Background
The Oncotype 21-gene breast recurrence score (RS) is the most commonly ordered multigene breast cancer biomarker in the United States,1 and the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Breast Cancer base its recommendations on the RS for patients with estrogen receptor (ER)–positive, HER2-negative tumors (henceforth referred to as ER-positive) that do not have axillary lymph node metastases.2 The 21-gene RS was developed as a predictive biomarker because it is intended to provide information on which patients are (or are not) likely to derive benefit from adjuvant chemotherapy.3,4 An important step in evaluating a cancer biomarker is to determine the clinical validity of the test, which is its ability to predict the clinically defined condition of interest.5 The 21-gene RS is considered clinically validated as a predictive biomarker if it identifies a group of patients with ER-positive breast cancer who do not benefit from adjuvant chemotherapy and another group who do.6–10
Differences in the underlying hazard rate of breast cancer death among patients with breast cancer according to race/ethnicity11 could influence the performance of the 21-gene RS in diverse populations, which may ultimately impact the clinical validity of the RS for racial and ethnic minority women. This concern prompted us to examine the prognostic accuracy of the RS12 using the SEER Oncotype DX database.13,14 We found that the RS has lower discriminatory accuracy for determining breast cancer–specific mortality in non-Hispanic Black (NHB) compared with non-Hispanic White (NHW) women with ER-positive, axillary node–negative tumors. This raises an important question regarding whether the 21-gene RS has been adequately validated as a predictive biomarker in racial and ethnic minority patients. Fewer than 10% of participants in the validation studies of the RS were NHB,4,15,16 underscoring this concern. A predictive biomarker that performs poorly in NHB women could perpetuate racial disparities in ER-positive breast cancer survival17 by misguiding treatment recommendations. This study examined the clinical validity of the RS as a predictive biomarker among racially and ethnically diverse women with ER-positive, axillary node–negative breast cancer. We conceptualized race and ethnicity as a social construct for this study.18,19
Methods
Study Design and Population
This population-based retrospective cohort study used the SEER Oncotype DX database13,14 to obtain variables generated from the 21-gene breast RS assay from Genomic Health linked to invasive breast cancer cases in the SEER registry diagnosed in 2004 through 2015, with follow-up for survival through 2016.
Women aged ≥18 years diagnosed from 2004 to 2015 with a first primary breast cancer that was classified as stage I–II, axillary node–negative, and ER-positive based on AJCC 6th edition staging criteria were included. Information on HER2 status was only available for cases diagnosed in 2010 and later (69% of the analytic cohort). We excluded women diagnosed in 2010 through 2015 with tumors that were HER2-positive/borderline. Race/Ethnicity was categorized per SEER recoding of race and Hispanic ethnicity as NHW, NHB, non-Hispanic American Indian/Alaska Native (AI/AN), non-Hispanic Asian/Pacific Islander (API), and Hispanic (any race). Vital status and cause of death were determined from cancer registry follow-up information. RS variables included the continuous measure (0–100 scale) categorized according to current NCCN Guidelines for Breast Cancer2: low risk, RS 0–10; intermediate risk, RS 11–25; and high risk, RS 26–100.7–9 Information on age at diagnosis (<50, 50–64, 65–74, ≥75 years), year of diagnosis (2004–2009, 2010–2015), tumor size (≤2.0, 2.1–5.0, >5.0 cm), tumor grade (I, II, III, IV, unknown), progesterone receptor status (positive/borderline, negative, unknown), receipt of surgery (yes, no), receipt of radiation (yes, no/unknown), and receipt of chemotherapy (yes, no/unknown) as part of the first course of therapy was collected from SEER. Insurance information was only collected after 2007 and categorized as uninsured, Medicaid, insured, insured–not specified (includes Medicare), and unknown. Patients with no information on RS, longitudinal follow-up for survival, or vital status were excluded from the analysis.
The outcome of interest was death due to breast cancer identified using ICD codes, autopsy, or death certification. Cause of death was determined based on SEER registry records. Women were followed from the month of breast cancer diagnosis until death or the end of the study period.
Statistical Analyses
Demographic and clinical characteristics were compared using descriptive statistics. Categorical and continuous variables were compared using Chi-square and Wilcoxon signed rank tests, respectively. Unadjusted Nelson-Aalen cumulative hazard plots for breast cancer death according to racial and ethnic group were compared with log-rank tests. Univariate propensity score–weighted Cox regression20 was conducted to determine the association between chemotherapy use and breast cancer death. Propensity score approaches have advantages over traditional multivariable regression modeling for dealing with confounding in observational studies when the outcome is rare and the treatment is common in the available data,21 as with this dataset. The propensity score was derived using a logistic regression model, with chemotherapy treatment as the dependent variable conditioned on age at diagnosis, insurance status, tumor size, tumor grade, progesterone receptor status, and RS. Inverse probability of treatment weighting20 was performed for women who received chemotherapy by assigning a weight that equals the reciprocal of their propensity score and by assigning a weight of 1/(1 − propensity score) for women who did not receive chemotherapy. To reduce instability in the weights, we collapsed values above the 99th percentile of the distribution to equal the value at the 99th percentile.22 Associations between chemotherapy treatment and breast cancer death were determined using overall, race/ethnicity, age stratum–specific, and RS stratum–specific hazard ratios (HRs) and 95% confidence intervals. The RS was considered clinically validated as a predictive biomarker for a racial/ethnic group if chemotherapy use was associated with a significantly lower hazard of breast cancer death for women with a high-risk RS but not for those with an intermediate-risk RS.5,6,8–10
An exploratory subgroup analysis restricted to women aged ≤50 years with an RS of 11–25 and at least 7 years of follow-up plotted the propensity score–weighted, 7-year breast cancer death rate as a best-fitted linear function of the RS, stratified by race/ethnicity and chemotherapy status. Formal hypothesis testing was not performed for this exploratory analysis. Out of concern for underascertainment of chemotherapy initiation in SEER data,23,24 we conducted sensitivity analyses using standard methods25 with each racial/ethnic group for patients with a high-risk RS. We varied the chemotherapy misclassification rate within a range of plausible misclassification rates23,24 for decedents and survivors and calculated “corrected” relative risks of breast cancer death with chemotherapy use for each scenario after correcting for the specified misclassification rate for this variable.
All relevant tests were 2-sided, and associations were considered statistically significant with α≤.05. All analyses were performed in SAS 9.4 (SAS Institute Inc.). The study was approved by the Institutional Review Board at University of Illinois at Chicago (IRB Protocol #2019-0170). The analysis was conducted between March 4, 2021, and August 15, 2022.
Results
A total of 73,363 women with a median age of 58 years (IQR, 50–65 years) were included in the analysis (supplemental eFigure 1, available with this article at JNCCN.org), including 6,033 (8.2%) API, 5,697 (7.8%) NHB, 6,688 (9.1%) Hispanic, and 54,945 (74.9%) NHW. AI/AN (n=295) and unknown race (n=344) women were excluded from the analysis due to the small numbers in those groups. Characteristics of the analytic cohort are shown in Table 1. Adjuvant chemotherapy use was significantly higher in NHB women (22.45%) compared with API (20.87%), Hispanic (20.31%), and NHW (19.13%) women (P<.0001). With a median follow-up of 56 months (IQR, 31–86 months), unadjusted Nelson-Aelen plots of the cumulative incidence of breast cancer death according to race and ethnicity (supplemental eFigure 2) showed that NHB women had a higher likelihood of breast cancer death compared with other women overall and when stratified by the age categories of ≤50 and ≥51 years (P<.001 for all comparisons). Propensity score–adjusted breast cancer mortality was higher for NHB women compared with NHW women overall (HR, 1.56; 95% CI, 1.29–1.89) and within each RS risk category (Table 2).
Demographic and Clinical Characteristics of Study Cohort (N=73,658)
Racial and Ethnic Differences in Death From ER-Positive, Axillary Node–Negative Breast Cancer
Reduction in Breast Cancer–Specific Death With Chemotherapy
Table 3 shows the reduction in breast cancer–specific death associated with chemotherapy for women from each racial/ethnic group according to age and RS risk categories. The total number of deaths are included in supplemental eTable 1. Analyses stratified by RS category showed no reduction in breast cancer death for women with an intermediate-risk RS overall or for any racial/ethnic group. Chemotherapy was associated with a significant reduction in breast cancer death among women with a high-risk RS for all groups except for API women (API: HR, 0.59 [95% CI, 0.28–1.24]; NHB: HR, 0.48 [95% CI, 0.28–0.81]; Hispanic: HR, 0.48 [95% CI, 0.25–0.94]; and NHW: HR, 0.80 [95% CI, 0.65–0.99]). A sensitivity analysis that included only women diagnosed in 2010 through 2015 whose tumors were HER2-negative was consistent in direction and effect size compared with the primary analysis (supplemental eTable 2).
Reduction in Breast Cancer Death With Chemotherapy According to Age and RS Categories
Age-Stratified Analyses
For women aged ≤50 years, there was a numerically larger reduction in breast cancer death with chemotherapy for NHB (HR, 0.37; 95% CI, 0.20–0.67) and Hispanic (HR, 0.27; 95% CI, 0.12–0.59) women compared with NHW (HR, 0.56; 95% CI, 0.44–0.74) women (Table 3). An interaction term for chemotherapy * race in a model combining NHB and NHW women was significant (P<.049), but the interaction term for chemotherapy * ethnicity in a separate model was not significant (P=.109). When further stratified by RS category (Table 4), the reduction in breast cancer death with chemotherapy was significant for the RS 26–100 category for all women combined, but not for any racial/ethnic group due to small numbers of events and wide confidence intervals. For women aged ≥51 years (Table 5), chemotherapy was associated with a significant reduction in breast cancer death only among NHB women with an RS of 26–100 (HR, 0.49; 95% CI, 0.25–0.95). An interaction term for chemotherapy * race in a model combining NHB and NHW women aged >50 years with an RS of 26–100 was not significant (P=.138).
Reduction in Breast Cancer Death With Chemotherapy for Women Aged ≤50 Years According to RS Category
Reduction in Breast Cancer Death With Chemotherapy for Women Aged ≥51 Years According to RS Category
We conducted an exploratory subgroup analysis of women aged ≤50 years with an RS of 11–25 and at least 7 years of follow-up to examine whether RS cutoffs for recommending chemotherapy should be adjusted in young women based on race/ethnicity. Trendlines for the propensity score–weighted, 7-year breast cancer death rate plotted as a function of the continuous RS for women treated with and without chemotherapy diverge at a lower RS for NHB (Figure 1B) compared with NHW patients (Figure 1D), suggesting that young NHB women may benefit from chemotherapy at a lower RS cutoff. Figure 2 presents the same modeled data displayed according to treatment group. The number of events is small within each racial/ethnic minority group (supplemental eTable 3), and these findings should be considered exploratory.
Sensitivity Analysis of Chemotherapy Misclassification
A sensitivity analysis was conducted with the unadjusted relative risks for breast cancer death according to chemotherapy status for women with an RS of 26–100 to determine the effect of misclassification of the chemotherapy variable (supplemental eFigure 3). This indicates that the adjusted HRs for chemotherapy receipt reported in the main analyses are conservative estimates (ie, the HRs are most likely biased toward the null as a result of misclassification of chemotherapy status in SEER).23,24
Discussion
This study of ER-positive, axillary node–negative breast cancer validated the 21-gene RS as a predictive biomarker for NHB, Hispanic, and NHW women but not for API women. This is the first study we are aware of to validate a genomic predictive biomarker specifically for racial/ethnic minority women with breast cancer. Notably, we found significant racial differences in the association between chemotherapy treatment and breast cancer death; NHB women aged ≤50 years had a greater reduction in breast cancer death with chemotherapy compared with their NHW counterparts. An exploratory subgroup analysis among women aged ≤50 years suggested that there may be a reduction in breast cancer death with chemotherapy at a lower RS cutoff for NHB compared with NHW women. This finding is exploratory and needs to be confirmed in an adequately powered prospective study. If replicated, it would indicate that the RS threshold for recommending adjuvant chemotherapy may need to be lower for young NHB women than for women from other racial/ethnic groups in future practice guidelines.
Our results are broadly consistent with the main findings of the TAILORx randomized trial.8 A secondary analysis of that trial examined outcomes according to race and ethnicity for women with an intermediate-risk RS (11–25) and also found no improvement in survival with chemotherapy for any racial/ethnic group.16 Current NCCN Guideline recommendations offer chemotherapy as an option for premenopausal women with a risk RS ≥16 due to a lower rate of distant recurrence with chemotherapy for that subgroup in TAILORx.2,8 However, the TAILORx investigators did not report results according to race for women aged ≤50 years with an intermediate-risk RS, presumably due to the small sample size of young NHB women in that risk category (471 NHB women of all ages in the RS 11–25 category). We found a nonsignificant numeric reduction in breast cancer death with chemotherapy for NHB women aged ≤50 years with an RS of 16–25 (HR, 0.43; 95% CI, 0.11–1.64) but no apparent benefit for NHW women (HR, 0.92; 95% CI, 0.58–1.47). Despite a 7-fold larger sample size of NHB women with an intermediate-risk RS in our study compared with TAILORx16 (3,498 vs 471), the number of events was still small among young NHB women, and confidence intervals are wide, so we cannot draw any firm conclusions regarding racial differences in treatment effect for young women with an RS of 16–25.
Strength of this study are the large number of women from racial and ethnic minority groups, the availability of data on breast cancer–specific death, the use of propensity score weighting to reduce confounding, and a population-based sample. However, this study has limitations. We were unable to determine whether differences in the use of adjuvant endocrine therapy across different racial and ethnic groups influenced the results, because the SEER registry does not include data on the use of adjuvant endocrine therapy. However, TAILORx and a cooperative group trial reported that racial differences in the use of endocrine therapy do not explain the survival disparity among NHB women with ER-positive breast cancer.16,26 A limitation of every observational study is the possibility that variables other than the predictor variable affect outcome and are unevenly distributed, leading to confounding.27 Propensity score weighting adjusts for confounding due to measured variables,20,27 but there is no analytic technique to adjust for confounding due to unmeasured variables.27 Only an adequately powered randomized trial can definitively determine the effect of chemotherapy on breast cancer survival.28 Chemotherapy data are incomplete in SEER.23,24 Our sensitivity analysis indicated that any bias introduced by misclassification of chemotherapy status would likely skew the results toward the null and should therefore not change the main findings. However, this is an important limitation of the analysis, and comparisons between different racial and ethnic group must be interpreted with caution. Confirmation is needed using datasets with more complete data on chemotherapy administration. HER2 status is unknown for patients included in SEER prior to 2010. The Oncotype test is not indicated for patients with HER2-positive tumors, so the rate of contamination of the analytic cohort by HER2-positive tumors is expected to be extremely low. Based on the number of HER2-positive/borderline tumors among ER-positive patients with an Oncotype score available in SEER diagnosed in 2010 through 2015 (excluded from this analysis), we estimate that only 1.2% of the entire analytic cohort had HER2-positive tumors, which is highly unlikely to introduce any meaningful bias. Finally, a median follow-up time of 56 months is relatively short for a study of ER-positive breast cancer. Unfortunately, SEER has not updated the survival data for this specialty database.14
Conclusions
This population-based study clinically validated the RS as a predictive biomarker for NHB, Hispanic, and NHW women with ER-positive, axillary node–negative breast cancer, but it also raises the possibility that the RS may underestimate the benefit of chemotherapy for NHB women. If confirmed, the RS cutoff for recommending adjuvant chemotherapy for young NHB women with ER-positive, axillary node–negative breast cancer may need to be lower than for other women. This study also underscores the need to account for the racial and ethnic diversity of the target population in the development and validation of cancer biomarkers.
References
- 1.↑
Ibraheem A, Olopade OI, Huo D. Propensity score analysis of the prognostic value of genomic assays for breast cancer in diverse populations using the National Cancer Data Base. Cancer 2020;126:4013–4022.
- 2.↑
Gradishar WJ, Moran MS, Abraham J, et al. NCCN Clinical Practice Guidelines in Oncology: Breast Cancer. Version 4.2023. Accessed April 10, 2023. To view the most recent version, visit https://www.nccn.org
- 3.↑
Hayes DF, Bast RC, Desch CE, et al. Tumor marker utility grading system: a framework to evaluate clinical utility of tumor markers. J Natl Cancer Inst 1996;88:1456–1466.
- 4.↑
Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004;351:2817–2826.
- 5.↑
Teutsch SM, Bradley LA, Palomaki GE, et al. The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) initiative: methods of the EGAPP Working Group. Genet Med 2009;11:3–14.
- 6.↑
Simon R. Roadmap for developing and validating therapeutically relevant genomic classifiers. J Clin Oncol 2005;23:7332–7341.
- 7.↑
Sparano JA, Gray RJ, Makower DF, et al. Prospective validation of a 21-gene expression assay in breast cancer. N Engl J Med 2015;373:2005–2014.
- 8.↑
Sparano JA, Gray RJ, Makower DF, et al. Adjuvant chemotherapy guided by a 21-gene expression assay in breast cancer. N Engl J Med 2018;379:111–121.
- 9.↑
Sparano JA, Gray RJ, Makower DF, et al. Clinical outcomes in early breast cancer with a high 21-gene recurrence score of 26 to 100 assigned to adjuvant chemotherapy plus endocrine therapy: a secondary analysis of the TAILORx randomized clinical trial. JAMA Oncol 2020;6:367–374.
- 10.↑
Kalinsky K, Barlow WE, Gralow JR, et al. 21-gene assay to inform chemotherapy benefit in node-positive breast cancer. N Engl J Med 2021;385:2336–2347.
- 11.↑
Menashe I, Anderson WF, Jatoi I, et al. Underlying causes of the black-white racial disparity in breast cancer mortality: a population-based analysis. J Natl Cancer Inst 2009;101:993–1000.
- 12.↑
Hoskins KF, Danciu OC, Ko NY, et al. Association of race/ethnicity and the 21-gene assay recurrence score with breast cancer-specific mortality among us women. JAMA Oncol 2021;7:370–378.
- 13.↑
Petkov VI, Miller DP, Howlader N, et al. Breast-cancer-specific mortality in patients treated based on the 21-gene assay: a SEER population-based study. NPJ Breast Cancer 2016;2:16017.
- 14.↑
Surveillance, Epidemiology, and End Results (SEER) Program. SEER*Stat Database: Incidence - SEER 18 Regs (Excl AK) Custom Data Malignant Breast (with Oncotype DX and Additional Treatment Fields), Nov 2018 Sub (2004–2015) - Linked To County Attributes - Total U.S., 1969–2017 Counties, released April 2019, based on the November 2018 submission. Accessed April 10, 2023. Available at: https://seer.cancer.gov/data-software/documentation/seerstat/previous-submissions.html
- 15.↑
Fisher B, Dignam J, Wolmark N, et al. Tamoxifen and chemotherapy for lymph node-negative, estrogen receptor-positive breast cancer. J Natl Cancer Inst 1997;89:1673–1682.
- 16.↑
Albain KS, Gray RJ, Makower DF, et al. Race, ethnicity, and clinical outcomes in hormone receptor-positive, HER2-negative, node-negative breast cancer in the randomized TAILORx trial. J Natl Cancer Inst 2021;113:390–399.
- 17.↑
American Cancer Society. Breast cancer: facts & figures 2019-2020. Accessed April 10, 2023. Available at: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/breast-cancer-facts-and-figures/breast-cancer-facts-and-figures-2019-2020.pdf
- 18.↑
Witzig R. The medicalization of race: scientific legitimization of a flawed social construct. Ann Intern Med 1996;125:675–679.
- 19.↑
Borrell LN, Elhawary JR, Fuentes-Afflick E, et al. Race and genetic ancestry in medicine – a time for reckoning with racism. N Engl J Med 2021;384:474–480.
- 21.↑
Braitman LE, Rosenbaum PR. Rare outcomes, common treatments: analytic strategies using propensity scores. Ann Intern Med 2002;137:693–695.
- 22.↑
Cole SR, Hernán MA. Constructing inverse probability weights for marginal structural models. Am J Epidemiol 2008;168:656–664.
- 23.↑
Noone AM, Lund JL, Mariotto A, et al. Comparison of SEER treatment data with Medicare claims. Med Care 2016;54:e55–64.
- 24.↑
Du XL, Key CR, Dickie L, et al. Information on chemotherapy and hormone therapy from tumor registry had moderate agreement with chart reviews. J Clin Epidemiol 2006;59:53–60.
- 25.↑
Greenland S. Basic methods for sensitivity analysis of biases. Int J Epidemiol 1996;25:1107–1116.
- 26.↑
Sparano JA, Wang M, Zhao F, et al. Race and hormone receptor-positive breast cancer outcomes in a randomized chemotherapy trial. J Natl Cancer Inst 2012;104:406–414.
- 27.↑
Desai RJ, Franklin JM. Alternative approaches for confounding adjustment in observational studies using weighting based on the propensity score: a primer for practitioners. BMJ 2019;367:l5657.
- 28.↑
Kumar A, Guss ZD, Courtney PT, et al. Evaluation of the use of cancer registry data for comparative effectiveness research. JAMA Netw Open 2020;3:e2011985.