Abstract
马恒敏,王乐,石菊芳,应建明,朱娟,陈莉莉,岳馨培,龚继勇,李晓,王家林,代敏.乳腺癌自然史模型研究系统评价:现状及构建中国人群特异性模型面临的挑战[J].Chinese journal of Epidemiology,2017,38(10):1419-1425
乳腺癌自然史模型研究系统评价:现状及构建中国人群特异性模型面临的挑战
A systematic review of international simulation models on the natural history of breast cancer:current understanding and challenges for Chinese-population-specific model development
Received:March 15, 2017  
DOI:10.3760/cma.j.issn.0254-6450.2017.10.025
KeyWord: 乳腺肿瘤  自然史  模型研究  系统综述
English Key Word: Breast neoplasms  Natural history  Modelling  Systematic review
FundProject:国家自然科学基金(81402740,81773521);教育部高等学校博士学科点专项科研基金(20131106120014);国家重大公共卫生服务项目城市癌症早诊早治项目
Author NameAffiliationE-mail
Ma Hengmin Program Office for Cancer Screening in Urban China, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
Department of Public Health, Shandong Cancer Hospital Affiliated to Shandong University, Jinan 250117, China 
 
Wang Le Program Office for Cancer Screening in Urban China, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China  
Shi Jufang Program Office for Cancer Screening in Urban China, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China shijf@cicams.ac.cn 
Ying Jianming Department of Pathology, National Cancer Center/Cancer Hospital, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College  
Zhu Juan Program Office for Cancer Screening in Urban China, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China  
Chen Lili Program Office for Cancer Screening in Urban China, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
Cancer Epidemiology Research Center, Gansu Provincial Cancer Hospital, Lanzhou 730050, China 
 
Yue Xinpei Program Office for Cancer Screening in Urban China, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
Department of Medical Records Management, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China 
 
Gong Jiyong Department of Public Health, Shandong Cancer Hospital Affiliated to Shandong University, Jinan 250117, China  
Li Xiao Oncology Prevention Center, Qingdao Central Hospital, Qingdao 266042, China  
Wang Jialin Department of Public Health, Shandong Cancer Hospital Affiliated to Shandong University, Jinan 250117, China wangjialin6681@sina.com 
Dai Min Program Office for Cancer Screening in Urban China, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China  
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Abstract:
      目的 系统评价全球乳腺癌自然史模型研究及相关参数,为构建我国人群特异性模型提供参考。方法 检索PubMed和Cochrane Library数据库1980-2015年乳腺癌自然史模型研究,根据纳入排除标准分别开展文献筛选及资料提取,归纳乳腺癌自然史状态及相关参数。结果 共纳入文献36篇,首篇文献发表于1990年;研究集中于欧美国家,仅2篇涉及中国人群;其中筛查项目评价有32篇,方法多采用为Markov模型(32篇)。模型设置状态包括"健康"(36篇)、乳腺导管原位癌(DCIS,17篇)、浸润癌(36篇)和死亡(27篇)。明确报道浸润癌分类系统主要有肿瘤大小(9篇)和TNM分期(9篇,其中3篇报道有1年进展概率):DCIS发展为Ⅰ期、Ⅰ~Ⅱ期、Ⅱ~Ⅲ期、Ⅲ~Ⅳ期乳腺癌的概率M值(范围)依次是0.279(0.259~0.299)、0.150(0.069~0.430)、0.100(0.060~0.128)和0.210(0.010~0.625)。有15篇报道乳腺癌从临床前期到临床出现症状的平均时间为1.95~4.70年,且随年龄增加逐渐延长;7篇报道了DCIS对应时长。结论 目前乳腺癌疾病自然史模型研究渐受关注,但未见不典型增生等癌前病变的报道;导管原位癌出现症状时长参数有待合理转化;采用浸润癌分类系统多样但进展概率参数有限,对构建我国人群特异性模型有一定参考但也提出挑战。
English Abstract:
      Objective To systematically review the worldwide simulation model studies on the natural history of breast cancer and to summarize related parameters. Methods A structured literature search was conducted in PubMed and the Cochrane Library to identify articles during 1980-2015. Articles were screened independently by two researchers. Health states in the natural history and relevant parameters were extracted. Results A total of 36 studies were included for analysis, within the earliest one was published in 1990. Most studies were from Europe and America countries, and 2 studies from China. Markov model was mostly applied to evaluating breast cancer screening programs (n=32). Reported health status included "healthy" (n=36), ductal carcinoma in situ (DCIS, n=17), invasive breast cancer (IBC, n=36), and death (n=27). There were two definite classifications for IBC, tumor size (n=9) and TNM staging (n=9, 3 studies reported transition rates). The median (range) of annual transition rates from DCIS to stage-Ⅰ IBC, Ⅰ to Ⅱ, Ⅱ to Ⅲ, Ⅲ to Ⅳ were 0.279 (0.259-0.299), 0.150 (0.069-0.430), 0.100 (0.060-0.128) and 0.210 (0.010-0.625), respectively. A total of 15 studies reported the mean duration from predinical to clinical stage for IBC was 1.95-4.70 years, which gradually increased with age, and 7 studies reported that for DCIS. Conclusions Despite closer attention was paid to breast cancer natural history models, in recent years atypical hyperplasia has been neglected. Data on the mean duration of DCIS requires reasonable conversion. Various classifications for IBC exist whereas transition rates are limited. Current findings would be valuable references but challenging for the Chinese-population specific natural history model, development.
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