall for imaging studies and invasive procedures if they were recommended on the basis of the screening mammography findings. We did not include cases recalled for repeated mammography requested for technical reasons.
Recall rates in the non—United States literature tend to be reported separately for prevalent and incident screening programs [13]. That method of reporting occurs less often in the United States, where both are usually combined. We were able to analyze our data by time elapsed since the previous screening examination, which approximates the prevalence and incidence screening data. In the Canadian screening programs, the recall rates were 9.5% for initial screening and 4.6% for subsequent screening [24]. Our recall rates were 8.7% for an interval longer than 36 months (including no previous screening) and 5.2% for an interval of 24 months or less. More than 60% of the women had previous screening within 3 years of the present screening. Our evaluation of the effect of elapsed time between mammograms shows that decreasing the time between subsequent mammograms reduces recall and improves other performance measures. Hunt et al. [33] found similar results in their study, indicating a significant 30% reduction in recall for annual mammography versus biennial, a finding that was consistent across age groups.
Our study was performed on data prospectively collected from 31 community practices for mammography in North Carolina. The women in this screened population represent approximately 25% of the women more than 40 years old in North Carolina. The women in our population are similar to the population distribution for North Carolina in their age and racial distribution except for underrepresentation of older black women, in keeping with the lower screening rates for these women in general, not just in North Carolina [34, 35]. As others have reported, we found that recall rates were higher for women who were younger; were black; had a history of breast biopsy, breast surgery, or breast cancer; or had higher breast density [7, 9, 36]. We also found that recall rates were greater for the presence of reported symptoms at screening and longer time elapsed since the previous screening. We found recall rates for women with and those without a family history of breast cancer to be virtually the same.
In our data, for the most part, recall rates stratified within the covariates of interest showed an association with sensitivity. As age increased, recall rates decreased and sensitivity increased. Recall rates increased and sensitivity decreased with increasing breast density when there was a history of breast (or other) cancer, previous breast surgery, or biopsy; or when symptoms were reported at screening. Only with an increase in time elapsed since the last screening did recall rates and sensitivity both increase.
For the association of recall rates with PPV, we found that women in the
oldest age group (
70 years) had a recall rate of 4.9% with a PPV of 12.7%,
and women 60-69 years old had a recall rate of 5.8% with a PPV of 8.2%. Welch
and Fisher [22] studied recall
from Medicare claims data in women 65 and older and reported a recall rate of
8.5% and a PPV of 8% for women having further testing within 8 months of
screening. We would have expected this PPV to be higher because it was based
on women who were actually followed up for further workup, whereas ours is
based on those for whom further workup was only recommended. Our findings for
the relationship between recall and history of biopsy or surgery are the same
as those reported by Slanetz et al.
[8], although those authors
reported recall only for women with a history of excisional biopsy. The recall
rates reported by Slanetz et al. were 6% in women who did not have a history
of biopsy and 7% for women who did have.
The association of recall rates with PPV in our study showed that as history of breast biopsy, surgery, or cancer, and the presence of symptoms at screening increased, an increase in recall rates was associated with an increase in PPV. As age decreased, breast density increased, time elapsed since previous mammography increased, recall rates increased, and PPV decreased. Black women had greater recall rates and lower PPVs than white women. The percentage of women with longer than 36 months from the previous screening or with no previous screening was also greater for black women than for white women. This trend of recall and PPV with increasing elapsed time since screening may explain the different findings in black and white women.
No reports exist of the association of recall with both PPV and sensitivity to compare with our results. When grouping practices by volume, we found that an increase in mean volume of mammograms was associated with a decrease in recall rate for screening volumes of more than 200 per month with no difference in sensitivity and an increase in PPV.
The key question we posed in this study was whether a point existed at which sensitivity reached a plateau as the recall rate increased, while PPV continued to decline. We did not find previous reports addressing this question. Our regression analyses showed that practices with recall rates of 4.4% or less had lower sensitivity than the remaining practices, which had recall rates of 4.8% or greater. However, no statistically significant increase in sensitivity was noted among the practices once a recall rate of 4.8% was reached. Although we must be cautious not to overinterpret the location of the cut point, both Figure 1 and Table 4 clearly show that, for these data, the sensitivity increased very little, if at all, beyond a recall rate of 4.8%. Conversely, a decline in PPV was observed with increasing recall rates for practices with recall rates of 8.9% or greater, and to a lesser extent for practices with recall rates of 5.9-8.7% (Fig. 2). Combining these findings, we conclude that practices with recall rates between 4.9% and 5.5% achieve the best trade-off of sensitivity and PPV.
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F. M. Hall and E. L. Rosen Malignancy in BI-RADS Category 3 Mammographic Lesions * Dr Rosen responds: Radiology, December 1, 2002; 225(3): 918 - 920. [Full Text] [PDF]
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 J. M. Boone, K. K. Lindfors, and J. A. Seibert Determining Sensitivity of Mammography from Screening Data, Cancer Incidence, and Receiver-Operating Characteristic Curve Parameters Med Decis Making, June 1, 2002; 22(3): 228 - 237. [Abstract] [PDF]
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F. M. Hall Immediate Reporting of Screening Mammography Am. J. Roentgenol., April 1, 2002; 178(4): 1031 - 1032. [Full Text] [PDF]
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 P. Shaffer, I. Khalkhali, and S. B. Haber Sestamibi Scanning of Breast Cancer J. Nucl. Med., January 1, 2002; 43(1): 125 - 126. [Full Text] [PDF]
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