Background: The U.S. Hispanic/Latino population is heterogeneous both socioculturally and by the proportion of European, Indigenous American, and African ancestry of the regions from which individuals originate. A previous study reported that genetic ancestry was associated with breast cancer survival among Latinas, independent of sociodemographic and tumor characteristics, suggesting that a genetic factor associated with ancestry may affect breast cancer survival.

Methods: We evaluated the association of genetic ancestry with breast cancer outcomes among 506 Latina women with invasive breast cancer in the Pathways Study, a cohort study within Kaiser Permanente, an integrated health care delivery system. Proportional hazards models were used to assess the effect of ancestry on breast cancer recurrence (53 events), breast cancer–specific mortality (31 events) and all-cause mortality (54 events), with a mean follow-up time of 6 years.

Results: Indigenous American ancestry was not associated with breast cancer recurrence [HR = 1.00 per 10% increase; 95% confidence interval (CI), 0.86–1.16], breast cancer mortality (HR = 0.95; 95% CI, 0.77–1.17), or all-cause mortality (HR = 0.93; 95% CI, 0.80–1.08). Adjustment for sociodemographic variables, tumor characteristics, and treatment did not alter the associations.

Conclusions: Our results suggest that previously reported differences in breast cancer survival by genetic ancestry may be overcome by improving health care access and/or quality.

Impact: Improving health care access and quality may reduce breast cancer disparities among U.S. Latinas. Cancer Epidemiol Biomarkers Prev; 26(9); 1466–9. ©2017 AACR.

A previous study tested the association between genetic ancestry and breast cancer mortality in U.S. Hispanic/Latina women from the San Francisco Bay Area Breast Cancer Study (SFBCS) and found an increased mortality hazard among Latina women with higher Indigenous American ancestry (1). This finding could be explained by the correlation between ancestry and germline genetic factors associated with mortality, comorbidities, or socioeconomic/sociocultural factors, such as access and quality of health care that were not controlled for appropriately in the study. We tested the effect of Indigenous American ancestry on breast cancer outcomes among Latina women with breast cancer in a setting where women have uniform access to healthcare.

The Pathways Study is a prospective cohort of women with breast cancer recruited from Kaiser Permanente Northern California (KPNC) between 2006 and 2013, and is described elsewhere (2). Women who self-reported as Latina (n = 565) were eligible for this analysis. Thirty-seven women (6.5%) with no available ancestry data, and 22 women with high Asian ancestry (>70%) were excluded from the analysis to improve comparability with the SFBCS study. The final sample included 506 women. Genetic ancestry was estimated using a panel of 118 ancestry informative markers (AIM) previously validated in Latin American samples (3) and the program ADMIXTURE version 1.22 (4).

Covariate data were obtained from baseline questionnaires and tumor characteristics and treatment were ascertained through KPNC medical records and tumor registry data. Outcome data on breast cancer recurrence, breast cancer-specific mortality, all-cause mortality, and disease-free survival were obtained through routine mail and/or phone contact and monthly searches of KPNC electronic medical records. Outcomes were confirmed by medical record review and the KPNC mortality file.

We used Cox proportional hazards models to evaluate the association between Indigenous American ancestry and outcomes. Follow-up time was calculated from the date of diagnosis to the date of event or last follow-up. Indigenous American ancestry was modeled as a continuous variable and coefficients scaled to reflect a 10% increase in ancestry. All analyses were two-sided and conducted in Stata 13.1 (5).

The study was approved by the institutional review board of KPNC. Informed consent was obtained from all individual participants included in the study.

Ancestry estimates were predominantly Indigenous American and European, with smaller proportions of African ancestry. Indigenous American ancestry was higher among women who were less educated, lower socioeconomic status, and had body mass index (BMI) ≥25 kg/m2, in concordance with the patterns observed in the Latinas from the SFBCS study (1). There were no differences in ancestry by tumor characteristics or treatment modality (Table 1).

Table 1.

Associations between genetic ancestry and demographic and clinical characteristics of Latinas in the Kaiser Permanente Northern California Pathways Study (n = 506).

Indigenous ancestryEuropean ancestry
N (%)Median (IQR)PaMedian (IQR)Pa
Age at diagnosis, y      
 <40 40 (7.9) 39.8 (23.9) <0.0001 51.4 (22.1) 0.0002 
 40–50 138 (27.3) 38.2 (23.9)  52.9 (23.4)  
 50–60 157 (31.0) 31.2 (25.6)  57.1 (25.3)  
 ≥60 171 (33.8) 28.9 (30.1)  59.1 (32.4)  
Body mass index      
 <25 kg/m2 136 (27.8) 30.1 (27.4) 0.02 59.7 (30.4) 0.01 
 25–29.9 kg/m2 157 (32.0) 36.2 (22.1)  52.6 (23.3)  
 30–34.9 kg/m2 105 (21.4) 32.5 (20.1)  55.8 (23.1)  
 ≥35 kg/m2 92 (18.8) 34.4 (30.4)  57.3 (25.0)  
Education level      
 High school 171 (33.9) 38.4 (22.1) <0.0001 51.3 (22.4) <0.0001 
 Some college 200 (39.6) 31.3 (24.8)  57.7 (22.2)  
 College graduate 77 (15.3) 31.1 (26.0)  56.9 (29.4)  
 Postgraduate degree 57 (11.3) 13.8 (30.2)  77.9 (28.7)  
Household income      
 <$25,000 60 (11.9) 37.5 (20.5) <0.0001 53.4 (24.6) <0.0001 
 $25000–49,999 104 (20.6) 33.5 (25.0)  56.5 (22.6)  
 $50,000–89,999 165 (32.6) 30.0 (28.1)  59.0 (28.7)  
 >$90,000 92 (18.2) 28.0 (31.2)  62.8 (34.3)  
 Not disclosed 85 (16.8) 38.3 (20.4)  50.2 (20.9)  
AJCC Stage      
 Stage I or II 433 (86.3) 32.3 (25.3) 0.45 56.9 (24.9) 0.56 
 Stage III or IV 69 (13.7) 35.2 (26.1)  56.1 (24.8)  
Estrogen receptor (ER) positive     
 No 94 (18.7) 31.0 (22.9) 0.13 59.2 (24.0) 0.21 
 Yes 408 (81.3) 33.0 (27.0)  56.4 (25.8)  
HER-2 positive      
 No 404 (84.3) 32.4 (26.5) 0.72 56.2 (25.7) 0.56 
 Yes 75 (15.7) 31.7 (26.5)  59.0 (22.9)  
Triple-negative      
 No 439 (86.8) 32.6 (26.5) 0.16 56.6 (25.6) 0.35 
 Yes 67 (13.2) 33.3 (32.2)  57.6 (26.7)  
Chemotherapy      
 No 229 (45.9) 32.2 (24.6) 0.53 56.3 (25.3) 0.73 
 Yes 270 (54.1) 33.2 (26.8)  57.5 (25.2)  
Hormonal therapy      
 No 138 (27.4) 31.7 (23.5) 0.35 57.6 (24.2) 0.46 
 Yes 366 (72.6) 33.0 (27.0)  56.4 (26.0)  
Radiotherapy      
 No 283 (56.4) 33.1 (27.3) 0.30 56.7 (25.4) 0.36 
 Yes 219 (43.6) 32.3 (24.8)  57.0 (25.9)  
Surgery      
 No surgery 5 (1.0) 25.8 (32.3) 0.72 55.6 (34.6) 0.70 
 Lumpectomy 291 (58.0) 33.1 (25.7)  57.0 (26.4)  
 Simple or radical mastectomy 206 (41.0) 31.7 (26.4)  56.7 (24.0)  
Indigenous ancestryEuropean ancestry
N (%)Median (IQR)PaMedian (IQR)Pa
Age at diagnosis, y      
 <40 40 (7.9) 39.8 (23.9) <0.0001 51.4 (22.1) 0.0002 
 40–50 138 (27.3) 38.2 (23.9)  52.9 (23.4)  
 50–60 157 (31.0) 31.2 (25.6)  57.1 (25.3)  
 ≥60 171 (33.8) 28.9 (30.1)  59.1 (32.4)  
Body mass index      
 <25 kg/m2 136 (27.8) 30.1 (27.4) 0.02 59.7 (30.4) 0.01 
 25–29.9 kg/m2 157 (32.0) 36.2 (22.1)  52.6 (23.3)  
 30–34.9 kg/m2 105 (21.4) 32.5 (20.1)  55.8 (23.1)  
 ≥35 kg/m2 92 (18.8) 34.4 (30.4)  57.3 (25.0)  
Education level      
 High school 171 (33.9) 38.4 (22.1) <0.0001 51.3 (22.4) <0.0001 
 Some college 200 (39.6) 31.3 (24.8)  57.7 (22.2)  
 College graduate 77 (15.3) 31.1 (26.0)  56.9 (29.4)  
 Postgraduate degree 57 (11.3) 13.8 (30.2)  77.9 (28.7)  
Household income      
 <$25,000 60 (11.9) 37.5 (20.5) <0.0001 53.4 (24.6) <0.0001 
 $25000–49,999 104 (20.6) 33.5 (25.0)  56.5 (22.6)  
 $50,000–89,999 165 (32.6) 30.0 (28.1)  59.0 (28.7)  
 >$90,000 92 (18.2) 28.0 (31.2)  62.8 (34.3)  
 Not disclosed 85 (16.8) 38.3 (20.4)  50.2 (20.9)  
AJCC Stage      
 Stage I or II 433 (86.3) 32.3 (25.3) 0.45 56.9 (24.9) 0.56 
 Stage III or IV 69 (13.7) 35.2 (26.1)  56.1 (24.8)  
Estrogen receptor (ER) positive     
 No 94 (18.7) 31.0 (22.9) 0.13 59.2 (24.0) 0.21 
 Yes 408 (81.3) 33.0 (27.0)  56.4 (25.8)  
HER-2 positive      
 No 404 (84.3) 32.4 (26.5) 0.72 56.2 (25.7) 0.56 
 Yes 75 (15.7) 31.7 (26.5)  59.0 (22.9)  
Triple-negative      
 No 439 (86.8) 32.6 (26.5) 0.16 56.6 (25.6) 0.35 
 Yes 67 (13.2) 33.3 (32.2)  57.6 (26.7)  
Chemotherapy      
 No 229 (45.9) 32.2 (24.6) 0.53 56.3 (25.3) 0.73 
 Yes 270 (54.1) 33.2 (26.8)  57.5 (25.2)  
Hormonal therapy      
 No 138 (27.4) 31.7 (23.5) 0.35 57.6 (24.2) 0.46 
 Yes 366 (72.6) 33.0 (27.0)  56.4 (26.0)  
Radiotherapy      
 No 283 (56.4) 33.1 (27.3) 0.30 56.7 (25.4) 0.36 
 Yes 219 (43.6) 32.3 (24.8)  57.0 (25.9)  
Surgery      
 No surgery 5 (1.0) 25.8 (32.3) 0.72 55.6 (34.6) 0.70 
 Lumpectomy 291 (58.0) 33.1 (25.7)  57.0 (26.4)  
 Simple or radical mastectomy 206 (41.0) 31.7 (26.4)  56.7 (24.0)  

Abbreviation: IQR, interquartile range.

aP values obtained by fitting univariable regression models for type of ancestry on each characteristic.

The mean follow-up time was 5.7 years (SD: 2.3 years) for disease-free survival and 6.05 years (SD: 2.1 years) for mortality outcomes. Indigenous American ancestry was not associated with breast cancer recurrence [HR = 1.00 per 10% increase; 95% confidence interval (CI), 0.86–1.16], breast cancer mortality (HR = 0.95; 95% CI, 0.77–1.17), all-cause mortality (0.93; 0.80, 1.08), or disease-free survival (HR = 0.96; 95% CI, 0.85–1.08). Adjustment for sociodemographics, tumor characteristics, and treatment did not alter the associations (Table 2), nor did analyses fitting ancestry as a nonlinear term.

Table 2.

HRs for the effect of Indigenous American ancestry on primary and secondary outcomes

Breast cancer recurrenceBreast cancer–specific mortalityAll-cause mortalityDisease-free survival
Crude HR (95% CI)Adjusted HRa (95% CI)Crude HR (95% CI)Adjusted HRa (95% CI)Crude HR (95% CI)Adjusted HRa (95% CI)Crude HR (95% CI)Adjusted HRa (95% CI)
Indigenous American ancestryb 1.00 (0.86–1.16) 0.98 (0.84–1.15) 0.95 (0.77–1.17) 0.97 (0.78–1.19) 0.93 (0.80–1.08) 0.98 (0.83–1.14) 0.96 (0.85–1.08) 0.98 (0.87–1.10) 
Age at diagnosis  0.99 (0.96–1.00)  1.00 (0.98–1.03)  1.02 (1.00–1.04)  1.01 (1.00–1.03) 
AJCC Stage         
 Stage I–II  ref  ref  ref  ref 
 Stage III–IV  4.01 (2.3–7.1)  7.35 (3.60–15.0)  4.61 (2.65–8.03)  3.65 (2.31–5.76) 
Hormonal therapy         
 No  ref  ref  ref  ref 
 Yes  0.56 (0.32–0.97)  0.49 (0.24–1.00)  0.39 (0.23–0.66)  0.57 (0.37–0.88) 
Breast cancer recurrenceBreast cancer–specific mortalityAll-cause mortalityDisease-free survival
Crude HR (95% CI)Adjusted HRa (95% CI)Crude HR (95% CI)Adjusted HRa (95% CI)Crude HR (95% CI)Adjusted HRa (95% CI)Crude HR (95% CI)Adjusted HRa (95% CI)
Indigenous American ancestryb 1.00 (0.86–1.16) 0.98 (0.84–1.15) 0.95 (0.77–1.17) 0.97 (0.78–1.19) 0.93 (0.80–1.08) 0.98 (0.83–1.14) 0.96 (0.85–1.08) 0.98 (0.87–1.10) 
Age at diagnosis  0.99 (0.96–1.00)  1.00 (0.98–1.03)  1.02 (1.00–1.04)  1.01 (1.00–1.03) 
AJCC Stage         
 Stage I–II  ref  ref  ref  ref 
 Stage III–IV  4.01 (2.3–7.1)  7.35 (3.60–15.0)  4.61 (2.65–8.03)  3.65 (2.31–5.76) 
Hormonal therapy         
 No  ref  ref  ref  ref 
 Yes  0.56 (0.32–0.97)  0.49 (0.24–1.00)  0.39 (0.23–0.66)  0.57 (0.37–0.88) 

aAdjusted for age at diagnosis (years), AJCC stage, and hormonal therapy.

bPer 10% increase in ancestry.

We found that, among Latina breast cancer patients enrolled at KPNC, Indigenous American ancestry was not associated with breast cancer outcomes.

Our findings are inconsistent with the Fejerman and colleagues' (2013) study in the SFBCS (1), and suggest no disparities in outcomes between highly Indigenous Latinas and those with greater European ancestry among women with uniform access to care. This finding suggests that if germline genetic factors associated with Indigenous ancestry predict poorer outcomes, this effect may be reversed among women with access to care. However, this conclusion should be taken with caution, as other socioeconomic factors correlated with access to care in Kaiser may explain the lack of observed disparities.

One limitation to the study is that the average follow-up in Pathways was 6 years compared with 9 years in the SFBCS study. However, a reanalysis of the data in the SFBCS study at 6 years of follow-up found similar, although slightly attenuated effects, compared with 9 years of follow-up (HR = 1.80, P = 0.137 vs., HR = 1.75, P = 0.014 for 6 vs., 9 years). While our study focused on assessing disparities in shorter-term outcomes, it is possible that long-term disparities may emerge with differential adherence to treatment or other sociocultural factors. We had only 40%–70% power (α = 5%) to detect a HR of 1.57 per 25% increase in ancestry (1.2 per 10% increase). However, with a 15% type I error rate (63%–82% power), our P values were much higher than P = 0.15, with point estimates very close to 1, suggesting that our findings are unlikely to be due to inadequate power.

The major strength of our study is the use of data from KPNC, which eliminates the challenge of adequate control for the complex concept of access and quality of health care (6, 7). However, the generalizeability of our results may be limited to women who have access to clinical care.

To conclude, genetic ancestry was not associated with breast cancer outcomes among Latina breast cancer patients enrolled at KPNC.

No potential conflicts of interest were disclosed.

Conception and design: N.J. Engmann, L.H. Kushi, L. Fejerman

Development of methodology: N.J. Engmann, I.J. Ergas, L. Fejerman

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): S. Yao, C.B. Ambrosone, L.H. Kushi

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): N.J. Engmann, I.J. Ergas, M.L. Kwan, L.H. Kushi, L. Fejerman

Writing, review, and/or revision of the manuscript: N.J. Engmann, S. Yao, M.L. Kwan, C.B. Ambrosone, L.H. Kushi, L. Fejerman

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): I.J. Ergas, J.M. Roh

Study supervision: L. Fejerman

The Pathways Study is supported by the National Cancer Institute at the NIH [R01 CA105274, principal investigator (PI): L.H. Kushi; R01 CA166701, PIs: M.L. Kwan and S. Yao; U01 CA195565, PIs: L.H. Kushi, C.B. Ambrosone; K01 CA160607, to L. Fejerman]. Electronic clinical data abstraction and integration was supported in part by the Cancer Research Network (U19 CA079689, U24 CA171524, PI: L.H. Kushi). Blood samples are stored and managed by the Roswell Park Cancer Institute DataBank and BioRepository. Genotyping was supported by an ARRA supplement to the Pathways Study (3R01CA105274-06S1), was performed by the Roswell Park Cancer Institute Genomics Shared Resource, both of which are Cancer Center Support Grant Shared Resources supported by P30 CA16056.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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