Associations of Obesity, Physical Activity, and Screening With State-Level Trends and Racial and Ethnic Disparities of Breast Cancer Incidence and Mortality in the US

Racial disparities in breast cancer risk factors and risk management

Racial disparities in breast cancer outcomes are well described across the spectrum of screening, diagnosis, treatment, and survivorship. Breast cancer mortality is markedly elevated for Non-Hispanic Black women compared with other racial and ethnic groups, with multifactorial causes. Here, we aim to reduce this burden by identifying disparities in breast cancer risk factors, risk assessment, and risk management before breast cancer is diagnosed. We describe a reproductive profile and modifiable risk factors specific to the development of triple-negative breast cancer. We also propose that screening strategies should be both risk- and race-based, given the prevalence of early-onset triple-negative breast cancer in young Black women. We emphasize the importance of early risk assessment and identification of patients at hereditary and familial risk and discuss indications for a high-risk referral. We discuss the subtleties following genetic testing and highlight "uncertain" genetic testing results and risk estimation challenges in women who test negative. We trace aspects of the obesity epidemic in the Black community to infant feeding patterns and emphasize healthy eating and activity. Finally, we discuss building an environment of trust to foster adherence to recommendations, follow-up care, and participation in clinical trials. Addressing relevant social determinants of health; educating patients and clinicians on factors impacting disparities in outcomes; and encouraging participation in targeted, culturally sensitive research are essential to best serve all communities.

"Shared decision-making" for prostate cancer screening: Is it a marker of quality preventative healthcare?

BACKGROUND

"Shared decision-making" (SDM) is a cornerstone of prostate cancer (PCa) screening guidelines due to tradeoffs between clinical benefits and concerns for over-diagnosis and over-treatment. SDM requires effort by primary-care-providers (PCP) in an often busy clinical setting to understand patient preferences with the backdrop of patient risk factors. We hypothesized that SDM for PCa screening, given its prominence in guidelines and practical challenges, may be associated with quality preventative healthcare in terms of other appropriate cancer screening and encouragement of other preventative health behaviors.

METHODS

From the 2020 Behavioral Risk Factor Surveillance Survey, 50-75 year old men who underwent PSA screening were assessed for their participation in SDM, PCa and colorectal cancer (CRC) screening, and other preventative health behaviors, like vaccination, exercise, and smoking status. Adjusted odds ratio of likelihood of PSA testing as a function of SDM was calculated. Likelihoods of SDM and PSA testing as a function of preventative health behaviors were also calculated.

RESULTS

Screening rates were 62 % for PCa and 88 % for CRC. Rates of SDM were 39.1 % in those with PSA screening, and 16.2 % in those without. Odds of PSA screening were higher when SDM was present (AOR = 2.68). History of colonoscopy was associated with higher odds of SDM (AOR = 1.16) and PSA testing (AOR = 1.94). Health behaviors, like regular exercise, were associated with increased odds of SDM (AOR = 1.14) and PSA testing (AOR = 1.28). History of flu vaccination (AOR = 1.29) and pneumonia vaccination (AOR = 1.19) were associated with higher odds of SDM. Those who received the flu vaccine were also more likely to have PSA testing (AOR = 1.36). Smoking was negatively associated with SDM (AOR = 0.86) and PSA testing (AOR = 0.93). Older age was associated with higher rates of PSA screening (AOR = 1.03, CI = 1.03-1.03). Black men were more likely than white men to have SDM (AOR = 1.6, CI = 1.59 - 1.6) and decreased odds of PSA testing (AOR = 0.94, CI = 0.94 - 0.95).

CONCLUSIONS

SDM was associated with higher odds of PSA screening, CRC screening, and other appropriate preventative health behaviors. Racial disparities exist in both SDM and PSA screening usage. SDM may be a trackable metric that can lead to wider preference-sensitive care and improved preventative care.

Geographical Variation in Social Determinants of Female Breast Cancer Mortality Across US Counties

Importance

Breast cancer mortality is complex and traditional approaches that seek to identify determinants of mortality assume that their effects on mortality are stationary across geographic space and scales.

Objective

To identify geographic variation in the associations of population demographics, environmental, lifestyle, and health care access with breast cancer mortality at the US county-level.

Design, Setting, and Participants

This geospatial cross-sectional study used data from the Surveillance, Epidemiology, and End Results (SEER) database on adult female patients with breast cancer. Statistical and spatial analysis was completed using adjusted mortality rates from 2015 to 2019 for 2176 counties in the US. Data were analyzed July 2022.

Exposures

County-level population demographics, environmental, lifestyle, and health care access variables were obtained from open data sources.

Main Outcomes and Measures

Model coefficients describing the association between 18 variables and age-adjusted breast cancer mortality rate. Compared with a multivariable linear regression (OLS), multiscale geographically weighted regression (MGWR) relaxed the assumption of spatial stationarity and allowed for the magnitude, direction, and significance of coefficients to change across geographic space.

Results

Both OLS and MGWR models agreed that county-level age-adjusted breast cancer mortality rates were significantly positively associated with obesity (OLS: β, 1.21; 95% CI, 0.88 to 1.54; mean [SD] MGWR: β, 0.72 [0.02]) and negatively associated with proportion of adults screened via mammograms (OLS: β, -1.27; 95% CI, -1.70 to -0.84; mean [SD] MGWR: β, -1.07 [0.16]). Furthermore, the MGWR model revealed that these 2 determinants were associated with a stationary effect on mortality across the US. However, the MGWR model provided important insights on other county-level factors differentially associated with breast cancer mortality across the US. Both models agreed that smoking (OLS: β, -0.65; 95% CI, -0.98 to -0.32; mean [SD] MGWR: β, -0.75 [0.92]), food environment index (OLS: β, -1.35; 95% CI, -1.72 to -0.98; mean [SD] MGWR: β, -1.69 [0.70]), exercise opportunities (OLS: β, -0.56; 95% CI, -0.91 to -0.21; mean [SD] MGWR: β, -0.59 [0.81]), racial segregation (OLS: β, -0.60; 95% CI, -0.89 to -0.31; mean [SD] MGWR: β, -0.47 [0.41]), mental health care physician ratio (OLS: β, -0.93; 95% CI, -1.44 to -0.42; mean [SD] MGWR: β, -0.48 [0.92]), and primary care physician ratio (OLS: β, -1.46; 95% CI, -2.13 to -0.79; mean [SD] MGWR: β, -1.06 [0.57]) were negatively associated with breast cancer mortality, and that light pollution was positively associated (OLS: β, 0.48; 95% CI, 0.24 to 0.72; mean [SD] MGWR: β, 0.27 [0.04]). But in the MGWR model, the magnitude of effect sizes and significance varied across geographical regions. Inversely, the OLS model found that disability was not a significant variable for breast cancer mortality, yet the MGWR model found that it was significantly positively associated in some geographical locations.

Conclusions and Relevance

This cross-sectional study found that not all social determinants associated with breast cancer mortality are spatially stationary and provides spatially explicit insights for public health practitioners to guide geographically targeted interventions.

Evaluation of a population-based breast cancer screening in North China

BACKGROUND

Despite mammography-based screening for breast cancer has been conducted in many countries, there are still little data on participation and diagnostic yield in population-based breast cancer screening in China.

METHODS

We enrolled 151,973 eligible women from four cities in Hebei Province within the period 2013-2021 and followed up until December 31, 2021. Participants aged 40-74 who assessed as high risk were invited to undergo breast ultrasound and mammography examination. Overall and group-specific participation rates were calculated. Multivariable analyses were used to estimate the factors associated with participation rates. The diagnostic yield of both screening and no screening groups was calculated. We further analyzed the stage distribution and molecular subtype of breast cancer cases by different modes of cancer detection.

RESULTS

A total of 42,547 participants were evaluated to be high risk of breast cancer. Among them, 23,009 subjects undertook screening services, with participation rate of 54.08%. Multivariable logistic regression model showed that aged 45-64, high education level, postmenopausal, current smoking, alcohol consumption, family history of breast cancer, and benign breast disease were associated with increased participation of screening. After median follow-up of 3.79 years, there were 456 breast cancer diagnoses of which 65 were screen-detected breast cancers (SBCs), 27 were interval breast cancers (IBCs), 68 were no screening cancers, and 296 were cancers detected outside the screening program. Among them, 92 participants in the screening group (0.40%) and 364 in the non-screening group (0.28%) had breast cancer detected, which resulted in an odds ratio of 1.42 (95% CI 1.13-1.78; P = 0.003). We observed a higher detection rate of breast cancer in the screening group, with ORs of 2.42 (95% CI 1.72-3.41) for early stage (stages 0-I) and 2.12 (95% CI 1.26-3.54) for luminal A subtype. SBCs had higher proportion of early stage (71.93%) and luminal A subtype (47.22%) than other groups.

CONCLUSIONS

The significant differences in breast cancer diagnosis between the screening and non-screening group imply an urgent need for increased breast cancer awareness and early detection in China.

Breast cancer incidence in Yogyakarta, Indonesia from 2008-2019: A cross-sectional study using trend analysis and geographical information system

BACKGROUND

Breast cancer is a significant public health concern worldwide, including in Indonesia. Little is known about the spatial and temporal patterns of breast cancer incidence in Indonesia. This study aimed to analyze temporal and spatial variations of breast cancer incidence in Yogyakarta Province, Indonesia.

METHODS

The study used breast cancer case data from the Yogyakarta Population-Based Cancer Registry (PBCR) from 2008 to 2019. The catchment areas of the PBCR included the 48 subdistricts of 3 districts (Sleman, Yogyakarta City, and Bantul). Age-standardized incidence rates (ASR) were calculated for each subdistrict. Joinpoint regression was used to detect any significant changes in trends over time. Global Moran's and Local Indicators of Spatial Association (LISA) analyses were performed to identify any spatial clusters or outliers.

RESULTS

The subdistricts had a median ASR of 41.9, with a range of 15.3-70.4. The majority of cases were diagnosed at a late stage, with Yogyakarta City having the highest proportion of diagnoses at stage 4. The study observed a significant increasing trend in breast cancer incidence over the study period the fastest of which is in Yogyakarta City with an average annual percentage change of 18.77%, with Sleman having an 18.21% and Bantul having 8.94% average changes each year (p <0.05). We also found a significant positive spatial autocorrelation of breast cancer incidence rates in the province (I = 0.581, p <0.001). LISA analysis identified 11 subdistricts which were high-high clusters in the central area of Yogyakarta City and six low-low clusters in the southeast region of the catchment area in the Bantul and Sleman Districts. No spatial outliers were identified.

CONCLUSIONS

We found significant spatial clustering of BC ASR in the Yogyakarta Province, and there was a trend of increasing ASR across the region. These findings can inform resource allocation for public health efforts to high-risk areas and develop targeted prevention and early detection strategies. Further res is needed to understand the factors driving the observed temporal and spatial patterns of breast cancer incidence in Yogyakarta Province, Indonesia.