Background: Benign breast disease (BBD) increases breast cancer (BC) risk progressively for women diagnosed with nonproliferative change, proliferative disease without atypia (PDWA), and atypical hyperplasia (AH). Leveraging data from 18 704 women in the Mayo BBD Cohort (1967-2013), we evaluated temporal trends in BBD diagnoses and how they have influenced associated BC risk over 4 decades. Methods: BC risk trends associated with BBD were evaluated using standardized incidence ratios (SIRs) and age–period–cohort modeling across 4 eras—premammogram (1967-1981), precore needle biopsy (CNB) (1982-1992), transition to CNB (1993-2001), and CNB era (2002-2013). Results: With a median follow-up of 15.8 years, 9.9% of women were diagnosed with BC (invasive and/or DCIS). From the premammogram era to the CNB era, we observed a significant increase in BC risk, rising from an SIR of 1.61 to 1.99. The proportion of proliferative BBD diagnoses (PDWA or AH) increased markedly over time (28.1%-49.7%), as did the proportion of DCIS events (11%-28%; χ2 P < .001). Within specific BBD categories, the risk of invasive BC increased modestly. Conclusions: Absolute risk of BC within BBD categories remained stable, but the relative risk of BC after BBD increased over time due to notable increases in higher risk BBD lesions, specifically PDWA and AH. These findings illustrate how evolving screening practices have changed the risk profile of BBD and should inform management strategies for patients with BBD in modern clinical settings.

Introduction: Although Hispanic White (HW) females have a lower incidence of breast cancer than non-Hispanic White (NHW) females, breast cancer risk is unclear for HW females after benign breast disease (BBD). Methods: We compared BBD characteristics and subsequent breast cancer risk among HW and NHW females in New Mexico using a population-based collection of benign breast biopsies (1996–2007). BBD was categorized as nonproliferative disease (NPD), proliferative disease without atypia (PDWA), or atypical hyperplasia (AH). Breast cancer risk was assessed as absolute risk (AR) using cumulative incidence and RR by comparing the number of breast cancer events in BBDs to non-BBD. Results: This study included 3,684 HW and 6,587 NHW females with BBD. HW females had similar proportions of NPD (58.6% vs. 54.3%), PDWA (21.4% vs. 23.5%), and AH (3.6% vs. 3.3%) as NHW females. Breast cancer risk among all females with BBD was higher than population-based expected rates (RR, 1.87) and was similar for HW and NHW subgroups (RR = 1.99 vs. 1.84). As expected, breast cancer risk increased with increasing BBD severity, both overall [RR, 1.81 (NPD), 1.85 (PDWA), and 3.10 (AH)] and in the HW and NHW subgroups. Adjusted AR of breast cancer at 5 years also increased with the severity of BBD (HW vs. NHW; NPD: 1.4% vs. 2.1%; PDWA: 1.5% vs. 2.7%; AH: 6% vs. 4.8%). Conclusions: We found similar breast cancer RRs and ARs in HW and NHW. Risk counseling should ensure that HW females receive breast cancer clinical management warranted by their similar absolute risks. Impact: The present population-based provides evidence for the clinical management of HW females with BBD for the prevention of breast cancer.

(1) Background: Telemetry units allow the continuous monitoring of vital signs and ECG of patients. Such physiological indicators work as the digital signatures and biomarkers of disease that can aid in detecting abnormalities that appear before cardiac arrests (CAs). This review aims to identify the vital sign abnormalities measured by telemetry systems that most accurately predict CAs. (2) Methods: We conducted a systematic review using PubMed, Embase, Web of Science, and MEDLINE to search studies evaluating telemetry-detected vital signs that preceded in-hospital CAs (IHCAs). (3) Results and Discussion: Out of 45 studies, 9 met the eligibility criteria. Seven studies were case series, and 2 were case controls. Four studies evaluated ECG parameters, and 5 evaluated other physiological indicators such as blood pressure, heart rate, respiratory rate, oxygen saturation, and temperature. Vital sign changes were highly frequent among participants and reached statistical significance compared to control subjects. There was no single vital sign change pattern found in all patients. ECG alarm thresholds may be adjustable to reduce alarm fatigue. Our review was limited by the significant dissimilarities of the studies on methodology and objectives. (4) Conclusions: Evidence confirms that changes in vital signs have the potential for predicting IHCAs. There is no consensus on how to best analyze these digital biomarkers. More rigorous and larger-scale prospective studies are needed to determine the predictive value of telemetry-detected vital signs for IHCAs.