Kong Chung Yin, Kroep Sonja, Curtius Kit, Hazelton William D, Jeon Jihyoun, Meza Rafael, Heberle Curtis R, Miller Melecia C, Choi Sung Eun, Lansdorp-Vogelaar Iris, van Ballegooijen Marjolein, Feuer Eric J, Inadomi John M, Hur Chin, Luebeck E Georg
Authors' Affiliations: Institute for Technology Assessment; Gastrointestinal Unit, Massachusetts General Hospital; Harvard Medical School, Boston, Massachusetts; Department of Applied Mathematics; Division of Gastroenterology, School of Medicine, University of Washington; Program in Biostatistics and Biomathematics; Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington; Department of Epidemiology, University of Michigan, Ann Arbor, Michigan; Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland; and Department of Public Health, Erasmus MC, Rotterdam, the NetherlandsAuthors' Affiliations: Institute for Technology Assessment; Gastrointestinal Unit, Massachusetts General Hospital; Harvard Medical School, Boston, Massachusetts; Department of Applied Mathematics; Division of Gastroenterology, School of Medicine, University of Washington; Program in Biostatistics and Biomathematics; Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington; Department of Epidemiology, University of Michigan, Ann Arbor, Michigan; Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland; and Department of Public Health, Erasmus MC, Rotterdam, the Netherlands
Authors' Affiliations: Institute for Technology Assessment; Gastrointestinal Unit, Massachusetts General Hospital; Harvard Medical School, Boston, Massachusetts; Department of Applied Mathematics; Division of Gastroenterology, School of Medicine, University of Washington; Program in Biostatistics and Biomathematics; Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington; Department of Epidemiology, University of Michigan, Ann Arbor, Michigan; Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland; and Department of Public Health, Erasmus MC, Rotterdam, the Netherlands.
Cancer Epidemiol Biomarkers Prev. 2014 Jun;23(6):997-1006. doi: 10.1158/1055-9965.EPI-13-1233. Epub 2014 Apr 1.
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.
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.
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.
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.
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.
自1975年以来,美国食管腺癌(EAC)的发病率增长了五倍。我们研究的目的是估计美国未来EAC的发病率和死亡率,并阐明疾病进程中可能导致EAC发病率急剧上升的潜在驱动因素。
由三个研究小组组成的联盟将独立的数学模型校准至临床和流行病学数据,包括1975年至2010年监测、流行病学和最终结果(SEER 9)登记处的EAC发病率。然后,我们采用比较建模方法预测到2030年EAC的发病率和死亡率。
重要的是,所有三个模型都将影响癌症进展的出生队列趋势确定为观察到的EAC发病率和死亡率增加的主要驱动因素。所有模型预测,发病率和死亡率将持续上升直至2030年,但近期男性队列呈平稳趋势。2030年男性发病率和死亡率的预测范围(每10万人年的病例数)分别为8.4至10.1和5.4至7.4,女性为1.3至1.8和0.9至1.2。2011年至2030年两性间特定病因EAC累积死亡估计数在142,300至186,298之间,几乎是过去20年死亡人数的两倍。
通过比较建模,预计EAC病例和死亡人数的增加是一个关键的公共卫生问题,值得癌症控制规划者关注以准备潜在干预措施。
量化这种疾病负担将有助于卫生政策制定者规划适当的癌症控制措施。《癌症流行病学、生物标志物与预防》;23(6);997 - 1006。©2014美国癌症研究协会。