Risk Calculator
1. What is the woman’s age?
Select Age
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90+
3. What was the woman’s highest BMI in the past 10 years?
Select BMI
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
7. Did the woman give birth to a child?
No
Yes, 1-2
Yes, 3 or more
8. Did she ever use hormone replacement therapy for relief of menopausal symptoms or for prevention of disease (do not include vaginal estrogens)?
No
Yes, estrogen combined with progesterone, and is still taking them
Yes, estrogen combined with progesterone, but stopped taking them
Yes, estrogen only, and is still taking it
Yes, estrogen only, but stopped taking it
Yes, unsure of type, and is still taking it
Yes, unsure of type, but stopped taking it
11. Health characteristics
1 A standard drink is about one bottle/can of beer, 1 glass of wine, or 1 cocktail.
2 If she had both of her ovaries removed before she experienced menopause naturally, please report her age at the time of this surgery. If she had her uterus removed before menopause but not both of her ovaries, please report her age when she thinks she started menopause based on symptoms.
Calculate risk ›
Information about the models
We created 2 competing-risk prediction models. One model estimates risk of breast cancer (within 5 and 10 years) with consideration of risk of non-breast cancer death. The other model estimates 10-year non-breast cancer death with consideration of risk of breast cancer death.
Breast cancer prediction model
The breast cancer prediction model was developed in 37,628 postmenopausal women age 55 and older from the Nurses' Health Study (NHS), with a 10-year follow-up starting in 2004 (mean age 70 years, 96% non-Hispanic white)
We excluded women with a history of invasive breast cancer and censored women with noninvasive breast cancer or other cancers at the time of diagnosis
The model was internally validated using NHS participants (N=18,980), and externally validated in the Black Women’s Health Study (BWHS, N=13,247, 0% non-Hispanic white), Women’s Health Initiative (WHI, N=82,634, 86% non-Hispanic white), and Multiethnic Cohort Study (MEC, N=39,206, 26% non-Hispanic white) cohorts.
Discrimination: The risk calculator correctly sorts patients who were diagnosed with breast cancer within 5 years 61% of the time (c-index 95% CI: 0.58-0.64), and within 10 years 60% of the time (c-index 95% CI: 0.58-0.62). (57% in BWHS, WHI and MEC).
Calibration: The model was well calibrated within all risk groups at 5 and 10 years.
Non-breast cancer death prediction model
The non-breast cancer death prediction model was developed in 48,102 postmenopausal women age 55 and older from the NHS, with a 10-year follow-up starting in 2004 (mean age 70 years, 96% white)
The model was internally validated using NHS participants (N=24,088), and externally validated in the BWHS (N=15,001, 0% non-Hispanic white), WHI (N=92,720, 86% non-Hispanic white), and MEC (N=47,973, 26% non-Hispanic white) cohorts.
Discrimination: The risk calculator correctly sorts patients who died of causes other than breast cancer within 10 years 79% of the time (c-index 95% CI: 0.78-0.80). (77% in BWHS, 76% in WHI and MEC).
Calibration: The model was well calibrated within all risk groups.
Citations:
Schonberg MA, Wolfson EA, Eliassen AH, Bertrand KA, Shvetsov YB, Rosner BA, Palmer JR, Ngo LH. A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old. Breast Cancer Res. 2023 Jan 24;25(1):8. doi: 10.1186/s13058-023-01605-8.
Wolfson EA, Schonberg MA, Eliassen AH, Bertrand KA, Shvetsov YB, Rosner BA, Palmer JR, LaCroix AZ, Chlebowski RT, Nelson RA, Ngo LH. Validating a Model for Predicting Breast Cancer and Non-Breast Cancer Death in Women Aged 55 and Older. J Natl Cancer Inst. 2023 Sep 7:djad188. doi: 10.1093/jnci/djad188.
DISCLAIMER The information provided on ePrognosis is designed to complement, not replace, the relationship between a patient and his/her own medical providers . ePrognosis was created with the support of the Division of Geriatrics at the University of California San Francisco . However, its content is strictly the work of its authors and has no affiliation with any organization or institution. This web site does not accept advertisements. If you reproduce the material on the website please cite appropriately. For feedback and questions regarding the site please email Sei Lee, MD (sei.lee@ucsf.edu ), Alex Smith, MD (aksmith@ucsf.edu ) or Eric Widera, MD (eric.widera@ucsf.edu ).