CP*Trends: An Online Tool for Comparing Cohort and Period Trends Across Cancer Sites

Use of 2-Stage Modeling to Identify How Colorectal Cancer Risk Changes With Period and Cohort

Colorectal cancer (CRC) incidence rates have decreased among adults aged 50 years or older while increasing in adults under age 50 years. Understanding these trends is challenging because of the multiple related time scales of age, diagnosis period, and birth cohort. We analyzed incidence rates of rectal, distal colon, and proximal colon cancer for individuals aged 20 years or more from the Surveillance, Epidemiology, and End Results Program for diagnosis years 1978-2017. We used a 2-stage generalized linear model to determine age, period, and cohort effects for CRC incidence. We first estimated birth cohort effects among people under age 45 years. We used these results to specify prior distributions for cohort effects in a Bayesian model to estimate period effects among people aged 45 years or more. There was no evidence of period effects for people under age 45 years. Risks of rectal and distal colon cancer increased for later birth cohorts. Compared with the 1943-1952 birth cohort, the 1983-1992 birth cohort had 2.2 times the risk of rectal cancer, 1.9 times the risk of distal colon cancer, and 1.3 times the risk of proximal colon cancer. For people aged ≥45 years, period effects showed declines in CRC risk that were attributable to screening.

Recent Changes in the Patterns of Breast Cancer as a Proportion of All Deaths According to Race and Ethnicity

BACKGROUND

Recent reports suggest that racial differences in breast cancer incidence rates have decreased. We examined whether these findings apply to breast cancer mortality while considering age, period, and cohort influences on both absolute and relative measures of breast cancer mortality.

METHODS

Using publicly available datasets (CDC WONDER, Human Mortality Database), we developed an age-period-cohort model of breast cancer mortality and breast cancer deaths as a proportion of all deaths during 1968-2019 among all women and by 5 race/ethnicity groups with sufficient numbers for estimation: Hispanic (all races), American Indian/Alaska Native and Asian/Pacific Islanders (regardless of ethnicity), non-Hispanic Black, and non-Hispanic White.

RESULTS

Initially increasing after 1968, age-adjusted breast cancer mortality rates have decreased among all racial/ethnic groups since 1988. The age-adjusted percent of all deaths due to breast cancer also has been declining for non-Hispanic White women since about 1990 while increasing or holding steady for other race/ethnic groups. In 2019, the age-adjusted percent of deaths due to breast cancer for women was highest for Asian/Pacific Islanders (5.6%) followed by non-Hispanic Black (4.5%), Hispanic (4.4%), non-Hispanic White (4.1%), and American Indian/Alaska Native women (2.6%).

CONCLUSIONS

Breast cancer mortality disparities are now greater on both relative and absolute scales for non-Hispanic Black women, and using the relative scale for Asian/Pacific Islander and Hispanic women, compared with non-Hispanic White women for the first time in 50 years.

Survival model methods for analyses of cancer incidence trends in young adults

Recent studies have reported increases in cancer incidence in adults under 50 years. However, there remains uncertainty about whether these are true increases or a result of incidental findings from increased medical imaging. To evaluate these trends, we propose an alternative method to age-period-cohort analyses based on survival modeling. Simulations show that our method is capable of quantifying cohort effects within various backgrounds including increasing medical imaging. We applied the method to analyze the changes in cancer incidence rates for 44 anatomic sites, stratified by sex, by birth cohort for individuals born from 1945 to 1969 in the US based on incidence data from the Surveillance, Epidemiology, and End Results (SEER) program, and tested the validity of our models using later birth cohorts (1970-1974 and 1975-1979). We found that cancer risks have increased significantly in 15 sites (9 in men and 11 in women) for 25-49 year-olds. These results were consistent with previous findings from age-period-cohort analyses. Furthermore, based on our simulations, these increases were independent of increased medical imaging and support substantial, increased extrinsic risks in the identified cancers. Although our approach has several limitations including the restriction to the younger age range and requirement of complete data for all ages of interest, we demonstrate many advantages of our approach including the ease in implementation and interpretation of cohort effects, robustness to various period backgrounds, and ability to make predictions. Our approach should help epidemiologists evaluate cohort effects using incidence data for cancer or other diseases.