Sage Journals: Discover world-class research

Abstract

Background:

The risk of breast cancer progression is one of the most difficult factors to predict as it is studied in different populations, patient groups, or time frames, resulting in conflicting estimates of incidence rates reported in the literature. The purpose of this study is to identify predictive factors for breast cancer recurrences in a sample of the Middle Eastern population.

Methodology:

A cohort retrospective study included all eligible breast cancer patients at the National Guard Health Affairs (NGHA) Hospital in Jeddah, Western region, from 2015 to 2021. Our primary outcome was the progression status of the patients; we adjusted for demographic, clinical, and molecule characteristics of the population. From 2015 to 2021, there were 319 patients diagnosed with breast cancer. Multiple logistic regression analysis was used to estimate predictors of breast cancer progression.

Results:

One of five breast cancer patients had breast cancer progression (20.83%), while 66.15% of the progression patients were between the ages of 41–65. In multivariate analysis, age, progesterone receptor (PR), family history, and tumor size were significant predictors of breast cancer progression. The age group of 20–40 years was a protective predictor of breast cancer progression, patients in the young age group were less likely to be diagnosed with progression (OR = 0.35; CI = 0.15, 0.81). While negative PRs and tumor size greater than 2 cm were significant predictor factors of breast cancer progression (OR = 2.07; CI = 1.09, 3.91, OR = 2.02; CI = 1.9, 3.78).

Conclusion:

Although the effect of young age as a protective factor for the progression of breast cancer remains controversial, our study revealed that patients between 41 and 60 years of age had a higher rate of progression. Future larger prospective studies are needed to delineate the role of age and PR hormone receptors in determining the best treatment options for women with breast cancer in the Saudi population.

Keywords

Breast cancer progression progesterone receptors treatment Middle Eastern population

Introduction

Breast cancer remains a major global public health challenge with a growing burden around the world.¹ Breast cancer is the most common cancer among women worldwide, with 2 088 849 diagnosed and an incident rate of 11.6% and 626 679 death cases and a mortality rate of 6.6% in 2018.² Furthermore, a systemic review concluded that in 2019, breast cancer is the most common cancer in Saudi Arabia among women, with an incidence rate of 14.6% and a mortality rate of 1.48%.¹ The National Cancer Institute’s Surveillance, Epidemiology and End Results Program reports that the 5-year survival rate of breast cancer in the United States is 90.6%.³ On the contrary, Aseafan et al⁴ reported a 72% 5-year survival rate for breast cancer in Saudi Arabia. Tumor characteristics are one of the leading understating factors of the prognostic agent for the outcome of breast cancer.⁵ Prognostic factors, such as tumor size greater than 2 cm, axillary nodal involvement, negative estrogen receptor (ER) and progesterone receptor (PR), and high grade have been demonstrated to increase the risk of progression, death, and metastases in breast cancer patients.⁵ Similarly, due to the overpenetration of more aggressive subtypes of breast cancer in young women, age is known to be another significant prognostic factor for breast cancer.⁶

Despite the availability of a large number of studies reporting a wide variety of prognostic factors for breast cancer, approximately half of breast cancer patients still have no identifiable risk factors other than age and gender.⁷ Therefore, breast cancer is a highly heterogeneous disease with unpredictable outcomes.⁸ However, in the last two decades, the use of genetic mutations to identify patient severity, prognostic factors, and effective therapy agents has increased the survival rate and improved the quality of life for breast cancer patients. Several gene mutations, such as BCRA1/2, HER2, EGFR, c-Myc, and RAS, have been identified to increase the risk of breast cancer.⁹ Recent advances in sequencing technology have also created a panel that tests for multigene variations that can be used to assess risk stratification for breast cancer.¹⁰ A comprehensive assessment of the histopathology of the primary tumor and the expression pattern of hormone receptors (ER/PR) and epidermal growth factor receptor 2 (HER2/Neu), along with genomic and transcriptomic profiling, classifies the molecular subtypes of breast cancer is crucial to determine the improvement of patient health.⁸ These patient-to-patient differences greatly affect the prognosis of the patient and treatment options. In addition, the existing heterogeneity among breast cancer patients makes it more difficult for researchers to predict common factors associated with risk of breast cancer progression.¹¹

The risk of progression of breast cancer is one of the most difficult factors to predict, as recurrence rates are studied in different populations, group of patients, or time frames, resulting in conflicting estimates of incidence rates reported in the literature.¹¹ Many studies have examined progression risk factors among breast cancer patients with variation in the progression reported.^12,13 Almost 20% of women with early-stage ER-positive (ER +) breast cancer develop progression at 10 years.¹⁴ The risk factors for breast cancer progression documented in the literature include young age, obesity by genetic inheritance, high-grade cancer, large tumor size, and negative ER and PR.^13,14 Furthermore, studies have reported that certain treatment factors, such as lack of adherence to endocrine therapy and delay in the initiation of adjuvant chemoradiation, influence the risk of progression.^11,14 Most of the previous studies were performed in the West and Asian population. In a Middle Eastern population, data remain limited and variable regarding molecular and clinical factors of breast cancer progression is scarce. Thus, to better understand prognostic factors that influence the progression of breast cancer patients in a sample of a Middle Eastern population, this study aims to examine clinical and demographic characteristics associated with progression in breast cancer patients residing in the Western region of Saudi Arabia.

Methods

Data sources

The current study is a retrospective cohort study using data from the Ministry of National Guard Health Affairs (MNG-HA) Cancer Registry. The registry, which was established in 2011, collects information on demographic information of cancer patients, clinical characteristics, including type of cancer, location, and extent at the time of diagnosis. The registry captures all cases diagnosed and treated in King Abdulaziz Medical City (KAMC) in Jeddah. The KAMC Oncology Center is one of the main oncology centers in the Western region of the kingdom. Approximately, 15%–20% of all cancer cases in Saudi Arabia were treated at KAMC Oncology Center in Jeddah. Approval was obtained from the Institutional Review Board (IRB) of NGHA, Jeddah, for this study (IRBC 27399/20). The IRB waived the requirement for informed consent and/or assent due to the retrospective nature of this study. Standard forms were used to retrieve data from electronic patient records for the study period.

Study population

Identification of patients

All individuals aged 20 years or older diagnosed with breast cancer based on the International Classification of Diseases (ICDs) (ICD-10 C50.0–C50.09) between 2015 and 2021, who were resident in Saudi Arabia and registered in the MNG-HA hospitals system with follow-up up to May 31, 2021, were eligible for analysis. The MNG-HA population includes military service personnel and their dependents, members of civilian workforce, and students from the MNG-HA-related health care system. The population (319 individuals) is served by tertiary care hospitals and four main primary and secondary care clinics.

Study variables

Patient and tumor characteristics

Patient demographics, including age, sex, body mass index, education, comorbidity, family history of cancer, and survival status. Clinical characteristics, such as received treatment, ERs, PRs, grades, stage, human HER2, histopathology, and biomarkers were extracted from electronic health records. Data were also collected for any occurrence and site of progression and patient status in the most recent electronic records entry. Our primary outcome was the patients’ progression status.

Statistical Analysis

In univariate analysis, the chi-square and Fisher exact tests assessed associations between demographics and clinical characteristics. Multivariate analysis included only those variables that were significant in univariate analysis and were assessed using multiple binary logistic regression analyses. Also, binary-adjusted multiple logistic regression was used to examine the association between progression and demographic and clinical factors. P-values were two-sided; all confidence intervals were at 95%. We assessed the model of fit using the Akaike information criterion (AIC), and all models were fit. We also checked the assumption for independence among dependent variable categories using the Hausman-McFadden test.¹⁵ All analyses were performed using SAS statistical software version 9.4 (SAS Institute Inc. Cary, NC).

Results

From 2015 to 2021, 319 female patients at KAMC in Jeddah were diagnosed with breast cancer. One in five breast cancer patients had a breast cancer progression (20.83%). A large proportion of the population was among the age group of 41–60 years (56.43%), with normal/underweight body mass index (BMI) (68.65%) and comorbidity (62.38%). Furthermore, 18% of the patients had a family history of cancer. Almost half of the progression population had a breast cancer progression less than 4 years ago, and the other half within 5–20 years (Table 1). In clinical characteristics, 74.92% of the patients had positive ER, 68% had positive PRs, while 28% had positive HER2. Almost half of the population (41.07%) was diagnosed with grade 2, while 31.35% had no evidence of distant metastases, and 25.71% were lymph node negative or cancer areas smaller than 0.2 mm in the lymph nodes; 26.33% of the population presented with tumors larger than 20 mm but not larger than 50 mm (T2). More than half of the population (61.44%) was diagnosed with invasive ductal carcinoma (IDC). In terms of treatment, all patients underwent mastectomy, (99.69%) received chemotherapy, (62.70%) received radiation therapy, and (78.06%) received hormonal therapy (Table 2).

Table 1.

Demographic characteristics of female breast cancer patients at NGHA, Jeddah (2015–2021).

	Progression-free survival	No-recurrences	Unknown	p-value^a
	n (%)^b	n (%)	n (%)
Total	65 (20.83)	227 (71.16)	27 (8.46)
Age				< .0001
20–40 years old	9 (13.85)	60 (26.43)	4 (14.81)
41–60 years old	43 (66.15)	119 (52.42)	18 (66.67)
≥ 61 years old	13 (20.00)	48 (21.15)	5 (18.52)
BMI				.006
Overweight or obese	16 (24.62)	77 (33.92)	7 (25.93)
Normal or underweight	49 (75.38)	150 (66.08)	20 (74.07)
Education				.0002
Elementary and high school	1 (1.54)	20(8.81%)	2 (7.41%)
Undergraduate/graduate college	6 (9.23)	26(11.45%)	4 (14.81%)
NA	58 (89.23)	181 (79.74%)	21 (77.78%)
Comorbidity				.014
Yes	43 (66.15)	140 (61.67)	16 (59.26)
No	22 (33.85)	87 (38.33)	11 (40.74)
Family history (breast, colon, ovarian, pancreatic, liver, and uterine cancer)				< .0001
Yes	5 (7.69)	46 (20.26)	9 (33.33)
No	12 (18.46)	54(23.79)	6 (22.22)
NA	48 (73.85)	127(55.95)	12 (44.44)
Length of follow-up in years				.0001
0–4 years	33 (50.77)	135(59.47)	23 (85.19)
5–20 years	32 (49.23)	92(40.53)	4 (14.81)
Current status of patients				.004
Alive	63 (96.92)	227 (100)	26 (96.30)
Dead	1 (1.54)	–	–
NA	1 (0.31)	–	1 (3.70)

Abbreviations: BMI, body mass index; NA, not available; NGHA, National Guard Health Affairs.

Fisher exact test for less than 5 frequency per cell and chi-square test for more than 5 frequency per cell.

n , sample size; %, percentage.

Table 2.

Clinical characteristics of female breast cancer patients at NGHA, Jeddah (2015–2021).

	Progression-free survival	No-recurrences	Unknown	p-value^a
	n (%)^b	n (%)	n (%)
Total	65 (20.83)	227 (71.16)	27 (8.46)
Estrogen receptors (ERs)				.015
Positive	48 (73.85)	171 (75.33)	20 (74.07)
Negative	17 (26.15)	55 (24.23)	7 (25.93)
NA	–^c	1 (0.44)	–
Progesterone receptors (PRs)				.002
Positive	18 (66.67)	159 (70.04)	40 (61.54)
Negative	9 (33.33)	65 (28.63)	25
NA	–	3 (1.32)	–
Grade				< .0001
1	3 (4.62)	5 (2.20)	2 (7.41)
2	26 (40.00)	94 (41.41)	11 (40.74)
3	17 (26.15)	55 (24.23)	7 (25.93)
NA	19 (29.23)	73 (32.16)	7 (25.93)
Human epidermal growth factor receptor 2 (HER2)				< .0001
Positive	21 (32.31)	64 (28.19)	5 (18.52)
Negative	41 (63.08)	147 (64.76)	20 (74.07)
Equivocal	1 (1.54)	10 (4.41)	2 (7.41)
NA	2 (3.08)	6 (2.64)	–
Metastasis				< .0001
M0	15 (23.08)	83 (36.56)	2 (7.41)
M1	11 (16.92)	23 (10.13)	3 (11.11)
Mx	5 (7.69)	26 (11.45)	3 (11.11)
NA	34 (52.31)	95 (41.85)	19 (70.37)
Histopathology				< .0001
Invasive ductal carcinoma (IDC)	38 (58.46)	141 (62.11)	17 (62.96)
Invasive lobular carcinoma (ILC)	–	14 (6.17)	–
Other	13 (20.00)	34 (14.98)	9 (33.33)
NA	14 (21.54)	38 (16.74)	1 (3.70)
Node				.01
Node+	7 (10.77)	33 (14.54)	3 (11.11)
Node -	21 (32.31)	113 (49.78)	8 (29.63)
NA	37 (56.92)	81 (35.68)	16 (59.26)
Biomarkers				.12
Ki67 1-25%	8 (29.63)	35 (15.42)	12 (18.46)
Ki67 30%-95%	13 (48.15)	66 (29.07)	17 (26.15)
NA	6 (22.22)	126 (55.51)	36 (55.38)
Tumor size				.006
⩽ 2 cm	5 (7.69)	43(18.94)	4 (14.81)
> 2 cm	22 (33.85)	94 (41.41)	5 (66.67)
NA	38 (58.46)	90 (39.65)	18 (18.52)
Mastectomy
Yes	65	227	26	< .0001
No	–	–	–
Chemotherapy				.004
Yes	65	227	26
No	–	–	1
Hormonal therapy				.16
Yes	25 (92.59)	174 (76.65)	50 (76.92)
No	2 (7.41)	53 (23.35)	15 (23.08)
Radiotherapy				.68
Yes	19 (70.37)	141 (62.11)	40 (61.54)
No	8 (29.63)	86 (37.890)	25 (38.46)

Abbreviations: NA, not available; NGHA, National Guard Health Affairs.

Fisher exact test for less than 5 frequency per cell and chi-square test for more than 5 frequency per cell.

n, sample size; %, percentage.

Zero cells.

After adjusting for demographic and clinical potential confounders in multivariate analysis, age, PR, family history of cancer, and tumor size were significant predictors of breast cancer progression. The age group of 20–40 years was a protective predictor of breast cancer progression, patients in the young age group were less likely to be diagnosed with progression (OR = 0.35; CI = 0.15, 0.81) (Table 3). While negative PRs and tumor size greater than 2 cm were significant predictor factors of breast cancer progression (OR = 2.07; CI = 1.09, 3.91), (OR = 2.02; CI = 1.9, 3.78). Patients with negative PRs and tumor size greater than 2 cm were twice as likely to experience progression of breast cancer (Table 3).

Table 3.

Predictors of progression-free survival among patients diagnosed with breast cancer.

	n (%)	AOR	95% CI	p-value
Age
20–40 years old	73 (22.88)	0.35	(0.15, 0.81)	.002
41–60 years old	180 (56.43)	Ref.	Ref.	Ref.
≥ 61 years old	66 (20.69)	0.72	(0.34, 1.53)	.01
Family history (breast, colon, ovarian, pancreatic, liver, and uterine cancer)
Yes	60 (18.81)	Ref.	Ref.	Ref.
No	72 (22.57)	1.76	(0.83, 3.75)	.09
NA	187 (58.62)	0.48	(0.15, 1.55)	.8
Node
Node+	43 (13.48)	1.09	(0.4, 2.98)	.08
Node–	142 (44.51)	Ref.	Ref.	Ref.
NA	134 (42.01)	2.52	(0.7, 1.05)	.21
Progesterone receptors (PRs)
Positive	217 (68.03)	Ref.	Ref.	Ref.
Negative	99 (31.03)	2.07	(1.09, 3.91)	.003
NA	3 (0.94)	0.52	(0.2, 3.22)	.07
Tumor size
⩽ 2 cm	52 (16.30)	Ref.	Ref.	Ref.
> 2 cm	121 (45.77)	2.02	(1.9, 3.78)	.001
NA	146 (37.93)	0.91	(0.24, 3.44)	.08

Abbreviations: AOR, adjusted odds ratio; CI, confidence interval; NA, not available; Ref, reference.

Discussion

In the current study, the researchers found that the demographic characteristics of our sample revealed that more than half of the patients are in the age group of 41–60 years. One in five breast cancer patients had progression, and nearly, half of the progression population in the study had progression within 4 years of the primary diagnosis, interestingly, fewer patients in the young age group (20–40) had progression compared with other older age groups. In our findings, younger age was a protective factor for breast cancer progression. In contrast, PR hormone receptors and tumor size were significant prognostic predictors of breast cancer progression. Patients with tumor size greater than 2 cm and negative PR hormone receptors were more two times more likely to have progression compared with their reference groups.

The finding of the age group of 41–60 years is consistent with a local study that indicated that the median age at diagnosis increased from 47 years in 2004 to 50 years in 2013, 2014, and 2016.¹⁶ Another Saudi cohort study also mirrors our findings suggesting that breast cancer was more commonly identified among middle-aged patients between 30 and 59 years.¹⁷ The prognostic factor for age at diagnosis remains controversial. Age has been a significant and counterseal factor in breast cancer. Aging can be a risk factor for breast cancer and a protective factor for breast cancer progression.¹⁸ Recent emerging data have valued young age as a strong predictor of breast cancer progression.¹⁹ However, our most intriguing finding was the effect of age on the progression of breast cancer in our patients. Our study showed that patients (20–40 years) had a lower probability of progression than older age groups. Young age was a protective factor against breast cancer progression in our population. These findings contradict several studies that analyze age as a prognostic factor.^20,21 A meta-analysis study concluded that age is an independent risk factor for breast cancer progression and observed that the risk of progression rate is associated with younger patients.²² On the contrary, a recent study that emphasizes older breast cancer patients found that patients aged 75–79 years were at increased risk of progression compared with patients aged 70–74 years.¹⁸ The possible explanation for this finding is that the selection and response to treatment are varied between breast cancers with different age groups and genetic mutations.¹⁸ This could result in the distinction between the two age groups, as younger ages are more resistant to different types of treatment compared with the older age group.²³ However, larger population studies should be conducted to confirm or reject this finding.

The most significant risk of progression associated with hormone receptor involvement in the study population is consistent with the published literature. Our findings showed a higher progression of breast cancer among patients who express PR hormone receptors. Another local study analyzed the expression of hormone receptors in Saudi Arabia from 1986 to 2002 and found that the receptors were positively expressed in 69% of patients under 40 years of age and 78.2% of patients with 40 years of age and older.²⁴ These findings align with various studies that found a strong correlation between invasive breast cancer and high expression of positive hormone receptors.^25
-27 However, after adjusting for other clinical and demographic factors, our finding indicated that patients with negative PRs were at risk of progression compared with positive PRs. Previous studies have conflicting findings with respect to the association of PR with breast cancer progression.^28,29 Therefore, a comprehensive focus study is needed that examines the independent effect of PR. In general, identifying predictors and prognostic factors associated with the progression or metastatic potential of the primary tumor in breast cancer would help physicians determine which node-negative patients would benefit from adjuvant therapy.

The strength of this study is the statistically significant detrimental prognostic effect associated with combinatorial biomarkers. Regarding the limitations of this study, the sample size from a single hospital is relatively small, the nature of the study, and the short follow-up timeline. In addition, some missing data on pathological markers would have resulted in a better outcome. Data extraction and re-assessment of tumors are usually done by a single pathologist who has a systematic, consistent approach toward pathological diagnosis and patient care. More studies will be necessary using a more extensive independent data set and longer follow-up time to confirm the prognostic value of the combinatorial pathological variables proposed before implementation in clinical practice.

Conclusion

Our finding indicates that one in five breast cancer patients had progression, and almost, half of the progression population in the study had a recurrence within 4 years of the primary diagnosis, while a larger number of age groups (20–40) patients had progression compared with the younger age group. The younger age was a protective factor for breast cancer progression in our study. The prognostic factors associated with breast cancer progression in our data were PR hormone receptors and tumor size. Patients with tumor size larger than 2 cm and negative PR hormone receptors were two times more likely to have progression compared with their reference groups. Future large prospective studies are needed to delineate the role of age and PR hormone receptors in determining the best treatment options for women with breast cancer in the Saudi population.

Footnotes

Acknowledgements

None.

Declarations

Competing Interests:

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding:

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Alqahtani

Almufareh

Domiaty

, et al. Epidemiology of cancer in Saudi Arabia thru 2010-2019: a systematic review with constrained meta-analysis. AIMS Public Health. 2020;7:679-696. www.ncbi.nlm.nih.gov/pmc/articles/PMC7505779/. Accessed April 12, 2022.

Bray

Ferlay

Soerjomataram

Siegel

Torre

Jemal

Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394-424.

NIH. Female breast cancer cancer stat facts. https://seer.cancer.gov/statfacts/html/breast.html. Accessed May 16, 2022.

Aseafan

Devol

AlAhwal

, et al. Population-based survival for cancer patients in Saudi Arabia for the years 2005-2009. Sci Rep. 2022;12:235. https://pubmed.ncbi.nlm.nih.gov/34997176. Accessed May 16, 2022.

Soerjomataram

Louwman

Ribot

Roukema

Coebergh

JW.

An overview of prognostic factors for long-term survivors of breast cancer. Breast Cancer Res Treat. 2008;107:309-330. https://pubmed.ncbi.nlm.nih.gov/17377838. Accessed June 20, 2022.

Assi

Khoury

Dbouk

Khalil

Mouhieddine

El Saghir

NS.

Epidemiology and prognosis of breast cancer in young women. J Thorac Dis. 2013;5:S2-S8. https://pubmed.ncbi.nlm.nih.gov/23819024. Accessed June 20, 2022.

WHO. Breast cancer. https://www.who.int/news-room/fact-sheets/detail/breast-cancer. Accessed April 12, 2022.

Lüönd

Tiede

Christofori

Breast cancer as an example of tumour heterogeneity and tumour cell plasticity during malignant progression. Br J Cancer. 2021;125:164-175. https://www.nature.com/articles/s41416-021-01328-7. Accessed June 20, 2022.

Sun

Zhao

Yang

, et al. Risk factors and preventions of breast cancer. Int J Biol Sci. 2017;13:1387-1397.

10.

Liu

Lin

Kuo

See

Chiou

HP.

Epidemiology and survival outcome of breast cancer in a nationwide study. Oncotarget. 2017;8:16939.

11.

Spronk

Schellevis

Burgers

de Bock

Korevaar

JC.

Incidence of isolated local breast cancer recurrence and contralateral breast cancer: a systematic review. Breast. 2018;39:70-79. https://pubmed.ncbi.nlm.nih.gov/29621695. Accessed June 20, 2022.

12.

Yekedüz

Dizdar Kertmen

ÖN

Aksoy

Comparison of clinical and pathological factors affecting early and late recurrences in patients with operable breast cancer. J Clin Med. 2022;11:2332. www.ncbi.nlm.nih.gov/pmc/articles/PMC9105518/. Accessed May 16, 2022.

13.

Lafourcade

His

Baglietto

Boutron-Ruault

Dossus

Rondeau

Factors associated with breast cancer recurrences or mortality and dynamic prediction of death using history of cancer recurrences: the French E3N cohort. BMC Cancer. 2018;18:171. https://pubmed.ncbi.nlm.nih.gov/29426294. Accessed June 20, 2022.

14.

Mannell

An overview of risk factors for recurrent breast cancer. S Afr J Surg. 2017;55:29-34. https://pubmed.ncbi.nlm.nih.gov/28876555. Accessed May 16, 2022.

15.

Mogas

Riera

Bennett

A comparison of contingent valuation and choice modelling with second-order interactions. J For Econ. 2006;12:5-30.

16.

Albeshan

Alashban

YI.

Incidence trends of breast cancer in Saudi Arabia: a joinpoint regression analysis (2004-2016). J King Saud Univ Sci. 2021;33:101578.

17.

Ahmed

AE.

Trends and projections of breast cancer in Saudi Arabia: a national incidence rates by gender, age, nationality, and years (1999-2014). Biomed J Sci Tech Res. 2019;12:9326-9331.

18.

de Boer

van

der

Hulst

van

der

Plas-Krijgsman

, et al. Impact of older age on the locoregional and distant breast cancer recurrence risk: a large population-based study. Ann Oncol. 2019;30:iii27

19.

Beadle

Woodward

Buchholz

TA.

The impact of age on outcome in early-stage breast cancer. Semin Radiat Oncol. 2011;21:26. www.ncbi.nlm.nih.gov/pmc/articles/PMC3041510. Accessed April 12, 2022.

20.

Ravichandran

Hamdan

Dyab

AR.

Population based survival of female breast cancer cases in Riyadh region, Saudi Arabia. Asian Pac J Cancer Prev. 2005;6:72-76. http://journal.waocp.org/article_24318.html.

21.

Abulkhair

Moghraby

Badri

Alkushi

Clinicopathologic features and prognosis of triple-negative breast cancer in patients 40 years of age and younger in Saudi Arabia. Hematol Oncol Stem Cell Ther. 2012;5:101-106.

22.

Zou

DH.

The association of young age with local recurrence in women with early-stage breast cancer after breast-conserving therapy: a meta-analysis. Sci Rep. 2017;7:1-13. https://www.nature.com/articles/s41598-017-10729-9. Accessed April 12, 2022.

23.

Elomrani

Zine

Afif

, et al. Management of early breast cancer in older women: from screening to treatment. Breast Cancer (Dove Med Press). 2015;7:165-171. https://pubmed.ncbi.nlm.nih.gov/26185468. Accessed June 20, 2022.

24.

Elkum

Dermime

Ajarim

, et al. Being 40 or younger is an independent risk factor for relapse in operable breast cancer patients: the Saudi Arabia experience. BMC Cancer. 2007;7:222. https://link.springer.com/articles/10.1186/1471-2407-7-222. Accessed April 12, 2022.

25.

Aksoy

Odabas

Kaya

, et al. Hormone receptor status and survival of medullary breast cancer patients. Saudi Med J. 2017;38:156-162. https://smj.org.sa/content/38/2/156. Accessed April 12, 2022.

26.

Niemeier

Dabbs

Beriwal

Striebel

Bhargava

Androgen receptor in breast cancer: expression in estrogen receptor-positive tumors and in estrogen receptor-negative tumors with apocrine differentiation. Mod Pathol. 2010;23:205-212. https://www.nature.com/articles/modpathol2009159. Accessed April 12, 2022.

27.

Onoda

Yamauchi

Yagata

, et al. The value of progesterone receptor expression in predicting the recurrence score for hormone-receptor positive invasive breast cancer patients. Breast Cancer. 2015;22:406-412. https://pubmed.ncbi.nlm.nih.gov/24081457. Accessed April 12, 2022.

28.

Utsumi

Kobayashi

Hikichi

Ushimado

Kuroda

Negative progesterone receptor status correlates with increased risk of breast cancer recurrence in luminal B HER2-positive and -negative subtypes. Fujita Med J. 2021;7:130-135. https://pubmed.ncbi.nlm.nih.gov/35111557/. Accessed June 20, 2022.

29.

Bardou

Arpino

Elledge

Osborne

Clark

GM.

Progesterone receptor status significantly improves outcome prediction over estrogen receptor status alone for adjuvant endocrine therapy in two large breast cancer databases. J Clin Oncol. 2003;21:1973-1979.

Risk of Breast Cancer Progression after Treatment in the Western Region of Saudi Arabia