# Ethnic Disparities of Female Infiltrating Duct and Lobular Breast Cancer
Survival by Cancer Stage: Findings From SEER 2006-2010

Ishmael Nii Amartei Amartey  Department of Statistics and Actuarial Science
Norhtern Illinois University, Dekalb, IL, 60115
<EMAIL_ADDRESS>
May 08, 2023

###### Abstract

Breast Cancer is a major disease affecting women’s health in the United States
with incidence and prevalence dominant among younger women and the Black race.
We analyzed the association between breast cancer characteristics with age and
race and how survival months and age differ in racial groups. Using the
Surveillance, Epidemiology, and End Results (SEER) datasets we performed a
logistic regression to examine significant predictors that affect survival
month. There were 3414 whites, 291 Blacks, and 320 Others (American Indian/AK
Native, Asian/Pacific Islander) in the sample. We found significant
associations between racial groups and ages with significant differences in
age between Blacks and Whites, and Whites and Others. Patients with a breast
cancer tumor in grades 1 and 2 have higher survival months (by 1.49 % and
0.49% respectively.

###### keywords:

SEER dataset , logistic regression , breast cancer , ductal carcinoma in situ.

††journal: Journal of Multivariate Analysis

##  1 Introduction

Breast cancer is one of the commonest cancers in the world accounting for
about 12.5% of all new cancer cases worldwide [1] . Statistics from the
American Cancer Society [2] report that breast cancer contributes to about 30%
of all female cancer cases recorded in the US accounting for a ratio of 1:3 of
every cancer case. Despite the significant improvement in research and
diagnosis, the disease incidence is still high amongst racial and age groups
[4, 11] with Blacks having the highest incidence compared to whites and other
racial groups [6, 7]. Other studies found that compared to non-Hispanic White,
non-Hispanic Black, Asian American/Pacific Islander, Native American, and
Hispanic women have a higher percentage of invasive breast cancers at younger
ages and at more advanced stages, and a higher percentage of breast cancer
deaths at younger ages [5]. In this study, we sought to examine the
differences in survival months, regional nodes examined (RNE), positive
regional nodes (RNP), age, and tumor size across racial groups of Blacks,
Whites, and Others (American Indian/AK Native, and Asian/Pacific Islander). We
also seek to establish the associations between breast cancer characteristics
across race and age groups and to determine significant predictors of
survivability through logistic regression models.

##  2 Methods

###  2.1 Data Source

The Surveillance, Epidemiology, and End Results (SEER) provide useful
information on cancer statistics in the United States for researchers. In this
study, we used a dataset of 4024 female patients diagnosed with infiltrating
duct and lobular breast cancer between 2006-2010 [9]. The data frame contains
information at the time of diagnosis on age, race, marital status, T-stage,
N-stage, 6th stage, differentiate, grade, A Grade, tumor size, estrogen, and
progesterone status (negative/positive), regional node examined, regional
nodes (positive/ examined), survival months, and status (dead/alive). The
categories in racial groups are Black, White, and Others (American Indian/AK
Native, Asian/Pacific Islander), marital status as single, married, separate,
widowed, divorced, T stage into 4 categories ranging from T1 to T4, N stage
ranging from N1 to N3, 6th stage into 5 categories of IIA, IIB, IIIA, IIIB,
and IIIC. Differentiation was categorized into 4 main parts: moderate, poor,
undifferentiated, and well differentiated, and A stage as regional or distant.
We categorized age as 30 to 39 years, 40 to 49 years, 50 to 59 years, and
$\geq$ 60 years and categorized survival months into ranges of $\leq$ 20
months, 21-49 months, 50-69 months, 70-89 months, and $\geq$ 90 months.

###  2.2 Statistical Analysis

Continuous variables were summarized using measures of central tendency and
dispersion, while categorical variables were summarized using frequency
measures. Difference between two means was tested using independent sample
t-test and between more than two means using analysis of variance (ANOVA) and
Bonferroni Post Hoc test, while difference in proportions was tested using chi
square test. Unadjusted and adjusted analysis for the survival prediction were
performed using logistic regression. Retrospective survival rate (stage
-specific diagnosis to death time) was calculated and compared by ethnicity.
Significance was set to 0.05. All the analyses were run using SPSS (V.27).

##  3 Results

###  3.1 Distribution of the sampled data

The overall mean and confidence interval (CI) for age, regional node examined
(RNE), regional node positive (RNP), tumor size (in millimeters), and survival
months as shown in table 1 were 53.97 years (95% CI, 53.70 to 54.27), 14.36
(95% CI, 14.11 to 14.60), 4.42 (95% CI, 4.00 to 4.32 ), 30.47mm (95% CI, 29.81
to 31.16), and 71.30 months (95% CI, 70.58 to 71.95) respectively. The race
distribution was 7.23% blacks, 84.82%, and 7.95% others (American Indian/AK
Native, Asian/Pacific Islander) as shown in fig 1.

Fig. 1: Race distribution of the 4024 sampled women Fig. 2: Distribution plot of age, RNE, RNP, Tumor size, and survival months by race Table 1: Distribution of Age, Regional Node Examined (RNE), Regional Node Positive (RNP), Tumor Size, and Survival Months by Race Race |  | Age | RNE | RNP | Tumor Size | Survival Months
---|---|---|---|---|---|---
Black | Mean | 52.58 | 14.31 | 4.42 | 30.52 | 66.61
| n | 291 | 291 | 291 | 291 | 291
|  | SD
---
95% CI
| 9.050
---
[51.62-53.58]
| 7.488
---
[13.39-15.12]
| 5.086
---
[3.86-5.03]
| 22.167
---
[27.98-33.04]
| 24.806
---
[63.70-69.55]
Other | Mean | 51.43 | 14.71 | 4.21 | 31.00 | 73.22
| n | 320 | 320 | 320 | 320 | 320
|  | SD
---
95% CI
| 9.541
---
[50.47-52.51]
| 7.510
---
[13.87-15.54]
| 4.897
---
[3.68-4.78]
| 19.892
---
[29.05-33.39]
| 23.075
---
[70.67-75.58]
White | Mean | 54.33 | 14.33 | 4.13 | 30.42 | 71.52
| n | 3413 | 3413 | 3413 | 3413 | 3413
|  | SD
---
95% CI
| 8.852
---
[54.03-54.64]
| 8.204
---
[14.06-14.59]
| 5.131
---
[3.96-4.31]
| 21.145
---
[29.72-31.14]
| 22.696
---
[70.74-72.27]
Total | Mean | 53.97 | 14.36 | 4.16 | 30.47 | 71.30
| n | 4024 | 4024 | 4024 | 4024 | 4024
|  | SD
---
95% CI
| 8.963
---
[53.70-54.27]
| 8.100
---
[14.11-14.60]
| 5.109
---
[4.00-4.32]
| 21.120
---
[29.81-31.16]
| 22.921
---
[70.58-71.95]

###  3.2 Association of breast cancer characteristics by Race and Across Age
Groups

Table 2 shows the distributions and Chi-square association of race with breast
cancer grade, marital status, stage, estrogen/ progesterone, status, and the
various categories of survival month, tumor size, RNE, and RNP. Breast cancer
grade had a significant association with race (p-value <0.0001), likewise
marital status (p-value <0.0001), N stage (p-value = 0.0416), differentiate
(p-value <0.0001), estrogen (p-value = 0.0012), status (0.0001), and survival
month category (0.0016). T stage (p-value =0.2061), 6th stage (p-value =
0.3560), A stage (p-value = 0.8577), tumor size category (p-value = 0.7481),
RNE category (p-value = 0.1462), and RNP category (p-value = 0.8094) were non-
significantly associated with race. The distribution across age categories is
presented in table 3. Grade, marital status, T stage, 6th stage,
differentiate, tumor size, estrogen, progesterone, and status (Dead/Alive)
were associated across age categories.

Table 2: Frequency distribution of breast cancer variables by race Characteristics |  | Race |  |
---|---|---|---|---
| Black n (%) | Other n (%) | White n (%) | p-value
Grade |  |  |  |
1 | 32(0.80) | 46 (1.15) | 465 (11.61) |
2 | 141 (3.52) | 180 (4.49) | 2030 (58.70) | <0.001
3 | 115 (2.87) | 94 (2.35) | 902 (27.74) |
Marital Status |  |  |  |
Divorced | 40 (0.99) | 29 (0.72) | 417 (10.36) |
Married | 113 (2.81) | 237 (5.89) | 2293 (56.98) |
Separate | 8 (0.20) | 4 (0.10) | 33 (0.82) | <0.001
Single | 102 (2.53) | 33 (0.82) | 480 (11.93) |
Widowed | 28 (0.70) | 17 (0.42) | 190 (4.72) |
T Stage |  |  |  |
T1 | 117 (2.91) | 113 (2.81) | 1373 (34.12) |
T2 | 132 (3.28) | 162 (4.03) | 1492 (37.08) | 0.2061
T3 | 33 (0.82) | 41 (1.02) | 459 (11.41) |
T4 | 9 (0.22) | 4 (0.10) | 89 (2.21) |
N Stage |  |  |  |
N1 | 184 (4.57) | 211 (5.24) | 2337 (58.08) |
N2 | 63 (1.57) | 74 (1.84) | 683 (16.97) | 0.0416
N3 | 44 (1.09) | 35 (0.87) | 393 (9.77) |
6th Stage |  |  |  |
IIA | 91 (2.26) | 90 (2.24) | 1124 (27.93) |
IIB | 81 (2.01) | 95 (2.36) | 954 (23.71) |
IIIA | 69 (1.71) | 96 (2.39) | 885 (21.99) | 0.3560
IIIB | 6 (0.15) | 4 (0.10) | 57 (1.42) |
IIIC | 44 (1.09) | 35 (0.87) | 393 (9.77) |
Differentiate |  |  |  |
Moderately Differentiated | 141 (3.50) | 180 (4.47) | 2030 (50.45) |
Poorly Differentiated | 115 (2.86) | 94 (2.34) | 902 (22.42) | <0.0001
Undifferentiated | 3 (0.07) | 0 (0.00) | 16 (0.40) |
Well Differentiated | 32 (0.80) | 46 (1.14) | 465 (11.56) |
A Stage |  |  |  |
Regional | 283 (7.03) | 313 (7.78) | 3336 (82.90) | 0.8577
Distant | 8 (0.20) | 7 (0.17) | 77 (1.91) |
Estrogen |  |  |  |
---|---|---|---|---
Negative | 33 (0.82) | 27 (0.67) | 209 (5.19) | 0.0012
Positive | 258 (6.41) | 293 (7.28) | 3204 (79.62) |
Progesterone |  |  |  |
Negative | 64 (1.59) | 58 (1.44) | 576 (14.31) | 0.0803
Positive | 227 (5.64) | 262 (6.51) | 2837 (70.50) |
Status |  |  |  |
Alive | 218 (5.42) | 287 (7.13) | 2903 (72.14) | <0.0001
Dead | 73 (1.81) | 33 (0.82) | 510 (12.67) |
Survival Month |  |  |  |
$\leq$ 20 | 20 (0.50) | 11 (0.27) | 108 (2.68) |
21-49 | 41 (1.02) | 30 (0.75) | 378 (9.39) |
50-69 | 98 (2.44) | 83 (2.06) | 1075 (26.71) | 0.0016
70-89 | 71 (1.76) | 109 (2.71) | 989 (24.58) |
$\geq$ 90 | 61 (1.52) | 87 (2.16) | 863 (21.45) |
Tumor Size |  |  |  |
$\leq$ 30 | 192 (4.77) | 207 (5.14) | 2269 (56.39) |
31-60 | 75 (1.86) | 91 (2.26) | 840 (20.87) |
61-90 | 16 (0.40) | 17 (0.42) | 237 (5.89) | 0.7481
91-120 | 7 (0.17) | 4 (0.10) | 56 (1.39) |
$\geq$ 120 | 1 (0.02) | 1 (0.02) | 11 (0.27) |
RNE |  |  |  |
$\leq$ 20 | 243 (6.04) | 244 (6.06) | 2752 (68.39) |
21-40 | 47 (1.17) | 76 (1.89) | 654 (16.25) | 0.1462
$\geq$ 50 | 1 (0.02) | 0 (0.00) | 7 (0.17) |
RNP |  |  |  |
$\leq$ 20 | 285 (7.08) | 314 (7.80) | 3327 (82.68) |
21-40 | 5 (0.12) | 6 (0.15) | 79 (1.96) | 0.8094
$\geq$ 50 | 1 (0.02) | 0 (0.00) | 7 (0.17) |
Table 3: Frequency distribution of breast cancer variables by age group Characteristics |  |  | Age group |  |
---|---|---|---|---|---
| 30-39 | 40-49 | 50-59 |  $\geq$ 60 | p-value
| n (%) | n (%) | n (%) | n (%) |
Grade |  |  |  |  |
1 | 12 (0.3) | 144 (3.6) | 192 (4.79) | 195 (4.87) |
2 | 120 (3) | 618 (15.43) | 837 (20.90) | 776 (19.38) | <0.0001
3 | 95 (2.37) | 357 (8.91) | 355 (8.86) | 304 (7.59) |
Race |  |  |  |  |
Black | 24 (0.6) | 97 (2.41) | 92 (2.29) | 78 (1.94) |
Other | 34 (0.84) | 110 (2.73) | 93 (2.31) | 83 (2.06) | <0.0001
White | 172 (4.27) | 917 (22.79) | 1205 (29.95) | 1119 (27.81) |
Marital Status |  |  |  |  |
Divorced | 15 (0.37) | 121 (3.01) | 183 (4.55) | 167 (4.15) |
Married | 146 (3.63) | 778 (19.33) | 926 (23.01) | 793 (19.71) |
Separate | 2 (0.05) | 19 (0.47) | 17 (0.42) | 7 (0.17) | <0.0001
Single | 64 (1.59) | 194 (4.82) | 209 (5.19) | 148 (3.68) |
Widowed | 3 (0.07) | 12 (0.30) | 55 (1.37) | 165 (4.10) |
T Stage |  |  |  |  |
---|---|---|---|---|---
T1 | 75 (1.86) | 410 (10.19) | 571 (14.19) | 547 (13.59) |
T2 | 103 (2.56) | 511 (12.70) | 607 (15.08) | 565 (14.04) | 0.0002
T3 | 45 (1.12) | 179 (4.45) | 170 (4.22) | 139 (3.45) |
T4 | 7 (0.17) | 24 (0.60) | 42 (1.04) | 29 (0.72) |
N Stage |  |  |  |  |
N1 | 149 (3.70) | 785 (19.51) | 916 (22.76) | 882 (21.92) |
N2 | 46 (1.14) | 223 (5.54) | 302 (7.50) | 249 (6.19) | 0.1908
6th Stage |  |  |  |  |
IIA | 62 (1.54) | 345 (8.57) | 446 (11.08) | 452 (11.08) |
IIB | 66 (1.64%) | 355 (8.82%) | 364 (9.05) | 345 (8.57) |
IIIA | 62 (1.54) | 293 (7.28) | 378 (9.39) | 317 (7.88) | 0.0193
IIIB | 5 (0.12) | 15 (0.37) | 30 (0.75) | 17 (0.42) |
IIIC | 35 (0.87) | 116 (2.88) | 172 (4.27) | 149 (3.70) |
Differentiate |  |  |  |  |
Moderately | 120 (2.98) | 618 (15.36) | 837 (20.80) | 776 (19.28) |
Poorly | 95 (2.36) | 357 (8.87) | 355 (8.82) | 304 (7.55) | <0.0001
Undifferentiated | 3 (0.07) | 5 (0.12) | 6 (0.15) | 5 (0.12) |
Well | 12 (0.30) | 12 (0.30) | 192 (4.77) | 195 (4.85) |
A Stage |  |  |  |  |
Regional | 9 (0.22) | 32 (0.80) | 27 (0.67) | 24 (0.60) | 0.1111
Distant |  | 221
---
(5.49%)
1092 (27.14) | 1363 (33.87) | 1256 (31.81) |
Estrogen |  |  |  |  |
Negative | 31 (0.77) | 77 (1.91) | 101 (2.51) | 60 (1.49) | <0.0001
Positive | 199 (4.95) | 1047 (26.02) | 1289 (32.03) | 1220 (30.32) |
Progesterone |  |  |  |  |
Negative | 46 (1.14) | 156 (3.88) | 281 (6.98) | 215 (5.34) | 0.0003
Positive | 184 (4.57) | 968 (24.06) | 1109 (27.56) | 1065 (26.47) |
Status |  |  |  |  |
Alive | 183 (4.55) | 988 (24.55) | 1201 (29.85) | 1036 (25.75) | <0.0001
Dead | 47 (1.17) | 136 (3.38) | 189 (4.70) | 244 (6.06) |
Survival Month |  |  |  |  |
$\leq$ 20 | 11 (0.27) | 41 (1.02) | 42 (1.04) | 45 (1.12) |
21-49 | 34 (0.84) | 113 (2.81) | 152 (3.78) | 150 (3.73) |
50-69 | 70 (1.74) | 325 (8.08) | 448 (11.13) | 413 (10.26) | 0.1304
70-89 | 73 (1.81) | 337 (8.37) | 400 (9.94) | 359 (8.92) |
$\geq$ 90 | 42 (1.04) | 308 (7.65) | 348 (8.65) | 313 (7.78) |
Tumor Size |  |  |  |  |
$\leq$ 30 | 131 (3.26) | 709 (17.62) | 939 (23.33) | 889 (22.09) |
31-60 | 65 (1.62) | 298 (7.41) | 349 (8.67) | 294 (7.31) |
61-90 | 28 (0.70) | 86 (2.14) | 80 (1.99) | 76 (1.89) | 0.0002
91-120 | 6 (0.15) | 23 (0.57) | 20 (0.50) | 18 (0.45) |
$\geq$ 120 | 0 (0.00) | 8 (0.20) | 2 (0.05) | 3 (0.07) |
RNE |  |  |  |  |
$\leq$ 20 | 181 (4.50) | 902 (22.42) | 1121 (27.86) | 1035 (25.72) |
21-40 | 49 (1.22) | 219 (5.44) | 265 (6.59) | 244 (6.06) | 0.8198
$\geq$ 50 | 0 (0.00) | 3 (0.07) | 4 (0.10) | 1 (0.01) |
RNP |  |  |  |  |
---|---|---|---|---|---
$\leq$ 20 | 225 (5.59) | 1105 (27.46) | 1349 (33.52) | 1247 (30.99) |
21-40 | 5 (0.12) | 16 (0.40) | 37 (0.92) | 32 (0.80) | 0.3059
$\geq$ 50 | 0 (0.00) | 3 (0.07) | 4 (0.10) | 1 (0.02) |

###  3.3 Differences in Age, RNE, RNP, Survival months, and Tumor size by Race
across Status

Figure 3 depicts the side-by-side plot with respect to race across survival
status. The mean difference in age between blacks and whites is -1.748 (95%
CI, -2.810 to -0.687), the difference in age between blacks and others
(American Indian/AK Native, Asian/Pacific Islander) is 1.150 with 95% CI from
-0.332 to 2.631 and the age difference between white and others is 2.898 (95%
CI, 1.876 to 3.919). For blacks and whites, there was a significant difference
in the means of age (p-value = 0.01), and survival months (p-value = 0.001,
95% CI, -7.866 to -1.945). For blacks and others, the only significant
difference was in survival months (p-value <0.001, 95% CI, -10.415 to -2.793)
and for whites and others, the significant difference in mean was recorded for
only age (p-value <0.001, 95% CI, 1.876 to 3.919). There was a significant
difference in all but RNE (p-value = 0.027, 95% CI, 0.087 to 1.477) for status
(Dead/Alive). Table 4 is a summary of the mean differences, p-values, 95%
Confidence Interval (CI), and Cohen’s d effect sizes.

Table 4: Mean differences between racial combinations and survival status for Age, RNE, RNP, and Survival Months Characteristics |  | Mean Difference | p-value | 95% CI | Cohen’s d
---|---|---|---|---|---
Age | Black vs Whites | -1.748 | 0.001 | [2.810, -0.687] | -0. 197
| Black vs Other | 1.150 | 0.128 | [-1.593, 0.793] | 0.123
| White vs Other | 2.898 | <0.001 | [1.876, 3.919] | 0.325
Status | Dead vs Alive | 1.392 | <0.001 | [0.624, 2.160]] | 0.156
RNE | Black vs Whites | -0.015 | 0.976 | [-0.991, 0.961] | -0.002
| Black vs Other | -0.400 | 0.511 | [-1.593, 0.793] | -0.053
| White vs Other | -0.385 | 0.419 | [-1.319, 0.549] | -0.047
Status | Dead vs Alive | 0.782 | 0.027 | [0.087, 1.477] | 0.097
RNP | Black vs Whites | 0.292 | 0.352 | [-3.22, 0.906] | 0.057
| Black vs Other | 0.216 | 0.592 | [-0.577, 1.010] | 0.043
| White vs Other | -0.075 | 0.801 | [-0.661, 0.511] | -0.015
Status | Dead vs Alive | 3.641 | <0.001 | [3.217, 4.065] | 0.737
Tumor size | Black vs Whites | 0.102 | 0.937 | [-2.440, 2.643] | 0.005
| Black vs Other | -0.475 | 0.780 | [-3.816, 2.867] | -0.023
| White vs Other | -0.576 | 0.639 | [-2.988, 1.835] | -0.027
Status | Dead vs Alive | 7.871 | <0.001 | [6.074, 9.667] | 0.376

Fig. 3: Boxplots of Age, Survival months, RNE, RNP, and Tumor size by Race
across status

###  3.4 Effects of Grade, Race, T stage, N stage, Estrogen, Progesterone,
Age, RNE, and RNP on Status

The effects of grade, race, T stage, N stage, estrogen, progesterone, age,
RNE, and RNP were p- value = <0.0001 for grade 1 and 0.0002 for grade 2,
p-value= 0.0004 for black and 0.0332 for others (American Indian/AK Native,
Asian/Pacific Islander), p-value = <0.0001 for T1, 0.002 for T2 and 0.0191 for
T3, p-value = 0.0125 for N1 and 0.3817 for N2, p-value <0.001 for estrogen and
progesterone (negative), p-value <0.001 for age, RNE, and RNP. The odds ratio
for grades 1 and 3 is 68% high (2.488, [CI, 1.709 to 3.622]) than for grades 2
and 3 (1.477, [CI, 1.203 to 1.813]). The racial odds ratio for black and white
was lower (0.566, [CI, 0.414 to 0.773]) compared to other (American Indian/AK
Native, Asian/Pacific Islander) and white (1.537, [CI, 1.035 to 2.283]). For
the T stage, the odds ratios were T1 vs T4 (3.136, [1.943 - 5.060]), T2 vs T4
(2.066, [CI, 1.303 - 3.276]), and T3 vs T4 (1.806, [CI, 1.101 - 2.960]) and
the odds for N stage (N1 vs N2 and N2 vs N3) are 1.798 [CI, 1.135 - 2.849],
and 1.189 [CI, 0.807 - 1.751] respectively. The odds for estrogen (negative vs
positive) and progesterone (negative vs positive) were 0.484 [CI, 0.341 -
0.687] and 0.552 [CI, 0.430 - 0.710] respectively. Table 5 shows the logistic
regression estimates for the 4024 sampled women.

Table 5: Logistic regression estimates Characteristics | Estimates | SE | Effect | OR (95% Wald CI) | p-value
---|---|---|---|---|---
Grade |  |  |  |  |
1 | 0.9116 | 0.1916 | Grade 1 vs 3 | 2.488 (1.709 - 3.622) | <0.0001
2 | 0.3898 | 0.1047 | Grade 2 vs 3 | 1.477 (1.203 - 1.813) | 0.0002
3 | Ref |  |  |  |
Race |  |  |  |  |
Black | -0.5693 | 0.1593 | Black vs White | 0.566 (0.414 - 0.773) | 0.0004
Other | 0.4300 | 0.2019 | Other vs White | 1.537 (1.035 - 2.283) | 0.0332
White | Ref |  |  |  |
T Stage |  |  |  |  |
T1 | 1.1429 | 0.2441 | T1 vs T4 | 3.136 (1.943 - 5.060) | <0.0001
T2 | 0.7255 | 0.2352 | T2 vs T4 | 2.066 (1.303 - 3.276) | 0.0002
T3 | 0.5909 | 0.2522 | T3 vs T4 | 1.806 (1.101 - 2.960) | 0.0191
T4 | Ref |  |  |  |
N Stage |  |  |  |  |
---|---|---|---|---|---
N1 | 0.5867) | 0.2349 | N1 vs N3 | 1.798 (1.135 - 2.849) | 0.0125
N2 | 0.1728 | 0.1976 | N2 vs N3 | 1.189 (0.807 - 1.751) | 0.3817
N3 | Ref |  |  |  |
Estrogen |  |  |  |  |
Negative | -0.7259 | 0.1786 | Neg vs Pos | 0.484 (0.341 - 0.687) | <0.001
Positive | Ref |  |  |  |
Progesterone |  |  |  |  |
Negative | -0.5935 | 0.1279 | Neg vs Pos | 0.552 (0.430 - 0.710) | <0.001
Positive | Ref |  |  |  |
Age | -0.0240 | 0.00547 |  | 0.976 (0.966 - 0.987) | <0.001
RNE | 0.0370 | 0.00726 |  | 1.038 (1.023 - 1.053) | <0.001
RNP | -0.0814 | 0.0153 |  | 0.922 (0.895 - 0.950) | <0.001

##  4 Discussion

The findings from this study indicate cancer grade, marital status, N stage,
differentiation, estrogen, and status (dead/ Alive) have a statistical
association with breast cancer with the distribution of race groups being
predominantly White with Blacks having the least representation similar to the
other results having an overwhelming majority of white patients in the sample
[8]. This may be due to racial disparities in access to healthcare facilities,
inadequate health insurance, and behavioral factors which have been captured
to be some of the contributing factors by [3, 10]. These significant
associations give an insight into the characteristics of breast cancer that
can be used to predict survival months, grade, tumor size, and other related
breast cancer outcomes. The associations between T stage, 6th stage, A stage,
and progesterone were statistically non-significant suggesting that racial
distribution across these factors does not differ. However, further research
would have to be conducted to eliminate potential confounders to make a more
accurate conclusion.

In table 1 we present our findings on the average differences in age, RNE,
RNP, tumor size, and survival months. The mean age for Blacks was
significantly lower than for Whites whereas Whites had a significantly higher
average age at diagnosis than for Others. Blacks on average had significantly
lower survival months compared to Whites and Others while Others had
significantly higher survival months than Whites. These findings correlate
with the findings of [5]. Another important finding is that there was no
significant difference in racial groups and status (Dead/ Alive) for RNE, RNP,
and tumor size suggesting that the number of RNE, RNP, and tumor size are
about the same for surviving or dead patients and across racial groups at
diagnostics. The logistic regression estimates presented in table 5 provide a
useful overview of the factors that are significantly associated with breast
cancer. For age, the log odds of dying from a breast cancer-related disease
increase by 2.1% whereas for negative progesterone and estrogen status, the
odds decrease by 96.9% and 70.1% respectively compared to a positive status.
The log odds for black mortality increase relative to whites compared to the
odds of others (American Indian/AK Native, and Asian/Pacific Islander) who has
a decreasing log odds of mortality compared to the white race.

##  5 Limitation

A limitation of this study was the unavailability of further information such
as income, and demographic indicators that could explain some of the
disparities from the findings in the study.

##  6 Conclusion

In conclusion, the presented results provide important information on the
distribution and association of breast cancer characteristics among different
races and age groups. These findings highlight the need for further research
to better understand the underlying causes of breast cancer disparities and to
develop targeted interventions to improve breast cancer outcomes.

## Acknowledgments

I would like to express my sincere gratitude to Professor Rana Jaber for her
invaluable guidance, support, and mentorship throughout the course of this
project. Her expertise, encouragement, and constructive feedback have been
instrumental in shaping this work and my academic journey. I am deeply
thankful for her dedication and inspiration.

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