Abstract
Purpose
Young age at breast cancer diagnosis is associated with poor survival. However, little is known about factors associated with first-course treatment receipt or survival among adolescent and young adult (AYA) females aged 15–39 years.
Methods
Data regarding 19,906 eligible AYA breast cancers diagnosed in California during 1992–2009 were obtained from the population-based California Cancer Registry. Multivariable logistic regression was used to evaluate clinical and sociodemographic differences in treatment receipt. Multivariable Cox proportional hazards regression was used to examine differences in survival by initial treatment, and by patient and tumor characteristics.
Results
Black and Hispanic AYAs diagnosed with in situ or stages I–III breast cancer were more likely than White AYAs to receive breast-conserving surgery (BCS) without radiation; Asian and Hispanic AYAs were more likely than Whites to receive mastectomy. Women in lower socioeconomic status (SES) neighborhoods were more likely to omit radiation after BCS, more likely to receive mastectomy, and less likely to receive chemotherapy, compared to those in higher SES neighborhoods. Among patients with invasive disease, survival improved an average of 5% per year during 1992–2009. AYAs who received BCS with radiation experienced better survival than other surgery/radiation options. Black AYAs had poorer survival than Whites. AYAs who resided in higher SES neighborhoods had better survival.
Conclusions
Treatment receipt among AYAs with breast cancer varied by race/ethnicity and neighborhood SES. Poor survival for Black AYAs and AYAs living in low SES neighborhoods in models adjusted for treatment receipt suggests that factors other than treatment may also be important to disease outcome.
Keywords: breast cancer, treatment, survival, race/ethnicity, socioeconomic status
Breast cancer accounts for 14% of all cancer diagnoses among adolescents and young adults (AYAs) between 15 and 39 years of age and 7% of all breast cancers in the United States occur in AYA females.1,2 AYA breast cancer has a molecular subtype distribution3 and etiology1 distinct from that in older women. In addition, many AYAs experience unique conditions that may affect treatment.1,4,5 For example, concerns over a burgeoning career, young children, maintenance of fertility, or inadequate insurance coverage may result in omissions, delays, or poor adherence to treatment.1,4 On the other hand, the possibility of recurrence during an extended survivorship period and fewer comorbid conditions among AYAs may lead them to receive more intense treatment regimens.1,4,5 The National Cancer Institute (NCI) and the LIVESTRONG Young Adult Alliance have called for research to determine factors that may affect cancer outcomes for AYAs.6 Understanding factors related to initial treatment and to survival among AYAs with breast cancer is important in addressing this goal.
Little is known about either the receipt of treatment or survival among AYAs diagnosed with breast cancer. Shavers et al. determined that young females who received BCS with radiation had a lower risk of breast cancer death compared to those who received BCS without radiation or mastectomy.7 The same report also found that African American and Hispanic women less than 35 years of age diagnosed between 1990 and 1998 were less likely to receive radiation after breast-conserving surgery (BCS) relative to Whites.7 To our knowledge, no reports have addressed chemotherapy receipt specifically among AYAs. To understand better the treatment received by AYAs with breast cancer and their survival after breast cancer diagnosis, we analyzed patient, clinical, and hospital data from the large and diverse population-based California Cancer Registry (CCR) from 1992 to 2009.
Methods
Cancer cases
California mandates that cancer cases be reported to the population-based CCR, which participates in the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program. We obtained information about all female California residents diagnosed with in situ or invasive breast cancer (International Classification of Disease for Oncology, 3rd Edition [ICD-O-3] site codes C50.0–50.9) from January 1, 1992, through December 31, 2009, the most recent years of diagnosis for which data on hormone receptor (HR) status are available. For each breast cancer case, we obtained cancer registry information routinely abstracted from the medical record (Table 1): age at diagnosis; American Joint Committee on Cancer (AJCC) stage at diagnosis; tumor size; tumor grade (low [1 or 2], high [3 or 4], or unknown); lymph node involvement; metastases; vital status as of December 31, 2010; and, for the deceased, the underlying cause of death. Vital status and cause of death are routinely determined by the CCR through hospital follow-up and database linkages. Race/ethnicity were collapsed into the categories Hispanic, non-Hispanic White, non-Hispanic Black, non-Hispanic Asian/Pacific Islander, and other/unknown (hereafter referred to as “White,” “Black,” “Hispanic,” “Asian,” and “other/unknown”).
Table 1.
Demographic and Clinical Characteristics of Adolescent and Young Adult Females with In Situ and Invasive Breast Cancer by First-Course Surgery and Radiation Treatment, California, 1992–2009
| Total N=19,906 n (%) | BCS with radiation n=6089 n (%) | BCS no radiation n=2809 n (%) | Mastectomy with radiation n=2886 n (%) | Mastectomy no radiation n=7450 n (%) | No surgery n=672 n (%) | |
|---|---|---|---|---|---|---|
| Age at diagnosis (years) | ||||||
| 15–24 | 261 (1.3) | 56 (0.9) | 52 (1.9) | 43 (1.5) | 93 (1.2) | 17 (2.5) |
| 25–29 | 1460 (7.3) | 418 (6.9) | 193 (6.9) | 254 (8.8) | 531 (7.1) | 64 (9.5) |
| 30–34 | 5216 (26.2) | 1554 (25.5) | 719 (25.6) | 805 (27.9) | 1938 (26.0) | 200 (29.8) |
| 35–39 | 12,969 (65.2) | 4061 (66.7) | 1845 (65.7) | 1784 (61.8) | 4888 (65.6) | 391 (58.2) |
| Race/ethnicity | ||||||
| White | 10,139 (50.9) | 3376 (55.4) | 1392 (49.6) | 1382 (47.9) | 3723 (50.0) | 266 (39.6) |
| Black | 1676 (8.4) | 503 (8.3) | 275 (9.8) | 211 (7.3) | 595 (8.0) | 92 (13.7) |
| Hispanic | 5133 (25.8) | 1374 (22.6) | 746 (26.6) | 859 (29.8) | 1923 (25.8) | 231 (34.4) |
| Asian/Pacific Islander | 2801 (14.1) | 809 (13.3) | 351 (12.5) | 419 (14.5) | 1148 (15.4) | 74 (11.0) |
| Other/unknown | 157 (0.8) | 27 (0.4) | 45 (1.6) | 15 (0.5) | 61 (0.8) | 9 (1.3) |
| Year of diagnosis | ||||||
| 1992–1993 | 2170 (10.9) | 668 (11.0) | 199 (7.1) | 212 (7.3) | 1044 (14.0) | 47 (7.0) |
| 1994–1995 | 2195 (11.0) | 718 (11.8) | 220 (7.8) | 253 (8.8) | 942 (12.6) | 62 (9.2) |
| 1996–1997 | 2148 (10.8) | 715 (11.7) | 289 (10.3) | 285 (9.9) | 806 (10.8) | 53 (7.9) |
| 1998–1999 | 2239 (11.2) | 736 (12.1) | 327 (11.6) | 347 (12.0) | 769 (10.3) | 60 (8.9) |
| 2000–2001 | 2355 (11.8) | 711 (11.7) | 393 (14.0) | 382 (13.2) | 813 (10.9) | 56 (8.3) |
| 2002–2003 | 2142 (10.8) | 658 (10.8) | 366 (13.0) | 344 (11.9) | 699 (9.4) | 75 (11.2) |
| 2004–2005 | 2216 (11.1) | 744 (12.2) | 299 (10.6) | 350 (12.1) | 736 (9.9) | 87 (12.9) |
| 2006–2007 | 2184 (11.0) | 644 (10.6) | 345 (12.3) | 344 (11.9) | 754 (10.1) | 97 (14.4) |
| 2008–2009 | 2257 (11.3) | 495 (8.1) | 371 (13.2) | 369 (12.8) | 887 (11.9) | 135 (20.1) |
| Stage at diagnosis | ||||||
| In situ | 2248 (11.3) | 551 (9.0) | 628 (22.4) | 52 (1.8) | 962 (12.9) | 55 (8.2) |
| I | 5014 (25.2) | 2292 (37.6) | 726 (25.8) | 163 (5.6) | 1799 (24.1) | 34 (5.1) |
| II | 9588 (48.2) | 2857 (46.9) | 1243 (44.3) | 1546 (53.6) | 3795 (50.9) | 147 (21.9) |
| III | 2248 (11.3) | 300 (4.9) | 126 (4.5) | 1003 (34.8) | 740 (9.9) | 79 (11.8) |
| IV | 808 (4.1) | 89 (1.5) | 86 (3.1) | 122 (4.2) | 154 (2.1) | 357 (53.1) |
| Tumor size | ||||||
| <2 cm | 6980 (35.1) | 2921 (48.0) | 1183 (42.1) | 430 (14.9) | 2379 (31.9) | 67 (10.0) |
| 2–3.9 cm | 7378 (37.1) | 2382 (39.1) | 1017 (36.2) | 1012 (35.1) | 2830 (38.0) | 137 (20.4) |
| 4+ cm | 4025 (20.2) | 547 (9.0) | 303 (10.8) | 1285 (44.5) | 1623 (21.8) | 267 (39.7) |
| Microinvasion | 322 (1.6) | 59 (1.0) | 83 (3.0) | 17 (0.6) | 160 (2.1) | 3 (0.4) |
| Diffuse | 90 (0.5) | 4 (0.1) | 2 (0.1) | 34 (1.2) | 33 (0.4) | 17 (2.5) |
| Unknown | 1111 (5.6) | 176 (2.9) | 221 (7.9) | 108 (3.7) | 425 (5.7) | 181 (26.9) |
| Lymph node involvement | ||||||
| Negative | 10,815 (54.3) | 3992 (65.6) | 1853 (66.0) | 544 (18.8) | 4229 (56.8) | 197 (29.3) |
| Positive | 8684 (43.6) | 2053 (33.7) | 891 (31.7) | 2295 (79.5) | 3141 (42.2) | 304 (45.2) |
| Unknown | 407 (2.0) | 44 (0.7) | 65 (2.3) | 47 (1.6) | 80 (1.1) | 171 (25.4) |
| Metastasis | ||||||
| Negative | 17,692 (88.9) | 5656 (92.9) | 2301 (81.9) | 2749 (95.3) | 6696 (89.9) | 290 (43.2) |
| Positive | 738 (3.7) | 76 (1.2) | 81 (2.9) | 104 (3.6) | 133 (1.8) | 344 (51.2) |
| Unknown | 1476 (7.4) | 357 (5.9) | 427 (15.2) | 33 (1.1) | 621 (8.3) | 38 (5.7) |
| Tumor grade | ||||||
| Low | 7090 (35.6) | 2408 (39.5) | 955 (34.0) | 904 (31.3) | 2633 (35.3) | 190 (28.3) |
| High | 10,536 (52.9) | 3113 (51.1) | 1390 (49.5) | 1810 (62.7) | 3936 (52.8) | 287 (42.7) |
| Unknown | 2280 (11.5) | 568 (9.3) | 464 (16.5) | 172 (6.0) | 881 (11.8) | 195 (29.0) |
| Hormone receptor status | ||||||
| Negative | 5234 (26.3) | 1711 (28.1) | 684 (24.4) | 853 (29.6) | 1826 (24.5) | 160 (23.8) |
| Positive or borderline | 10,627 (53.4) | 3426 (56.3) | 1255 (44.7) | 1727 (59.8) | 3951 (53.0) | 268 (39.9) |
| Unknown | 4045 (20.3) | 952 (15.6) | 870 (31.0) | 306 (10.6) | 1673 (22.5) | 244 (36.3) |
| Chemotherapy | ||||||
| None | 6472 (32.5) | 1695 (27.8) | 1500 (53.4) | 193 (6.7) | 2876 (38.6) | 208 (31.0) |
| Given | 12,992 (65.3) | 4324 (71.0) | 1213 (43.2) | 2674 (92.7) | 4336 (58.2) | 445 (66.2) |
| Unknown | 442 (2.2) | 70 (1.1) | 96 (3.4) | 19 (0.7) | 238 (3.2) | 19 (2.8) |
| Neighborhood SES quintile | ||||||
| Highest | 4924 (24.7) | 1624 (26.7) | 648 (23.1) | 669 (23.2) | 1866 (25.0) | 117 (17.4) |
| Higher-middle | 4603 (23.1) | 1557 (25.6) | 641 (22.8) | 698 (24.2) | 1592 (21.4) | 115 (17.1) |
| Middle | 4033 (20.3) | 1237 (20.3) | 573 (20.4) | 578 (20.0) | 1518 (20.4) | 127 (18.9) |
| Lower-middle | 3497 (17.6) | 957 (15.7) | 525 (18.7) | 504 (17.5) | 1373 (18.4) | 138 (20.5) |
| Lowest | 2849 (14.3) | 714 (11.7) | 422 (15.0) | 437 (15.1) | 1101 (14.8) | 175 (26.0) |
| National Cancer Institute–designated hospital | ||||||
| No | 18,394 (92.4) | 5604 (92.0) | 2612 (93.0) | 2655 (92.0) | 6936 (93.1) | 587 (87.4) |
| Yes | 1512 (7.6) | 485 (8.0) | 197 (7.0) | 231 (8.0) | 514 (6.9) | 85 (12.6) |
BCS, breast-conserving surgery; SES, socioeconomic status.
HR categories were determined according to estrogen receptor (ER) and progesterone receptor (PR) expression. ER and PR status, extracted from patients' medical records, were recorded as positive, negative, borderline, not tested, not recorded, or unknown.8 “HR-positive or borderline” was defined as ER- and/or PR-positive or borderline, “HR-negative” as ER- and PR-negative, and “HR-unknown” as ER and PR unknown or not determined. Our analyses are limited to 1992–2009 due to higher completeness of these data in the CCR since 1992.9–11 We also obtained cancer registry information on first-course treatment modality (chemotherapy, radiation, and surgery). Cases were categorized as having received mastectomy with radiation, mastectomy without radiation, BCS with radiation, BCS without radiation, or no surgery.
Of the 23,656 female breast cancer cases aged 15 to 39 years diagnosed between 1992 and 2009 in California, we excluded those cases with inflammatory carcinoma (n=630); mammographic or xerographic diagnosis only, or with no mass or tumor found (n=121); autopsy or death certificate only (n=12); Paget's disease (n=27); surgery and/or radiation therapy unknown or NOS (n=54); with breast cancer as a non-first primary (n=1655); or with unknown stage (n=1251). The resulting study population included 19,906 cases.
Neighborhood and hospital variables
Each cancer case was assigned to a census block group based on home address at diagnosis. Neighborhood socioeconomic status (SES) was measured using a previously described index that incorporates 1990 or 2000 census data on education, occupation, unemployment, household income, and poverty.12 This index was in turn classified into a quintile based on its distribution across all census block groups in California. As a measure of quality of care, we classified the reporting hospitals according to whether or not they were a National Cancer Institute–designated comprehensive or noncomprehensive cancer center (hereafter collectively referred to as “NCI-designated cancer hospital”).
Analyses
Treatment analyses
Multivariate logistic regression was used to evaluate associations of clinical and sociodemographic characteristics with breast cancer treatment. Odds ratios (ORs) and associated 95% confidence intervals (CIs) are presented. The National Comprehensive Cancer Network (NCCN) guidelines do not recommend BCS for stage IV breast cancer or diffuse histology, so treatment analyses were restricted to in situ and stages I–III. Thus, we excluded 808 females with stage IV disease and 63 cases with diffuse histology for a final population of 19,035 eligible patients. ORs for the “no surgery” treatment category (n=672) are not presented, as this group comprised a very small portion (1.6%) of the study population.
Survival analyses
Cox proportional hazards regression models were used to estimate hazard ratios and associated 95% CIs. For deceased patients, survival time was measured in days from the date of diagnosis to the date of death from any cause for overall survival or to the date of death from breast cancer for breast cancer–specific survival. Patients who died from other causes were censored at the time of death for analyses of breast cancer–specific survival. Patients alive at the study end date (December 31, 2010) were censored at this time or at date of last follow-up (i.e., last known contact). Ninety-two percent of censored patients had a follow-up date (i.e., were verified as being alive) within 2 years of the study end date, somewhat lower than the percentage for women over 40 years of age (97%). After exclusion of 2248 patients with in situ (Stage 0) disease, the final population for the survival analyses included 17,658 eligible patients and 4314 deaths.
We assessed the proportional hazards assumption by statistical testing of the correlation between weighted Schoenfeld residuals and logarithmically transformed survival time. No violations of the assumption were observed. Multivariate Cox regression models included all variables significant at p<0.05 in unadjusted models. AJCC stage levels I–IV were included as a stratifying variable in the model to account for varying baseline hazards by stage. Analyses were carried out using SAS software v9.3 (SAS Institute Inc., Cary, NC). All p-values reported are two-sided, and those with p<0.05 were considered to be statistically significant.
Results
Mastectomy without radiation was the most frequent initial surgery/radiation treatment (37.4%), followed by BCS with radiation (30.6%), mastectomy with radiation (14.5%), BCS without radiation (14.1%), and no surgery (3.4%; Table 1). Most women were of White race/ethnicity (50.9%), with fewer of Hispanic (25.8%), Asian (14.1%), or Black (8.4%) race/ethnicity. AYAs were most often diagnosed with stage II disease (48.2%) and high-grade tumors (52.9%). Most AYAs (65.3%) received chemotherapy. Nearly half (47.8%) resided in the two highest neighborhood SES quintiles, and fewer than 10% received treatment at NCI-designated cancer hospitals.
Treatment receipt according to patient and tumor characteristics
Relative to diagnoses in 1992–1993, AYAs diagnosed after 2000 were more than twice as likely to receive BCS without radiation compared to BCS with radiation (Table 2). Mastectomy receipt remained below 1992–1993 levels until 2008–2009, when it was significantly higher relative to BCS with radiation. Chemotherapy receipt decreased in 2008–2009 compared to 1992–1993.
Table 2.
Adjusteda Odds Ratios for First-Course Treatment Type Among Adolescent and Young adult Females 15–39 Years of Age with In Situ and Stages I–III Breast Cancerb by Select Demographic and Tumor Characteristics, California 1992–2009
| |
Surgery/Radiationc (versus BCS with radiation) |
Chemotherapy (versus none) |
|
|---|---|---|---|
| BCS without radiation | Mastectomyd | Given | |
| Age at diagnosis (years) | 0.99 (0.97–1.00) | 0.99 (0.98–1.00) | 0.97 (0.96–0.99) |
| Race/ethnicity | |||
| White | Ref | Ref | Ref |
| Black | 1.25 (1.05–1.49) | 0.92 (0.81–1.05) | 0.98 (0.84–1.13) |
| Hispanic | 1.13 (1.00–1.28) | 1.11 (1.01–1.21) | 1.14 (1.03–1.26) |
| Asian/Pacific Islander | 0.93 (0.80–1.08) | 1.30 (1.18–1.44) | 0.92 (0.82–1.03) |
| Other/unknown | 3.33 (2.00–5.55) | 1.79 (1.13–2.85) | 0.96 (0.61–1.49) |
| Year of diagnosis | |||
| 1992–1993 | Ref | Ref | Ref |
| 1994–1995 | 1.08 (0.85–1.36) | 0.85 (0.74–0.97) | 1.01 (0.86–1.18) |
| 1996–1997 | 1.51 (1.20–1.88) | 0.80 (0.70–0.92) | 1.04 (0.88–1.22) |
| 1998–1999 | 1.76 (1.41–2.20) | 0.77 (0.67–0.88) | 1.02 (0.86–1.19) |
| 2000–2001 | 2.27 (1.83–2.82) | 0.85 (0.74–0.98) | 1.06 (0.90–1.24) |
| 2002–2003 | 2.36 (1.90–2.95) | 0.79 (0.68–0.91) | 1.05 (0.89–1.23) |
| 2004–2005 | 1.77 (1.41–2.22) | 0.66 (0.58–0.77) | 0.95 (0.80–1.12) |
| 2006–2007 | 2.40 (1.91–3.00) | 0.79 (0.69–0.92) | 0.93 (0.79–1.10) |
| 2008–2009 | 3.52 (2.80–4.43) | 1.22 (1.05–1.42) | 0.75 (0.64–0.88) |
| AJCC stage at diagnosis | |||
| In situ | 2.19 (1.86–2.58) | 1.84 (1.62–2.10) | 0.01 (0.01–0.02) |
| I | Ref | Ref | Ref |
| II | 1.29 (1.15–1.44) | 2.16 (2.00–2.34) | 4.00 (3.69–4.34) |
| III | 1.09 (0.86–1.38) | 6.68 (5.80–7.68) | 7.03 (6.02–8.21) |
| Tumor grade | |||
| Low | Ref | Ref | Ref |
| High | 1.10 (0.98–1.23) | 1.10 (1.02–1.19) | 1.58 (1.45–1.72) |
| Unknown | 1.53 (1.29–1.81) | 1.16 (1.02–1.32) | 0.59 (0.52–0.68) |
| Hormone receptor status | |||
| Positive or borderline | Ref | Ref | Ref |
| Negative | 0.95 (0.84–1.07) | 1.18 (1.08–1.28) | 0.78 (0.71–0.86) |
| Unknown | 2.00 (1.71–2.34) | 1.48 (1.32–1.66) | 0.32 (0.28–0.37) |
| Neighborhood SES quintile | |||
| Highest | Ref | Ref | Ref |
| Higher-middle | 0.99 (0.86–1.13) | 0.88 (0.80–0.97) | 1.04 (0.93–1.16) |
| Middle | 1.09 (0.94–1.26) | 0.98 (0.89–1.09) | 1.02 (0.91–1.15) |
| Lower-middle | 1.20 (1.03–1.40) | 1.09 (0.98–1.22) | 0.88 (0.78–0.99) |
| Lowest | 1.24 (1.04–1.47) | 1.10 (0.97–1.24) | 0.77 (0.67–0.88) |
| National Cancer Institute-–designated hospital | |||
| No | Ref | Ref | Ref |
| Yes | 0.90 (0.75–1.07) | 0.85 (0.75–0.97) | 1.53 (1.30–1.80) |
Note: p<0.05 indicated in bold.
Adjusted for all variables in table.
Models include 19,035 patients.
Odds ratios for the “no surgery” treatment category are not presented as this group comprised a very small portion (n=313, 1.6%) of the study population.
Including mastectomy with radiation and mastectomy without radiation.
AJCC, American Joint Committee on Cancer; BCS, breast-conserving surgery; Ref, reference; SES, socioeconomic status.
Relative to Whites, Black AYAs were 25% more likely to have BCS without radiation than BCS with radiation. Hispanic AYAs were 13% more likely than Whites to have BCS without radiation, and 11% more likely to have mastectomy than BCS with radiation. Hispanic AYAs were also 14% more likely to receive chemotherapy compared to Whites. Asian AYAs were more likely than Whites to have mastectomy.
Relative to the highest neighborhood SES quintile, AYAs in the lower-middle and lowest quintiles were 20% and 24% more likely to receive BCS without radiation than BCS with radiation, and 9% and 10% more likely to receive mastectomy respectively. AYAs in the lowest neighborhood SES quintile were also 23% less likely to receive chemotherapy. In addition, women who were HR negative were 22% less likely to receive chemotherapy than those that were HR positive or borderline. AYAs treated at NCI-designated cancer hospitals were 15% less likely to receive mastectomy and 53% more likely to receive chemotherapy.
Survival analyses
Risk of all-cause and breast cancer–specific death for AYAs with breast cancer improved by 5% per year from 1992 to 2009 (Table 3). Relative to BCS with radiation, all other forms of surgery/radiation were associated with a significantly increased risk of death. Receipt of chemotherapy was also associated with an increased risk of death. Relative to Whites, Black AYAs were 47% more likely to die from breast cancer. Having a high-grade or larger-sized tumor, lymph-node involvement, or the presence of metastases were all associated with an increased risk of death. Relative to the highest neighborhood SES quintile, the lower four neighborhood SES quintiles were associated with an increased risk of death. Patients treated at NCI-designated cancer hospitals were 20% less likely to die from breast cancer. Associations did not vary substantially when treatment was removed from the model or when in situ cancers were included (data not shown).
Table 3.
Risk of Deatha From any Cause or From Breast Cancer for Adolescent and Young Adult Females 15 to 39 Years of Age with Invasive Breast Cancer,b California, 1992–2009
| |
Deaths, all causes |
Deaths, breast-cancer specific |
||
|---|---|---|---|---|
| Number of deaths | Hazard ratio (95% CI) | Number of deaths | Hazard ratio (95% CI) | |
| Age at diagnosis (years)c | 4314 (100%) | 0.99 (0.98–1.00) | 3764 (100%) | 0.99 (0.98–1.00) |
| Year of diagnosis (years)c | 4314 (100%) | 0.96 (0.95–0.96) | 3764 (100%) | 0.95 (0.94–0.95) |
| Race/ethnicity | ||||
| White | 2094 (48.5%) | 1.00 (ref) | 1830 (48.6%) | 1.00 (ref) |
| Black | 560 (13.0%) | 1.45 (1.31–1.61) | 493 (13.1%) | 1.47 (1.32–1.64) |
| Hispanic | 1181 (27.4%) | 1.00 (0.93–1.09) | 1027 (27.3%) | 1.02 (0.93–1.11) |
| Asian/Pacific Islander | 470 (10.9%) | 0.96 (0.87–1.07) | 407 (10.8%) | 0.96 (0.86–1.07) |
| Other/unknown | 9 (0.2%) | 0.47 (0.21–1.05) | 7 (0.2%) | 0.37 (0.14–0.99) |
| First-course surgical/radiation treatment | ||||
| BCS with radiation | 990 (22.9%) | 1.00 (ref) | 856 (22.7%) | 1.00 (ref) |
| BCS without radiation | 425 (9.9%) | 1.22 (1.08–1.37) | 363 (9.6%) | 1.21 (1.07–1.38) |
| Mastectomy radiation | 956 (22.2%) | 1.35 (1.23–1.49) | 862 (22.9%) | 1.36 (1.22–1.51) |
| Mastectomy without radiation | 1593 (36.9%) | 1.25 (1.15–1.36) | 1387 (36.8%) | 1.25 (1.14–1.37) |
| No surgery | 350 (8.1%) | 2.17 (1.82–2.60) | 296 (7.9%) | 2.04 (1.69–2.48) |
| Chemotherapy | ||||
| No | 665 (15.4%) | 1.00 (ref) | 528 (14.0%) | 1.00 (ref) |
| Yes | 3556 (82.4%) | 1.27 (1.16–1.39) | 3158 (83.9%) | 1.36 (1.22–1.50) |
| Unknown | 93 (2.2%) | 1.02 (0.81–1.28) | 78 (2.1%) | 1.05 (0.82–1.35) |
| Tumor grade | ||||
| Low | 1129 (26.2%) | 1.00 (ref) | 982 (26.1%) | 1.00 (ref) |
| High | 2772 (64.3%) | 1.46 (1.36–1.57) | 2446 (65.0%) | 1.47 (1.36–1.58) |
| Unknown | 413 (9.6%) | 1.07 (0.94–1.22) | 336 (8.9%) | 1.00 (0.87–1.15) |
| Tumor size (cm)c | 4314 (100%) | 1.02 (1.01–1.03) | 3764 (100%) | 1.02 (1.01–1.03) |
| Lymph node involvement | ||||
| Negative | 1112 (25.8%) | 1.00 (ref) | 902 (24.0%) | 1.00 (ref) |
| Positive | 2928 (67.9%) | 1.93 (1.75–2.12) | 2623 (69.7%) | 2.02 (1.83–2.24) |
| Unknown | 274 (6.4%) | 2.30 (1.92–2.74) | 239 (6.3%) | 2.42 (2.00–2.92) |
| Metastasis | ||||
| Negative | 3788 (87.8%) | 1.00 (ref) | 3295 (87.5%) | 1.00 (ref) |
| Positive | 517 (12.0%) | 1.91 (1.31–2.78) | 461 (12.2%) | 2.07 (1.40–3.07) |
| Unknown | 9 (0.2%) | 2.28 (0.82–6.34) | 8 (0.2%) | 2.73 (0.98–7.65) |
| Neighborhood SES quintile | ||||
| Highest | 830 (19.2%) | 1.00 (ref) | 731 (19.4%) | 1.00 (ref) |
| Higher-middle | 922 (21.4%) | 1.13 (1.03–1.25) | 817 (21.7%) | 1.14 (1.03–1.26) |
| Middle | 918 (21.3%) | 1.22 (1.10–1.35) | 795 (21.1%) | 1.19 (1.07–1.33) |
| Lower-middle | 860 (19.9%) | 1.36 (1.23–1.51) | 761 (20.2%) | 1.36 (1.22–1.52) |
| Lowest | 784 (18.2%) | 1.37 (1.23–1.53) | 660 (17.5%) | 1.29 (1.14–1.45) |
| National Cancer Institute–designated hospital | ||||
| No | 4025 (93.3%) | 1.00 (ref) | 3526 (93.7%) | 1.00 (ref) |
| Yes | 289 (6.7%) | 0.86 (0.76–0.98) | 238 (6.3%) | 0.80 (0.70–0.92) |
Note: p<0.05 indicated in bold.
Cox models were adjusted for all variables in the table; AJCC stage levels I–IV were included as a stratifying variable.
Models include 17,658 eligible patients.
Age at diagnosis, year of diagnosis, and tumor size are presented as continuous variables. Relevant units are presented in parentheses.
AJCC, American Joint Committee on Cancer; BCS, breast-conserving surgery; CI, confidence interval; ref, reference; SES, socioeconomic status.
Discussion
Treatment receipt according to race/ethnicity
Our study adds to the sparse literature describing first-course treatment receipt and survival among AYAs with breast cancer. Hispanic and Black AYAs were more likely than Whites to omit radiation after BCS. Omission of radiation after BCS by Hispanics and Blacks is well documented in older women, and one study in females less than 35 years of age found lower receipt of radiation after BCS for these groups.7,13,14 Some studies have suggested that socioeconomic factors mediate these differences in breast cancer treatment by race, but our results indicate race was an independent factor.15 Treatment disparities in receipt of radiation after BCS are a concern, as omission of radiation after BCS decreases 10- and 15-year overall survival in pooled analyses.16,17 Omission of radiation by Hispanics and Blacks has been attributed to differences in insurance coverage, nativity (among Hispanics), and patient–physician interaction.18–21
Asian and Hispanic AYAs in our study were more likely than Whites to receive mastectomy. Studies involving females of all ages have also reported a greater receipt of mastectomies by Asians and Hispanics compared to Whites.22 For Asian women of all ages, the receipt of mastectomy varies by ethnic subgroup and nativity, and may be influenced by cross-cultural and language barriers.23–26 Given the lack of survival difference between BCS and mastectomy in clinical studies, the higher rates of mastectomy among some groups may indicate a treatment disparity in which these women receive more invasive surgeries for disease that could be equally controlled with BCS.27–29
Treatment receipt according to neighborhood SES and hospital NCI designation
Our results indicate that AYAs living in lower SES versus higher SES neighborhoods were more likely to omit radiation after BCS, more likely to receive mastectomy, and less likely to receive chemotherapy. Similarly, women treated at NCI-designated cancer hospitals were less likely to receive mastectomy and more likely to receive chemotherapy. Earlier studies have linked greater hospital volume or metropolitan location to BCS use in women of all ages.30,31 Likewise, while studies considering treatment according to SES are scarce, studies of Medicaid-enrolled women of all ages have shown that significant portions of these women did not receive radiation after BCS or failed to complete radiation therapy.14,32 Additionally, socioeconomic factors like rural residence, lower income, and lower educational attainment have been associated with greater mastectomy use and nonstandard or lower-dose chemotherapy regimens among women of all ages.33–35 These results underscore the need to target low-SES groups for treatment adherence and support, as these women are also more likely to be diagnosed with triple-negative breast cancer—an aggressive subtype with poor prognosis that is negative for HR and human epidermal growth factor receptor 2 (HER2) and is not currently amenable to targeted therapy.36,37 In this study, we were unable to account for breast cancer subtype in our models, as pre-2005 data on HER2 are not considered sufficiently robust.3
Changes in treatment receipt over time
Compared to BCS with radiation, we found that receipt of BCS without radiation increased steadily after 1996 and doubled by 2000. Increases in BCS without radiation have also been observed among women of all ages in recent years.38 Nevertheless, this result is surprising, since the importance of radiation after BCS is well accepted.16,17 Increasing receipt of BCS without radiation over time may be driven by concerns over long-term effects of chest irradiation in young women.39,40 On the other hand, it is also likely that radiation receipt is under-ascertained by the registry, particularly with increasing use of neoadjuvant therapies that may result in underreport of adjuvant radiation occurring later in the treatment process.41
Compared to BCS with radiation, mastectomy receipt increased in the final years of the study period. In this same period, chemotherapy receipt decreased. Two recent studies also noted increasing mastectomy rates among early-stage breast cancer diagnoses;42,43 one found this trend to be driven, in part, by women less than 50 years of age.42 Recent decreases in chemotherapy have not been reported previously. Once additional years of data are available, future analyses will determine whether these recent changes in treatment receipt constitute the beginning of a trend.
Survival according to treatment
We found a 5% improvement in survival each year of the study period. BCS with radiation was associated with better survival than other initial treatment regimens, similar to prior results in females under 35 years of age and in females under the age of 50 with early-stage disease.7,44 However, these findings contrast with large randomized trials that found equivalent survival between mastectomy and BCS with radiation in women of all ages with early-stage disease, and seem at odds with the lower local-recurrence rates in young women receiving mastectomy compared to BCS.27,45–47 It is possible that females with poorer prognoses at diagnosis may be more likely to choose mastectomy, biasing our results despite adjustment for available prognostic factors.48 The association of chemotherapy with worse outcomes may also be a result of such a bias. Some studies attempt to account for potential treatment bias with propensity analyses and instrumental variable analyses, but these methods have not been shown to reduce bias more than multivariable regression analyses.49
Survival according to race/ethnicity
Black AYAs in our study had poorer survival after adjustment for neighborhood SES and treatment receipt. This result echoes findings of a meta-analysis concluding the African American race to be associated with worse breast cancer–specific survival in women of all ages, independent of area measures of SES.50 A SEER-Medicaid analysis including women of all ages, however, did not find race/ethnicity to be significantly associated with breast cancer survival after controlling for treatment receipt.51 Compared to Whites, studies have found that Blacks diagnosed with breast cancer have a much higher proportion of triple-negative breast cancer, which may contribute to survival estimates.3,52
Compared to Whites, we found no differences in survival for Hispanic or Asian AYAs. A previous SEER study in females under 35 years of age diagnosed from 1990 to 1998, on the other hand, found marginally poorer survival for Hispanic women compared to White women in models adjusted for treatment and other prognostic indicators.7 Survival of Hispanic populations (compared to Whites) likely depends on the population being studied, as reports in women of all ages are mixed and results differ by nativity.18,53–55 In addition, foreign-born nativity is associated with poorer breast cancer survival among Asian populations, suggesting that nativity is important to consider in future AYA studies.56
Survival according to neighborhood SES and hospital NCI designation
AYAs with breast cancer who resided in low SES neighborhoods at the time of diagnosis had worse survival. This association was independent of patients' race/ethnicity and treatment receipt. Others have shown indicators of individual-level SES to be independent predictors of poor prognosis among women of all ages with breast cancer.57,58 Furthermore, we have previously shown that neighborhood SES is also associated with worse survival among Hispanic and Japanese women of all ages with breast cancer, further suggesting that SES is an independent predictor of survival.53,56 AYAs treated at NCI-designated cancer hospitals had better survival. NCI designation has been shown to associate with better postsurgical outcomes among cancer patients, but associations with long-term survival have been less clear.59–61
Study limitations
Under-ascertainment of radiation by the cancer registry is a potential limitation of this study based on a recent report,41 although an earlier report concluded that SEER and Medicare data were well correlated (94% for breast cancer) for radiation receipt in older women.62 Under-ascertainment of radiation receipt may have led to our observation that females diagnosed at AJCC stage levels II–III were more likely to omit radiation after BCS.41 A greater frequency of under-ascertainment among women with low income and under-insurance may suggest that radiation receipt is underreported for females in our study with low neighborhood SES.41 Others have also observed that patients of non-White race or low SES are more likely to delay radiation therapy, potentially causing underreport of this mode of treatment.63 As with other studies using registry data, our study is also subject to the potential misclassification of race/ethnicity. However, we have previously found the level of agreement between the CCR data and self-reported race/ethnicity to be excellent for Whites and Blacks and intermediate for Hispanics and Asians.64,65
Conclusions
Treatment receipt among AYAs with breast cancer varied by race/ethnicity, neighborhood SES, and hospital NCI designation. We found that both Hispanic and Black AYAs were less likely to receive radiation after BCS, and that Asians and Hispanics were more likely to receive mastectomy relative to Whites. AYAs living in lower SES neighborhoods were less likely to receive radiation after BCS, more likely to receive mastectomy, and less likely to receive chemotherapy. Survival improved for AYAs over the study period, but differences were found by race/ethnicity and neighborhood SES, with poorer survival for Blacks compared to Whites and for those in lower SES neighborhoods, suggesting that issues in addition to treatment and available prognostic factors contribute to these observations.
Acknowledgments
The collection of cancer incidence data used in this study was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885; the National Cancer Institute's Surveillance, Epidemiology and End Results Program under contract HHSN2612010000140C awarded to the Cancer Prevention Institute of California, contract HHSN261201000035C awarded to the University of Southern California, and contract HHSN261201000034C awarded to the Public Health Institute; and the Centers for Disease Control and Prevention's National Program of Cancer Registries, under agreement #1U58 DP000807-01 awarded to the Public Health Institute.
Disclaimer
The ideas and opinions expressed herein are those of the authors and endorsement by the State of California, Department of Health Services, the National Cancer Institute, and the Centers for Disease Control and Prevention, or their contractors and subcontractors is not intended nor should be inferred.
Author Disclosure Statement
No competing financial interests exist.
References
- 1.Gabriel CA. Domchek SM. Breast cancer in young women. Breast Cancer Res. 2010;12(5):212. doi: 10.1186/bcr2647. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Bleyer A. Barr R. Hayes-Lattin B, et al. The distinctive biology of cancer in adolescents and young adults. Nat Rev Cancer. 2008;8(4):288–98. doi: 10.1038/nrc2349. [DOI] [PubMed] [Google Scholar]
- 3.Keegan TH. Derouen MC. Press DJ, et al. Occurrence of breast cancer subtypes in adolescent and young adult women. Breast Cancer Res. 2012;14(2):R55. doi: 10.1186/bcr3156. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Bleyer WA. Cancer in older adolescents and young adults: epidemiology, diagnosis, treatment, survival, and importance of clinical trials. Med Pediatr Oncol. 2002;38(1):1–10. doi: 10.1002/mpo.1257. [DOI] [PubMed] [Google Scholar]
- 5.Gnerlich JL. Deshpande AD. Jeffe DB, et al. Elevated breast cancer mortality in women younger than age 40 years compared with older women is attributed to poorer survival in early-stage disease. J Am Coll Surg. 2009;208(3):341–7. doi: 10.1016/j.jamcollsurg.2008.12.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Schmidt C. Lack of progress in teen and young adult cancers concerns researchers, prompts study. J Natl Cancer Inst. 2006;98(24):1760–3. doi: 10.1093/jnci/djj517. [DOI] [PubMed] [Google Scholar]
- 7.Shavers VL. Harlan LC. Stevens JL. Racial/ethnic variation in clinical presentation, treatment, and survival among breast cancer patients under age 35. Cancer. 2003;97(1):134–47. doi: 10.1002/cncr.11051. [DOI] [PubMed] [Google Scholar]
- 8.Cancer reporting in California: abstracting and coding procedures for hospitals. 8th. Vol. 1. Sacramento: California Cancer Registry, Data Standards and Quality Control Unit; 2008. California Cancer Reporting System Standards. [Google Scholar]
- 9.Bauer KR. Brown M. Cress RD, et al. Descriptive analysis of estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative invasive breast cancer, the so-called triple-negative phenotype: a population-based study from the California Cancer Registry. Cancer. 2007;109(9):1721–8. doi: 10.1002/cncr.22618. [DOI] [PubMed] [Google Scholar]
- 10.Keegan TH. Chang ET. John EM, et al. Recent changes in breast cancer incidence and risk factor prevalence in San Francisco Bay area and California women: 1988 to 2004. Breast Cancer Res. 2007;9(5):R62. doi: 10.1186/bcr1768. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Li CI. Daling JR. Malone KE. Incidence of invasive breast cancer by hormone receptor status from 1992 to 1998. J Clin Oncol. 2003;21(1):28–34. doi: 10.1200/JCO.2003.03.088. [DOI] [PubMed] [Google Scholar]
- 12.Yost K. Perkins C. Cohen R, et al. Socioeconomic status and breast cancer incidence in California for different race/ethnic groups. Cancer Causes Control. 2001;12(8):703–11. doi: 10.1023/a:1011240019516. [DOI] [PubMed] [Google Scholar]
- 13.Freedman RA. He Y. Winer EP. Keating NL. Trends in racial and age disparities in definitive local therapy of early-stage breast cancer. J Clin Oncol. 2009;27(5):713–9. doi: 10.1200/JCO.2008.17.9234. [DOI] [PubMed] [Google Scholar]
- 14.Anderson RT. Kimmick GG. Camacho F, et al. Health system correlates of receipt of radiation therapy after breast-conserving surgery: a study of low-income Medicaid-enrolled women. Am J Manag Care. 2008;14(10):644–52. [PubMed] [Google Scholar]
- 15.Berz JP. Johnston K. Backus B, et al. The influence of black race on treatment and mortality for early-stage breast cancer. Med Care. 2009;47(9):986–92. doi: 10.1097/MLR.0b013e31819e1f2b. [DOI] [PubMed] [Google Scholar]
- 16.Vinh-Hung V. Verschraegen C. Breast-conserving surgery with or without radiotherapy: pooled-analysis for risks of ipsilateral breast tumor recurrence and mortality. J Natl Cancer Inst. 2004;96(2):115–21. doi: 10.1093/jnci/djh013. [DOI] [PubMed] [Google Scholar]
- 17.Clarke M. Collins R. Darby S, et al. Effects of radiotherapy and of differences in the extent of surgery for early breast cancer on local recurrence and 15-year survival: an overview of the randomised trials. Lancet. 2005;366(9503):2087–106. doi: 10.1016/S0140-6736(05)67887-7. [DOI] [PubMed] [Google Scholar]
- 18.Kouri EM. He Y. Winer EP. Keating NL. Influence of birthplace on breast cancer diagnosis and treatment for Hispanic women. Breast Cancer Res Treat. 2010;121(3):743–51. doi: 10.1007/s10549-009-0643-3. [DOI] [PubMed] [Google Scholar]
- 19.Roetzheim RG. Gonzalez EC. Ferrante JM, et al. Effects of health insurance and race on breast carcinoma treatments and outcomes. Cancer. 2000;89(11):2202–13. doi: 10.1002/1097-0142(20001201)89:11<2202::aid-cncr8>3.0.co;2-l. [DOI] [PubMed] [Google Scholar]
- 20.Sharma C. Harris L. Haffty BG, et al. Does compliance with radiation therapy differ in African-American patients with early-stage breast cancer? Breast J. 2010;16(2):193–6. doi: 10.1111/j.1524-4741.2009.00874.x. [DOI] [PubMed] [Google Scholar]
- 21.Kaplan CP. Napoles AM. Hwang ES, et al. Selection of treatment among Latina and non-Latina white women with ductal carcinoma in situ. J Womens Health (Larchmt). 2011;20(2):215–23. doi: 10.1089/jwh.2010.1986. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Morris CR. Cohen R. Schlag R. Wright WE. Increasing trends in the use of breast-conserving surgery in California. Am J Public Health. 2000;90(2):281–4. doi: 10.2105/ajph.90.2.281. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Lin Gomez S. Press DJ. Lichtensztajn D, et al. Patient, hospital, and neighborhood factors associated with treatment of early-stage breast cancer among Asian American women in California. Cancer Epidemiol Biomarkers Prev. 2012;21(5):821–34. doi: 10.1158/1055-9965.EPI-11-1143. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Prehn AW. Topol B. Stewart S, et al. Differences in treatment patterns for localized breast carcinoma among Asian/Pacific Islander women. Cancer. 2002;95(11):2268–75. doi: 10.1002/cncr.10965. [DOI] [PubMed] [Google Scholar]
- 25.Kagawa-Singer M. Wellisch DK. Durvasula R. Impact of breast cancer on Asian American and Anglo American women. Cult Med Psychiatry. 1997;21(4):449–80. doi: 10.1023/a:1005314602587. [DOI] [PubMed] [Google Scholar]
- 26.Killoran M. Moyer A. Surgical treatment preferences in Chinese-American women with early-stage breast cancer. Psychooncology. 2006;15(11):969–84. doi: 10.1002/pon.1032. [DOI] [PubMed] [Google Scholar]
- 27.Litiere S. Werutsky G. Fentiman IS, et al. Breast conserving therapy versus mastectomy for stage I-II breast cancer: 20 year follow-up of the EORTC 10801 phase 3 randomised trial. Lancet Oncol. 2012;13(4):412–9. doi: 10.1016/S1470-2045(12)70042-6. [DOI] [PubMed] [Google Scholar]
- 28.Lichter AS. Lippman ME. Danforth DN, Jr., et al. Mastectomy versus breast-conserving therapy in the treatment of stage I and II carcinoma of the breast: a randomized trial at the National Cancer Institute. J Clin Oncol. 1992;10(6):976–83. doi: 10.1200/JCO.1992.10.6.976. [DOI] [PubMed] [Google Scholar]
- 29.Komaki R. Cox JD. Kister SJ, et al. Stage I and II breast carcinoma: treatment with limited surgery and radiation therapy versus mastectomy. Radiology. 1990;174(1):255–7. doi: 10.1148/radiology.174.1.2104676. [DOI] [PubMed] [Google Scholar]
- 30.Nattinger AB. Gottlieb MS. Veum J, et al. Geographic variation in the use of breast-conserving treatment for breast cancer. N Engl J Med. 1992;326(17):1102–7. doi: 10.1056/NEJM199204233261702. [DOI] [PubMed] [Google Scholar]
- 31.Kotwall CA. Covington DL. Rutledge R, et al. Patient, hospital, and surgeon factors associated with breast conservation surgery. A statewide analysis in North Carolina. Ann Surg. 1996;224(4):419–26. doi: 10.1097/00000658-199610000-00001. ; discussion 26–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Ramsey SD. Zeliadt SB. Richardson LC, et al. Discontinuation of radiation treatment among medicaid-enrolled women with local and regional stage breast cancer. Breast J. 2010;16(1):20–7. doi: 10.1111/j.1524-4741.2009.00865.x. [DOI] [PubMed] [Google Scholar]
- 33.Michalski TA. Nattinger AB. The influence of black race and socioeconomic status on the use of breast-conserving surgery for Medicare beneficiaries. Cancer. 1997;79(2):314–9. [PubMed] [Google Scholar]
- 34.Griggs JJ. Culakova E. Sorbero ME, et al. Effect of patient socioeconomic status and body mass index on the quality of breast cancer adjuvant chemotherapy. J Clin Oncol. 2007;25(3):277–84. doi: 10.1200/JCO.2006.08.3063. [DOI] [PubMed] [Google Scholar]
- 35.Albain KS. Green SR. Lichter AS, et al. Influence of patient characteristics, socioeconomic factors, geography, and systemic risk on the use of breast-sparing treatment in women enrolled in adjuvant breast cancer studies: an analysis of two intergroup trials. J Clin Oncol. 1996;14(11):3009–17. doi: 10.1200/JCO.1996.14.11.3009. [DOI] [PubMed] [Google Scholar]
- 36.Ihemelandu CU. Leffall LD., Jr. Dewitty RL, et al. Molecular breast cancer subtypes in premenopausal African-American women, tumor biologic factors and clinical outcome. Ann Surg Oncol. 2007;14(10):2994–3003. doi: 10.1245/s10434-007-9477-6. [DOI] [PubMed] [Google Scholar]
- 37.Vona-Davis L. Rose DP. The influence of socioeconomic disparities on breast cancer tumor biology and prognosis: a review. J Womens Health (Larchmt). 2009;18(6):883–93. doi: 10.1089/jwh.2008.1127. [DOI] [PubMed] [Google Scholar]
- 38.Tuttle TM. Jarosek S. Habermann EB, et al. Omission of radiation therapy after breast-conserving surgery in the United States: a population-based analysis of clinicopathologic factors. Cancer. 2012;118(8):2004–13. doi: 10.1002/cncr.26505. [DOI] [PubMed] [Google Scholar]
- 39.Fowble B. Hanlon A. Freedman G, et al. Second cancers after conservative surgery and radiation for stages I-II breast cancer: identifying a subset of women at increased risk. Int J Radiat Oncol Biol Phys. 2001;51(3):679–90. doi: 10.1016/s0360-3016(01)01665-0. [DOI] [PubMed] [Google Scholar]
- 40.Lundstedt D. Gustafsson M. Steineck G, et al. Long-term symptoms after radiotherapy of supraclavicular lymph nodes in breast cancer patients. Radiother Oncol. 2012;103(2):155–60. doi: 10.1016/j.radonc.2011.12.017. [DOI] [PubMed] [Google Scholar]
- 41.Jagsi R. Abrahamse P. Hawley ST, et al. Underascertainment of radiotherapy receipt in Surveillance, Epidemiology, and End Results registry data. Cancer. 2012;118(2):333–41. doi: 10.1002/cncr.26295. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Gomez SL. Lichtensztajn D. Kurian AW, et al. Increasing mastectomy rates for early-stage breast cancer? Population-based trends from California. J Clin Oncol. 2010;28(10):e155–7. doi: 10.1200/JCO.2009.26.1032. ; author reply e8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Katipamula R. Degnim AC. Hoskin T, et al. Trends in mastectomy rates at the Mayo Clinic Rochester: effect of surgical year and preoperative magnetic resonance imaging. J Clin Oncol. 2009;27(25):4082–8. doi: 10.1200/JCO.2008.19.4225. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Hwang ES. Lichtensztajn D. Gomez S, et al. Survival after lumpectomy and mastectomy for early stage invasive breast cancer: the effect of age and hormone receptor status. Cancer. 2013;119(7):1402–11. doi: 10.1002/cncr.27795. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Borger J. Kemperman H. Hart A, et al. Risk factors in breast-conservation therapy. J Clin Oncol. 1994;12(4):653–60. doi: 10.1200/JCO.1994.12.4.653. [DOI] [PubMed] [Google Scholar]
- 46.Kurtz JM. Jacquemier J. Amalric R, et al. Why are local recurrences after breast-conserving therapy more frequent in younger patients? J Clin Oncol. 1990;8(4):591–8. doi: 10.1200/JCO.1990.8.4.591. [DOI] [PubMed] [Google Scholar]
- 47.Bollet MA. Sigal-Zafrani B. Mazeau V, et al. Age remains the first prognostic factor for loco-regional breast cancer recurrence in young (<40 years) women treated with breast conserving surgery first. Radiother Oncol. 2007;82(3):272–80. doi: 10.1016/j.radonc.2007.01.001. [DOI] [PubMed] [Google Scholar]
- 48.Giordano SH. Kuo YF. Duan Z, et al. Limits of observational data in determining outcomes from cancer therapy. Cancer. 2008;112(11):2456–66. doi: 10.1002/cncr.23452. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Bosco JL. Silliman RA. Thwin SS, et al. A most stubborn bias: no adjustment method fully resolves confounding by indication in observational studies. J Clin Epidemiol. 2010;63(1):64–74. doi: 10.1016/j.jclinepi.2009.03.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Newman LA. Griffith KA. Jatoi I, et al. Meta-analysis of survival in African American and white American patients with breast cancer: ethnicity compared with socioeconomic status. J Clin Oncol. 2006;24(9):1342–9. doi: 10.1200/JCO.2005.03.3472. [DOI] [PubMed] [Google Scholar]
- 51.Bradley CJ. Given CW. Roberts C. Race, socioeconomic status, and breast cancer treatment and survival. J Natl Cancer Inst. 2002;94(7):490–6. doi: 10.1093/jnci/94.7.490. [DOI] [PubMed] [Google Scholar]
- 52.Carey LA. Perou CM. Livasy CA, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. J Am Med Assoc. 2006;295(21):2492–502. doi: 10.1001/jama.295.21.2492. [DOI] [PubMed] [Google Scholar]
- 53.Keegan TH. Quach T. Shema S, et al. The influence of nativity and neighborhoods on breast cancer stage at diagnosis and survival among California Hispanic women. BMC Cancer. 2010;10:603. doi: 10.1186/1471-2407-10-603. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Curtis E. Quale C. Haggstrom D. Smith-Bindman R. Racial and ethnic differences in breast cancer survival: how much is explained by screening, tumor severity, biology, treatment, comorbidities, and demographics? Cancer. 2008;112(1):171–80. doi: 10.1002/cncr.23131. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Boyer-Chammard A. Taylor TH. Anton-Culver H. Survival differences in breast cancer among racial/ethnic groups: a population-based study. Cancer Detect Prev. 1999;23(6):463–73. doi: 10.1046/j.1525-1500.1999.99049.x. [DOI] [PubMed] [Google Scholar]
- 56.Gomez SL. Clarke CA. Shema SJ, et al. Disparities in breast cancer survival among Asian women by ethnicity and immigrant status: a population-based study. Am J Public Health. 2010;100(5):861–9. doi: 10.2105/AJPH.2009.176651. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.O'Malley CD. Le GM. Glaser SL, et al. Socioeconomic status and breast carcinoma survival in four racial/ethnic groups: a population-based study. Cancer. 2003;97(5):1303–11. doi: 10.1002/cncr.11160. [DOI] [PubMed] [Google Scholar]
- 58.Gordon NH. Crowe JP. Brumberg DJ. Berger NA. Socioeconomic factors and race in breast cancer recurrence and survival. Am J Epidemiol. 1992;135(6):609–18. doi: 10.1093/oxfordjournals.aje.a116340. [DOI] [PubMed] [Google Scholar]
- 59.Paulson EC. Mitra N. Sonnad S, et al. National Cancer Institute designation predicts improved outcomes in colorectal cancer surgery. Ann Surg. 2008;248(4):675–86. doi: 10.1097/SLA.0b013e318187a757. [DOI] [PubMed] [Google Scholar]
- 60.Hillner BE. Smith TJ. Desch CE. Hospital and physician volume or specialization and outcomes in cancer treatment: importance in quality of cancer care. J Clin Oncol. 2000;18(11):2327–40. doi: 10.1200/JCO.2000.18.11.2327. [DOI] [PubMed] [Google Scholar]
- 61.Birkmeyer NJ. Goodney PP. Stukel TA, et al. Do cancer centers designated by the National Cancer Institute have better surgical outcomes? Cancer. 2005;103(3):435–41. doi: 10.1002/cncr.20785. [DOI] [PubMed] [Google Scholar]
- 62.Virnig BA. Warren JL. Cooper GS, et al. Studying radiation therapy using SEER-Medicare-linked data. Med Care. 2002;40(8 Suppl):IV-49–54. doi: 10.1097/00005650-200208001-00007. [DOI] [PubMed] [Google Scholar]
- 63.Gold HT. Thwin SS. Buist DS, et al. Delayed radiotherapy for breast cancer patients in integrated delivery systems. Am J Manag Care. 2009;15(11):785–9. [PMC free article] [PubMed] [Google Scholar]
- 64.Clegg LX. Reichman ME. Hankey BF, et al. Quality of race, Hispanic ethnicity, and immigrant status in population-based cancer registry data: implications for health disparity studies. Cancer Causes Control. 2007;18(2):177–87. doi: 10.1007/s10552-006-0089-4. [DOI] [PubMed] [Google Scholar]
- 65.Gomez SL. Glaser SL. Misclassification of race/ethnicity in a population-based cancer registry (United States) Cancer Causes Control. 2006;17(6):771–81. doi: 10.1007/s10552-006-0013-y. [DOI] [PubMed] [Google Scholar]