Table 2.
Performance measure | Biennial recommendation (n = 733 637) (Referent) |
Annual recommendation by reason |
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---|---|---|---|---|---|---|---|---|---|---|---|
Family or personal history* (n = 157 425) |
Mammographic density ≥75% (n = 83 192) |
Family or personal history* + mammographic density ≥75% (n = 6605) |
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No. (screens) | Rate (95% CI) | No. (screens) | Rate (95% CI) | OR (95% CI) | No. (screens) | Rate (95% CI) | OR (95% CI) | No. (screens) | Rate (95% CI) | OR (95% CI) | |
Abnormal recall rate, %† | 52 690 | 8.3 | 9863 | 8.4 | 1.01 | 6228 | 9.4 | 1.14 | 466 | 9.1 | 1.10 |
(733 637) | (7.6 to 9.1) | (157 425) | (7.6 to 9.2) | (0.97 to 1.04) | (83 192) | (8.4 to 10.6) | (1.05 to 1.25)¶ | (6605) | (7.8 to 10.6) | (0.97 to 1.26) | |
Nonmalignant biopsy rate per 1000† | 4017 | 6.4 | 759 | 7.1 | 1.10 | 579 | 9.7 | 1.51 | 44 | 9.8 | 1.52 |
(733 637) | (5.4 to 7.7) | (157 425) | (5.9 to 8.5) | (1.01 to 1.21) | | (83 192) | (7.9 to 11.9) | (1.32 to 1.73)** | (6605) | (7.0 to 13.6) | (1.14 to 2.04)‡‡ | |
Positive predictive value, %† | 3987 | 7.8 | 752 | 8.3 | 1.07 | 354 | 7.5 | 0.96 | 56 | 15.5 | 2.17 |
(52 690) | (6.8 to 8.8) | (9863) | (7.1 to 9.6) | (0.98 to 1.17) | (6228) | (6.2 to 8.9) | (0.81 to 1.13) | (466) | (11.5 to 20.4) | (1.55 to 3.04)** | |
Cancer detection rate per 1000† | 3987 | 6.5 | 752 | 7.0 | 1.07 | 354 | 7.0 | 1.08 | 56 | 14.1 | 2.17 |
(733 637) | (5.8 to 7.3) | (157 425) | (6.1 to 8.0) | (0.98 to 1.17) | (83 192) | (6.0 to 8.2) | (0.93 to 1.24) | (6605) | (10.4 to 19.0) | (1.61 to 2.94)** | |
Breast cancer type†,‡ | |||||||||||
Invasive | 3280 | 5.4 | 617 | 5.6 | 1.05 | 262 | 5.2 | 0.98 | 39 | 9.7 | 1.83 |
(732 927) | (4.7 to 6.1) | (157 290) | (4.9 to 6.5) | (0.95 to 1.16) | (83 100) | (4.4 to 6.2) | (0.84 to 1.14) | (6588) | (6.6 to 14.3) | (1.25 to 2.67)§§ | |
DCIS | 681 | 1.1 | 131 | 1.2 | 1.17 | 87 | 1.6 | 1.49 | 17 | 4.2 | 3.93 |
(730 328) | (0.9 to 1.3) | (156 804) | (0.9 to 1.7) | (0.96 to 1.42) | (82 925) | (1.1 to 2.2) | (1.11 to 1.99)†† | (6566) | (2.5 to 4.9) | (2.42 to 6.39)** | |
Age at screen, y† | |||||||||||
50–59 | 1078 | 4.7 | 161 | 4.8 | 1.02 | 183 | 5.8 | 1.22 | 21 | 9.8 | 2.09 |
(290 830) | (4.1 to 5.5) | (53 796) | (3.8 to 6.0) | (0.84 to 1.23) | (50 715) | (4.5 to 7.4) | (0.98 to 1.53) | (3549) | (6.4 to 15.0) | (1.38 to 3.14)** | |
60–74 | 2909 | 9.9 | 591 | 10.8 | 1.09 | 171 | 9.7 | 0.97 | 35 | 22.1 | 2.25 |
(442 807) | (7.4 to 13.2) | (103 629) | (8.1 to 14.3) | (0.98 to 1.21) | (32 477) | (7.0 to 13.3) | (0.82 to 1.16) | (3056) | (14.8 to 32.9) | (1.53 to 3.32)** | |
Menopausal status§ | |||||||||||
Premenopausal | 175 | 4.9 | 27 | 6.7 | 1.27 | 59 | 6.9 | 1.30 | 4 | 7.9 | 1.49 |
(35 650) | (3.6 to 7.8) | (4521) | (3.7 to 12.4) | (0.77 to 2.11) | (10 502) | (4.3 to 11.1) | (0.89 to 1.90) | (579) | (2.9 to 21.3) | (0.56 to 3.98) | |
Postmenopausal | 3737 | 5.1 | 717 | 5.5 | 1.07 | 284 | 5.3 | 1.03 | 52 | 11.3 | 2.23 |
(689 743) | (4.7 to 5.6) | (151 737) | (4.9 to 6.1) | (0.97 to 1.18) | (72 025) | (4.5 to 6.2) | (0.89 to 1.19) | (5965) | (8.3 to 15.5) | (1.63 to 3.06)** |
Two or more first-degree female relatives with breast cancer at any age, one first-degree female relative with breast cancer younger than 50 years, one first-degree male relative with breast cancer at any age, a personal history of ovarian cancer, or one first-degree female relative with ovarian cancer at any age. DCIS = ductal carcinoma in situ.
Adjusted for age at screen, year of screen, menopausal status, use of estrogen therapy at last screen, community status, time (days) between previous and index rescreen date, and clustering by screening center attended.
Thirty-eight cancers with missing morphology excluded (29 biennial; 4 family or personal history; 5 mammographic density ≥75%).
Adjusted for age at screen, year of screen, use of estrogen therapy at last screen, community status, time (days) between previous and index rescreen date, and clustering by screening center attended.
Compared with biennial P = .04.
P = .003
P < .001
P = .007
P = .005
P = .002. All P values (two-sided) were calculated using logistic regression with generalized estimating equation models.