Regular use of aspirin and other non-steroidal anti-inflammatory drugs and breast cancer risk for women at familial or genetic risk: a cohort study
verfasst von:
Rebecca D. Kehm, John L. Hopper, Esther M. John, Kelly-Anne Phillips, Robert J. MacInnis, Gillian S. Dite, Roger L. Milne, Yuyan Liao, Nur Zeinomar, Julia A. Knight, Melissa C. Southey, Linda Vahdat, Naomi Kornhauser, Tessa Cigler, Wendy K. Chung, Graham G. Giles, Sue-Anne McLachlan, Michael L. Friedlander, Prue C. Weideman, Gord Glendon, Stephanie Nesci, Irene L. Andrulis, Saundra S. Buys, Mary B. Daly, Mary Beth Terry, kConFab Investigators
The use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been associated with reduced breast cancer risk, but it is not known if this association extends to women at familial or genetic risk. We examined the association between regular NSAID use and breast cancer risk using a large cohort of women selected for breast cancer family history, including 1054 BRCA1 or BRCA2 mutation carriers.
Methods
We analyzed a prospective cohort (N = 5606) and a larger combined, retrospective and prospective, cohort (N = 8233) of women who were aged 18 to 79 years, enrolled before June 30, 2011, with follow-up questionnaire data on medication history. The prospective cohort was further restricted to women without breast cancer when medication history was asked by questionnaire. Women were recruited from seven study centers in the United States, Canada, and Australia. Associations were estimated using multivariable Cox proportional hazards regression models adjusted for demographics, lifestyle factors, family history, and other medication use. Women were classified as regular or non-regular users of aspirin, COX-2 inhibitors, ibuprofen and other NSAIDs, and acetaminophen (control) based on self-report at follow-up of ever using the medication for at least twice a week for ≥1 month prior to breast cancer diagnosis. The main outcome was incident invasive breast cancer, based on self- or relative-report (81% confirmed pathologically).
Results
From fully adjusted analyses, regular aspirin use was associated with a 39% and 37% reduced risk of breast cancer in the prospective (HR = 0.61; 95% CI = 0.33–1.14) and combined cohorts (HR = 0.63; 95% CI = 0.57–0.71), respectively. Regular use of COX-2 inhibitors was associated with a 61% and 71% reduced risk of breast cancer (prospective HR = 0.39; 95% CI = 0.15–0.97; combined HR = 0.29; 95% CI = 0.23–0.38). Other NSAIDs and acetaminophen were not associated with breast cancer risk in either cohort. Associations were not modified by familial risk, and consistent patterns were found by BRCA1 and BRCA2 carrier status, estrogen receptor status, and attained age.
Conclusion
Regular use of aspirin and COX-2 inhibitors might reduce breast cancer risk for women at familial or genetic risk.
Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm
CI
Confidence interval
COX
Cyclooxygenase
ER
Estrogen receptor
HR
Hazard ratio
kConFab
Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer
NSAID
Non-steroidal anti-inflammatory drug
OR
Odds ratio
ProF-SC
Prospective Family Study Cohort
RCT
Randomized controlled trial
Background
Women vary greatly in their underlying familial risk of breast cancer (BC). Those with an affected first-degree relative are on average at 2-fold increased risk of BC. [1] Women with a BRCA1 or BRCA2 mutation are at about a 10-fold increased risk of BC, depending on their age, family history, and location of mutation [2]. The two leading risk-reduction strategies for women at increased BC risk are risk-reducing mastectomy, which could reduce risk by over 90% [3], and use of medications such as the selective estrogen receptor modulators or aromatase inhibitors, which reduce risk of estrogen receptor (ER)-positive BC by about 30–65% [4‐6]. Despite the proven efficacy of these options, uptake remains low- and high-risk women often inquire about alternative BC prevention strategies [7‐12]. Regular use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) including COX-2 inhibitors could be one such alternative. NSAIDs might impede tumor development and growth by modulating cellular proliferation and apoptosis, predominately by suppressing endogenous production of prostaglandin through the inhibition of cyclooxygenase (COX) enzyme activity, particularly COX-2, which is shown to be over-expressed in cancer cells [13, 14]. NSAIDs may also impede the development of ER positive BC through the inhibition of aromatase [13, 15]. The use of aspirin and other NSAIDs for BC prevention is an attractive strategy given that over-the-counter NSAIDs are inexpensive and widely available. However, even if regular NSAID use proves to be an effective BC prevention strategy, as with other risk-reducing options, the potential benefits of NSAIDs will need to be weighed against the potential harms of long-term use [16‐21].
The cancer prevention effects of aspirin and other NSAIDs are well established for colon cancer [22, 23], and accumulating evidence from epidemiologic studies of women unselected for familial or genetic risk suggests that regular, long-term use of aspirin could reduce BC risk by about 14% [24, 25]. Comparable estimates have been reported for COX-2 inhibitors [26, 27]. However, the current body of evidence is far from conclusive [28], especially given that the only mature randomized controlled trial (RCT) of aspirin and primary prevention of BC did not find evidence for an effect, although no effect was found for colon cancer either [29]. While ongoing secondary prevention trials in women affected with breast cancer, such as the Aspirin for Breast Cancer (ABC) trial and Add-Aspirin trial [30, 31], will also inform this question, results from these trials have yet to be published. Recently published findings from the Aspirin in Reducing Events in the Elderly (ASPREE) found that cancer-related deaths, including BC, were higher in the aspirin group compared to those in the placebo group [21].
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Little is known about whether aspirin and other NSAIDs reduce BC risk for women across the familial risk spectrum. For example, no study appears to have estimated the association for BRCA1 and BRCA2 mutation carriers. One study tested the association stratified by first-degree BC family history (12% of the overall sample) and found that regular aspirin use (≥ 6 times per week versus never) was associated with a reduced BC risk both for women with and without an affected first-degree relative (OR = 0.62, 95% CI = 0.41–0.93 and OR = 0.73, 95% CI = 0.61–0.88, respectively) [13]. The Sister Study, a prospective cohort study of women with a sister diagnosed with BC, also found a negative association between lifetime NSAID use (≥ 49 versus < 0.75 pill-years) and BC risk, although only for premenopausal women (HR = 0.66, 95% CI = 0.50–0.87; postmenopausal HR = 0.95, 95% CI = 0.82–1.09) [32]. However, both of these studies relied on a binary definition of family history, which discounts the fact that there is a strong gradient in risk due to underlying familial risk factors such as number of affected relatives and their age at diagnosis. Mathematical modeling demonstrates that in order to explain the average 2-fold increased risk of BC associated with having an affected first-degree relative, the risk of developing BC must vary by approximately 20-fold between people in the lowest quartile of familial risk versus the highest quartile of familial risk [33]. In our family cohort enriched with women with a family history of BC, remaining lifetime risk of BC ranges anywhere from < 1% to > 90% in women unaffected with BC at baseline [34]. It is possible to get a reliable estimate of this underlying familial risk, referred to as familial risk profile, from multi-generational breast and ovarian cancer history data using risk models such as the Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), which includes consideration of BRCA1 and BRCA2 gene mutations [35‐37]. In this study, we employed the BOADICEA model to evaluate associations of regular NSAID use and BC risk by familial risk profile using a large cohort of women enriched for family history, including 1054 women with a BRCA1 or BRCA2 mutation.
Methods
Study sample
This study was based on the Prospective Family Study Cohort (ProF-SC), which comprises baseline and follow-up data from the Breast Cancer Family Registry (BCFR) [38] and the Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab) [39]; additional details are available elsewhere [34]. These cohorts involved women affected with BC and included their affected and unaffected female relatives; ProF-SC is therefore enriched for familial risk of BC (82% with a first-degree relative and 95% with a first- or second-degree relative with BC). Baseline and follow-up questionnaires asked about personal and family history of BC, demographics, reproductive history, and lifestyle factors. Medication history was not asked about at baseline, but was included on follow-up questionnaires. Women were followed prospectively for cancer and other health outcomes for up to 20 years, and screening for germline BRCA1 and BRCA2 mutations has been conducted over time [39, 40]. The BCFR and kConFab received ethical approval by each participating study center’s institutional review board. All participants provided written informed consent.
Prospective cohort
The prospective cohort included women who were enrolled in the BCFR or kConFab before June 30, 2011, aged 18–79 years at follow-up, who self-reported medication history by follow-up questionnaire, and had not undergone a bilateral mastectomy or been diagnosed with BC prior to follow-up questionnaire (N = 5606). To ensure that we did not include prevalent cancers in the prospective cohort, person-years were calculated from age at 2 months after the questionnaire with medication history was completed to age at first invasive breast cancer diagnosis, based on self- or relative-report and confirmed pathologically for 81% of cases, or censoring (Fig. 1). Women were censored at the earliest of the following events: risk-reducing bilateral mastectomy, age 80 years, loss to follow-up, or death.
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Combined cohort
The combined, retrospective and prospective, cohort included all women who were enrolled in the BCFR or kConFab before 30 June 2011, aged 18–79 years at baseline, who self-reported medication history by follow-up questionnaire. In addition to women in the prospective cohort, this included women who were diagnosed with BC prior to baseline (N = 1973), women who were diagnosed with BC after baseline but before follow-up questionnaire (N = 232), and women who were censored prior to follow-up questionnaire (N = 422). We excluded 16 cases missing BC diagnosis date, resulting in a final sample of 8233 women in the combined cohort. We used a general modeling approach for the combined cohort that was similar to the prospective cohort, except that we calculated person-years from age 17 years, 1 year prior to earliest age at diagnosis (Fig. 1).
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Exposure assessment
Medication history was asked by follow-up questionnaire including use of (1) aspirin, (2) COX-2 inhibitors, (3) ibuprofen and other non-selective NSAIDs, and (4) acetaminophen (paracetamol). Median time between baseline and follow-up questionnaire was 8.7 years. In the BCFR, women in the prospective cohort were asked if they had ever used each of the four types of medication for at least twice a week for 1 month or longer at any time in the past; kConFab participants were asked a slightly modified question that asked if medication use occurred for at least twice a week for more than 1 month. Participants were prompted with country-specific examples of each medication type to help with recall (e.g., Tylenol, Anacin-3, and Panadol were provided as examples of acetaminophen-based medications on the US-based questionnaire). Women in the combined cohort with a personal history of BC were asked if they had ever used (for at least twice a week for ≥ 1 month) the listed medications prior to diagnosis. Women who gave affirmative responses for a given medication were classified as regular users of that drug. Women who used these medications less frequently than twice per week for ≥ 1 month or never were classified as non-regular users. A subset of women (77% of the combined cohort) also reported total duration of regular medication use in either months or years.
Statistical analysis
We used multivariable Cox proportional hazards regression, with age as the time scale, to estimate associations of regular medication use with BC risk. The proportionality assumption was assessed by evaluating Schoenfeld residuals. We estimated associations separately for regular use of aspirin, COX-2 inhibitors, ibuprofen and other NSAIDs, and acetaminophen, the latter as a negative control to determine if any associations observed between NSAIDs and BC risk reflected a non-specific use of analgesics [41]. We used a robust variance estimator to account for the family structure of the cohort. We stratified models by birth cohort (in 10-year categories) and adjusted for baseline age (continuous), race/ethnicity (non-Hispanic white versus otherwise), and study center (Model 1). We adjusted for familial risk profile using the 1-year BC risk score predicted from the BOADICEA model (Model 2) [35]. We also tested models adjusted for baseline health behaviors (never, former, current) including cigarette smoking, alcohol consumption, hormone therapy use, and hormonal birth control use, which collectively altered parameter estimates of some NSAID variables by > 10% (Model 3). Further adjustment for parity, breastfeeding, age at menarche, and body mass index did not alter the parameter estimates by > 10% and were not included in the final parsimonious model. Lastly, we tested a model further adjusted for use of the other three types of medications (Model 4). We estimated cross-product terms to test for multiplicative interactions between regular medication use and familial risk profile (continuous). We also plotted the predicted age-specific absolute cumulative risk for women with different familial risk based on BOADICEA and underlying age-specific incidences from the Surveillance, Epidemiology, and End Results Program [42‐44]. We chose three scenarios of familial risk: 12% (population average), 20–30% (moderate familial risk), and > 30% (high familial risk) full lifetime BC risk, and two scenarios of medication use: regular aspirin user and non-regular aspirin user.
Subgroup analyses
Using the combined cohort, we estimated associations stratified by gene mutation carrier status defined as non-carriers (either true negative or not tested), BRCA1 carriers, or BRCA2 carriers. We conducted a sensitivity analysis using the weighting approach of Antoniou et al. (2005) [45] to account for non-random selection of mutation carriers. Weighting did not substantively alter medication-associated risk estimates or their standard errors. We also estimated associations by tumor ER status (positive or negative); the alternative ER subtype was censored at diagnosis. For example, ER-negative BC cases were censored at age at diagnosis in the analysis of ER-positive BC. Finally, we fitted attained age models, truncating follow-up time at ages 45, 55, and 65 years, to assess associations for younger women.
Sensitivity analyses
Although our primary analysis was based on regular NSAID use, we did an additional analysis examining duration of use (categorized as ≥ 5 years versus < 5 years) for women who provided this information. We conducted a sensitivity analysis excluding women who reported tamoxifen use at baseline (N = 64) and found this did not alter estimates. We conducted another sensitivity analysis further adjusting for diabetes and other cancers to account for comorbidities and found that this also did not appreciably alter estimates. To account for missing data, we conducted a sensitivity analysis using multiple imputation by chained equations, which produced comparable findings (data not shown). Statistical significance was determined as p < 0.05 for a two-sided hypothesis test. Analyses were conducted using Stata 15.1 (College Station, TX) [46].
Results
There were 139 incident cases of BC in the prospective cohort over 27,923 person-years. Prevalences of medication use were similar in the prospective and combined cohorts (18% and 19% for aspirin, 9% and 8% for COX-2 inhibitors, 17% and 19% for ibuprofen, and 17% and 17% for acetaminophen, respectively). Tetrachoric correlations between medications were statistically significant, but all ≤ 0.47 (see Additional File 1). At study enrollment, regular aspirin users were older on average than non-regular users (53.1 versus 41.7 years). Regular aspirin users were also less likely to smoke cigarettes, consume alcohol, or use hormonal birth control than non-regular users, but were more likely to use hormone therapy and other types of medication (Table 1). On average, regular aspirin users had a higher 1-year BOADICEA risk score than non-regular users, which is influenced by baseline age; a smaller proportion of aspirin users had a known mutation in the BRCA1 or BRCA2 gene. The distribution of 1-year BOADICEA risk score by regular medication use is provided in the supplemental materials (see Additional File 2).
Table 1
Baseline characteristics of women in the Prospective Family Study Cohort by regular aspirin use
Prospective cohorta
Combined cohortb
Non-regular user
Regular user
Non-regular User N = 6636
Regular user
N = 4616
N = 990
N = 1597
Baseline characteristic
Mean (SD)
Mean (SD)
Mean (SD)
Mean (SD)
Age, years
41.7 (12.7)
53.1 (11.7)
44.0 (12.9)
54.2 (11.5)
Race and ethnicity, No. (%)
Non-Hispanic white
4269 (92.5)
888 (89.7)
5860 (88.3)
1366 (85.5)
Other
274 (5.9)
94 (9.5)
694 (10.5)
223 (14.0)
Missing
73 (1.6)
8 (0.8)
82 (1.2)
8 (0.5)
Cigarette smoking, No. (%)
Never
2688 (58.2)
575 (58.1)
3862 (58.2)
896 (56.1)
Former
1088 (23.6)
267 (27.0)
1705 (25.7)
492 (30.8)
Current
469 (10.2)
91 (9.2)
663 (10.0)
140 (8.8)
Missing
371 (8.0)
57 (5.8)
406 (6.1)
69 (4.3)
Alcohol consumption, No. (%)
Never
1852 (40.1)
532 (53.7)
2943 (44.4)
841 (52.7)
Former
755 (16.4)
129 (13.0)
1062 (16.0)
220 (13.8)
Current
1924 (41.7)
318 (32.1)
2514 (37.9)
513 (32.1)
Missing
85 (1.8)
11 (1.1)
117 (1.8)
23 (1.4)
Hormone therapy use, No. (%)
Never
3717 (80.5)
542 (54.8)
5255 (79.2)
895 (56.0)
Former
409 (8.9)
191 (19.3)
758 (11.4)
361 (22.6)
Current
430 (9.3)
230 (23.2)
522 (7.9)
290 (18.2)
Missing
60 (1.3)
27 (2.7)
101 (1.5)
51 (3.2)
Hormonal birth control use, No. (%)
Never
635 (13.8)
253 (25.6)
1224 (18.4)
480 (30.1)
Former
3043 (65.9)
659 (66.6)
4373 (65.9)
1015 (63.6)
Current
900 (19.5)
59 (6.0)
973 (14.7)
69 (4.3)
Missing
38 (0.8)
19 (1.9)
66 (1.0)
33 (2.1)
COX-2 inhibitors, No. (%)
Non-regular user
4227 (91.6)
814 (82.2)
6140 (92.5)
1366 (85.5)
Regular user
358 (7.8)
161 (16.3)
428 (6.5)
199 (12.5)
Missing
31 (0.7)
15 (1.5)
68 (1.0)
32 (2.0)
Ibuprofen and other NSAIDsc, No. (%)
Non-regular user
3911 (84.7)
714 (72.1)
5512 (83.1)
1139 (71.3)
Regular user
682 (14.8)
258 (26.1)
1063 (16.0)
426 (26.7)
Missing
23 (0.5)
18 (1.8)
61 (0.9)
32 (2.0)
Acetaminophen, No. (%)
Non-regular user
3859 (83.6)
740 (74.8)
5597 (84.3)
1214 (76.0)
Regular user
737 (16.0)
238 (24.0)
985 (14.8)
361 (22.6)
Missing
20 (0.4)
12 (1.2)
54 (0.8)
22 (1.4)
BOADICEA 1-year risk score, %
0.51 (0.71)
0.68 (0.85)
0.50 (0.72)
0.64 (0.83)
Mutation carrier status, No. (%)
Non-carrierd
4070 (88.2)
915 (92.4)
5739 (86.5)
1440 (90.2)
BRCA1 mutation carrier
292 (6.3)
37 (3.7)
500 (7.5)
84 (5.3)
BRCA2 mutation carrier
254 (5.5)
38 (3.8)
397 (6.0)
73 (4.6)
aIncludes women with no personal history of breast cancer when regular medication use was asked by questionnaire (N = 5606)
bIncludes retrospective breast cancer cases (diagnosed prior to baseline and/or follow-up questionnaire) and prospective breast cancer cases (diagnosed after follow-up questionnaire) (N = 8233)
cNon-steroidal anti-inflammatory drugs
dIncludes true negatives and women who did not undergo genetic testing for BRCA1 and BRCA2
As shown in Table 2, from analysis of the prospective cohort, regular aspirin use was associated with a 39% reduced BC risk in the fully adjusted model (Model 4: prospective hazard ratio (HRp) = 0.61, 95% confidence interval (CI) = 0.33 to 1.14); a very similar, but more precise, estimate was obtained from analysis of the combined cohort (Model 4: combined hazard ratio (HRc) = 0.63, 95% CI = 0.57 to 0.71). When we considered duration of aspirin use in the combined cohort, < 5 years versus never use was associated with an estimated 32% reduced BC risk (HRc = 0.68, 95% CI = 0.58 to 0.80); ≥ 5 years versus never use was associated with an estimated 66% reduced BC risk (HRc = 0.34, 95% CI = 0.27 to 0.44). From fully adjusted models, regular use of COX-2 inhibitors was associated with a 61% reduced BC risk for the prospective cohort (Model 4: HRp = 0.39, 95% CI = 0.15 to 0.97) and a 71% reduced BC risk for the combined cohort (Model 4: HRc = 0.29, 95% CI = 0.23 to 0.38). After adjusting for regular use of other medications (Model 4), regular use of ibuprofen and other NSAIDs (or ibuprofen exclusively) was not associated with BC risk, nor was acetaminophen.
Table 2
Adjusted hazard ratios (HRs) and 95% confidence intervals (CI) of breast cancer risk comparing regular medication users with non-regular users in the Prospective Family Study Cohort
Number of events
Person-years
Model 1a
Model 2b
Model 3c
Model 4d
Medication
HR (95% CI)
HR (95% CI)
HR (95% CI)
HR (95% CI)
Aspirin-based medications
Prospective cohorte
Non-regular user
124
23,545
1.00 (ref)
1.00 (ref)
1.00 (ref)
1.00 (ref)
Regular user
15
4378
0.57 (0.32, 1.00)
0.56 (0.32, 1.00)
0.55 (0.29, 1.06)
0.61 (0.33, 1.14)
Combined cohortf
Non-regular user
1838
236,452
1.00 (ref)
1.00 (ref)
1.00 (ref)
1.00 (ref)
Regular user
503
71,610
0.57 (0.51, 0.63)
0.57 (0.51, 0.63)
0.60 (0.54, 0.67)
0.63 (0.57, 0.71)
COX-2 inhibitors
Prospective cohorte
Non-regular user
133
25,203
1.00 (ref)
1.00 (ref)
1.00 (ref)
1.00 (ref)
Regular user
6
2519
0.39 (0.17, 0.90)
0.38 (0.16, 0.88)
0.37 (0.14, 0.94)
0.39 (0.15, 0.97)
Combined cohortf
Non-regular user
2236
274,964
1.00 (ref)
1.00 (ref)
1.00 (ref)
1.00 (ref)
Regular user
66
29,076
0.25 (0.20, 0.32)
0.26 (0.20, 0.33)
0.28 (0.22, 0.36)
0.29 (0.23, 0.38)
Ibuprofen and other NSAIDsg
Prospective cohorte
Non-regular user
116
23,081
1.00 (ref)
1.00 (ref)
1.00 (ref)
1.00 (ref)
Regular user
22
4645
0.93 (0.57, 1.52)
0.94 (0.57, 1.54)
1.04 (0.61, 1.76)
1.24 (0.72, 2.12)
Combined cohortf
Non-regular user
1836
248,675
1.00 (ref)
1.00 (ref)
1.00 (ref)
1.00 (ref)
Regular user
459
55,695
0.79 (0.71, 0.88)
0.80 (0.72, 0.89)
0.84 (0.76, 0.94)
0.93 (0.83, 1.04)
Ibuprofen-based medicationsh
Prospective cohorte
Non-regular user
39
8170
1.00 (ref)
1.00 (ref)
1.00 (ref)
1.00 (ref)
Regular user
11
2888
0.68 (0.34, 1.37)
0.69 (0.35, 1.39)
0.84 (0.42, 1.69)
0.99 (0.49, 2.01)
Combined cohortf
Non-regular user
1685
134,961
1.00 (ref)
1.00 (ref)
1.00 (ref)
1.00 (ref)
Regular user
439
42,044
0.77 (0.61, 0.96)
0.74 (0.59, 0.94)
0.81 (0.64, 1.02)
0.83 (0.65, 1.05)
Acetaminophen-based medications
Prospective cohorte
Non-regular user
116
23,415
1.00 (ref)
1.00 (ref)
1.00 (ref)
1.00 (ref)
Regular user
23
4370
0.96 (0.61, 1.53)
1.00 (0.63, 1.60)
0.86 (0.49, 1.49)
0.96 (0.55, 1.65)
Combined cohortf
Non-regular user
1985
250,745
1.00 (ref)
1.00 (ref)
1.00 (ref)
1.00 (ref)
Regular user
318
54,649
0.82 (0.73, 0.93)
0.82 (0.73, 0.93)
0.83 (0.73, 0.95)
0.98 (0.85, 1.12)
aModel 1 is adjusted for race/ethnicity, study center, and baseline age; stratified by birth cohort
bModel 2 is further adjusted for familial risk profile
cModel 3 is further adjusted for cigarette smoking, alcohol consumption, hormone therapy use, and hormonal birth control use
dModel 4 is further adjusted for regular use of the other types of medication. For example, the Model 4 estimates for regular aspirin use are adjusted for regular use of COX-2 inhibitors, ibuprofen and other NSAIDs, and acetaminophen
eIncludes women with no personal history of breast cancer when regular medication use was asked by questionnaire (N = 5606)
fIncludes retrospective breast cancer cases (diagnosed prior to baseline and/or follow-up questionnaire) and prospective breast cancer cases (diagnosed after follow-up questionnaire) (N = 8233)
gNon-steroidal anti-inflammatory drugs
hkConFab participants are excluded from these models because they were only asked about regular use of other NSAIDs, including ibuprofen, but not about ibuprofen specifically
Associations of regular use of aspirin and Cox-2 inhibitors with reduced breast cancer risk were not modified by familial risk profile as estimated by the BOADICEA 1-year BC risk score (Fig. 2a). When we stratified the combined cohort by gene mutation carrier status (Fig. 2b), similar HR estimates were found for women not known to be mutation carriers (HRc = 0.71, 95% CI = 0.63 to 0.80), BRCA1 carriers (HRc = 0.73, 95% CI = 0.49 to 1.09), and BRCA2 carriers (HRc = 0.80, 95% CI = 0.53 to 1.21), although the latter two confidence intervals were wide. Consistent estimates were also found for the association between COX-2 inhibitors and BC risk for women not known to be mutation carriers (HRc = 0.34, 95% CI = 0.25 to 0.48), BRCA1 carriers (HRc = 0.46, 95% CI = 0.20 to 1.08), and BRCA2 carriers (HRc = 0.51, 95% CI = 0.26 to 1.03); confidence intervals were again wide for known mutation carriers. Similar associations were also found when we stratified by ER status (Fig. 2c) and when we assessed attained age models (Fig. 2d).
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No associations with BC risk were found for regular use of ibuprofen and other NSAIDs or acetaminophen from subgroup analyses by familial risk profile, BRCA1 or BRCA2 mutation carrier status, tumor ER status, or attained age (Fig. 3).
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Figure 4 shows the overall implications of the study estimates on the predicted age-specific BC cumulative risk for non-regular users of aspirin and regular users of aspirin with different familial risk profiles. In terms of absolute risk, the risk difference between regular users and non-regular users is greater for women with higher familial risk. For cumulative BC risk to age 80 years, the risk difference is 4.1%, 6.9%, and 9.8% for women at population average risk, moderate familial risk, and high familial risk, respectively.
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Discussion
From studying a prospective and combined (prospective and retrospective) cohort enriched with women having a family history of BC across a wide range of absolute predicted familial BC risk (10-year risk: mean, 5.3%; range, < 0.1–68.5%), we found regular aspirin use to be associated with a 39% and 37% reduction in BC risk in the two cohorts, respectively. Regular use of COX-2 inhibitors was associated with a 61% and 71% reduction in BC risk in the two cohorts, respectively. The strength of these associations did not differ by familial risk or mutation status, and although not nominally significant, negative associations were found for both BRCA1 and BRCA2 mutation carriers. Negative associations were also found for younger women based on attained age models examining risk up to age 45 years.
Our findings are consistent with most, but not all, other studies of NSAIDS and BC risk conducted using samples of average-risk women unselected for family history [24]. As previously noted, the only RCT of aspirin and BC risk as the primary endpoint did not observe an association after 10 years of follow-up (relative risk = 0.98; 95% CI = 0.89–1.08), but this could reflect the fact that participants were randomized to a low dose of aspirin (100 mg every other day) [29]. We found that regular use of aspirin and COX-2 inhibitors was associated with reduced risk of both ER-positive and ER-negative BCs, which again aligns with most, but not all [41, 47, 48], other studies that considered hormone receptor status [49]. This suggests that these NSAIDs might operate through multiple underlying biological pathways to lower BC risk, including a direct effect through ER mediated signaling pathways [13, 41], the COX-2 pathway [13, 50], phosphatidylinositol 3-kinase down-regulation [13, 51], B cell lymphoma 2-mediated apoptosis [13, 52], or epidermal growth factor receptor inhibition and p53 acetylation [13, 53].
We no longer found a statistically significant association between ibuprofen and other NSAIDs and BC risk after we adjusted for regular use of other medications. This could be because ibuprofen does not have an effect on BC risk, as some NSAIDs might inhibit COX-2 more intensely than others [26]. It could also reflect differences in the duration and frequency of ibuprofen and other NSAID use compared with aspirin and COX-2 inhibitors. Women might be more likely to use aspirin regularly because of its anticlotting effect [27, 54, 55], which ibuprofen does not deliver [56]. We also found no evidence of an association between acetaminophen, an analgesic with minimal anti-inflammatory action, and BC risk. This supports the known pharmacological effects of NSAIDs and minimizes concerns that the associations we found are due to confounding from other unmeasured lifestyle factors associated with regular analgesic use [41, 57].
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The present study has several strengths. Most notably, we used data from a large cohort of women that is enriched for familial or genetic BC risk. This allowed us to test if associations between NSAIDs and BC risk vary in strength across a wide range of familial BC risk. Another strength is the use of the BOADICEA [34] to estimate a woman’s familial risk profile [35]. We also estimated associations by known BRCA1 and BRCA2 mutation carrier status. Although we had low statistical power, this is the first study to consider carrier-specific associations between NSAIDs and BC risk. One limitation of the present study is the use of binary measures of regular medication use. We also did not have information on dosage, and we had only limited data to examine duration of use. We recognize that these factors need to be considered to fully understand the association of NSAIDs with BC risk. Another limitation is that our exposure measures were retrospective, and thus, recall bias is a concern when interpreting the estimates from the combined cohort analyses. Survival bias is another potential limitation, but the consistency of associations between the prospective and combined cohorts supports that biases that operate differently in prospective and retrospective settings are unlikely to explain these findings. Confounding by indication could also be of concern, given that we did not have information on the reason for medication use. However, attained age models estimated similar associations in young women for whom comorbidities are unlikely, and the sensitivity analysis that further adjusted for diabetes and other cancers produced comparable estimates.
Conclusion
In summary, our findings add to growing evidence for an association between regular use of aspirin and COX-2 inhibitors and reduced BC risk. The potential impact of using these medications for primary BC prevention is underscored by the fact that associations were not modified by familial risk, and suggestive negative associations were found for BRCA1 and BRCA2 mutation carriers. This means that individuals at higher risk of BC could benefit even more in terms of absolute risk reduction from modifying medication use. Additionally, our findings suggest that regular use of aspirin and COX-2 inhibitors are associated with BC risk independent of ER status, which is important because risk-reducing medications are currently only available for ER-positive BC. Although RCTs are ultimately needed to confirm associations of NSAIDs with BC risk, our findings support that the consistent results seen in observational studies of average-risk women may extend to women at the higher range of absolute BC risk.
Acknowledgements
We thank the entire team of Breast Cancer Family Registry (BCFR) past and current investigators as well as the kConFab investigators. We also thank Heather Thorne, Eveline Niedermayr, Lucy Stanhope, Sandra Picken, all the BCFR and kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the many families who contribute to the BCFR and kConFab for their contributions to this resource.
Funding
The six sites of the Breast Cancer Family Registry were supported by grant UM1 CA164920 from the USA National Cancer Institute. This work was also supported by grants to kConFab and the kConFab Follow-Up Study from Cancer Australia [grant numbers 809195, 1100868], the Australian National Breast Cancer Foundation [grant number IF 17 kConFab], the National Health and Medical Research Council [grant numbers 454508, 288704, 145684], the National Institute of Health U.S.A. [grant number 1RO1CA159868], the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and the Cancer Foundation of Western Australia [grant numbers not applicable]. RDK is supported by the National Institutes of Health, National Cancer Institute, Cancer Epidemiology Training Grant [grant number T32-CA009529]. KAP is an Australian National Breast Cancer Foundation Practitioner Fellow.
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The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the BCFR, nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR.
Availability of data and materials
The datasets analyzed during the current study are available from the corresponding author on reasonable request.
Ethics approval and consent to participate
All participants in the BCFR and kConFab provided written informed consent before participation. Human research ethics committees at the participating institutions granted ethics approval for the six sites of the BCFR and for kConFab:
Northern California—Cancer Prevention Institute of California, Institutional Review Board (2001–033) and Stanford University School of Medicine, Institutional Review Board (45842).
New York—Columbia University Medical Center, Institutional Review Board (AAA7794).
Philadelphia—Fox Chase Cancer Center, Institutional Review Board (95–009).
Utah—Huntsman Cancer Institute, University of Utah, Institutional Review Board (00004965).
Ontario—Mount Sinai Hospital Research Ethics Board (#02–0076-U) and University Health Network Research Ethics Board (#96-U107-CE).
Australia—University of Melbourne, Human Ethics Sub-Committee (1441420.1).
kConFab—Peter MacCallum Cancer Centre, the Peter Mac Ethics Committee (97/27).
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Regular use of aspirin and other non-steroidal anti-inflammatory drugs and breast cancer risk for women at familial or genetic risk: a cohort study
verfasst von
Rebecca D. Kehm John L. Hopper Esther M. John Kelly-Anne Phillips Robert J. MacInnis Gillian S. Dite Roger L. Milne Yuyan Liao Nur Zeinomar Julia A. Knight Melissa C. Southey Linda Vahdat Naomi Kornhauser Tessa Cigler Wendy K. Chung Graham G. Giles Sue-Anne McLachlan Michael L. Friedlander Prue C. Weideman Gord Glendon Stephanie Nesci Irene L. Andrulis Saundra S. Buys Mary B. Daly Mary Beth Terry kConFab Investigators
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