Breast cancer risk factors in relation to molecular subtypes in breast cancer patients from Kenya

Abstract

Background Few studies have investigated risk factor heterogeneity by molecular subtypes in indigenous African populations where prevalence of traditional breast cancer (BC) risk factors, genetic background, and environmental exposures show marked differences compared to European ancestry populations. Methods We conducted a case-only analysis of 838 pathologically confirmed BC cases recruited from 5 groups of public, faith-based, and private institutions across Kenya between March 2012 to May 2015. Centralized pathology review and immunohistochemistry (IHC) for key markers (ER, PR, HER2, EGFR, CK5-6, and Ki67) was performed to define subtypes. Risk factor data was collected at time of diagnosis through a questionnaire. Multivariable polytomous logistic regression models were used to determine associations between BC risk factors and tumor molecular subtypes, adjusted for clinical characteristics and risk factors. Results The median age at menarche and first pregnancy were 14 and 21 years, median number of children was 3, and breastfeeding duration was 62 months per child. Distribution of molecular subtypes for luminal A, luminal B, HER2-enriched, and triple negative (TN) breast cancers was 34.8%, 35.8%, 10.7%, and 18.6%, respectively. After adjusting for covariates, compared to patients with ER-positive tumors, ER-negative patients were more likely to have higher parity (OR = 2.03, 95% CI = (1.11, 3.72), p = 0.021, comparing ≥ 5 to ≤ 2 children). Compared to patients with luminal A tumors, luminal B patients were more likely to have lower parity (OR = 0.45, 95% CI = 0.23, 0.87, p = 0.018, comparing ≥ 5 to ≤ 2 children); HER2-enriched patients were less likely to be obese (OR = 0.36, 95% CI = 0.16, 0.81, p = 0.013) or older age at menopause (OR = 0.38, 95% CI = 0.15, 0.997, p = 0.049). Body mass index (BMI), either overall or by menopausal status, did not vary significantly by ER status. Overall, cumulative or average breastfeeding duration did not vary significantly across subtypes. Conclusions In Kenya, we found associations between parity-related risk factors and ER status consistent with observations in European ancestry populations, but differing associations with BMI and breastfeeding. Inclusion of diverse populations in cancer etiology studies is needed to develop population and subtype-specific risk prediction/prevention strategies.

Association of rs4646903 and rs1048943 CYP1A1 estrogen-metabolizing gene polymorphisms with estrogen receptor-positive breast cancer in Kenyan women

“…In this study, most cases (47%) were diagnosed as stage II of the disease. Our findings are consistent with two previous studies conducted in AKUH in which 50% and 49.1% of the cases were diagnosed at stage II in 2014 and 2021, respectively [2,21]. Contrary to our findings, it was reported that most breast cancers (77%) in the sub-Saharan African region were diagnosed at late stages [20].…”

“…In this study, the mean age at the time of breast cancer diagnosis was 51 years. An earlier study of Kenyan women with BC showed that the mean age at diagnosis of breast cancer was 49.2 years [2]. Another study conducted in Nigeria reported an average diagnostic age of 49.5 years [18].…”

“…In Kenya, breast cancer was reported to have an incidence of 6799 (ASR 41/100 000) and mortalities of 3107 (ASR 19.4/100 000) [1]. A recent study reported that 54% of breast cancer cases were diagnosed in patients aged >50 years [2].…”

Breast Cancer Subtypes and Prognosis: Answers to Subgroup Classification Questions, Identifying the Worst Subgroup in Our Single-Center Series

“…The need to determine the subgroup with the worst prognosis emerged from our patientspecific experiences, which were not always in line with the current literature. [40][41][42][43][44] Although HER2-specific antagonists have revolutionized the treatment of HER2-overexpressing BC and a better clinical outcome for the HER2-enriched subgroup is now possible, it was still identified as the subgroup with the lowest DFS and OS in our study. In the HER2 enriched subgroup, Herceptin decreased the risk of death 2.109 times compared to the patients who could not receive Herceptin (p=0.021).…”

“…The need to determine the subgroup with the worst prognosis emerged from our patient-specific experiences, which were not always in line with the current literature. 40–44 …”