Literature DB >> 29255374

Impact of patient demographics, tumor characteristics, and treatment type on treatment delay throughout breast cancer care at a diverse academic medical center.

Shivani Khanna1, Kristine N Kim1, Muhammad M Qureshi1, Ankit Agarwal1, Divya Parikh1, Naomi Y Ko2, Alexander E Rand1, Ariel E Hirsch1.   

Abstract

PURPOSE AND
OBJECTIVE: The aim of this study was to examine the impact of patient demographics, tumor characteristics, and treatment type on time to treatment (TTT) in patients with breast cancer treated at a safety net medical center with a diverse patient population. PATIENTS AND METHODS: A total of 1,130 patients were diagnosed and treated for breast cancer between 2004 and 2014 at our institution. We retrospectively collected data on patient age at diagnosis, race/ethnicity, primary language spoken, marital status, insurance coverage, American Joint Committee on Cancer (AJCC) stage, hormone receptor status, and treatment dates. TTT was determined from the date of breast cancer biopsy to treatment start date. Nonparametric Mann-Whitney U-test (or Kruskal-Wallis test when appropriate) and multivariable quantile regression models were employed to assess for significant differences in TTT associated with each factor.
RESULTS: Longer median TTT was noted for Black (P=0.002) and single (P=0.002) patients. AJCC stage IV patients had shorter TTT (27.5 days) compared to earlier AJCC patients (36, 35, 37, 37 days for stage 0, I, II, III, respectively), P=0.028. Age, primary language spoken, insurance coverage, and hormone receptor status had no significant impact on TTT. On multivariate analysis, race/ethnicity remained the only significant factor with Black reporting longer TTT, P=0.025. However, race was not a significant factor for time from first to second treatment. More Black patients were noted to be single (P<0.0001) and received chemotherapy as first treatment (P=0.008) compared to White, Hispanic, or other race/ethnicity patients.
CONCLUSION: In this retrospective analysis, Black patients had longer TTT, were more likely to receive chemotherapy as first treatment, and have a single marital status. These patient factors will help identify vulnerable patients and guide further research to understand the barriers to care and the impact of treatment delays on outcomes.

Entities:  

Keywords:  breast cancer; patient demographics; race; treatment delay; tumor characteristics

Year:  2017        PMID: 29255374      PMCID: PMC5723124          DOI: 10.2147/IJWH.S150064

Source DB:  PubMed          Journal:  Int J Womens Health        ISSN: 1179-1411


Introduction

Breast cancer is the most commonly diagnosed malignancy and the second leading cause of cancer death among women in the USA. The National Cancer Institute estimates that there were 252,710 new breast cancer cases and 40,610 deaths in 2017.1 Unfortunately, breast cancer disparities in outcomes among different races and vulnerable populations have been a long-standing problem. Previously, breast cancer incidence rates had been higher for White women than for Black women in the USA, but in 2012, the incidence rates converged.2 Despite this, the disparity in mortality between White and Black women continues to widen, and Black women are 42% more likely to die from breast cancer than their White counterparts.2 Even with an increase in the use of screening mammography across races in the USA, there remain socioeconomic and race-related disparities in treatment and outcomes.3 Specifically, large multi-institutional studies have demonstrated differences in cancer stage at diagnosis, types of treatment available and outcomes by primary language spoken, race, insurance coverage, marital status, and other demographic factors.3–18 Previous studies of breast cancer disparities have looked at delays to care across the cancer continuum. Research has revealed that delays to treatment are significantly associated with low socioeconomic status and race.19 A meta-analysis of 87 studies by Richards et al showed that delays of >3–6 months after an initial diagnosis may have a 12% lower 5-year survival than those without delay.13 Breast cancer treatment is complex, with potentially several different sequential treatments: surgery, chemotherapy, and radiation therapy. Delays anywhere along the treatment pathway can have a significant impact on mortality. Studies have shown that treatment delay >4 weeks to postoperative chemotherapy or 8 weeks to initiation of postoperative radiotherapy is associated with shorter disease-free and overall survival.21–24 Despite these findings, there are limited data in the literature regarding treatment delay across the entire patient diagnosis and treatment pathway. The purpose of our study is to assess the disparities in both the time to first treatment and the time to second treatment in order to better understand treatment delay throughout the entirety of breast cancer care. We stratify patients by age at diagnosis, race/ethnicity, primary language spoken, insurance coverage, marital status, tumor stage, and hormone receptor status. This study is also novel because it is based at a large academic institution that serves as the major safety net hospital in New England, and the results are evaluated in a setting where the majority of patients are non-White.

Patients and methods

Patient selection

A total of 1,547 patients were diagnosed with breast cancer between April 2004 and April 2014 at our academic medical institution. All patients received multidisciplinary care involving surgeons, medical oncologists, radiation oncologists, radiologists, and allied health professionals prior to the initiation of treatment. We excluded 417 patients from the study for the following reasons: patients did not have complete biopsy information prior to surgery or biopsy was not performed at this institution (n=275), treatment started >365 days after initial diagnosis (n=4), patients transferred their medical care to another institution after receiving their diagnosis (n=125), patients refused all care after receiving their diagnosis (n=6), or patients had metastatic disease from another primary cancer (n=7).

Data collection and study variables

Clinical Data Warehouse staff reviewed the institution’s medical records for breast cancer patients diagnosed in the stated time frame. The data collected included patient’s age, race/ethnicity, primary language spoken, marital status, insurance coverage, and American Joint Committee on Cancer (AJCC) stage at diagnosis. Age at diagnosis was categorized as ≤50, >50 to ≤70, and >70 years old. Race/ethnicity was categorized as Black, White, Hispanic, and others. Primary language spoken was categorized as English, Spanish, Haitian Creole, and others. Marital status was categorized as married, single, and others (including divorced, widowed, separate, and other status). Insurance coverage was categorized as private/commercial, charity/Medicaid/self-pay/uninsured, and Medicare. The research team reviewed individual patient medical records to collect tumor information, date of pathologic diagnosis, dates of treatment, and type of treatment(s) received. Data on tumor information included tumor hormone receptor status: estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Stage at diagnosis was classified according to the 2002 AJCC classification scheme: 0, I, II, III, and IV.

Treatment

Patients underwent a combination of surgery, radiation therapy, chemotherapy, and hormone therapy. Time to treatment (TTT) was calculated from the date of biopsy to the date of first treatment received. In addition to the first treatment received, information on follow-up treatment was ascertained for all patients.

Statistical analysis

Descriptive statistics were computed to describe the patient cohort. Frequencies are presented as number of patients (column %) and time metrics as median (interquartile range [IQR]). Nonparametric Mann–Whitney U-test or Kruskal–Wallis test (when appropriate) was used to assess the differences in the distribution of TTT and the time to second treatment by patient, tumor, and treatment characteristics. Dwass–Steel–Critchlow–Fligner multiple comparison procedure was used to perform pairwise comparisons. The procedure controls for experiment-wise error rate. Furthermore, multivariable quantile (median) regression models were employed, and covariate-adjusted parameter estimates with 95% confidence intervals (CIs) were computed. For each time metric, the estimates generated from quantile regression are interpreted as difference in time interval (days) associated with one unit change in each covariate. Only those covariates that had an overall P-value <0.1 in the univariate model were selected for the multivariate model. All of the analyses were two-sided, and P-values <0.05 were considered statistically significant. All statistical computations were performed on SAS 9.1 system (SAS Institute Inc., Cary, NC, USA).

Ethics

Approval for this research was granted by the institutional review board at Boston Medical Center. All medical records were de-identified for this study, and thus, patient consent to review medical records was not required as part of the institutional review board approval.

Results

Of the 1,130 patients diagnosed with breast cancer, 910 (80.5%) patients received surgery, 162 (14.3%) patients received chemotherapy, and 58 (5.1%) patients received hormone therapy as first treatment. A total of 955 (84.5%) underwent second treatment. The distribution of second treatment received was as follows: radiation therapy (36.4%, n=411), chemotherapy (22.8%, n=258), hormone therapy (13.3%, n=150), and surgery (12.0%, n=136). The majority of the patients were between the ages 50 and 70 years (51.7%, n=584) and reported English as their primary language spoken (70.7%, n=799). Non-White race/ethnicity was reported in 64.5% (n=729) of the patient cohort reflecting a diverse patient population. At the time of diagnosis, 35.6% (n=402) of the patient cohort was married, 37.3% (n=421) was single, while 27.2% (n=307) reported their marital status as others. Of the 1,130 patients, complete hormone receptor status was available for 723 patients (~64% of the cohort). The patients were classified into following groups according to their ER/PR/HER2 status: 1) ER+/PR+/HER2− (67.8%, n=490), 2) ER−/PR−/HER2+ (12.5%, n=90), and 3) ER−/PR−/HER2− (19.8%, n=143). Full characteristics are presented in Table 1. The median TTT and the time from first to second treatment were 36 days (IQR =31) and 69 days (IQR =74), respectively.
Table 1

Time to first treatment (days) in breast cancer patients

CategorynPercentageCrude model
P-valueMultivariate model*
P-value
Median (IQR)Adjusted parameter estimate (95% CI)
InterceptN/A32.5 (28.2, 36.8)
Age (years)0.360
 ≤5034130.235 (32)
 >50 to ≤7058451.735.5 (30)
 >7020518.138 (29)
Race/ethnicity0.0020.025
 White40135.535 (28)Ref
 Black41536.739 (34)4.5 (0.69, 8.3)
 Hispanic15413.632 (28)−1.5 (−6.0, 3.0)
 Other16014.233 (29)0.50 (−5.1, 6.1)
Primary language spoken0.260
 English79970.736 (33)
 Spanish11910.532 (28)
 Haitian Creole908.039 (32)
 Other12210.835 (28)
Marital status0.00020.107
 Married40235.633 (28)Ref
 Single42137.338 (33)4.0 (0.26, 7.7)
 Other30727.235 (30)1.5 (−2.4, 5.5)
Insurance coverage0.643
 Charity/Medicaid/self-pay/uninsured28825.536 (33)
 Commercial/private52546.535 (30)
 Medicare/military31728.136 (30)
AJCC stage at diagnosis0.0280.087
 020718.336 (30)Ref
 I40435.835 (28.5)−2 (−6.1, 2.1)
 II33129.337 (34)2 (−2.6, 6.6)
 III14412.737 (34)1 (−6, 8)
 IV443.927.5 (30.5)−10.5 (−21.8, 0.83)
InterceptN/A32.5 (28.2, 36.8)
ER/PR/HER2**0.779
 ER+/PR+/HER2−49067.836 (31)
 ER−/PR−/HER2+9012.535 (26)
 ER−/PR−/HER2−14319.835 (39)
First treatment0.0790.577
 Surgery91080.535.5 (29)Ref
 Chemotherapy16214.339.5 (31)2.5 (−2.6, 7.6)
 Hormone therapy585.134 (55)−1.5 (−13.2, 10.2)

Notes: Overall median time to treatment is 36 days (IQR =31).

Multivariate model included all characteristics with P<0.1 in crude model.

Analysis is based on 723 patients.

Abbreviations: AJCC, American Joint Committee on Cancer; CI, confidence interval; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; IQR, interquartile range; n, number of patients; N/A, not applicable; PR, progesterone receptor; Ref, reference.

Time to first treatment by demographics

In the univariate analysis comparing median TTT by demographics, there was no significant association of patient age (overall P=0.36), primary language spoken (overall P=0.26), and insurance coverage (overall P=0.64) with TTT. Pairwise comparisons did not identify any significant differences among subgroups within each factor. Black women were found to have longer TTT (39 days) compared to White, Hispanic, and other women (35, 32, and 33 days, respectively) (overall P<0.01). On pairwise comparisons, the overall significance was primarily driven from Black vs White (P<0.01). In the analysis of marital status and TTT, married patients had significantly shorter TTT (33 days) compared to single (38 days) and other groups (35 days) (overall P<0.01). In pairwise comparisons, the married vs single (P<0.01) and married vs others (P=0.04) comparisons were significant (Table 1).

Time to first treatment by tumor characteristics and first treatment received

Patients diagnosed with stage IV disease had the shortest TTT (27.5 days) compared to patients diagnosed with earlier stages (overall P=0.03). Stage IV patients had significantly shorter TTT compared to stage III (P=0.05) and stage II (P=0.04). Overall, time to first treatment did not correlate strongly with the type of first treatment received (overall P=0.08) (Table 1).

Time to first treatment: multivariate model

In the multivariate model with race/ethnicity, marital status, AJCC stage, and first treatment received (all factors with overall P<0.1 in the univariate analysis), race/ethnicity was the only independent predictor of TTT (overall P=0.03). Black patients had longer TTT compared to White patients (adjusted parameter estimate 4.5, 95% CI: 0.69, 8.3, P=0.03). When compared to married patients, single patients still had longer TTT (adjusted parameter estimate 4.0, 95% CI: 0.26, 7.7, P=0.04) (Table 1).

Time to second treatment by demographics

Younger patients (≤50 years) had a longer lapse in time from their first to second treatment (76 days) compared to older patients (68 days for >50 to ≤70 years and >70 years) (overall P=0.02). On pairwise comparison, age ≤50 years vs >50 to ≤70 years was significant (P=0.02). Marital status predicted time to second treatment (overall P=0.01), single (75 days) patients had longer time to second treatment compared to married (66 days) with a pairwise P-value of 0.01 (Table 2).
Table 2

Time from first to second to treatment (days) in breast cancer patients

CategorynPercentageCrude model
P-valueMultivariate model*
P-value
Median (IQR)Adjusted parameter estimate (95% CI)
InterceptN/A54 (44.8, 63.2)
Age (years)0.0170.626
 ≤5029230.676 (103.5)Ref
 >50 to ≤051353.768 (69)3 (−3.1, 9.1)
 >7015015.768 (56)2 (−7.8, 11.8)
Race/ethnicity0.196
 White31933.467 (72)
 Black35637.370 (96.5)
 Hispanic14214.976 (66)
 Other13814.568.5 (52)
Primary language spoken0.358
 English66369.468 (76)
 Spanish10911.470 (52)
 Haitian Creole737.681 (112)
 Other11011.563.5 (84)
Marital status0.0070.093
 Married34936.566 (66)Ref
 Single35337.075 (99)7 (0.71, 13.3)
 Other25326.568 (65)3 (−4.2, 10.2)
Insurance coverage0.0510.402
 Charity/Medicaid/self-pay/uninsured24225.377.5 (86)Ref
 Commercial/private44746.868 (71)−5 (−12.4, 2.4)
 Medicare/military26627.968 (70)−3 (−12.3, 6.3)
AJCC stage at diagnosis<0.0001<0.0001
 015816.554.5 (44)Ref
 I35236.959 (38)2 (−5.1, 9.1)
 II29430.879 (85)15 (6.7, 23.3)
 III13013.6154 (164)31 (16.5, 45.5)
 IV212.291 (177)1 (−53.4, 55.4)
InterceptN/A54 (44.6, 66.3)
ER/PR/HER2**0.003
 ER+/PR+/HER2−43069.063 (65)
 ER−/PR−/HER2+7211.673 (138)
 ER−/PR−/HER2−12119.476 (118)
First treatment<0.0001<0.0001
 Surgery79182.862 (43)Ref
 Chemotherapy13414.0203 (69)125 (111.2, 138.8)
 Hormone therapy303.1123 (229)54 (2.8, 105.2)

Notes: Overall median time from first to second treatment is 69 days (IQR =74).

Multivariate model included all characteristics with P<0.1 in crude model.

Analysis is based on 723 patients.

Abbreviations: AJCC, American Joint Committee on Cancer; CI, confidence interval; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; IQR, interquartile range; n, number of patients; N/A, not applicable; PR, progesterone receptor; Ref, reference.

Time to second treatment by tumor characteristics and first treatment received

In contrast to the analysis of TTT, patients with early-stage disease had a shorter median time to second treatment (54.5 and 59 days for stages 0 and I, respectively) compared to more advance stage disease (154 and 91 days for stages III and IV, respectively) (overall P<0.01). Pairwise comparisons resulted in several significant differences: stage 0 vs stage II (P<0.01), stage 0 vs stage III (P<0.01), stage I vs stage II (P<0.01), stage I vs stage III (P<0.01), and stage II vs stage III (P<0.01). ER+/PR+/HER2− patients had the shortest time from first to second treatment (63 days) compared to 73 and 76 days for ER−/PR−/HER2+ and ER−/PR−/HER2−, respectively (overall P<0.01). In pairwise analysis, ER+/PR+/HER2− was significantly different from ER−/PR−/HER2+ (P=0.05) and ER−/PR−/HER2− (P=0.01). Surgical patients had the shortest time to second treatment (62 days) compared to patients who got chemotherapy (203 days) or hormone therapy (123 days) as their first treatment (overall P<0.01). In pairwise analysis, surgical patient was significantly less delayed compared to chemotherapy (P<0.01) and hormone therapy (P<0.01) groups (Table 2).

Time to second treatment: multivariate model

Advanced AJCC stage remained a significant predictor of longer time to second treatment after adjusting for other factors (overall P<0.01). Pairwise comparisons resulted in several significant differences: stage 0 vs stage II (P<0.01), stage 0 vs stage III (P<0.01), stage I vs stage II (P<0.01), stage I vs stage III (P<0.01), and stage II vs stage III (P=0.03). Finally, chemotherapy (adjusted parameter estimate 125, 95% CI: 111.2, 138.8, P<0.01) and hormone therapy (adjusted parameter estimate 54, 95% CI: 2.8, 105.2, P=0.04) patients had longer time to second treatment compared to surgical patients, reflecting the different durations of systemic and local treatment modalities (Table 2).

Race/ethnicity and patient characteristics

Race/ethnicity correlated with marital status, insurance coverage, AJCC stage, and first treatment received. The distribution of single marital status was 47.7, 38.3, 30.6, and 28.7% among Black, Hispanic, other, and White women, respectively (P<0.01). More Black, Hispanic, and other patients (27.7, 40.3, and 40.6%) had charity/Medicaid/self-pay/uninsured as their insurance status compared to their White counterparts (11.5%) (P<0.01). Advanced disease presentation (stages III–IV) was noted among Black and other women (19.0 and 20.0%) compared to their White and Hispanic counterparts (15.5 and 9.7%) (P<0.01). A total of 19.3% of Black patients underwent chemotherapy as their first treatment compared to White, Hispanic, and other race/ethnic patients (10.2, 13.0, and 13.1%, respectively) (P<0.01) (Table 3).
Table 3

Distribution of marital status, insurance coverage, tumor stage, and first treatment received by race/ethnicity

Categoryn (%)
P-value
White(N=401)Black(N=415)Hispanic(N=154)Other(N=160)
Marital status<0.0001
 Married167 (41.6)105 (25.3)54 (35.1)76 (47.5)
 Single115 (28.7)198 (47.7)59 (38.3)49 (30.6)
 Other119 (29.7)112 (27.0)41 (26.6)35 (21.9)
Insurance coverage<0.0001
 Charity/Medicaid/self-pay/uninsured46 (11.5)115 (27.7)62 (40.3)65 (40.6)
 Commercial/private216 (53.9)169 (40.7)72 (46.8)68 (42.5)
 Medicare/military139 (34.7)131 (31.6)20 (13.0)27 (16.9)
AJCC stage at diagnosis0.003
 0242 (60.4)205 (49.4)82 (53.3)82 (51.3)
 I–II97 (24.2)131 (31.6)57 (37.0)46 (28.8)
 III–IV62 (15.5)79 (19.0)15 (9.7)32 (20.0)
First treatment0.008
 Surgery339 (84.5)313 (75.4)130 (84.4)128 (80.0)
 Chemotherapy41 (10.2)80 (19.3)20 (13.0)21 (13.1)
 Hormone therapy21 (5.2)22 (5.3)4 (2.6)11 (6.9)

Abbreviation: AJCC, American Joint Committee on Cancer.

Subgroup analysis of race/ethnicity and time to first treatment

When the results were stratified by marital status, the longest time to first treatment was noted among single White patients (39 days) and Black patients (41 days) compared to single Hispanic patients (33 days) and others (32 days) (overall P<0.01). Black patients with AJCC stage III disease had 44 days until first treatment compared to White patients who had 28.5 days (overall P=0.03). When the results were stratified by the type of first treatment, Black patients had a longer duration to chemotherapy as first treatment (46 days) compared to White patients (31 days), Hispanic patients (41.5 days), or other race patients (35 days) (Table 4).
Table 4

Time to treatment (days) by marital status, insurance coverage, tumor stage, and first treatment in different race/ethnic groups

CategoryTime to first treatment
nMedianP-value
Marital status*0.0002
White0.0004
 Married16730
 Single11539
 Other11936
Black0.194
 Married10536
 Single19841
 Other11236
Hispanic0.731
 Married5431.5
 Single5933
 Other4134
Other0.720
 Married7636.5
 Single4932
 Other3532
Insurance coverage*0.005
White0.163
 Charity/Medicaid/self-pay/uninsured4636.5
 Commercial/private21632.5
 Medicare/military13935
Black0.958
 Charity/Medicaid/self-pay/uninsured11540
 Commercial/private16941
 Medicare/military13136
Hispanic0.069
 Charity/Medicaid/self-pay/uninsured6232
 Commercial/private7231
 Medicare/military2048
Other0.296
 Charity/Medicaid/self-pay/uninsured6532
 Commercial/private6836.5
 Medicare/military2732
AJCC stage at diagnosis*0.026
White0.430
 024235
 I–II9735
 III–IV6228.5
Black0.749
 020537
 I–II13141
 III–IV7944
Hispanic0.230
 08231
 I–II5736
 III–IV1543
Other0.323
 08232
 I–II4637.5
 III–IV3230.5
First treatment*0.003
White0.705
 Surgery33935
 Chemotherapy4131
 Hormone therapy2135
Black0.152
 Surgery31337
 Chemotherapy8046
 Hormone therapy2242.5
Hispanic0.309
 Surgery13031.5
 Chemotherapy2041.5
 Hormone therapy434.5
Other0.029
 Surgery12834
 Chemotherapy2135
 Hormone therapy1121

Note:

Overall P-value from nonparametric Kruskal–Wallis test assessing differences in median time to treatment by marital status/insurance coverage/tumor stage and different race/ethnic groups.

Abbreviation: AJCC, American Joint Committee on Cancer.

Discussion

The US Department of Health and Human Services, the American Cancer Society, and many other national organizations have identified reducing health care disparities, particularly in the setting of cancer care, as a key goal in the effort to improve health outcomes nationally.25 On a smaller scale, there have been successful local interventions to reduce health care disparity in breast cancer care in Black women. These interventions include culturally sensitive educational community programs that focus on preventative health measures with the understanding that Black women are known to have more barriers to cancer detection and care compared to White women.26,27 Black and Hispanic women with breast cancer are more often uninsured or insured by Medicaid and present with more advanced disease than White women.28 In particular, Black women with breast cancer are more likely than White women to present with advanced stage and more aggressive disease and are more likely to have Medicaid coverage.9 This is also true for Hispanic women, who, along with Black women, are more likely to be diagnosed at a later stage of disease and be uninsured or have Medicaid.24,25 Our analysis shows similar disparities for Black women compared to their White counterparts. AJCC stages 0, I–II, and III–IV were reported in 49.4, 31.6, and 19.0% of Black women as compared to 60.4, 24.2, and 15.5% of White women, respectively, indicating more advanced disease presentation for Black women. A similar disparity was noted in insurance coverage in this study with 27.7% of Blacks in charity/Medicaid/self-pay/uninsured group as compared to only 11.5% of Whites. The highest percentage of commercial/private insurance coverage was reported among White women (53.9%), with Black women reporting the lowest percentage (40.7%) in this study. With respect to the impact of race on treatment delay, some researchers have found that Black women have longer delays than White women, whereas other researchers did not note a significant difference.20 Our analysis shows a disparity in TTT for Black women, with both White and Hispanic women having shorter time to first treatment. This finding is despite the ethnically diverse patient population at our institution, which serves as a major safety net hospital. Of note, Black patients who received chemotherapy as first treatment had a longer TTT (46 days) compared to White patients (31 days). Interestingly, among patients who received second treatment, race was not significantly associated with time to second treatment, unlike time to first treatment. One possible explanation may be that once patients initiate treatment after diagnosis, they are in more frequent contact with health care providers and thus more likely to not have delays throughout their course of care. Outside of race, there are many known variables that may contribute to treatment delay. For example, insurance coverage often dictates access to care and lack of health insurance is associated with inferior access to primary and preventative care.29 Previous studies have shown that uninsured patients and those covered with Medicaid are more likely to present with advanced disease and have decreased survival compared to privately insured patients.30,31 Our study did not find a statistically significant association between insurance type and time to first treatment. This may reflect the nature of this institution being the largest safety net hospital in the region that serves a large proportion of care to the uninsured and Medicaid beneficiaries. In addition, given that neoadjuvant chemotherapy is used primarily to downstage large breast tumors to facilitate breast conservation surgery and that metastatic patients receive chemotherapy as primary treatment, chemotherapy as first treatment can be used as a pseudo-marker for more advanced stage tumors.32 This is consistent with our data that showed more Black patients using charity/Medicaid/self-pay/uninsured as insurance compared to White patients and Black patients presenting with more advanced disease and using chemotherapy as first treatment. Furthermore, in previous studies, being married has been shown to have a survival advantage for patients with cancer. Unmarried women are more likely to be diagnosed with advanced disease and have a higher mortality rate than their married counterparts.33,34 In our study, married patients had significantly shorter TTT and time to second treatment compared to single patients. Also, 47.7% of Black patients were single compared to Hispanic, other, and White patients (38.3, 30.6, and 28.7%, respectively). The longest time to first treatment was noted among single Black patients (41 days) and White patients (39 days) compared to single Hispanic and other patients. The relationship between the marital status of Black patients and their delays in time to first treatment should be further investigated. Our study demonstrated significant associations between treatment delay and demographic factors previously shown to affect mortality such as race and marital status. However, this study did not look at survival outcomes. Many early studies have shown that delay in the diagnosis and delivery of effective treatments for breast cancer results in advanced states of disease and increased breast cancer mortality. However, recent studies on treatment delay are more mixed and many show no difference in survival related to treatment delay.8,11,35–37 These conflicting results may be explained by differences in patient selection, cutoffs for treatment delay, and availability of biological, clinical, and socioeconomic covariates. Our study is limited to a single institution and does not address comorbid medical conditions or all possible cofounders of tumor characteristics and demographic factors like socioeconomic status. Another possible limitation is the inclusion of all AJCC stages since in metastatic disease, the approach to optimal timing of treatment differs from that in earlier stages and is often decided on an individual basis according to hormonal status, previous treatments, patient symptoms, and preferences.39 Further research is needed to understand the direct impact of treatment delays on clinical outcomes in order to guide potential interventions to reduce treatment delays. The major strength of our study is that it assesses disparities in both the time to first treatment and the time from first to second treatment in order to better understand treatment delay throughout the entire course of breast cancer care. On multivariate analysis, advanced tumor stage was a significant predictor of longer time from first to second treatment, with AJCC stage III patients having the longest interval (median of 154 days) compared to stage 0 (54.5 days), stage I (59 days), and stage II (79 days). First treatment modality also remained a significant predictor; patients who received chemotherapy first had significantly longer time to second treatment compared to surgical patients. This may simply reflect the fact that it may take longer to recover from the effects of chemotherapy before receiving the second treatment. Patients who receive chemotherapy as first treatment likely have more advanced disease and thus more perceived urgency to initiate treatment.32 In this study, there was no statistically significant difference in the time to first treatment based on treatment modality in the multivariate model. In locally advanced stage disease, it is not known whether the time from breast cancer diagnosis to neoadjuvant chemotherapy affects survival. A previous study showed that delay (>55 days) in neoadjuvant chemotherapy had an increased risk of death, especially in HER2-positive patients.38 In our study, it is unclear if patients who received chemotherapy as first treatment were being treated for metastatic disease or as neoadjuvant therapy, and this is a question that could be further investigated. Few studies have evaluated breast cancer disparities in truly multiethnic populations and compared two or more population subsets with White counterparts.12 Given that our study population is a large, multiethnic cohort over an extended time period, the results of this study can be used as a paradigm to better understand breast cancer disparities in other urban and ethnically diverse communities. Similar to previous literature, our results demonstrate that Black patients present more often with charity/uninsured insurance status and more advanced AJCC breast cancer stage, require chemotherapy as first treatment, and have significantly longer TTT delays compared to their non-White counterparts. This study shows that despite the progress in improving access to health care, demographic factors and tumor biology remain the drivers of disparity in time to breast cancer treatment and warrant further investigation.

Conclusion

We demonstrate that Black patients had significantly longer time from diagnosis to treatment compared to other race patients in a setting where the majority of patients are non-White. The study also assesses both the time to first treatment and the time to second treatment, which will help the field better understand treatment delay throughout the continuum of breast cancer care.
  37 in total

Review 1.  Racial and ethnic disparities in the receipt of cancer treatment.

Authors:  Vickie L Shavers; Martin L Brown
Journal:  J Natl Cancer Inst       Date:  2002-03-06       Impact factor: 13.506

2.  Assessing the impact of socio-economic variables on breast cancer treatment outcome disparity.

Authors:  Min Rex Cheung
Journal:  Asian Pac J Cancer Prev       Date:  2013

3.  Delay, stage of disease and survival from breast cancer.

Authors:  G S Wilkinson; F Edgerton; H J Wallace; P Reese; J Patterson; R Priore
Journal:  J Chronic Dis       Date:  1979

4.  Effect on survival of longer intervals between confirmed diagnosis and treatment initiation among low-income women with breast cancer.

Authors:  John M McLaughlin; Roger T Anderson; Amy K Ferketich; Eric E Seiber; Rajesh Balkrishnan; Electra D Paskett
Journal:  J Clin Oncol       Date:  2012-11-19       Impact factor: 44.544

Review 5.  Timing of adjuvant systemic therapy and radiotherapy after breast-conserving surgery and mastectomy.

Authors:  Alessandra Balduzzi; Maria Cristina Leonardi; Anna Cardillo; Roberto Orecchia; Silvia Dellapasqua; Monica Iorfida; Aron Goldhirsch; Marco Colleoni
Journal:  Cancer Treat Rev       Date:  2010-03-20       Impact factor: 12.111

6.  Racial differences in diagnosis, treatment, and clinical delays in a population-based study of patients with newly diagnosed breast carcinoma.

Authors:  Karin Gwyn; Melissa L Bondy; Deborah S Cohen; Mary Jo Lund; Jonathan M Liff; Elaine W Flagg; Louise A Brinton; J William Eley; Ralph J Coates
Journal:  Cancer       Date:  2004-04-15       Impact factor: 6.860

7.  Delay in surgical treatment and survival after breast cancer diagnosis in young women by race/ethnicity.

Authors:  Erlyn C Smith; Argyrios Ziogas; Hoda Anton-Culver
Journal:  JAMA Surg       Date:  2013-06       Impact factor: 14.766

8.  Determinants of delay for breast cancer diagnosis.

Authors:  Isabelle Bairati; Edith Jobin; Lise Fillion; Marie Larochelle; Linda Vincent
Journal:  Cancer Detect Prev       Date:  2007

9.  Factors associated with wait times across the breast cancer treatment pathway in Ontario.

Authors:  Amalia Plotogea; Anna M Chiarelli; Lucia Mirea; Maegan V Prummel; Nelson Chong; Rene S Shumak; Frances P O'Malley; Claire M B Holloway
Journal:  Springerplus       Date:  2013-08-19

10.  Race/Ethnicity, Primary Language, and Income Are Not Demographic Drivers of Mortality in Breast Cancer Patients at a Diverse Safety Net Academic Medical Center.

Authors:  Divya A Parikh; Rani Chudasama; Ankit Agarwal; Alexandar Rand; Muhammad M Qureshi; Taylor Ngo; Ariel E Hirsch
Journal:  Int J Breast Cancer       Date:  2015-10-28
View more
  3 in total

1.  The association of delay in curative intent treatment with survival among breast cancer patients: findings from the Women's Health Initiative.

Authors:  Rachel Yung; Roberta M Ray; Joshua Roth; Lisa Johnson; Greg Warnick; Garnet L Anderson; Candyce H Kroenke; Rowan T Chlebowski; Michael S Simon; Chunkit Fung; Kathy Pan; Di Wang; Wendy E Barrington; Kerryn W Reding
Journal:  Breast Cancer Res Treat       Date:  2020-02-15       Impact factor: 4.872

2.  Longer time-to-treatment but better survival for colorectal cancer patients presumptively not diagnosed in a hospital.

Authors:  Cara L Frankenfeld; Timothy F Leslie; Nirup M Menon
Journal:  Cancer Causes Control       Date:  2021-06-23       Impact factor: 2.506

3.  Novel semi-automated algorithm for high-throughput quantification of adipocyte size in breast adipose tissue, with applications for breast cancer microenvironment.

Authors:  Frank L Lombardi; Naser Jafari; Kimberly A Bertrand; Lauren J Oshry; Michael R Cassidy; Naomi Y Ko; Gerald V Denis
Journal:  Adipocyte       Date:  2020-12       Impact factor: 3.553

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.