Breast Cancer Mortality Data Research Articles

Comparative Analysis of Mortality due to Breast Cancer and Mammography Uptake in the Federative Units of Brazil-2015 to 2021.

Objective: Compare the breast cancer mortality rate and the rate of mammograms with socioeconomic factors, in Brazilian´s Federative Units, during the period of 2015 to 2021. Methods: This is an ecological study, of a descriptive nature, which covers the 27 Brazilian federative units, using secondary data extracted from the DATASUS System. The information analyzed was mammography data, breast cancer mortality, demographic and economic data of the resident population and women over 20 years of age. Results: There is a direct relationship between mortality rate and mammograms rates in the Federative Units. The data obtained for Brazil presents a total of 133,048 deaths from breast cancer and 17,324,526 mammography exams in the period from 2015 to 2021. In other words, Brazil presents a standardized mortality rate value, 19.25 deaths per 100,000 women. Regarding the mammography rate, the value of the exam-specific mammography rate was 2,506.55 per 100,000 women. In relation to socioeconomic data by mortality rate group, higher mortality rates from breast cancer present higher rates in the variables: income rate by State (2,594.86), people with income (63.5), average percentage of women with more over 50 years old (29.5%), women with average years of education (6.64), white population (55.1%) and mammography exam rate (2873.20). When analysing the highest rates of mammography exam rates, higher rates are observed income rate by State (2,161.47), people with income (62.5%), average percentage of women over 50 years old (28.6%), women with an average number of years of education (5.8). Conclusion: Brazil has a high mortality rate due to breast cancer, when compared to other countries. The reasons are diverse, such as the modern, industrialized and populous lifestyle. The Federative Units with the highest mortality rate also have high rates of mammograms, that is, in the Federative Units with "better" sociodemographic conditions, the South and Southeast.

Impact of state health disparity on lung, breast, and prostate cancer incidence and mortality in the United States.

e18639 Background: Lung cancer is the second most common cancer and the leading cause of cancer deaths in both sex in the United States (US). Prostate cancer is the most common in men, while in women being breast cancer. America’s Health Rankings (AHR) is a comprehensive assessment of the nation's health on a state-by-state basis to determine state health rankings annually. We aimed to evaluate the association, which has not been investigated, between state-level health disparity as measured by AHR and lung, breast, and prostate cancer incidence and mortality in the US. Methods: We examined lung, breast and prostate cancer incidence and mortality data for 2015-2019 from the United States Cancer Statistics (USCS) database provided by the Centers for Disease Control and Prevention (CDC). Overall state health rankings were obtained from AHR and calculated by an equation using weighted measures in five different categories: 25% Behaviors, 22.5% Community & Environment, 12.5% Policy, 15% Clinical Care, and 25% Outcomes. We extracted 2015-2019 AHR data and further classified state health rankings into quartiles (1st [the healthiest] = rank 1 to 13; 4th [the least healthy] = rank 38 to 50). Associations of cancer incidence and mortality with overall state health rankings were analyzed by negative binomial regressions. Results: From 2015 to 2019, age-adjusted incidence rate per 100,000 population for lung, breast, and prostate cancer were 56.3, 128.0 and 109.8, respectively. Age-adjusted mortality rate per 100,000 population for lung, breast, and prostate cancer were 36.7, 19.9 and 18.9, respectively. Among 50 states we included for analysis, AHR indicated that Hawaii was the healthiest state (No.1) whereas Mississippi was the least healthy state (No. 50) for overall health rankings. States in the 4th quartile of health ranking were significantly associated with greater lung cancer incidence (Rate Ratio [RR]: 1.34 [95% CI, 1.18-1.52]) and mortality (1.50 [1.32-1.71]) than those in the 1st quartile. This was pronounced for age < 65 (Incidence [I]: 1.63 [1.36-1.96]; Mortality [M]: 1.93 [1.51-2.48]), Male (I: 1.48 [1.30-1.67]); M: 1.66 [1.47-1.87]), and Black (I: 1.43 [1.22-1.66]; M: 1.54 [1.32-1.79]). Black women living in states with worse health rankings had higher relative risks of breast cancer incidence (1.14 [1.03-1.26]) and mortality (1.27 [1.05-1.53]). There was no significant association between state health rankings and prostate cancer incidence and mortality in the US. Conclusions: There are significant differences in lung, breast, and prostate cancer incidence and mortality within the US. States with worse health rankings had higher cancer incidence and mortality, and varied by different demographics. Our findings suggests that advanced cancer screening and targeted public health interventions should be prioritized in areas with health disadvantages to improve cancer disparity.

Spatial and temporal epidemiological analysis on the mortality rate of female breast cancer in Suzhou, China: 2006–2020

Objective: The epidemiological trend and spatial distribution of female breast cancer mortality in Suzhou were analyzed, so as to provide a scientific basis for the prevention and treatment of breast cancer. Materials and Methods: The annual trend of female breast cancer mortality data from 2006 to 2020 years was analyzed. The spatial autocorrelation analysis was carried out by Moran’s I method of GeoDa software to explore its regional aggregation. Results: The average annual crude mortality rate (CR) of breast cancer in Suzhou was 8.54 per 100 000 from 2006 to 2020, while the age-standardized mortality rate (ASMR) was 7.38 per100 000. The annual change percentage (APC) of CR in the recent 15 years was 1.98% (1.30–2.66%), which was statistically significant (P<0.001). The annual change trend of ASMR was decreased slightly (APC=−0.95%, P=0.04). Spatial analysis indicated that there was a certain clustering of breast cancer in Suzhou. The CR of female breast cancer in Suzhou showed an upward trend, but ASMR decreased slightly. Conclusion: Health promotion and education should be strengthened in the areas with a high incidence of female breast cancer death in Suzhou, and the participation rate of breast cancer screening should be further improved.

Impact of Two-level Spatial Structure Model in Spatio-temporal Hospitalization of Female Breast Cancer Patients in Nigeria

This paper investigated the impact of two-level spatial structure model in spatio-temporal hospitalization of female breast cancer in Nigerian Health-care areas and States. The objective is to measure the relative contribution of each of the model parameters. The model has been fitted using full Laplace approximation strategy to an observational hospital-based female breast cancer mortality data from 2009 to 2016. The study explained risk variations across health-care areas and State-levels. The results showed that the State-level captured higher risk than the health-care area-level (24.18% against 17.60%). Furthermore, assessing each health-care area performance, six (6) health-care areas with large population States showed higher risk. The study recommended o further research on the risk factors responsible for the significant high risk in these health-care areas.

Abstract P6-03-02: Social determinants, food deserts, and their combined contribution to breast cancer mortality

Abstract Recent studies have found that both food deserts (FD) and lower socio-economic status (SES) are individually associated with increased breast cancer mortality in the US. However, further work is needed to investigate their combined contribution to breast cancer mortality. Furthermore, valid inference for area-level disease mapping requires careful consideration of spatial clustering. In our study, we utilize data from the USDA Food Access Research Atlas and the American Community Survey. Breast cancer mortality data come from the National Center of Health Statistics 2014 report. We consider a latent class mixture model to determine deprivation categories which incorporate six SES proportion variables (no car, poverty, no HS graduation, crowded housing, unemployment, crowded housing), two FD (Low income and > 1 mile from supermarket and receiving snap benefits and > 1 mile from supermarket) variables. Our latent class model has three levels: Low, Moderate, and High, making up 36.6%, 45.6%, and 17.8% of US counties, respectively. We then incorporated these levels as a fixed effect in a Bayesian hierarchical spatial negative binomial model using R-INLA. In this model, we account for both spatially structured and unstructured effects. Counties classified as “High” on our deprivation categories were associated with a 50% increase in breast cancer mortality rates (95% CrI: [1.12, 2.02]). Also, the county proportion of women >65 was significantly associated with 1.42 times higher breast cancer mortality (95% CrI [1.37, 1.42]). Policies that allow for access in the face of deprivation may contribute to lower overall breast cancer mortality. Citation Format: Kara McCormack. Social determinants, food deserts, and their combined contribution to breast cancer mortality [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-03-02.

A Statistical Review of Template Model Builder: A Flexible Tool for Spatial Modelling

SummaryThe integrated nested Laplace approximation (INLA) is a well‐known and popular technique for spatial modelling with a user‐friendly interface in the R‐INLA package. Unfortunately, only a certain class of latent Gaussian models are amenable to fitting with INLA. In this paper, we review template model builder (TMB), an existing technique and software package which is well‐suited to fitting complex spatio‐temporal models. TMB is relatively unknown to the spatial statistics community, but it is a flexible random effects modelling tool which allows users to define customizable and complex mixed effects models through C++ templates. After contrasting the methodology behind TMB with INLA, we provide a large‐scale simulation study assessing and comparing R‐INLA and TMB for continuous spatial models, fitted via the stochastic partial differential equations (SPDE) approximation. The results show that the predictive fields from both methods are comparable in most situations even though TMB estimates for fixed or random effects may have slightly larger bias than R‐INLA. We also present a smaller discrete spatial simulation study, in which both approaches perform well. We conclude with a joint analysis of breast cancer incidence and mortality data implemented in TMB which requires a model which cannot be fit with R‐INLA.

Breast Cancer Epidemiology and Survival Analysis of Shenyang in Northeast China: A Population-Based Study from 2008 to 2017.

To investigate the status of breast cancer incidence, trends, and survival in women in urban Shenyang from 2008-2017 using large Cancer Registry data. Breast cancer incidence and mortality data were abstracted from the Shenyang Cancer Registry between 2008 and 2017. The crude and age-standardized incidence and mortality rates were calculated for each year. Average annual percentage changes (AAPC) were used to describe the change over time. A total of 14,255 out of 18,782,956 women were diagnosed with breast cancer between 2008 and 2017 in urban Shenyang. The overall crude and age-standardized incidences were 75.89 and 43.42 per 100,000, respectively. The crude incidence increased from 61.93 per 100,000 in 2008 to 90.07 per 100,000 in 2017, with an AAPC of 5.10%. The crude mortality increased from 11.41 per 100,000 in 2008 to 17.29 per 100,000 in 2017, with an AAPC of 4.60. The highest age-specific incidence occurs in the 55-59 year age group at a rate of 140.67 per 100,000. During the study period, 2,710 women died from breast cancer. The overall crude and age-standardized mortality rates were 14.43 and 7.43 per 100,000, respectively. The highest age-specific mortality occurs at 80-84 years old at a rate of 57.57 per 100,000. The 3-year and 5-year survival rates for female breast cancer in urban Shenyang from 2008 to 2013 were 85.61% and 77.39%, respectively, and both declined with age. The incidence and mortality rates of breast cancer in Shenyang increased over time. Screening and control strategies should be enhanced, especially for perimenopausal females.

Reducing bias due to misclassified exposures using instrumental variables

AbstractExposures are often misclassified in observational studies. Any analysis that does not make proper adjustments for misclassification may result in biased estimates of model parameters, resulting in distorted inference. Settings where a multicategory exposure variable has more than two nominal categories or where no validation data are available to assess misclassification probabilities are common in practice but seldom considered in the literature. This article presents a novel method of analyzing cohort data with a misclassified, multicategory exposure variable and a binary response variable that uses instrumental variables in lieu of a validation dataset. First, a sufficient condition is obtained for model identifiability. Then, methods for model estimation and inference are proposed after adopting a sufficient condition for identifiability. We consider a variational Bayesian inference procedure aided by automatic differentiation along with Markov chain Monte Carlo‐based computation. Operating characteristics of the proposed methods are assessed through simulation studies. For the purpose of illustration, the proposed Bayesian methods are applied to the U.S. breast cancer mortality data sampled from the Surveillance Epidemiology and End Results database, where reported treatment therapy is the misclassified multicategory exposure variable.

Opting into breast screening over the age of 70 years: seeking evidence to support informed choice

To provide evidence specific to the Scottish population regarding the risk-benefit balance of women >70 years opting into continued breast screening, which may be used as a basis for patient information documentation. The present study consisted of a parallel, retrospective data analysis of breast cancer mortality data for breast cancer cases diagnosed between 2009 and 2013 (n=22,013) followed up to 31/12/18, and breast screening programme data from 2010 and 2015 (n=47,235). Screening outcome measures included recall for assessment, oncome of assessment, and tumour features. Tumours were classified as high, intermediate, or low risk according to grade and presence of invasion. Mortality data were linked to age at diagnosis and cause of death was recorded. The proportion of all deaths due breast cancer is inversely related to age at diagnosis. From 77 years, women are more likely to die with breast cancer, than directly due to breast cancer. Mammographic screening accurately identifies breast cancer in older women; however, many of the cancers detected were considered intermediate or low risk. Harms may outweigh the benefits of continued breast screening in older women. This information should be available to all older women.

Trend of breast cancer mortality in Montenegro, 1990-2018 - Joinpoint regression.

In this study, we analyzed breast cancer mortality data overall and by age groups in women in Montenegro, to determine if there were any changes in trend for period 1990-2018. The study gathered data on breast cancer mortality in Montenegro obtained from Vital Registration System. Annual data on breast cancer mortality were extracted for period 1990-2018 and analyzed using World Standard Population age-standardized and age-specific rates and Joinpoint regression. In 2018 in Montenegro, breast cancer accounted for 4.64% of all deaths in women and for 19.78% of all cancer deaths in women. In terms of total cancer mortality, it ranked first among women. Age-standardized rates ranged from 11.41/100,000 in 1990 to 20.46/100,000 in 2016. Joinpoint regression showed no one joinpoint for the entire population of all women and age groups. In the observed period, breast cancer mortality rates significantly increased in the women in Montenegro [average annual percentage change (AAPC) = 1.44%; 95% confidence interval (CI): 0.9-2.0]. The most affected age group was 55-64 years. There is a growing breast cancer mortality trend in Montenegro. It is necessary to create specific programs for urgent action, in order to reduce this undesirable trend. At the same time, support from the competent institutions is needed for increasing screening coverage and better prevention of breast cancer in the target population.

Space-time interactions in Bayesian disease mapping with recent tools: Making things easier for practitioners.

Spatio-temporal disease mapping studies the distribution of mortality or incidence risks in space and its evolution in time, and it usually relies on fitting hierarchical Poisson mixed models. These models are complex for practitioners as they generally require adding constraints to correctly identify and interpret the different model terms. However, including constraints may not be straightforward in some recent software packages. This paper focuses on NIMBLE, a library of algorithms that contains among others a configurable system for Markov chain Monte Carlo (MCMC) algorithms. In particular, we show how to fit different spatio-temporal disease mapping models with NIMBLE making emphasis on how to include sum-to-zero constraints to solve identifiability issues when including spatio-temporal interactions. Breast cancer mortality data in Spain during the period 1990-2010 is used for illustration purposes. A simulation study is also conducted to compare NIMBLE with R-INLA in terms of parameter estimates and relative risk estimation. The results are very similar but differences are observed in terms of computing time.

Trends in Breast Cancer Mortality Between 2001 and 2017: An Observational Study in the European Union and the United Kingdom.

PURPOSEBreast cancer is the most common cancer in women worldwide, representing 25.4% of the newly diagnosed cases in 2018. The past two decades have seen advancements in screening technologies, guidelines, and newer modalities of treatment. Our study reports and compares trends in breast cancer mortality in the European Union and the United Kingdom.MATERIALS AND METHODSWe used the WHO Mortality Database. We extracted breast cancer mortality data from 2001 to 2017 on the basis of the International Classification of Diseases, 10th revision system. Crude mortality rates were dichotomized by sex and reported by year. We computed age-standardized death rates (ASDRs) per 100,000 population using the world standard population. Breast cancer mortality trends were compared using joinpoint regression analysis.RESULTSWe analyzed data from 24 EU countries, including the United Kingdom. For women, breast cancer mortality was observed to be downtrending in all countries except Croatia, France, and Poland. For the most recent female data, the highest ASDR for breast cancer was identified in Croatia (19.29 per 100,000), and the lowest ASDR was noted in Spain (12.8 per 100,000). Denmark had the highest change in ASDR and the highest estimated annual percentage change of −3.2%. For men, breast cancer mortality decreased in 18 countries, with the largest relative reduction observed in Denmark with an estimated annual percentage change of −27.5%. For the most recent male data, the highest ASDR for breast cancer was identified in Latvia (0.54 per 100,000).CONCLUSIONBreast cancer mortality rates have down trended in most EU countries between 2001 and 2017 for both men and women. Given the observational nature of this study, causality to the observed trends cannot be reliably ascribed. However, possible contributing factors should be considered and subject to further study.

Global patterns of breast cancer incidence and mortality: A population-based cancer registry data analysis from 2000 to 2020.

BackgroundBreast cancer is the most commonly diagnosed cancer and leading cause of cancer death among women worldwide but has patterns and trends which vary in different countries. This study aimed to evaluate the global patterns of breast cancer incidence and mortality and analyze its temporal trends for breast cancer prevention and control.MethodsBreast cancer incidence and mortality data in 2020 were obtained from the GLOBOCAN online database. Continued data from the Cancer Incidence in Five Continents Time Trends, the International Agency for Research on cancer mortality and China National Central Cancer Registry were used to analyze the time trends from 2000 to 2015 through Joinpoint regression, and annual average percent changes of breast cancer incidence and mortality were calculated. Association between Human Development Index and breast cancer incidence and mortality were estimated by linear regression.ResultsThere were approximately 2.3 million new breast cancer cases and 685,000 breast cancer deaths worldwide in 2020. Its incidence and mortality varied among countries, with the age‐standardized incidence ranging from the highest of 112.3 per 100,000 population in Belgium to the lowest of 35.8 per 100,000 population in Iran, and the age‐standardized mortality from the highest of 41.0 per 100,000 population in Fiji to the lowest of 6.4 per 100,000 population in South Korea. The peak age of breast cancer in some Asian and African countries were over 10 years earlier than in European or American countries. As for the trends of breast cancer, the age‐standardized incidence rates significantly increased in China and South Korea but decreased in the United States of America (USA) during 2000‐2012. Meanwhile, the age‐standardized mortality rates significantly increased in China and South Korea but decreased in the United Kingdom, the USA, and Australia during 2000 and 2015.ConclusionsThe global burden of breast cancer is rising fast and varies greatly among countries. The incidence and mortality rates of breast cancer increased rapidly in China and South Korea but decreased in the USA. Increased health awareness, effective prevention strategies, and improved access to medical treatment are extremely important to curb the snowballing breast cancer burden, especially in the most affected countries.

Abstract PS7-27: Trends in breast cancer mortality in Brazil - a 14-year registry-based study

Abstract Background: Breast cancer (BC) is the leading cause of cancer-related deaths among women worldwide. BC mortality rates have been decreasing over the past decades in the developed countries. In the United States, BC mortality declined on average 1.5% each year over 2008-2017. Given the paucity of BC mortality data in Brazil, we sought to characterize BC mortality trends in southeastern Brazil and its relationship with demographic variables. Methods: A cross-sectional registry-based analysis was conducted to describe BC mortality trends in the State of Sao Paulo (Brazil) from 2004 to 2017. Sao Paulo is the most populous state in Brazil, with 45.5 million inhabitants, corresponding to 21.8% of the country's total population. BC-related death records, including gender and age were collected from SEADE Foundation’s database, an official entity charged with generating statistical data for the State of Sao Paulo. Mortality rates are expressed in units of deaths per 100,000 individuals per year. The annual percentage change (APC) was calculated to identify mortality trends over the period. Trend analysis was carried out by linear regression and an increase or decrease in trend was considered statistically significant when p-value < 0.05. Results: From 2004 to 2017, 52,005 deaths from BC were recorded in the State of São Paulo, Brazil. Average annual mortality was 8.96/100,000 (17.38/100,000 for females and 0.11/100,000 for males). Average mortality rates were higher in the age group over 65 years-old (46.47/100,000). BC mortality rates remained stable during the period analyzed (APC 0, 95%CI -0.2% to +0.3%, P = 0.9) for both females (APC 0, 95%CI -0.3% to +0.2%, P = 0.7) and males (APC +2.4%, 95%CI -1.7% to +6.6%, P = 0.2). Among females, an increasing BC mortality trend was detected for patients under 40 years-old (APC +2.4%, 95%CI +1.6% to +3.2%, P < 0.0001) and remained stable for the age groups between 40 - 65 years-old (APC -0.3%, 95%CI -0.7% to +0.1%, P = 0.1) and over 65 years-old (APC -0.1%, 95%CI -0.4% to +0.2%, P 0.5). Conclusion: In contrast with data from other developing countries, a stable BC mortality has been demonstrated in southeastern Brazil over a 14-year period for the general population. However, a significant increase in BC mortality rates has been demonstrated among patients under 40 years-old. Citation Format: Guilherme Nader Marta, Laura Testa, Rodrigo Santa Cruz Guindalini, Gustavo Nader Marta, Maria Del Pilar Estevez Diz, Paulo M. Hoff. Trends in breast cancer mortality in Brazil - a 14-year registry-based study [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-27.

A multi-country comparison of stochastic models of breast cancer mortality with P-splines smoothing approach

BackgroundPrecise predictions of incidence and mortality rates due to breast cancer (BC) are required for planning of public health programs as well as for clinical services. A number of approaches has been established for prediction of mortality using stochastic models. The performance of these models intensely depends on different patterns shown by mortality data in different countries.MethodsThe BC mortality data is retrieved from the Global burden of disease (GBD) study 2017 database. This study include BC mortality rates from 1990 to 2017, with ages 20 to 80+ years old women, for different Asian countries. Our study extend the current literature on Asian BC mortality data, on both the number of considered stochastic mortality models and their rigorous evaluation using multivariate Diebold-Marino test and by range of graphical analysis for multiple countries.ResultsStudy findings reveal that stochastic smoothed mortality models based on functional data analysis generally outperform on quadratic structure of BC mortality rates than the other lee-carter models, both in term of goodness of fit and on forecast accuracy. Besides, smoothed lee carter (SLC) model outperform the functional demographic model (FDM) in case of symmetric structure of BC mortality rates, and provides almost comparable results to FDM in within and outside data forecast accuracy for heterogeneous set of BC mortality rates.ConclusionConsidering the SLC model in comparison to the other can be obliging to forecast BC mortality and life expectancy at birth, since it provides even better results in some cases. In the current situation, we can assume that there is no single model, which can truly outperform all the others on every population. Therefore, we also suggest generating BC mortality forecasts using multiple models rather than relying upon any single model.

Historical trends in breast Cancer among women in China from age-period-cohort modeling of the 1990\u20132015 breast Cancer mortality data

BackgroundEvidence on historical trends extracted embedded in recent data can advance our understanding of the epidemiology of breast cancer for Chinese women. China is a country with significant political, socioeconomic, and cultural events since the 1900s; however, no such studies are reported in the literature.MethodsAge-specific mortality rates of breast cancer during 1990–2015 in China were analyzed using APC modeling (age-period-cohort modeling) method. Net effect from birth cohort was derived to measure cancer mortality risk during 1906–1990 when no mortality data were collected, and net effect from time period was derived to measure cancer mortality risk during 1990–2015 when data were collected. Model parameters were estimated using intrinsic estimator, a novel method to handle collinearity. The estimated effects were numerical differentiated to enhance presentations of time/age trend.ResultsBreast cancer mortality rate per 100,000 women increased from 6.83 in 1990 to 12.07 in 2015. After controlling for age and period, the risk of breast cancer mortality declined from 0.626 in 1906–10 to − 1.752 in 1991–95 (RR = 0.09). The decline consisted of 3 phases, a gradual phase during 1906–1940, a moderate phase with some fluctuations during 1941–1970, and a rapid phase with large fluctuations during 1971–1995. After controlling for age and cohort, the risk of breast cancer mortality increased from − 0.141 in 1990 to 0.258 in 2015 (RR = 1.49) with an acceleration after 2005. The time trends revealed by both the cohort effect and the period effect were in consistency with the significant political and socioeconomic events in China since the 1900s.ConclusionsWith recent mortality data in 1990–2015, we detected the risk of breast cancer mortality for Chinese women over a long period from 1906 to 2015. The risk declined more than 90% from the highest level in 1906–10 to the lowest in 1990–95, followed by an increase of 49% from 1990 to 2015. Findings of this study connected historical evidence with recent data, supporting further research to exam the relationship between development and risk of breast cancer for medical and health decision-making at the population level and prevention and treatment at the individual level.

Evaluating the Effect of Medicaid Expansion on Black/White Breast Cancer Mortality Disparities: A Difference-in-Difference Analysis.

PURPOSEMedicaid expansion was designed to increase access to health care. Evidence is mixed, but theory and empirical data suggest that lower cost of care through greater access to insurance increases health care utilization and possibly improves the health of poor and sick populations. However, this major health policy has yet to be thoroughly investigated for its effect on health disparities. The current study is motivated by one of today’s most stark inequalities: the disparity in breast cancer mortality rates between Black and White women.METHODSThis analysis used a difference-in-difference fixed effects regression model to evaluate the impact of Medicaid expansion on the disparity between Black and White breast cancer mortality rates. State-level breast cancer mortality data were obtained from the Centers for Disease Control and Prevention. Each state’s Medicaid expansion status was provided by a Kaiser Family Foundation white paper. Two tests were conducted, one compared all expanding states with all nonexpanding states, and the second compared all expanding states with nonexpanding states that voted to expand—but did not by 2014. The difference-in-difference regression models considered the year 2014 a washout period and compared 2012 and 2013 (pretreatment) with 2015 and 2016 (posttreatment).RESULTSMedicaid expansion did not lower the disparity in breast cancer mortality. In contrast to expectations, the Black/White mortality ratio increased in states expanding Medicaid for all Medicaid-eligible age groups, with significant effects in younger age groups (P = .01 to .15).CONCLUSIONThese results suggest that states cannot solely rely on access to insurance to alleviate disparities in cancer or other chronic conditions. More exploration of the impacts of low-quality health systems is warranted.

Assessment of Breast Cancer Mortality Trends Associated With Mammographic Screening and Adjuvant Therapy From 1986 to 2013 in the State of Victoria, Australia

Diagnosis of early breast cancer (EBC) in women by mammographic screening and postsurgical adjuvant endocrine therapy and chemotherapy (termed adjuvant therapy) began simultaneously in many countries in the 1990s. Subsequent breast cancer mortality declines were variously attributed to mammographic screening and/or adjuvant therapy. To determine the relative mortality reductions associated with these 2 interventions in women with EBC who had been exposed to both. This secondary analysis of cross-sectional studies assessed groups of women with invasive breast cancer in the State of Victoria, Australia, from January 1, 1982, to December 31, 2013, who were included in the Victorian Cancer Registry (VCR). The population consisted of participants in population-based studies of female breast cancer from 1986 to 2013 using data from 4 VCR population-based surveys of breast cancer treatment from 1986 to 1999; VCR data on breast cancer incidence, mortality, and TNM stage at diagnosis from 1986 to 2013; and Victorian mammographic screening program (BreastScreen Victoria) data from 1992 to 2007. Breast cancer incidence and mortality data were analyzed for all 76 630 women registered with invasive breast cancer with the VCR from January 1, 1982, to December 31, 2013, and breast cancer treatment and screening data were analyzed additionally for the groups of surveyed women as described above. Participation in BreastScreen Victoria and receipt of adjuvant therapy after surgery for EBC. Data were analyzed for associations between crude breast cancer mortality trends and uptake of adjuvant therapy and downstaging by mammographic screening. Of all 76 630 women registered with breast cancer with the VCR from January 1, 1982, to December 31, 2013. Joinpoint analyses of the time trend in crude mortality showed an increase from 31.6 per 100 000 women in 1982 to 34.3 per 100 000 women in 1994, with a single joinpoint at 1994, followed by a significant declining trend to 23.9 per 100 000 women in 2013 (annual percentage change, -1.3%; 95% CI, -1.6% to -0.9%). By 1999, 74% of all Victorian women with EBC (737 of 1001) had commenced adjuvant endocrine therapy, and 72% (187 of 260) of premenopausal and 29% (215 of 741) of postmenopausal women with EBC had commenced adjuvant chemotherapy. Crude incidence of advanced-stage breast cancer almost doubled from 12.2 per 100 000 women in 1986 to 23.9 per 100 000 women in 2013. This study found that mammographic screening did not downstage breast cancer in Victoria from advanced to early, so population mortality benefit is lacking. Adjuvant therapy uptake was associated with all of the decline in Victorian breast cancer mortality since 1994. Given these findings, monitoring the relative contributions of mammographic screening and adjuvant therapy for EBC to breast cancer mortality reductions in populations of women exposed to both should be mandatory.

Trends and Projections in Breast Cancer Mortality among four Asian countries (1990\u20132017): Evidence from five Stochastic Mortality Models

The current study aimed to explore some important insights into the breast cancer mortality (BCM) trends and projections among four Asian countries by using five advanced stochastic mortality models. BCM data over 28 years from 1990–2017 with ages 20–84 were retrieved from the Global Burden of Disease (GBD) Study 2017 for four Asian countries, namely, China, India, Pakistan, and Thailand. Five stochastic mortality models with the family of generalized age-period-cohort were implemented to find the present and future BCM trends in these four Asian countries. Based on Cairns-Blake-Dowd (CBD) model and Lee-Carter model (LCM), overall, results revealed that BCM increased with the passage of time. Aging factor was the most influential factor of elevated BCM in each Asian country under consideration. Projection of BCM showed that mortality rates might continue to grow with time, especially in older ages in each Asian country under study. The highest forecasted BCM rates were observed in Pakistan as compared to other countries. The obvious increase in BCM suggested that earlier tactics should be implemented to reduce the subsequent morbidity and mortality due to breast cancer. The last but not least, some additional tactics to mitigate the BCM in older ages must be adopted.

Evaluating the Effect of Medicaid Expansion on Black/White Breast Cancer Mortality Disparities: A Difference-in-Difference Analysis

PURPOSE This analysis used a difference-in-difference (DID) fixed effects regression model to evaluate the impact of Medicaid Expansion on the disparity between black and white breast cancer mortality rates. Medicaid Expansion was designed to increase access to health care. Evidence is mixed, but theory and empirical data suggest that lower cost of care, through greater access to insurance, increases health care utilization and possibly improves the health of poor and sick populations. The goal of Medicaid Expansion was to improve equity. However, this major health policy has yet to be thoroughly investigated for its effect on health disparities. Many widely accepted methods exist to evaluate variations in health policy, but few studies have used such quasi-experimental designs to explore health disparities. The current study is motivated by one of today’s most stark inequalities: the disparity in breast cancer mortality rates between black and white women. To test the impact Medicaid Expansion had on the black/white breast cancer mortality ratio, a DID analysis calculated the policy’s average treatment effect (ATE). METHODS State-level breast cancer mortality data were obtained from the Centers for Disease Control and Prevention. Each state’s Medicaid Expansion status was provided by a Kaiser Family Foundation white paper. Two tests were conducted: one compared all expanding states with all nonexpanding states, and the other compared all expanding states with nonexpanding states that voted to expand (but did not by 2014). Fixed-effects and random-effects regression models were constructed for each specific age group. A Hausman test was calculated to determine which model was most appropriate. The DID regression models considered the year 2014 a wash-out period and compared 2012 and 2013 (pretreatment) to 2015 and 2016 (post-treatment). A graph was presented to test the necessary parallel trend assumption for expanding and nonexpanding states. DID estimators (average treatment effect) and respective P values were reported for each age group. Non–Medicaid-eligible age groups were included as a pseudo-control. RESULTS Medicaid Expansion did not lower the disparity in breast cancer mortality. Converse to expectations, the black/white mortality ratio increased in states expanding Medicaid for all Medicaid-eligible age groups, with significant effects in younger age groups ( P = .01 to .15). CONCLUSION Investigators should use proven quasi-experimental methods to analyze the effect of policy variation on health disparities. Policy makers must consider institutional factors that may limit minority groups from benefiting from macrochanges in health policy. These results suggest that states cannot solely rely on access to insurance to alleviate disparities in cancer or other chronic conditions. More exploration into the impacts of low-quality health systems remain warranted.