Minkyo Song, Jae-Jeong Yang, H. Sung, S. Kong, H. Lee, Hyung-Ho Kim, S. Kim, Han-Kwang Yang, N. Sawada, S. Tsugane, M. Inoue, D. Kang
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引用次数: 0
Abstract
Background: Despite the rapid decline of the incidence and mortality over the past few decades, gastric cancer still remains to be the third leading cause of cancer death and the fifth most common cancer worldwide. Furthermore, the absolute number of gastric cancer cases is increasing globally due to the aging of the world population. With available methods to detect and treat precancerous and early stage lesions, development of a prediction model to estimate the probability of developing gastric cancer for various age intervals and risk profiles have important public health implications. Methods: Candidate predictors were selected combining expert opinion and literature search. Using a case-control study with 4,603 Korean subjects, a logistic regression model was used for estimating relative risks, separately for men and women. The discriminatory ability of the models was assessed by receiver operator characteristic area under the curve (AUC). Absolute risk parameters were then calculated combined with the relative risk estimates with baseline age-specific cancer hazard rates from Korean Cancer Registry data. The developed models were validated using an independent prospective cohort data, a Japanese population-based cohort study, which includes 40,173 subjects, by calculating the ratio of expected number (E) over observed number (O) and 95% confidence interval (CI). Results: The models for both men and women included low education, past medical history of diabetes mellitus, no regular use of nonsteroidal inflammatory drugs intake, smoking, no regular exercising, and consumption of high salted food, less fruit, less nonstarchy vegetables, and less nonfermented soy food. The AUC for the relative risk model was 0.73 (95% CI 0.71-0.75) for men and 0.76 (95% CI 0.74-0.79) for women. The overall E/O ratio was 1.05 (95% CI 0.98-1.12) in men, and 0.93 (95% CI 0.83-1.04) in women in the external validation population. Conclusions: To our knowledge this is the first study to estimate the absolute risk of gastric cancer in Korean population. The mathematical models developed in the present study will help predict the occurrence of gastric cancer for an individual considering combined risk factors which will help at a personalized level by enabling early detection and preventive efforts. A further development of a model incorporating biomarkers can provide strategies to select individuals at high risk, for screening for gastric cancer. This abstract is also being presented as PosterB11. Citation Format: Minkyo Song, Jae Jeong Yang, Hyuna Sung, Seong-Ho Kong, Hyuk-Joon Lee, Hyung-Ho Kim, Sang Gyun Kim, Han-Kwang Yang, Norie Sawada, Shoichiro Tsugane, Manami Inoue, Daehee Kang. Projecting individualized absolute risk of developing gastric cancer in Koreans. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR15.
背景:尽管在过去的几十年里,胃癌的发病率和死亡率迅速下降,但它仍然是世界上第三大癌症死亡原因和第五大常见癌症。此外,由于世界人口老龄化,胃癌病例的绝对数量在全球范围内不断增加。随着现有方法的发现和治疗癌前病变和早期病变,开发预测模型来估计不同年龄间隔和风险概况的胃癌发生概率具有重要的公共卫生意义。方法:结合专家意见和文献检索筛选出候选预测因子。采用一项包含4603名韩国受试者的病例对照研究,使用逻辑回归模型分别估计男性和女性的相对风险。用接收算子曲线下特征面积(AUC)评价模型的判别能力。然后计算绝对风险参数,结合相对风险估计和韩国癌症登记处数据中的基线年龄特异性癌症危险率。通过计算期望数(E)与观察数(O)的比值和95%置信区间(CI),使用独立的前瞻性队列数据(日本基于人群的队列研究,包括40,173名受试者)对所开发的模型进行了验证。结果:男性和女性的模型包括低教育程度、既往糖尿病病史、不经常使用非甾体类消炎药、吸烟、不经常运动、食用高盐食物、少吃水果、少吃非淀粉类蔬菜和少吃非发酵豆制品。男性相对风险模型的AUC为0.73 (95% CI 0.71-0.75),女性为0.76 (95% CI 0.74-0.79)。在外部验证人群中,男性的总E/O比为1.05 (95% CI 0.98-1.12),女性的总E/O比为0.93 (95% CI 0.83-1.04)。结论:据我们所知,这是第一项估计韩国人群胃癌绝对风险的研究。在本研究中建立的数学模型将有助于预测个人胃癌的发生,考虑综合危险因素,这将有助于在个性化水平上通过早期发现和预防工作。结合生物标志物的模型的进一步发展可以提供选择高风险个体的策略,用于筛查胃癌。此摘要也以PosterB11的形式呈现。引文格式:宋明教、杨宰正、成泫、孔成浩、李赫俊、金亨镐、金尚均、杨汉光、泽田尚惠、津根昭一郎、井上真美、姜大熙。预测韩国人患胃癌的个体化绝对风险。[摘要]。摘自:AACR特别会议论文集:改进癌症风险预测以预防和早期发现;2016年11月16日至19日;费城(PA): AACR;Cancer epidemiology Biomarkers pre2017;26(5增刊):摘要nr PR15。