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. 2014 Jun;23(6):997-1006.
doi: 10.1158/1055-9965.EPI-13-1233. Epub 2014 Apr 1.

Exploring the recent trend in esophageal adenocarcinoma incidence and mortality using comparative simulation modeling

Affiliations

Exploring the recent trend in esophageal adenocarcinoma incidence and mortality using comparative simulation modeling

Chung Yin Kong et al. Cancer Epidemiol Biomarkers Prev. 2014 Jun.

Abstract

Background: The incidence of esophageal adenocarcinoma (EAC) has increased five-fold in the United States since 1975. The aim of our study was to estimate future U.S. EAC incidence and mortality and to shed light on the potential drivers in the disease process that are conduits for the dramatic increase in EAC incidence.

Methods: A consortium of three research groups calibrated independent mathematical models to clinical and epidemiologic data including EAC incidence from the Surveillance, Epidemiology, and End Results (SEER 9) registry from 1975 to 2010. We then used a comparative modeling approach to project EAC incidence and mortality to year 2030.

Results: Importantly, all three models identified birth cohort trends affecting cancer progression as a major driver of the observed increases in EAC incidence and mortality. All models predict that incidence and mortality rates will continue to increase until 2030 but with a plateauing trend for recent male cohorts. The predicted ranges of incidence and mortality rates (cases per 100,000 person years) in 2030 are 8.4 to 10.1 and 5.4 to 7.4, respectively, for males, and 1.3 to 1.8 and 0.9 to 1.2 for females. Estimates of cumulative cause-specific EAC deaths between both sexes for years 2011 to 2030 range between 142,300 and 186,298, almost double the number of deaths in the past 20 years.

Conclusions: Through comparative modeling, the projected increases in EAC cases and deaths represent a critical public health concern that warrants attention from cancer control planners to prepare potential interventions.

Impact: Quantifying this burden of disease will aid health policy makers to plan appropriate cancer control measures. Cancer Epidemiol Biomarkers Prev; 23(6); 997-1006. ©2014 AACR.

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Figures

Figure 1
Figure 1
The EAC incidence rates by 10 year birth cohorts for all males. The cohort born in 1959 would be 71 years old in calendar year 2030. (A) FHCRC – All Males (B) MGH – All Males (C) UW-MISCAN – All Males.
Figure 2
Figure 2
The SEER and projected EAC incidence rates for both males and females are shown in (A) and (B). The black line is the SEER data and the colored lines are predictions from the three simulation models. The incidence based mortality rates are shown in (C) and (D).
Figure 3
Figure 3
The SEER and projected EAC incidence rates for all males stratified by stage at diagnosis are shown below. (A) Localized (B) Regional (C) Distant.
Figure 4
Figure 4
Progression rates by birth year are shown below. The progression rates were calculated for age-at-diagnosis with BE at age 60 with five years of follow-up time. (A) All Males (B) All Females.
Figure 5
Figure 5
The estimated GERD symptom and BE prevalence of all males (top row) and all females (bottom row) in the US. (A) GERD Symptom Prevalence, All Males (B) BE Prevalence, All Males (C) GERD Symptom Prevalence, All Females (D) BE Prevalence, All Females.
Figure 6
Figure 6
The EAC sojourn times (time between preclinical cancer and cancer diagnosis) for males and females are shown below. (A) All Male EAC Sojourn Time (B) All Female EAC Sojourn Time.

References

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Supplementary concepts