METHODS: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype.
RESULTS: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (P adj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus <20 years at first pregnancy [0.79 (0.72-0.86)]; >0-<5 years versus ≥10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking.
CONCLUSIONS: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype.
IMPACT: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.
MATERIAL AND METHODS: We performed a systematic search via PubMed, MEDLINE, SCOPUS, Science Direct, Cochrane library, Emerald Insight, and Google scholar for identifying studies published on BC risk factors up to March 2021. Pooled odds ratios (OR) are calculated using fixed and random-effect models. Data were processed using Review Manager 5.4 (RevMan 5.4).
RESULTS: From a total of 73 articles, seven case-control studies met the criteria for systematic review. Meta-analysis results showed that of the known modifiable risk factors for BC, diabetes mellitus (DM) had the highest odds ratio (OR = 4.97, 95% CI 3.00- 8.25) followed by hypertension (OR = 3.21, 95% CI 1.96-5.23), obesity (BMI >30 Kg/m2) (OR = 2.90, 95% CI 2.00- 4.21), and passive smoking (OR = 1.50, 95% CI 1.12- 2.02). Controversially, breastfeeding (OR = 0.37, 95% CI 0.23- 0.61) was protective factor in BC. Of non-modifiable risk factors for BC has reached menopause had the highest odds ratio (OR = 3.74, 95% CI 2.64- 5.29), followed by family history of BC (OR = 2.63, 95% CI 1.07-6.44) and age (≥ 40 years) (OR = 2.49, 95% CI 1.43-4.34).
CONCLUSIONS: The most significant predictors of BC in Palestine were DM, hypertension, passive smokers, age (>40), reached menopause, and family history of BC. Almost all these risk factors are consistent with known risk factors for breast cancer in other parts of the world.
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METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.
RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.
CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).