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Simple Summary: The COVID-19 pandemic may have impacted cancer mortality rates by disrupting patient health behaviors and access to cancer care, as well as being directly affected by infection with SARS-CoV-2. There is limited population-based research that investigates the impact of the COVID-19 pandemic on cancer mortality in the United States. The aim of our retrospective study was to quantify the change in cancer mortality from before the COVID-19 pandemic to during the COVID-19 pandemic in Pennsylvania. We found that mortality rates did not continue their previous downward trajectory and twenty-six counties had an increase in the rate in 2020. The 2015–2019 rates were positively associated with the 2020 rates, and the impact of sociodemographic and geographic factors on the 2020 rates varied by county. Our findings suggest a negative effect of the pandemic on cancer mortality in Pennsylvania and had a varied effect on its counties. Future research could confirm our findings, and if confirmed, may inform cancer research, care, and outreach. Background. We sought to quantify the impact of the COVID-19 pandemic on cancer mortality and identify associated factors in Pennsylvania. Methods. The retrospective study analyzed cross-sectional cancer mortality data from CDC WONDER for 2015 through 2020 for Pennsylvania and its 67 counties. The spatial distributions of 2019, 2020, and percentage change in age-adjusted mortality rates by county were analyzed via choropleth maps and spatial autocorrelation. A Wilcoxon Signed Rank Test was used to analyze whether the rates differed between 2019 and 2020. Quasi-Poisson and geographically weighted regression at the county level were used to assess the association between the 2019 rates, sex (percent female), race (percent non-White), ethnicity (percent Hispanic/Latino), rural–urban continuum codes, and socioeconomic status with the 2020 rates. Results. At the state level, the rate in 2020 did not reflect the declining annual trend (−2.7 per 100,000) in the rate since 2015. Twenty-six counties had an increase in the rate in 2020. Of the factors examined, the 2019 rates were positively associated with the 2020 rates, and the impact of sociodemographic and geographic factors on the 2020 rates varied by county. Conclusions. In Pennsylvania, the 2020 cancer mortality rates did not decline as much as reported before the COVID-19 pandemic. The top five cancer types by rate were the same type for 2019 and 2020. Future cancer control efforts may need to address the impact of the COVID-19 pandemic on trends and geospatial distribution in cancer mortality. [ABSTRACT FROM AUTHOR]

Simple Summary: We analyzed the long-term mortality trends and their Age-Period-cohort effects for overall cancer and its 10 sub-types in China. The results show that the overall cancer ASMR has declined, but the absolute cancer cases kept increasing due to the growing elderly population, with the death rates for almost all types of cancer among older Chinese continued to rise during the past three decades. The birth cohort RRs peaked in 1920–1930 and tended to decline in successive cohorts for most cancers except for leukemia, lung cancer in rural, and breast and cervical cancer in females, whose relative risks were rising in the very recent cohorts. The rising mortality related to lung, colorectal, breast and cervical cancer and the increasing burden of cancer death in rural areas should receive higher priority in managing cancer burden and calls for targeted public health actions to reverse the trend. Background: China has the highest number of new cancer cases and deaths worldwide, posing huge health and economic burdens to society and affected families. This study comprehensively analyzed secular trends of national cancer mortality statistics to inform future prevention and intervention programs in China. Methods: The annual estimate of overall cancer mortality and its major subtypes were derived from the National Health Commission (NHC). Joinpoint analysis was used to detect changes in trends, and we used age-period-cohort modeling to estimate cohort and period effects in Cancers between 1987 and 2020. Net drift (overall annual percentage change), local drift (annual percentage change in each age group), longitudinal age curves (expected longitudinal age-specific rate), and period (cohort) relative risks were calculated. Results: The age-standardized cancer mortality in urban China has shown a steady downward trend but has not decreased significantly in rural areas. Almost all cancer deaths in urban areas have shown a downward trend, except for colorectal cancer in men. Decreasing mortality from cancers in rural of the stomach, esophagus, liver, leukemia, and nasopharynx was observed, while lung, colorectal cancer female breast, and cervical cancer mortality increased. Birth cohort risks peaked in the cohorts born around 1920–1930 and tended to decline in successive cohorts for most cancers except for leukemia, lung cancer in rural, and breast and cervical cancer in females, whose relative risks were rising in the very recent cohorts. In addition, mortality rates for almost all types of cancer in older Chinese show an upward trend. Conclusions: Although the age-standardized overall cancer mortality rate has declined, and the urban-rural gap narrowed, the absolute cancer cases kept increasing due to the growing elderly population in China. The rising mortality related to lung, colorectal, female breast, and cervical cancer should receive higher priority in managing cancer burden and calls for targeted public health actions to reverse the trend. [ABSTRACT FROM AUTHOR]

Purpose: Thyroid cancer incidence is rising, possibly secondary to increased imaging and surveillance. Based on rural access to care disparities, we hypothesized that incidence would be greater in urban compared to rural counties with no significant difference in long‐term survival. Methods: An observational study was performed on thyroid cancer patients using Surveillance Epidemiology and End Results data (2000‐2012). Age‐adjusted incidence rates, incidence rate ratios, and survival rates were calculated across rural‐urban designations. Findings: Incidence rates were 11.2, 9.8, and 10.1 per 100,000 for urban, rural‐adjacent, and rural‐nonadjacent counties, respectively. Statistically significantly lower incidence was noted in rural‐adjacent and rural‐nonadjacent compared to urban areas. Five‐year and 10‐year survival was significantly lower in rural‐nonadjacent counties compared to urban counties. Conclusions: Higher incidence and increased long‐term survival for thyroid cancer were noted in urban areas compared to rural areas. It is uncertain if rural‐urban differences in long‐term survival reflect health care disparities, differences in therapy, or other origins. [ABSTRACT FROM AUTHOR]

Background: Cancer contributes substantially to the life expectancy gap between US blacks and whites, and racial cancer disparities remain stubborn to eradicate. Disparities vary geographically, suggesting that they are not inevitable.Methods: The authors examined the relationship between housing discrimination and the size of cancer disparities across large US metropolitan statistical areas (MSAs). MSA-level cancer disparities were measured using data from the US Centers for Disease Control and Prevention. Mortgage discrimination for each MSA was estimated using the Home Mortgage Disclosure Act database, and MSA racial segregation was determined using US Census data. Patterns of housing discrimination and cancer disparities were mapped, and the associations between these place-based factors and cancer disparities across MSAs were measured.Results: Black-to-white cancer mortality disparities (rate ratios) varied geographically, ranging from 1.50 to 0.86; 88% of mortality ratios were >1, indicating higher mortality for blacks. In areas with greater mortgage discrimination, the gap between black and white cancer mortality rates was larger (correlation coefficient [r] = 0.32; P = .001). This relationship persisted in sex-specific analyses (males, r = 0.37; P < .001; females, r = 0.23; P = .02) and in models controlling for confounders. In contrast, segregation was inconsistently associated with disparities. Adjusting for incidence disparities attenuated, but did not eliminate, the correlation between mortgage discrimination and mortality disparities (r = 0.22-0.24), suggesting that cancer incidence and survival each account for part of the mortality disparity.Conclusions: Mortgage discrimination is associated with larger black-to-white cancer mortality disparities. Some areas are exceptions to this trend. Examination of these exceptions and of policies related to housing discrimination may offer novel strategies for explaining and eliminating cancer disparities. [ABSTRACT FROM AUTHOR]

Abstract Objectives China is undergoing a rapid aging transition. The trends in age-specific mortality rates from colorectal cancer remain unknown, and a number of studies have not distinguished the age, period, and cohort effects simultaneously. Study design A descriptive study was implemented with a joinpoint regression analysis and age–period–cohort (APC) model based on the intrinsic estimator (IE). Methods Age-specific mortality rates of colorectal cancer (1987–2016) were collected by gender (men/women) and region (urban/rural). The average annual percentage change (AAPC) and relative risks in the trend were identified using joinpoint Poisson regression and APC model (IE), respectively. Results Joinpoint regression analysis revealed that the rates decreased in the younger (men aged <45 years and women aged <75 years) but increased in the older (men aged >75 years and women aged >80 years) age groups. The APC model (IE) showed that the rates increased with age and time period but decreased with birth cohorts. But from 2000 to 2005, the period effects showed a substantial decline among urban residents. From the 1910–1914 to the 1915–1919 birth cohort, mortality increased among men, and from the 1925–1929 to the 1930–1934 birth cohort, mortality increased among rural residents. Conclusions The trends in colorectal cancer mortality are different between age groups. The younger age groups show a decreasing trend, whereas the older age groups an increasing trend. Cost-effective prevention and control should be implemented more in the elderly and for older cohorts at high risk. Highlights • Through the joinpoint Poisson regression, colorectal cancer mortality decreased in the younger (men aged <45 years and women aged <75 years) but increased in the older (men aged >75 years and women aged >80 years) over the last 30 years. • Through the age–period–cohort model (intrinsic estimator), the rates increased with age and time period but decreased with birth cohorts. • Analysis based on age-specific mortality rates reveals more information than that based on age-standardized rate. [ABSTRACT FROM AUTHOR]

The region of Campania in Southern Italy features high levels of socio-economic deprivation and low levels of environmental quality. A vast strand of the scientific literature has tried to verify whether poor environmental quality and widespread socio-economic deprivation might explain the high cancer mortality rates (CMRs) observed, especially in the municipalities – infamously labelled as the 'Land of Fires' – that were hit most severely by the crisis. While some studies managed to identify links between these two confounding factors and cancer mortality, the evidence is overall mixed. Interesting information may be drawn from the observation of municipal data: in spite of previous claims, some municipalities featuring high environmental quality and low socio-economic deprivation also display high CMRs, while other Campanian municipalities facing disastrous environmental and socio-economic conditions are characterised by low CMRs. These figures, in contrast to common sentiment and previous studies, need to be investigated thoroughly in order to assess the exact role of the confounding factors. In this work, we aim to identify the municipalities where confounding factors act as driving forces in the determination of high CMRs through an original multi-step analysis based on frequentist and Bayesian analysis. Pinpointing these municipalities could allow policymakers to design targeted and effective policy measures aimed at reducing cancer mortality. • This work studies Cancer Mortality Rates (CMRs) at the municipal level in Campania. • We identify environmental quality and socio-economic deprivation as confounding factors. • A multistep analysis is proposed to assess the role of the Confounding Factors (CFs). • Using Bayesian methods, we find that the CFs drive municipal differences in CMRs. [ABSTRACT FROM AUTHOR]