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. 2017 Jul;6(7):1762-1775.
doi: 10.1002/cam4.1102. Epub 2017 May 31.

Comparison of annual percentage change in breast cancer incidence rate between Taiwan and the United States-A smoothed Lexis diagram approach

Li-Hsin Chien  1 , Tzu-Jui Tseng  2 , Chung-Hsing Chen  3 , Hsin-Fang Jiang  3 , Fang-Yu Tsai  3 , Tsang-Wu Liu  3 , Chao A Hsiung  1 , I-Shou Chang  1   2   3
Affiliations

Comparison of annual percentage change in breast cancer incidence rate between Taiwan and the United States-A smoothed Lexis diagram approach

Li-Hsin Chien et al. Cancer Med. 2017 Jul.

Abstract

Recent studies compared the age effects and birth cohort effects on female invasive breast cancer (FIBC) incidence in Asian populations with those in the US white population. They were based on age-period-cohort model extrapolation and estimated annual percentage change (EAPC) in the age-standardized incidence rates (ASR). It is of interest to examine these results based on cohort-specific annual percentage change in rate (APCR) by age and without age-period-cohort model extrapolation. FIBC data (1991-2010) were obtained from the Taiwan Cancer Registry and the U.S. SEER 9 registries. APCR based on smoothed Lexis diagrams were constructed to study the age, period, and cohort effects on FIBC incidence. The patterns of age-specific rates by birth cohort are similar between Taiwan and the US. Given any age-at-diagnosis group, cohort-specific rates increased overtime in Taiwan but not in the US; cohort-specific APCR by age decreased with birth year in both Taiwan and the US but was always positive and large in Taiwan. Given a diagnosis year, APCR decreased as birth year increased in Taiwan but not in the US. In Taiwan, the proportion of APCR attributable to cohort effect was substantial and that due to case ascertainment was becoming smaller. Although our study shows that incidence rates of FIBC have increased rapidly in Taiwan, thereby confirming previous results, the rate of increase over time is slowing. Continued monitoring of APCR and further investigation of the cause of the APCR decrease in Taiwan are warranted.

Keywords: Age effects; annual percentage change in rates; breast cancer; cohort effects; period effects.

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Figures

Figure 1
Figure 1
Age‐specific rates by year of birth (rates vs. age of diagnosis, observations within each birth cohort are connected) and their 95% credible intervals. (A) Age‐specific rates by year of birth for Taiwan. (B) Age‐specific rates by year of birth for US SEER‐9.
Figure 2
Figure 2
Cohort‐specific rates by age at diagnosis (rates vs. birth cohort, observation within each age group are connected) and their 95% credible intervals. (A) Cohort‐specific rates by age at diagnosis for Taiwan. (B) Cohort‐specific rates by age at diagnosis for US SEER‐9.
Figure 3
Figure 3
Cohort‐specific APCR by age at diagnosis (APCR vs. year of birth, observations with the same age at diagnosis are connected) and their 95% credible intervals. (A) Cohort‐specific APCR by age at diagnosis for Taiwan. (B) Cohort‐specific APCR by age at diagnosis for US SEER‐9.
Figure 4
Figure 4
Period‐specific APCR by age at diagnosis (APCR vs. year of diagnosis, observations with the same age at diagnosis are connected) and their 95% credible intervals. (A) Period‐specific APCR by age at diagnosis for Taiwan. (B) Period‐specific APCR by age at diagnosis for US SEER‐9.
Figure 5
Figure 5
Age‐specific rates by year of diagnosis (rates vs. age at diagnosis, observations within each year of diagnosis are connected) and their 95% credible intervals. (A) Age‐specific rates by year of diagnosis for Taiwan. (B) Age‐specific rates by year of diagnosis for US SEER‐9.
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