Changes In Cancer Mortality Rates Research Articles

Age-Specific Cancer Mortality in the US During the COVID-19 Pandemic, March to December 2020

Abstract Background: It is important to understand the impact of the COVID-19 pandemic on cancer death rates in 2020 in the US. We estimated whether there were larger-than-expected changes in cancer mortality rates from March to December 2020 after accounting for temporal and seasonal patterns using data from January 2011 to February 2020 by cancer type and age. Methods: We obtained death counts and underlying causes of death by cancer type, month/year (2011–2020), and age group from the National Center for Health Statistics and population estimates from the US Census Bureau. Poisson regression was used to test for significant changes in cancer death rates from March to December 2020 compared with prior years. Results: After accounting for temporal trends and seasonal patterns, total cancer death rates were significantly lower than expected during March to December 2020 among 55- to 64-year-olds and ≥75-year-olds, but not in other age groups. Cancer death rates were 2% lower than expected from March to June among 55- to 64-year-olds and 2% to 3% lower from March to July and December among ≥75-year-olds. Among ≥75-year-olds, colorectal cancer death rates were lower from March to June [rate ratios (RR) = 0.94–0.96; P < 0.05]; however, lung cancer death rates were 5% lower across each month (all RRs = 0.95; P < 0.05). Conclusions: In the US, cancer death rates based on the underlying cause of death were broadly similar to expected rates from March to December 2020. However, cancer death rates were lower than expected among 55- to 64-year-olds and ≥75-year-olds, likely due to COVID-19 as a competing cause of death. Impact: Cancer mortality rates from 2020 should be interpreted with caution.

Changes in cancer mortality rates after Medicaid expansion under the Affordable Care Act and the role of changes in stage at diagnosis.

74 Background: Medicaid expansion is associated with earlier cancer diagnoses and improved cancer survival. However, it is unclear if the expansion-associated survival benefits are driven primarily by early detection leading to improved prognosis and/or increased access to appropriate cancer care. A nationwide analysis was performed to determine the degree to which expansion-associated changes in cancer mortality rates can be explained by changes in stage at diagnosis. Methods: State-level cancer incidence and mortality data from 2001-2019 for individuals ages 20-64 years were obtained from the combined Surveillance, Epidemiology, and End Results and National Program of Cancer Registries databases (incidence) and the National Center for Health Statistics (mortality), which cover the 50 US States and Washington DC. Difference-in-differences analyses were conducted to compare changes in localized and distant stage cancer incidence rates and cancer mortality rates from pre- vs. post-2014 in expansion vs. non-expansion states. We utilized generalized estimating equations to account for autocorrelation within states and adjusted for age, race, sex, year, state, early Medicaid expansion effects, and state-level covariates (unemployment, education, poverty, race/ethnicity, and insurance). Analyses were conducted overall and by cancer site subtype. Mediation analyses were utilized to assess whether local and/or distant stage diagnosis rates were mediators of the changes in cancer mortality rates. Results: The data consisted of 16,470 state-year observations stratified by age, sex and race. In our adjusted analyses with all cancer sites combined, there were decreases in the distant stage cancer incidence rate (OR: 0.966, 95% CI = 0.942 - 0.991, P=.009) and cancer mortality rate (OR: 0.974, 95% CI = 0.950 - 0.999, P=.041) after Medicaid expansion in expansion relative to non-expansion states. There were no expansion-associated changes in localized cancer incidence rates (OR: 0.989, P=.45). Changes in distant stage cancer incidence mediated 26% of the expansion-associated change in cancer mortality ( P=.013). By cancer site, there were Medicaid expansion-associated decreases in cancer mortality rates for breast (OR: 0.954, P<.001), cervical (OR: 0.934, P=.020), and colorectal (OR: 0.945, P=.045) cancers, though local or distant stage incidence rates were not found to be statistically significant mediators. Conclusions: Medicaid expansion was associated with decreased metastatic stage cancer incidence and decreased overall cancer mortality. Approximately 25% of the improvements in cancer mortality can be attributed to decreases in metastatic diagnoses suggesting increased rates of curative-intent treatment, amongst other factors. Remaining survival benefits may reflect access to timely, quality cancer care not captured in this analysis.

Early Medicaid Expansion and Cancer Mortality.

Although Medicaid expansion is associated with decreased uninsured rates and earlier cancer diagnoses, no study has demonstrated an association between Medicaid expansion and cancer mortality. Our primary objective was to quantify the relationship between early Medicaid expansion and changes in cancer mortality rates. We obtained county-level data from the National Center for Health Statistics for adults aged 20-64 years who died from cancer from 2007 to 2009 (preexpansion) and 2012 to 2016 (postexpansion). We compared changes in cancer mortality rates in early Medicaid expansion states (CA, CT, DC, MN, NJ, and WA) vs nonexpansion states through a difference-in-differences analysis using hierarchical Bayesian regression. An exploratory analysis of cancer mortality changes associated with the larger-scale 2014 Medicaid expansions was also performed. In adjusted difference-in-differences analyses, we observed a statistically significant decrease of 3.07 (95% credible interval = 2.19 to 3.95) cancer deaths per 100 000 in early expansion vs nonexpansion states, which translates to an estimated decrease of 5276 cancer deaths in the early expansion states during the study period. Expansion-associated decreases in cancer mortality were observed for pancreatic cancer. Exploratory analyses of the 2014 Medicaid expansions showed a decrease in pancreatic cancer mortality (-0.18 deaths per 100 000, 95% confidence interval = -0.32 to -0.05) in states that expanded Medicaid by 2014 compared with nonexpansion states. Early Medicaid expansion was associated with reduced cancer mortality rates, especially for pancreatic cancer, a cancer with short median survival where changes in prognosis would be most visible with limited follow-up.

Associations of Early Medicaid Expansion and Cancer Mortality

There is a growing body of evidence that Medicaid expansion improves insurance rates and leads to earlier cancer diagnoses. However, there is no published data to date showing an improvement in survival or mortality for cancer patients. Our objective was to determine whether early Medicaid expansion (2010-2011) was associated with decreased cancer mortality rates. Mortality rates were obtained from the Surveillance, Epidemiology, and End Results (SEER) program in the year ranges available in SEER: 2005-2007 (pre-expansion) and 2012-2016 (post-expansion). Deaths in 2008-2011 were excluded as a phase-in/washout period. Difference-in-differences (DID) analyses were utilized to compare changes in mortality rates from pre- to post-expansion between early expansion (EXP states: CA, CT, DC, MN, NJ, and WA) and non-early expansion states (NEXP states: all others). Adjusted DID analyses were based on county-year group level observations and accounted for county-level covariates. Mortality rates were calculated for all malignancies combined, screenable cancers, and cancer sites with leading causes of death. To ensure minimal confounding due to differing mortality trends between EXP and NEXP states (i.e. to test the parallel trends assumption), changes in cancer mortality rates from 2002-2004 to 2005-2007 and from 2005-2007 to 2008-2011 were compared between EXP and NEXP states. There were 270,150 and 1,148,638 cancer deaths in EXP and NEXP states, respectively. Cancer mortality rates (rate = # deaths / 100,000 persons) declined in both EXP (rate = 75.7 pre-expansion to 64.7 post-expansion) and NEXP (rate = 88.0 to 77.9) states after early Medicaid expansion. In adjusted DID analyses, there was a reduction of 1.30 (95% CI = 0.62 to 1.99, P = .0001) cancer deaths/100,000 persons in EXP relative to NEXP states. Significant expansion-associated reductions were observed for liver and pancreas but not colon, breast, cervix, lung, or prostate cancers (Table). While there was a decrease in cancer mortality irrespective of expansion status, early Medicaid expansion was associated with a decrease of 1.3 cancer deaths per 100,000 persons, translating to about 900 cancer deaths prevented in early expansion states due to Medicaid expansion (based on 2013 EXP states population = 69.2M). As more data emerge, future studies should describe longer-term trends in mortality post-Medicaid expansion.Abstract 202; TableAdjusted DID estimates by cancer siteDID Estimate (95% CI)PAll Malignancies-1.30 (-1.99, -0.62)<0.001Breast0.21 (-0.24, 0.66)0.36Cervix-0.20 (-0.41, 0.02)0.076Colon0.06 (-0.14, 0.28)0.52Liver-0.23 (-0.39, -0.07)0.006Lung0.18 (-0.13, 0.50)0.25Pancreas-0.22 (-0.38, -0.05)0.012Prostate-0.18 (-0.39, 0.02)0.082 Open table in a new tab

Changes in cancer mortality rates after the adoption of the Affordable Care Act.

2003 Background: The Affordable Care Act (ACA) was designed to improve health status in the US primarily through improving access to health insurance. As adoption of Medicaid expansion varied at the state level, this study aims to compare cancer mortality rates over time between states who did (EXP) and did not adopt (NonEXP) Medicaid expansion. Methods: Age-adjusted mortality rates per 100,000 were gathered from the National Center for Health Statistics from 1999-2017 to establish trends. Only deaths due to cancer in patients less than 65 were included. Absolute change in cancer mortality was calculated from 2011-2013 and then from 2015-2017 with 2014 as washout year. Changes within subpopulations (gender, race, ethnicity) were also assessed. Mortality changes between EXP and NonEXP groups were via “difference in differences” analysis. Results: Overall age-adjusted cancer mortality in the US fell from 1999-2017 from 66.9 to 48.8 per 100,000. EXP states had higher population (157 vs 118 million) with less black/African Americans (19.2 vs 21.8 million) and more Hispanics (33.0 vs 21.7 million) than NonEXP states (all examples from 2017). The overall age-adjusted cancer mortality was consistently worse in NonEXP states, cancer mortality fell from 64.7 to 46.0 per 100,000 in EXP states and from 69.0 to 51.9 per 100,000 in NonEXP states from 1999-2017 (both trends p &lt; 0.001, comparison p &lt; 0.001). Comparing the mortality changes in the peri-ACA years (2011-2013 vs 2015-2017) between the 2 cohorts, the difference in differences between EXP and NonEXP states was -1.1 and -0.6 per 100,000 respectively (p = 0.006 EXP, p = 0.14 NonEXP). The estimated overall cancer mortality benefit gained in EXP states after Medicaid expansion (∆∆∆) is -0.5 per 100,000 (p = NS). In EXP states, this translates to an estimated 785 less cancer deaths in 2017. Age-adjusted cancer mortality per 100,000 was worse in NonEXP states for black patients (58.5 EXP vs 63.4 NonEXP in 2017) however there was no differential mortality benefit after ACA expansion when comparing between the peri-ACA years. Of the subpopulations assessed, Hispanics in EXP states had the highest differential cancer mortality benefit at -2.1 per 100,000 (p = 0.07). Conclusions: This is the first study to show a directly measured cancer survival benefit from the ACA on a national scale using a comprehensive database. Hispanic populations appear to have the highest differential cancer mortality benefit after Medicaid expansion. Further study is needed to elucidate why other populations like black patients did not appear to reap the same mortality decrease.

Interrogating of cancer genomes: towards more profile-based therapeutics

Although death rates due to common diseases such as heart disease, stroke and infectious diseases have declined over the last half-century, there has been only a small change in cancer mortality rates. The availability of the draft human genome sequence and a number of technological advances now provide us with the opportunity to explore the genomic landscape of cancer in an unprecedented way. Here, we will describe the application of multiple genomic technologies toward the interrogation of a number of cancer genomes, in order to discover molecular determinants of cancer that might be associated with clinical outcome and those that might be candidates for targeted therapy. It is our hope that these data would one day be translated into clinical practice to improve therapeutic decision-making for more knowledge-based clinical management.

Aging and cancer mortality: Dynamics of change and sex differences

Age-related changes in cancer mortality risk are important for understanding the processes of disease and aging interaction. The extent to which these age changes differ by sex further contributes to this understanding but has not been well studied to date. We conducted a systematic examination of dynamics and heterogeneity of age changes in cancer mortality rates for the top 14 cancer sites using vital statistics from the NCHS and SEER between 1969 and 2007. We assessed patterns of age changes in site-specific mortality rates in terms of both increase (age slope) and acceleration (change in age slope) as measured by the log–log acceleration rate (LLA). We assessed sex differences in mortality rates through sex mortality rate ratios and sex differences in age changes through comparisons of the LLA by sex. The logged male-to-female mortality ratios are positive but vary substantially with age in magnitude. And the age patterns of sex ratios also vary across sites. The LLA values show similar declines and hence slowdowns of mortality increment into or during old age for both sexes for most sites and periods. Post-reproductive changes in sex differences in cancer mortality are not entirely consistent with the estrogenic hypothesis about the anticarcinogenic effects of sex hormones and suggest the utility of the multistage model of disease progression for some tumor sites. Analysis of age dynamics and sex differences in cancer mortality may modify extant aging-related theories of carcinogenesis and frame future searches for specific explanatory factors.

Changes in cancer mortality rates and per capita alcohol consumption in Ontario, 1963-1983.

Data on Ontario per capita alcohol consumption and alcohol-related cancer mortality rates from 1963 to 1983 generally correlated positively and significantly. Correlations for the period of rising consumption (1963-1974) were similar to those observed for the total period, but during the period of stabilization and decline of alcohol consumption the magnitude of nearly all relationships decreased substantially. The overall positive and significant correlation between per capita alcohol consumption and various cancer site mortality rates may be partly due to lag effects from the period when consumption was on the rise.

Does community-wide prevention of cardiovascular diseases influence cancer mortality?

The North Karelia Project, a community-based demonstration project for prevention of cardiovascular diseases since 1972 in Finland, was successful in reducing the population levels of the major cardiovascular risk factors. A net decline in risk factors and coronary heart disease mortality was observed in North Karelia in the 1970s. Thereafter, the mortality from coronary heart disease has declined markedly in all of Finland. The aim of the study was to find out how the cancer mortality has changed in North Karelia during this longer follow-up period. Age-adjusted mortality trends were calculated for the male population aged between 35 and 64 years in the province of North Karelia, and in all of Finland for the period 1969-91, using the official mortality data. The trends and the changes were calculated using general linear model procedures. During the 20-year period, cancer mortality declined in North Karelia by 45.4% and in all of Finland by 32.7% (P = 0.006 for difference). The greater decline in North Karelia occurred particularly in the second decade of the follow up, and lung cancer. The results support the hypothesis that reduction in the population levels of the cardiovascular risk factors lead to beneficial changes in cancer mortality rates, but such changes take longer time to manifest than for coronary heart disease.

Influence of Death Certificate Errors on Cancer Mortality Trends

Evaluation of mortality data is an important tool in assessing both disease time trends and differences in populations. However, the reasons for changes in cancer mortality rates have been controversial. Questions have been raised concerning whether these increases are real or simply the result of changing diagnoses and death certificate reporting. Our purpose was to determine on the basis of autopsy data if death certificate reporting varies over age, time, and cancer type and to explore the effect of death certificate error on recent cancer mortality trends. Data were analyzed from 5886 autopsies collected by the Radiation Effects Research Foundation in Hiroshima, Japan, between 1961 and 1987. Death certificates were linked to autopsy data for analyses. An adjustment factor was calculated as a ratio of the accuracy of these death certificates in identifying cancer (detection rate) and listing cancer (confirmation rate) as the cause of death. This adjustment factor measures bias in mortality rates due to death certification errors and quantifies underestimation and overestimation of cancer mortality rates. Our analyses focused on lymphoma, breast cancer, neoplasms of the brain, multiple myeloma, and melanoma because of reported mortality increases. For these cancers, the adjustment factor decreased significantly (P = .02) over time, implying that death certificate accuracy has improved. This change appears to account for 60% of the observed increase in these cancers during the time period of study. For total cancer, persons 75 years or older have a high adjustment factor but it decreased over time. This decrease suggests an artifactual increase in total cancer mortality rates of about 1% per year for this older group. The quality of death certificate reporting has generally remained constant for most groups during the period 1961-1987. In the study population, there was a consistent underestimation of total cancer mortality of about 18%. For the five types of cancer studied, there has been less underestimation of cancer mortality since 1976. For some specific cancers and for persons 75 years or older, improvements in death certificate accuracy have occurred over time. These data imply that the total death certificate error rate varies considerably by cancer type, time period, and age at death. The changes in death certificate reporting for some sites and the elderly appear to have artifactually created increases in cancer mortality rates. These artifacts need to be considered when using mortality data for prevention research and health care planning.

Research Policy and Review 16. Geographical Disparities in State Cancer-Prevention Policies: The Need for Strong Federal Intervention

Analysis of changes in cancer mortality rates and cancer prevention programs shows that the states that experienced the sharpest increases in cancer mortality during the last thirty years have the weakest cancer-prevention programs. The federal government should intervene to increase cancer prevention, especially in these laggard states.

A method to separate the geographical components of temporal change in cancer mortality rates.

This communication sets forth and illustrates a method to isolate local changes in cancer mortality rates from national and regional components. The method is suggested as a means of identifying note-worthy places for case control and other local studies from large data bases with temporal and geographical dimensions.