Limited evidence, mostly from studies in Western populations, suggests that the prognostic effects of lifestyle-related risk factors may be molecular subtype-dependent. Here, we examined whether pre-diagnostic lifestyle-related risk factors for breast cancer are associated with clinical outcomes by molecular subtype among patients from an understudied Asian population. In this population-based case series, we evaluated breast cancer risk factors in relation to 10-year all-cause mortality (ACM) and 5-year recurrence by molecular subtype among 3012 women with invasive breast cancer in Sarawak, Malaysia. A total of 579 deaths and 314 recurrence events occurred during a median follow-up period of ~ 24 months. Subtypes (luminal A-like, luminal B-like, HER2-enriched, triple-negative) were defined using immunohistochemical markers for hormone receptors and human epidermal growth factor receptor 2 (HER2) in conjunction with histologic grade. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between risk factors and ACM/recurrence were estimated in subtype-specific Cox regression models. We observed heterogeneity in the relationships between parity/breastfeeding, age at first full-term pregnancy (FFP), family history, body mass index (BMI), and tumor subtype (p value < 0.05). Among luminal A-like patients only, older age at menarche [HR (95% CI) ≥15 vs ≤ 12 years = 2.28 (1.05, 4.95)] and being underweight [HRBMI < 18.5kg/m2 vs. 18.5–24.9kg/m2 = 3.46 (1.21, 9.89)] or overweight [HR25–29.9kg/m2 vs. 18.5–24.9kg/m2 = 3.14 (1.04, 9.50)] were associated with adverse prognosis, while parity/breastfeeding [HRbreastfeeding vs nulliparity = 0.48 (0.27, 0.85)] and older age at FFP [HR > 30 vs < 21 years = 0.20 (0.04, 0.90)] were associated with good prognosis. For these women, the addition of age at menarche, parity/breastfeeding, and BMI, provided significantly better fit to a prognostic model containing standard clinicopathological factors alone [LRχ2 (8df) = 21.78; p value = 0.005]. Overall, the results were similar in relation to recurrence. Our finding that breastfeeding and BMI were associated with prognosis only among women with luminal A-like breast cancer is consistent with those from previously published data in Western populations. Further prospective studies will be needed to clarify the role of lifestyle modification, especially changes in BMI, in improving clinical outcomes for women with luminal A-like breast cancer.

Although most women with luminal breast cancer do well on endocrine therapy alone, some will develop fatal recurrence thereby necessitating the need to prospectively determine those for whom additional cytotoxic therapy will be beneficial. Categorical combinations of immunohistochemical measures of ER, PR, HER2, and KI67 are traditionally used to classify patients into luminal A-like and B-like subtypes for chemotherapeutic reasons, but this may lead to the loss of prognostically relevant information. Here, we compared the prognostic value of quantitative measures of these markers, combined in the IHC4-score, to categorical combinations in subtypes. Using image analysis-based scores for all four markers, we computed the IHC4-score for 2498 patients with luminal breast cancer from two European study populations. We defined subtypes (A-like (ER + and PR + : and HER2- and low KI67) and B-like (ER + and/or PR + : and HER2 + or high KI67)) by combining binary categories of these markers. Hazard ratios and 95% confidence intervals for associations with 10-year breast cancer-specific survival were estimated in Cox proportional-hazard models. We accounted for clinical prognostic factors, including grade, tumor size, lymph-nodal involvement, and age, by using the PREDICT-score. Overall, Subtypes [hazard ratio (95% confidence interval) B-like vs. A-like = 1.64 (1.25–2.14); P-value < 0.001] and IHC4-score [hazard ratio (95% confidence interval)/1 standard deviation = 1.32 (1.20–1.44); P-value < 0.001] were prognostic in univariable models. However, IHC4-score [hazard ratio (95% confidence interval)/1 standard deviation = 1.24 (1.11–1.37); P-value < 0.001; likelihood ratio chi-square (LRχ²) = 12.5] provided more prognostic information than Subtype [hazard ratio (95% confidence interval) B-like vs. A-like = 1.38 (1.02–1.88); P-value = 0.04; LRχ²= 4.3] in multivariable models. Further, higher values of the IHC4-score were associated with worse prognosis, regardless of subtype (P-heterogeneity = 0.97). These findings enhance the value of the IHC4-score as an adjunct to clinical prognostication tools for aiding chemotherapy decision-making in luminal breast cancer patients, irrespective of subtype.

Limited epidemiological evidence suggests that the etiology of hormone receptor positive (HR+) breast cancer may differ by levels of histologic grade and proliferation. We pooled risk factor and pathology data on 5,905 HR+ breast cancer cases and 26,281 controls from 11 epidemiological studies. Proliferation was determined by centralized automated measures of KI67 in tissue microarrays. Odds ratios (OR), 95% confidence intervals (CI) and p‐values for case–case and case–control comparisons for risk factors in relation to levels of grade and quartiles (Q1–Q4) of KI67 were estimated using polytomous logistic regression models. Case–case comparisons showed associations between nulliparity and high KI67 [OR (95% CI) for Q4 vs. Q1 = 1.54 (1.22, 1.95)]; obesity and high grade [grade 3 vs. 1 = 1.68 (1.31, 2.16)] and current use of combined hormone therapy (HT) and low grade [grade 3 vs. 1 = 0.27 (0.16, 0.44)] tumors. In case–control comparisons, nulliparity was associated with elevated risk of tumors with high but not low levels of proliferation [1.43 (1.14, 1.81) for KI67 Q4 vs. 0.83 (0.60, 1.14) for KI67 Q1]; obesity among women ≥50 years with high but not low grade tumors [1.55 (1.17, 2.06) for grade 3 vs. 0.88 (0.66, 1.16) for grade 1] and HT with low but not high grade tumors [3.07 (2.22, 4.23) for grade 1 vs. 0.85 (0.55, 1.30) for grade 3]. Menarcheal age and family history were similarly associated with HR+ tumors of different grade or KI67 levels. These findings provide insights into the etiologic heterogeneity of HR+ tumors.

Benign breast disease (BBD) is associated with heterogeneous breast cancer risk. Identifying key breast cancer risk factors for this population may inform breast cancer prevention or early detection strategies. We systematically searched literature databases PubMed, Embase, Scopus, Web of Science, and the Cochrane Library to identify studies reporting associations of demographic, lifestyle, reproductive, and radiological factors with risk of breast cancer among women with biopsy-confirmed BBD. 67 studies met eligibility criteria. Variation was observed for study time period, exposure measurement, comparison groups, outcomes, and adjustment for confounders, precluding meta-analysis. The literature suggested positive risk associations for age at biopsy, family history, mammographic breast density, and time since biopsy, and no association for body mass index, alcohol, smoking, age at menarche, and use of hormonal contraceptives. More research is needed to understand risk factor associations among women with BBD, particularly studies that account for heterogeneity within BBD and breast cancer.

Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2). The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance. Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10^-6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted. The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.

Benign breast disease (BBD) is a strong breast cancer risk factor, but identifying patients that might develop invasive breast cancer remains a challenge. By applying machine-learning to digitized hematoxylin and eosin–stained biopsies and computer-assisted thresholding to mammograms obtained circa BBD diagnosis, we generated quantitative tissue composition metrics and determined their association with future invasive breast cancer diagnosis. Archival breast biopsies and mammograms were obtained for women (18-86 years of age) in a case-control study, nested within a cohort of 15 395 BBD patients from Kaiser Permanente Northwest (1970-2012), followed through mid-2015. Patients who developed incident invasive breast cancer (ie, cases; n = 514) and those who did not (ie, controls; n = 514) were matched on BBD diagnosis age and plan membership duration. All statistical tests were 2-sided. Increasing epithelial area on the BBD biopsy was associated with increasing breast cancer risk (odds ratio [OR]_{Q4 vs Q1} = 1.85, 95% confidence interval [CI] = 1.13 to 3.04; P_trend = .02). Conversely, increasing stroma was associated with decreased risk in nonproliferative, but not proliferative, BBD (P_{heterogeneity} = .002). Increasing epithelium-to-stroma proportion (OR_{Q4 vs Q1} = 2.06, 95% CI =1.28 to 3.33; P_trend = .002) and percent mammographic density (MBD) (OR_{Q4 vs Q1} = 2.20, 95% CI = 1.20 to 4.03; P_trend = .01) were independently and strongly predictive of increased breast cancer risk. In combination, women with high epithelium-to-stroma proportion and high MBD had substantially higher risk than those with low epithelium-to-stroma proportion and low MBD (OR = 2.27, 95% CI = 1.27 to 4.06; P_trend = .005), particularly among women with nonproliferative (P_trend = .01) vs proliferative (P_trend = .33) BBD. Among BBD patients, increasing epithelium-to-stroma proportion on BBD biopsies and percent MBD at BBD diagnosis were independently and jointly associated with increasing breast cancer risk. These findings were particularly striking for women with nonproliferative disease (comprising approximately 70% of all BBD patients), for whom relevant predictive biomarkers are lacking.